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• Survey Paper
• Open access
• Published: 09 December 2019

Internet of Things is a revolutionary approach for future technology enhancement: a review

• Sachin Kumar   ORCID: orcid.org/0000-0003-3949-0302 1 ,
• Prayag Tiwari 2 &
• Mikhail Zymbler 1  

Journal of Big Data volume  6 , Article number:  111 ( 2019 ) Cite this article

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Internet of Things (IoT) is a new paradigm that has changed the traditional way of living into a high tech life style. Smart city, smart homes, pollution control, energy saving, smart transportation, smart industries are such transformations due to IoT. A lot of crucial research studies and investigations have been done in order to enhance the technology through IoT. However, there are still a lot of challenges and issues that need to be addressed to achieve the full potential of IoT. These challenges and issues must be considered from various aspects of IoT such as applications, challenges, enabling technologies, social and environmental impacts etc. The main goal of this review article is to provide a detailed discussion from both technological and social perspective. The article discusses different challenges and key issues of IoT, architecture and important application domains. Also, the article bring into light the existing literature and illustrated their contribution in different aspects of IoT. Moreover, the importance of big data and its analysis with respect to IoT has been discussed. This article would help the readers and researcher to understand the IoT and its applicability to the real world.

Introduction

The Internet of Things (IoT) is an emerging paradigm that enables the communication between electronic devices and sensors through the internet in order to facilitate our lives. IoT use smart devices and internet to provide innovative solutions to various challenges and issues related to various business, governmental and public/private industries across the world [ 1 ]. IoT is progressively becoming an important aspect of our life that can be sensed everywhere around us. In whole, IoT is an innovation that puts together extensive variety of smart systems, frameworks and intelligent devices and sensors (Fig.  1 ). Moreover, it takes advantage of quantum and nanotechnology in terms of storage, sensing and processing speed which were not conceivable beforehand [ 2 ]. Extensive research studies have been done and available in terms of scientific articles, press reports both on internet and in the form of printed materials to illustrate the potential effectiveness and applicability of IoT transformations. It could be utilized as a preparatory work before making novel innovative business plans while considering the security, assurance and interoperability.

General architecture of IoT

A great transformation can be observed in our daily routine life along with the increasing involvement of IoT devices and technology. One such development of IoT is the concept of Smart Home Systems (SHS) and appliances that consist of internet based devices, automation system for homes and reliable energy management system [ 3 ]. Besides, another important achievement of IoT is Smart Health Sensing system (SHSS). SHSS incorporates small intelligent equipment and devices to support the health of the human being. These devices can be used both indoors and outdoors to check and monitor the different health issues and fitness level or the amount of calories burned in the fitness center etc. Also, it is being used to monitor the critical health conditions in the hospitals and trauma centers as well. Hence, it has changed the entire scenario of the medical domain by facilitating it with high technology and smart devices [ 4 , 5 ]. Moreover, IoT developers and researchers are actively involved to uplift the life style of the disabled and senior age group people. IoT has shown a drastic performance in this area and has provided a new direction for the normal life of such people. As these devices and equipment are very cost effective in terms of development cost and easily available within a normal price range, hence most of the people are availing them [ 6 ]. Thanks to IoT, as they can live a normal life. Another important aspect of our life is transportation. IoT has brought up some new advancements to make it more efficient, comfortable and reliable. Intelligent sensors, drone devices are now controlling the traffic at different signalized intersections across major cities. In addition, vehicles are being launched in markets with pre-installed sensing devices that are able to sense the upcoming heavy traffic congestions on the map and may suggest you another route with low traffic congestion [ 7 ]. Therefore IoT has a lot to serve in various aspects of life and technology. We may conclude that IoT has a lot of scope both in terms of technology enhancement and facilitate the humankind.

IoT has also shown its importance and potential in the economic and industrial growth of a developing region. Also, in trade and stock exchange market, it is being considered as a revolutionary step. However, security of data and information is an important concern and highly desirable, which is a major challenging issue to deal with [ 5 ]. Internet being a largest source of security threats and cyber-attacks has opened the various doors for hackers and thus made the data and information insecure. However, IoT is committed to provide the best possible solutions to deal with security issues of data and information. Hence, the most important concern of IoT in trade and economy is security. Therefore, the development of a secure path for collaboration between social networks and privacy concerns is a hot topic in IoT and IoT developers are working hard for this.

The remaining part of the article is organized as follows: “ Literature survey ” section will provide state of art on important studies that addressed various challenges and issues in IoT. “ IoT architecture and technologies ” section discussed the IoT functional blocks, architecture in detail. In “ Major key issues and challenges of IoT ” section, important key issues and challenges of IoT is discussed. “ Major IoT applications ” section provides emerging application domains of IoT. In “ Importance of big data analytics in IoT ” section, the role and importance of big data and its analysis is discussed. Finally, the article concluded in “ Conclusions ” section.

Literature survey

IoT has a multidisciplinary vision to provide its benefit to several domains such as environmental, industrial, public/private, medical, transportation etc. Different researchers have explained the IoT differently with respect to specific interests and aspects. The potential and power of IoT can be seen in several application domains. Figure  2 illustrates few of the application domains of IoTs potentials.

Some of the potential application domains of IoT

Various important IoT projects have taken charge over the market in last few years. Some of the important IoT projects that have captured most of the market are shown in Fig.  3 . In Fig.  3 , a global distribution of these IoT projects is shown among American, European and Asia/Pacific region. It can be seen that American continent are contributing more in the health care and smart supply chain projects whereas contribution of European continent is more in the smart city projects [ 8 ].

Global distribution of IoT projects among America (USA, South America and Canada), Europe and APAC (Asia and Pacific region) [ 8 ]

Figure  4 , illustrates the global market share of IoT projects worldwide [ 8 ]. It is evident that industry, smart city, smart energy and smart vehicle based IoT projects have a big market share in comparison to others.

Global share of IoT projects across the world [ 8 ]

Smart city is one of the trendy application areas of IoT that incorporates smart homes as well. Smart home consists of IoT enabled home appliances, air-conditioning/heating system, television, audio/video streaming devices, and security systems which are communicating with each other in order to provide best comfort, security and reduced energy consumption. All this communication takes place through IoT based central control unit using Internet. The concept of smart city gained popularity in the last decade and attracted a lot of research activities [ 9 ]. The smart home business economy is about to cross the 100 billion dollars by 2022 [ 10 ]. Smart home does not only provide the in-house comfort but also benefits the house owner in cost cutting in several aspects i.e. low energy consumption will results in comparatively lower electricity bill. Besides smart homes, another category that comes within smart city is smart vehicles. Modern cars are equipped with intelligent devices and sensors that control most of the components from the headlights of the car to the engine [ 11 ]. The IoT is committed towards developing a new smart car systems that incorporates wireless communication between car-to-car and car-to-driver to ensure predictive maintenance with comfortable and safe driving experience [ 12 ].

Khajenasiri et al. [ 10 ] performed a survey on the IoT solutions for smart energy control to benefit the smart city applications. They stated that at present IoT has been deployed in very few application areas to serve the technology and people. The scope of IoT is very wide and in near future IoT is able to capture almost all application areas. They mentioned that energy saving is one of the important part of the society and IoT can assist in developing a smart energy control system that will save both energy and money. They described an IoT architecture with respect to smart city concept. The authors also discussed that one of the challenging task in achieving this is the immaturity of IoT hardware and software. They suggested that these issues must be resolved to ensure a reliable, efficient and user friendly IoT system.

Alavi et al. [ 13 ] addressed the urbanization issue in the cities. The movement of people from rural to urban atmosphere resulting in growing population of the cities. Therefore, there is a need to provide smart solutions for mobility, energy, healthcare and infrastructure. Smart city is one of the important application areas for IoT developers. It explores several issues such as traffic management, air quality management, public safety solutions, smart parking, smart lightning and smart waste collection (Fig.  5 ). They mentioned that IoT is working hard to tackle these challenging issues. The need for improved smart city infrastructure with growing urbanization has opened the doors for entrepreneurs in the field of smart city technologies. The authors concluded that IoT enabled technology is very important for the development of sustainable smart cities.

Potential IoT application areas for smart cities

Another important issue of IoT that requires attention and a lot of research is security and privacy. Weber [ 14 ] focused on these issues and suggested that a private organization availing IoT must incorporate data authentication, access control, resilience to attacks and client privacy into their business activities that would be an additional advantage. Weber suggested that in order to define global security and privacy issues, IoT developers must take into account the geographical limitations of the different countries. A generic framework needs to be designed to fit the global needs in terms of privacy and security. It is highly recommended to investigate and recognize the issues and challenges in privacy and security before developing the full fledge working IoT framework.

Later, Heer et al. [ 15 ] came up with a security issue in IP based IoT system. They mentioned that internet is backbone for the communication among devices that takes place in an IoT system. Therefore, security issues in IP based IoT systems are an important concern. In addition, security architecture should be designed considering the life cycle and capabilities of any object in the IoT system. It also includes the involvement of the trusted third party and the security protocols. The security architecture with scalability potential to serve the small-scale to large-scale things in IoT is highly desirable. The study pointed out that IoT gave rise to a new way of communication among several things across the network therefore traditional end to end internet protocol are not able to provide required support to this communication. Therefore, new protocols must be designed considering the translations at the gateways to ensure end-to-end security. Moreover, all the layers responsible for communication has their own security issues and requirements. Therefore, satisfying the requirements for one particular layers will leave the system into a vulnerable state and security should be ensured for all the layers.

Authentication and access control is another issue in IoT that needs promising solutions to strengthen the security. Liu et al. [ 16 ] brought up a solution to handle authentication and access control. Authentication is very important to verify the communicating parties to prevent the loss of confidential information. Liu et al. [ 16 ] provided an authentication scheme based on Elliptic Curve Cryptosystem and verified it on different security threats i.e. eavesdropping, man-in-the-middle attack, key control and replay attack. They claimed that there proposed schemes are able to provide better authentication and access control in IoT based communication. Later, Kothmayr et al. [ 17 ] proposed a two-way authentication scheme based of datagram transport layer security (DTLS) for IoT. The attackers over the internet are always active to steal the secured information. The proposed approach are able to provide message security, integrity, authenticity and confidentiality, memory overhead and end-to-end latency in the IoT based communication network.

Li et al. [ 18 ] proposed a dynamic approach for data centric IoT applications with respect to cloud platforms. The need of an appropriate device, software configuration and infrastructure requires efficient solutions to support massive amount of IoT applications that are running on cloud platforms. IoT developers and researchers are actively engaged in developing solutions considering both massive platforms and heterogeneous nature of IoT objects and devices. Olivier et al. [ 19 ] explained the concept of software defined networking (SDN) based architecture that performs well even if a well-defined architecture is not available. They proposed that SDN based security architecture is more flexible and efficient for IoT.

Luk et al. [ 20 ] stated that the main task of a secure sensor network (SSN) is to provide data privacy, protection from replay attacks and authentication. They discussed two popular SSN services namely TinySec [ 21 ] and ZigBee [ 22 ]. They mentioned that although both the SSN services are efficient and reliable, however, ZigBee is comparatively provides higher security but consumes high energy whereas TinySec consumes low energy but not as highly secured as ZigBee. They proposed another architecture MiniSec to support high security and low energy consumption and demonstrated its performance for the Telos platform. Yan et al. [ 23 ] stated that trust management is an important issue in IoT. Trust management helps people to understand and trust IoT services and applications without worrying about uncertainty issues and risks [ 24 ]. They investigated different issues in trust management and discussed its importance with respect to IoT developers and users.

Noura et al. [ 25 ] stated the importance of interoperability in IoT as it allows integration of devices, services from different heterogeneous platforms to provide the efficient and reliable service. Several other studies focused on the importance of interoperability and discussed several challenges that interoperability issue is facing in IoT [ 26 , 27 , 28 ]. Kim et al. [ 29 ] addressed the issue of climate change and proposed an IoT based ecological monitoring system. They mentioned that existing approaches are time consuming and required a lot of human intervention. Also, a routine visit is required to collect the information from the sensors installed at the site under investigation. Also, some information remained missing which leads to not highly accurate analysis. Therefore, IoT based framework is able to solve this problem and can provide high accuracy in analysis and prediction. Later, Wang et al. [ 30 ] shows their concern for domestic waste water treatment. They discussed several deficiencies in the process of waste water treatment and dynamic monitoring system and suggested effective solutions based on IoT. They stated that IoT can be very effective in the waste water treatment and process monitoring.

Agriculture is one of the important domain around the world. Agriculture depends on several factors i.e. geographical, ecological etc. Qiu et al. [ 31 ] stated that technology that is being used for ecosystem control is immature with low intelligence level. They mentioned that it could be a good application area for IoT developers and researchers.

Qiu et al. [ 31 ] proposed an intelligent monitoring platform framework for facility agriculture ecosystem based on IoT that consists of four layer mechanism to manage the agriculture ecosystem. Each layer is responsible for specific task and together the framework is able to achieve a better ecosystem with reduced human intervention.

Another important concern around the world is climate change due to global warming. Fang et al. [ 32 ] introduced an integrated information system (IIS) that integrates IoT, geo-informatics, cloud computing, global positioning system (GPS), geographical information system (GIS) and e-science in order to provide an effective environmental monitoring and control system. They mentioned that the proposed IIS provides improved data collection, analysis and decision making for climate control. Air pollution is another important concern worldwide. Various tools and techniques are available to air quality measures and control. Cheng et al. [ 33 ] proposed AirCloud which is a cloud based air quality and monitoring system. They deployed AirCloud and evaluated its performance using 5 months data for the continuous duration of 2 months.

Temglit et al. [ 34 ] considered Quality of Service (QoS) as an important challenge and a complex task in evaluation and selection of IoT devices, protocols and services. QoS is very important criteria to attract and gain trust of users towards IoT services and devices. They came up with an interesting distributed QoS selection approach. This approach was based on distributed constraint optimization problem and multi-agent paradigm. Further, the approach was evaluated based on several experiments under realistic distributed environments. Another important aspect of IoT is its applicability to the environmental and agriculture standards. Talavera et al. [ 35 ] focused in this direction and presented the fundamental efforts of IoT for agro-industrial and environmental aspects in a survey study. They mentioned that the efforts of IoT in these areas are noticeable. IoT is strengthening the current technology and benefiting the farmers and society. Jara et al. [ 36 ] discussed the importance of IoT based monitoring of patients health. They suggested that IoT devices and sensors with the help of internet can assist health monitoring of patients. They also proposed a framework and protocol to achieve their objective. Table 1 provides a summary of the important studies and the direction of research with a comparison of studies on certain evaluation parameters.

IoT architecture and technologies

The IoT architecture consists of five important layers that defines all the functionalities of IoT systems. These layers are perception layer, network layer, middleware layer, application layer, business layer. At the bottom of IoT architecture, perception layer exists that consists of physical devices i.e. sensors, RFID chips, barcodes etc. and other physical objects connected in IoT network. These devices collects information in order to deliver it to the network layer. Network layer works as a transmission medium to deliver the information from perception layer to the information processing system. This transmission of information may use any wired/wireless medium along with 3G/4G, Wi-Fi, Bluetooth etc. Next level layer is known as middleware layer. The main task of this layer is to process the information received from the network layer and make decisions based on the results achieved from ubiquitous computing. Next, this processed information is used by application layer for global device management. On the top of the architecture, there is a business layer which control the overall IoT system, its applications and services. The business layer visualizes the information and statistics received from the application layer and further used this knowledge to plan future targets and strategies. Furthermore, the IoT architectures can be modified according to the need and application domain [ 19 , 20 , 37 ]. Besides layered framework, IoT system consists of several functional blocks that supports various IoT activities such as sensing mechanism, authentication and identification, control and management [ 38 ]. Figure  6 illustrates such functional blocks of IoT architecture.

A generic function module of IoT system

There are several important functional blocks responsible for I/O operations, connectivity issues, processing, audio/video monitoring and storage management. All these functional block together incorporates an efficient IoT system which are important for optimum performance. Although, there are several reference architectures proposed with the technical specifications, but these are still far from the standard architecture that is suitable for global IoT [ 39 ]. Therefore, a suitable architecture is still needsvk to be designed that could satisfy the global IoT needs. The generic working structure of IoT system is shown in Fig.  7 . Figure  7 shows a dependency of IoT on particular application parameters. IoT gateways have an important role in IoT communication as it allows connectivity between IoT servers and IoT devices related to several applications [ 40 ].

Working structure of IoT

Scalability, modularity, interoperability and openness are the key design issues for an efficient IoT architecture in a heterogenous environment. The IoT architecture must be designed with an objective to fulfil the requirements of cross domain interactions, multi-system integration with the potential of simple and scalable management functionalities, big data analytics and storage, and user friendly applications. Also, the architecture should be able to scaleup the functionality and add some intelligence and automation among the IoT devices in the system.

Moreover, increasing amount of massive data being generated through the communication between IoT sensors and devices is a new challenge. Therefore, an efficient architecture is required to deal with massive amount of streaming data in IoT system. Two popular IoT system architectures are cloud and fog/edge computing that supports with the handling, monitoring and analysis of huge amount of data in IoT systems. Therefore, a modern IoT architecture can be defined as a 4 stage architecture as shown in Fig.  8 .

Four stage IoT architecture to deal with massive data

In stage 1 of the architecture, sensors and actuators plays an important role. Real world is comprised of environment, humans, animals, electronic gadgets, smart vehicles, and buildings etc. Sensors detect the signals and data flow from these real world entities and transforms into data which could further be used for analysis. Moreover, actuators is able to intervene the reality i.e. to control the temperature of the room, to slow down the vehicle speed, to turn off the music and light etc. Therefore, stage 1 assist in collecting data from real world which could be useful for further analysis. Stage 2 is responsible to collaborate with sensors and actuators along with gateways and data acquisition systems. In this stage, massive amount of data generated in stage 1 is aggregated and optimized in a structured way suitable for processing. Once the massive amount of data is aggregated and structured then it is ready to be passed to stage 3 which is edge computing. Edge computing can be defined as an open architecture in distributed fashion which allows use of IoT technologies and massive computing power from different locations worldwide. It is very powerful approach for streaming data processing and thus suitable for IoT systems. In stage 3, edge computing technologies deals with massive amount of data and provides various functionalities such as visualization, integration of data from other sources, analysis using machine learning methods etc. The last stage comprises of several important activities such as in depth processing and analysis, sending feedback to improve the precision and accuracy of the entire system. Everything at this stage will be performed on cloud server or data centre. Big data framework such as Hadoop and Spark may be utilized to handle this large streaming data and machine learning approaches can be used to develop better prediction models which could help in a more accurate and reliable IoT system to meet the demand of present time.

Major key issues and challenges of IoT

The involvement of IoT based systems in all aspects of human lives and various technologies involved in data transfer between embedded devices made it complex and gave rise to several issues and challenges. These issues are also a challenge for the IoT developers in the advanced smart tech society. As technology is growing, challenges and need for advanced IoT system is also growing. Therefore, IoT developers need to think of new issues arising and should provide solutions for them.

Security and privacy issues

One of the most important and challenging issues in the IoT is the security and privacy due to several threats, cyber attacks, risks and vulnerabilities [ 41 ]. The issues that give rise to device level privacy are insufficient authorization and authentication, insecure software, firmware, web interface and poor transport layer encryption [ 42 ]. Security and privacy issues are very important parameters to develop confidence in IoT Systems with respect to various aspects [ 43 ]. Security mechanisms must be embedded at every layer of IoT architecture to prevent security threats and attacks [ 23 ]. Several protocols are developed and efficiently deployed on every layer of communication channel to ensure the security and privacy in IoT based systems [ 44 , 45 ]. Secure Socket Layer (SSL) and Datagram Transport Layer Security (DTLS) are one of the cryptographic protocols that are implemented between transport and application layer to provide security solutions in various IoT systems [ 44 ]. However, some IoT applications require different methods to ensure the security in communication between IoT devices. Besides this, if communication takes place using wireless technologies within the IoT system, it becomes more vulnerable to security risks. Therefore, certain methods should be deployed to detect malicious actions and for self healing or recovery. Privacy on the other hand is another important concern which allows users to feel secure and comfortable while using IoT solutions. Therefore, it is required to maintain the authorization and authentication over a secure network to establish the communication between trusted parties [ 46 ]. Another issue is the different privacy policies for different objects communicating within the IoT system. Therefore, each object should be able to verify the privacy policies of other objects in IoT system before transmitting the data.

Interoperability/standard issues

Interoperability is the feasibility to exchange the information among different IoT devices and systems. This exchange of information does not rely on the deployed software and hardware. The interoperability issue arises due to the heterogeneous nature of different technology and solutions used for IoT development. The four interoperability levels are technical, semantic, syntactic and organizational [ 47 ]. Various functionalities are being provided by IoT systems to improve the interoperability that ensures communication between different objects in a heterogeneous environment. Additionally, it is possible to merge different IoT platforms based on their functionalities to provide various solutions for IoT users [ 48 ]. Considering interoperability an important issue, researchers approved several solutions that are also know as interoperability handling approaches [ 49 ]. These solutions could be adapaters/gateways based, virtual networks/overlay based, service oriented architecture based etc. Although interoperability handling approaches ease some pressure on IoT systems but there are still certain challenges remain with interoperability that could be a scope for future studies [ 25 ].

Ethics, law and regulatory rights

Another issue for IoT developers is the ethics, law and regulatory rights. There are certain rules and regulations to maintain the standard, moral values and to prevent the people from violating them. Ethics and law are very similar term with the only difference is that ethics are standards that people believes and laws are certain restrictions decided by the government. However, both ethics and laws are designed to maintain the standard, quality and prevent people from illegal use. With the development of IoT, several real life problems are solved but it has also given rise to critical ethical and legal challenges [ 50 ]. Data security, privacy protection, trust and safety, data usability are some of those challenges. It has also been observed that majority of IoT users are supporting government norms and regulations with respect to data protection, privacy and safety due to the lack of trust in IoT devices. Therefore, this issue must be taken into consideration to maintain and improve the trust among people for the use of IoT devices and systems.

Scalability, availability and reliability

A system is scalable if it is possible to add new services, equipments and devices without degrading its performance. The main issue with IoT is to support a large number of devices with different memory, processing, storage power and bandwidth [ 28 ]. Another important issue that must be taken into consideration is the availability. Scalability and availability both should be deployed together in the layered framework of IoT. A great example of scalability is cloud based IoT systems which provide sufficient support to scale the IoT network by adding up new devices, storage and processing power as required.

However, this global distributed IoT network gives rise to a new research paradigm to develop a smooth IoT framework that satisfy global needs [ 51 ]. Another key challenge is the availability of resources to the authentic objects regardless of their location and time of the requirement. In a distributed fashion, several small IoT networks are timely attached to the global IoT platforms to utilize their resources and services. Therefore, availability is an important concern [ 52 ]. Due to the use of different data transmission channels i.e. satellite communication, some services and availability of resources may be interrupted. Therefore, an independent and reliable data transmission channel is required for uninterrupted availability of resources and services.

Quality of Service (QoS)

Quality of Service (QoS) is another important factor for IoT. QoS can be defined as a measure to evaluate the quality, efficiency and performance of IoT devices, systems and architecture [ 34 ]. The important and required QoS metrics for IoT applications are reliability, cost, energy consumption, security, availability and service time [ 53 ]. A smarter IoT ecosystem must fulfill the requirements of QoS standards. Also, to ensure the reliability of any IoT service and device, its QoS metrics must be defined first. Further, users may also be able to specifiy their needs and requirements accordingly. Several approaches can be deployed for QoS assessment, however as mentioned by White et al. [ 54 ] there is a trade-off between quality factors and approaches. Therefore, good quality models must be deployed to overcome this trade-off. There are certain good quality models available in literature such as ISO/IEC25010 [ 55 ] and OASIS-WSQM [ 56 ] which can be used to evaluate the approaches used for QoS assessment. These models provides a wide range of quality factors that is quite sufficient for QoS assessment for IoT services. Table  2 summarizes the different studies with respect to IoT key challenges and issues discussed above.

Major IoT applications

Emerging economy, environmental and health-care.

IoT is completely devoted to provide emerging public and financial benefits and development to the society and people. This includes a wide range of public facilities i.e. economic development, water quality maintenance, well-being, industrialization etc. Overall, IoT is working hard to accomplish the social, health and economic goals of United Nations advancement step. Environmental sustainability is another important concern. IoT developers must be concerned about environmental impact of the IoT systems and devices to overcome the negative impact [ 48 ]. Energy consumption by IoT devices is one of the challenges related to environmental impact. Energy consumption is increasing at a high rate due to internet enabled services and edge cutting devices. This area needs research for the development of high quality materials in order to create new IoT devices with lower energy consumption rate. Also, green technologies can be adopted to create efficient energy efficient devices for future use. It is not only environmental friendly but also advantageous for human health. Researchers and engineers are engaged in developing highly efficient IoT devices to monitor several health issues such as diabetes, obesity or depression [ 57 ]. Several issues related to environment, energy and healthcare are considered by several studies.

Smart city, transport and vehicles

IoT is transforming the traditional civil structure of the society into high tech structure with the concept of smart city, smart home and smart vehicles and transport. Rapid improvements are being done with the help of supporting technologies such as machine learning, natural language processing to understand the need and use of technology at home [ 58 ]. Various technologies such as cloud server technology, wireless sensor networks that must be used with IoT servers to provide an efficient smart city. Another important issue is to think about environmental aspect of smart city. Therefore, energy efficient technologies and Green technologies should also be considered for the design and planning of smart city infrastructure. Further, smart devices which are being incorporated into newly launched vehicles are able to detect traffic congestions on the road and thus can suggest an optimum alternate route to the driver. This can help to lower down the congestion in the city. Furthermore, smart devices with optimum cost should be designed to be incorporated in all range vehicles to monitor the activity of engine. IoT is also very effective in maintaining the vehicle’s health. Self driving cars have the potential to communicate with other self driving vehicles by the means of intelligent sensors. This would make the traffic flow smoother than human-driven cars who used to drive in a stop and go manner. This procedure will take time to be implemented all over the world. Till the time, IoT devices can help by sensing traffic congestion ahead and can take appropriate actions. Therefore, a transport manufacturing company should incorporate IoT devices into their manufactured vehicles to provide its advantage to the society.

Agriculture and industry automation

The world’s growing population is estimated to reach approximate 10 billion by 2050. Agriculture plays an important role in our lives. In order to feed such a massive population, we need to advance the current agriculture approaches. Therefore, there is a need to combine agriculture with technology so that the production can be improved in an efficient way. Greenhouse technology is one of the possible approaches in this direction. It provides a way to control the environmental parameters in order to improve the production. However, manual control of this technology is less effective, need manual efforts and cost, and results in energy loss and less production. With the advancement of IoT, smart devices and sensors makes it easier to control the climate inside the chamber and monitor the process which results in energy saving and improved production (Fig.  9 ). Automatization of industries is another advantage of IoT. IoT has been providing game changing solutions for factory digitalization, inventory management, quality control, logistics and supply chain optimization and management.

A working structure of IoT system in agriculture production

Importance of big data analytics in IoT

An IoT system comprises of a huge number of devices and sensors that communicates with each other. With the extensive growth and expansion of IoT network, the number of these sensors and devices are increasing rapidly. These devices communicate with each other and transfer a massive amount of data over internet. This data is very huge and streaming every second and thus qualified to be called as big data. Continuous expansion of IoT based networks gives rise to complex issue such as management and collection of data, storage and processing and analytics. IoT big data framework for smart buildings is very useful to deal with several issues of smart buildings such as managing oxygen level, to measure the smoke/hazardous gases and luminosity [ 59 ]. Such framework is capable to collect the data from the sensors installed in the buildings and performs data analytics for decision making. Moreover, industrial production can be improved using an IoT based cyber physical system that is equipped with an information analysis and knowledge acquisition techniques [ 60 ]. Traffic congestion is an important issue with smart cities. The real time traffic information can be collected through IoT devices and sensors installed in traffic signals and this information can be analyzed in an IoT based traffic management system [ 61 ]. In healthcare analysis, the IoT sensors used with patients generate a lot of information about the health condition of patients every second. This large amount of information needs to be integrated at one database and must be processed in real time to take quick decision with high accuracy and big data technology is the best solution for this job [ 62 ]. IoT along with big data analytics can also help to transform the traditional approaches used in manufacturing industries into the modern one [ 63 ]. The sensing devices generates information which can be analyzed using big data approaches and may help in various decision making tasks. Furthermore, use of cloud computing and analytics can benefit the energy development and conservation with reduced cost and customer satisfaction [ 64 ]. IoT devices generate a huge amount of streaming data which needs to be stored effectively and needs further analysis for decision making in real time. Deep learning is very effective to deal with such a large information and can provide results with high accuracy [ 65 ]. Therefore, IoT, Big data analytics and Deep learning together is very important to develop a high tech society.

Conclusions

Recent advancements in IoT have drawn attention of researchers and developers worldwide. IoT developers and researchers are working together to extend the technology on large scale and to benefit the society to the highest possible level. However, improvements are possible only if we consider the various issues and shortcomings in the present technical approaches. In this survey article, we presented several issues and challenges that IoT developer must take into account to develop an improved model. Also, important application areas of IoT is also discussed where IoT developers and researchers are engaged. As IoT is not only providing services but also generates a huge amount of data. Hence, the importance of big data analytics is also discussed which can provide accurate decisions that could be utilized to develop an improved IoT system.

Availability of data and materials

Not applicable.

Abbreviations

Internet of Things

Quality of Service

Web of Things

Cloud of Things

Smart Home System

Smart Health Sensing System

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Kumar, S., Tiwari, P. & Zymbler, M. Internet of Things is a revolutionary approach for future technology enhancement: a review. J Big Data 6 , 111 (2019). https://doi.org/10.1186/s40537-019-0268-2

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Unleashing the power of iot: a comprehensive review of iot applications and future prospects in healthcare, agriculture, smart homes, smart cities, and industry 4.0.

1. Introduction

2. applications of iot devices, 2.1. healthcare applications, 2.2. agriculture applications, 2.3. smart home applications, 2.4. smart cities, 2.5. industry 4.0, 3. challenges and active research topics, 3.1. security of iot devices, 3.2. authentication and password security, 3.3. interoperability challenges, 3.4. cloud computing research, 3.5. potential future directions and developments, 4. conclusions, author contributions, institutional review board statement, informed consent statement, data availability statement, acknowledgments, conflicts of interest, abbreviations.

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Chataut, R.; Phoummalayvane, A.; Akl, R. Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4.0. Sensors 2023 , 23 , 7194. https://doi.org/10.3390/s23167194

Chataut R, Phoummalayvane A, Akl R. Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4.0. Sensors . 2023; 23(16):7194. https://doi.org/10.3390/s23167194

Chataut, Robin, Alex Phoummalayvane, and Robert Akl. 2023. "Unleashing the Power of IoT: A Comprehensive Review of IoT Applications and Future Prospects in Healthcare, Agriculture, Smart Homes, Smart Cities, and Industry 4.0" Sensors 23, no. 16: 7194. https://doi.org/10.3390/s23167194

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Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future

Sandro nižetić.

a LTEF-Laboratory for Thermodynamics and Energy Efficiency, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Rudjera Boskovica 32, 21000, Split, Croatia

Petar Šolić

b Department of Electronics, Faculty of Electrical Engineering, Mechanical Engineering and Naval Architecture, University of Split, Rudjera Boskovica 32, 21000, Split, Croatia

Diego López-de-Ipiña González-de-Artaza

c Faculty of Engineering, DeustoTech - Fundación Deusto, Universidad de Deusto, Despacho 545 Avda, Universidades 24, 48007, Bilbao, Spain

Luigi Patrono

d Department of Innovation Engineering, University of Salento, Ecotekne Campus - S.P. 6, Lecce, Monteroni, 73100, LECCE, LE, Italy

The rapid development and implementation of smart and IoT (Internet of Things) based technologies have allowed for various possibilities in technological advancements for different aspects of life. The main goal of IoT technologies is to simplify processes in different fields, to ensure a better efficiency of systems (technologies or specific processes) and finally to improve life quality. Sustainability has become a key issue for population where the dynamic development of IoT technologies is bringing different useful benefits, but this fast development must be carefully monitored and evaluated from an environmental point of view to limit the presence of harmful impacts and ensure the smart utilization of limited global resources. Significant research efforts are needed in the previous sense to carefully investigate the pros and cons of IoT technologies. This review editorial is partially directed on the research contributions presented at the 4th International Conference on Smart and Sustainable Technologies held in Split and Bol, Croatia, in 2019 (SpliTech 2019) as well as on recent findings from literature. The SpliTech2019 conference was a valuable event that successfully linked different engineering professions, industrial experts and finally researchers from academia. The focus of the conference was directed towards key conference tracks such as Smart City, Energy/Environment, e-Health and Engineering Modelling. The research presented and discussed at the SpliTech2019 conference helped to understand the complex and intertwined effects of IoT technologies on societies and their potential effects on sustainability in general. Various application areas of IoT technologies were discussed as well as the progress made. Four main topical areas were discussed in the herein editorial, i.e. latest advancements in the further fields: (i) IoT technologies in Sustainable Energy and Environment, (ii) IoT enabled Smart City, (iii) E-health – Ambient assisted living systems (iv) IoT technologies in Transportation and Low Carbon Products. The main outcomes of the review introductory article contributed to the better understanding of current technological progress in IoT application areas as well as the environmental implications linked with the increased application of IoT products.

Graphical abstract

1. Introduction

With rising technological developments in society, new possibilities have occurred and that could simplify our daily life and provide more efficient services or production processes. Digitalization has allowed ‘‘smart’’ ( Zheng et al., 2019 ) to become the epicentre of already ongoing technological developments. In fact, IoT technologies are nowadays assumed to be one of the key pillars of the fourth industrial revolution due to significant potential in innovations and useful benefits for the population. On the other side, each development utilizes limited resources leaving behind different environmental footprints, ( Li et al., 2020a ), especially different kinds of pollutants, ( Zeinalnezhad et al., 2020 ). Internet of things (IoT) based technologies bring a completely new perspective on the further progress of various fields, such as for instance in engineering, ( Zaidan and Zaidan, 2020 ), agriculture ( Farooq et al., 2020 ), or medicine ( Salagare and Prasad, 2020 ), and in other fields that have not been explored yet. Some potential application areas in IoT technologies are still unknown or insufficiently clear on how to approach them which is an evident indication that more intense research activity should be conducted in this challenging field towards new and important potential benefits for society. Therefore, the relevance and importance of IoT technologies in future terms are more than clear and should play an important role.

The rise of IoT technologies is currently intense and according to projections for the next 10 years, over 125 ·10 9 IoT devices are expected to be connected, ( Techradar, 2019 ). The expected investments in IoT technologies are also high with expectations being over 120 ·10 9 USD by 2021, with a compound annual growth rate of about 7.3%, ( Forbes, 2018 ). The general present market structure of IoT technologies is presented in Fig. 1 , where it is evident that the majority of the market is focused on smart cities and industrial IoT.

General market structure of IoT technologies ( Nižetić et al., 2019 ).

If recent projects in IoT technologies are being analysed than most of them are in the field of smart cities and industrial IoT. Other significant potentials are connected buildings, connected cars and energy segments ( Forbes, 2018 ), but lower than the first mentioned fields. It is also found that the most rising trend in the number of IoT projects currently is as expected in smart cities, connected health and smart supply chain segments, with an annual rise over 30% in the EU and USA. Industrial IoT, connected cars and agriculture segments has recorded a decrease in the number of realized projects, i.e. over 25% in the USA and EU, ( Forbes, 2018 ). From a perspective of high upcoming population pressure on cities and because a population of almost 11 ·10 9 is expected by the end of the century ( Pewresearch, 2019 ), the smart city concept could become a vital one to allow for a normal operation of highly populated cities.

In order to support the rapid technical development of IoT technologies, as well as novel potential applications areas, specific technical issues would need to be resolved, ( Techradar, 2019 ). One of the main issues is associated with the development of different tools for the monitoring of network operations ( Kakkavas et al., 2020 ), then issues with security tools and their management, ( Conti et al., 2020 ), issues with software bugs, demanding maintenance of IoT networks, and finally security issues related to IoT networks, ( Almusaylim et al., 2020 ). The important problem linked with the efficient implementation of IoT technologies is linked with the available speed and coverage of wireless networks (Wi-Fi), where expectations are high due to noticeable increases in Wi-Fi network coverage in the period of 2017–2022 as well as increases in Wi-Fi speed Fig. 2 . In a global sense, increases in Wi-Fi speed are expected for more than a factor of two, i.e. from about 24 Mbps to more than 54 Mbps. The most intense increase in Wi-Fi speed is expected in the Asian region, ( Zdnet, 2018 ).

Expected increase in global Wi-Fi speeds in period of 2017–2022 ( Zdnet, 2018 ),

The lowest Wi-Fi speed is noticeable in the Latin America and Middle East&Africa regions, which are an indication of potential problems for the efficient implementation of IoT products or novel more advanced upcoming technologies.

An increased implementation of IoT technologies would lead to a more intense utilization of fossil technologies to ensure the necessary energy supply for IoT production lines. The production of electronic equipment is causing potentially unbalanced waste of limited metals and resources in general, which could become a critical issue in the long run. Unfortunately, the recycling rate of electronic waste is low and currently in the amount of about 20% ( Thebalancesmb, 2020 ) which makes matters questionable regarding the available resource capacity to produce IoT products when taking into accounts the rising market demands. The production of electronic gadgets has led to the consumption of various chemicals, water and finally fossil fuels that have all left environmental impacts. As already tackled, different metals are also being used to produce electronics such as copper, silver, gold, palladium etc. One of the major issues is the led content in e-waste and its severe impact to the environment. Recycling in the previous sense is very important, where the present recycling rate of electronic equipment is certainly not sufficient and must be increased. Globally, the annual rise of the recycling rate ranges from about 4% to 5% ( Thebalancesmb, 2020 ). The legislation related to the e-waste is one of the main drawbacks since more than 50% of world population is still not well covered with proper legislation related to e-waste, ( Globalewaste, 2017 ), which is preventing the further development of e-waste facilities. The market value of raw materials from e-waste is estimated to be more than 50·10 9 Euros, ( Globalewaste, 2017 ). Certainly, more strategic and targeted actions are needed in the e-waste issue to secure a more balanced and sustainable development of IoT technologies. Overall, the annual generation of e-waste is more than 44·10 9 metric tonnes, which is equivalent to more than 6 kg per inhabitant annually, ( Globalewaste, 2017 ). A potential exists and must be better utilized to ensure a sufficient quantity of valuable raw resources.

It should be highlighted that there is no doubt in what IoT technologies would bring to the table, such as various useful benefits to society and an overall improvement in life quality. Each technology has specific issues and drawbacks that need to be detected and closely investigated on time, since IoT technologies have the potential to change our lives and habits. Several important facts need to be emphasized when addressing IoT technologies to be able to understand the long-term effects associated with the fast development of IoT:

• - IoT technologies have caused an increase in the utilization of limited resources or raw materials where some of them have become rare or are already rare (for instance, specific precious metals for electronics),
• - The prices of electronic devices have become more acceptable, which means an increase in production volume, finally more resources are being utilized. A rebound effect is possible in that sense,
• - The long term environmental impacts of IoT technologies are unknown. A noticeable amount of energy would be needed to support the production and operation of IoT devices,
• - An increase in electronic waste is expected due to the large estimated number of IoT based devices in the near future,
• - In some sectors, IoT technologies could have social impacts due to the reduced necessity for labour and limitation of direct social contacts, which is vital and an important aspect for each human being.

The main point of the above raised issues is not to indicate and create a negative attitude towards IoT technologies but to carefully analyze the overall aspects in order to secure a smart and sustainable development of IoT technologies, which are a valuable opportunity for humanity.

1.1. Necessity for smart technologies

The world is rapidly changing, i.e. developing in a technological sense and is being driven by the present economic system globally. Unfortunately, each technological development has got its price, which can be sensed through the intense utilization of limited fossil-based resources and the production of various impacts to the environment, ( Chen et al., 2020a ). The population is constantly growing with an annual rate of about 1.1% per year with the current population being over 7.7·10 9 ( Data.worldbank, 2020 ). As previously addressed, the population concentration is in cities and according to UN projections, about 68% of the population will be living in cities by 2050, ( UN, 2018 ). A significant infrastructure pressure is expected in cities due to boosted urbanization, thus novel technological solutions would be key to secure the normal operation of cities in the given complex and demanding circumstances. In the previous sense, the general application of IoT and smart technologies would have an important role and could help to bridge some major infrastructure related issues in cities. The necessity for IoT technologies is closely linked with ongoing technological advancements and digitalization where a variety of different electronic products need to be somehow connected in a useful manner. There is a necessity for more efficient services and flexible processes in general, which could be obtained with the proper implementation of IoT technologies. IoT technologies have allowed for a variety of efficient services and smart networking, applications or devices that can ensure useful synergic effects and produce benefits. The major advantage of IoT technologies is their connectivity aspect that has enormous potential, Fig. 3 .

General structure of IoT network and connectivity ( Zhang et al., 2018 ).

Various benefits are possible and would be gradually integrated in our lives thorough upcoming years in different application areas and will be briefly discussed in the upcoming section of the introductory review editorial.

1.2. Application areas

The application areas of IoT are various and based on current available technological solutions, the most represented application sectors are shown in Fig. 4 . The most important and most progressing application areas of IoT are related to the industry ( Osterrieder et al., 2020 ) and smart city concept ( Sivanageswara Rao et al., 2020 ), with respect to the number of realized projects.

Application areas of IoT technologies.

The transportation ( Porru et al., 2020 ), smart energy management in buildings ( Douglas et al., 2020 ) or management of power networks ( Martín-Lopo et al., 2020 ), as well as the agriculture sector ( Villa-Henriksen et al., 2020 ) are also promising, having significant potential.

The development of specific IoT application areas strongly depends from several key factors such as:

• - general available advancements in electronic components,
• - available software solutions and user friendly surrounding,
• - solutions related to sensor technologies and data acquisition,
• - quality of network, i.e. network connectivity and infrastructure,
• - sufficient energy supply for production and operation of IoT devices.

In the continuation of the review editorial, some key IoT application areas will be briefly addressed together with the main developments and current challenges.

1.2.1. IoT in industry

The application of IoT technologies in industrial applications would allow for an increase in efficiency regarding the production process and would ensure more efficient communication and networking between operators and machines, Fig. 5 . Finally, it would allow for more competitive companies on the market with more efficient quality control with a minimization in losses. A critical feature would be the development, design and integration of various useful sensors in the industrial applications ( Li et al., 2020b ), to form integral and effective management systems. More intense research efforts are needed towards an efficient application of IoT technologies in the industry and to better understand how IoT technologies could be implemented in specific industries where benefits would be possible. Progress is crucial in the sense of how to connect different industrial sensors, use and process the collected various data to enable enhanced industrial processes, i.e. ensue for instance smart IoT based Computer-Integrated Manufacturing, ( Chen et al., 2020b ).

General concept of IoT industrial application ( Aazam et al., 2018 ).

1.2.2. IoT in smart city concept

The role of IoT technologies in the smart city concept ( Janik et al., 2020 ) is crucial to bridge the already mentioned global infrastructural challenges in cities, which are linked with the current increase of population in cities. IoT technologies in smart cities would enable the utilization of different devices, which would increase the life quality in cities as well as the efficiency of different daily services such as transportation, security (surveillance), smart metering, smart energy systems, smart water management, etc. Different sensing devices would receive information, which would be processed towards efficient and useful solutions. The main benefit of IoT technologies in smart cities would be directed to the early detection of different problems or infrastructural faults (such as issues with traffic jams, energy supply, water shortage, security incidents, etc.). In smart cities, many sensors are installed and linked with many other devices over the internet which gives information to the users as for instance parking spaces, any malfunctions, electrical failure and many other issues. Developing these technologies would help in leading the cities towards smart grids, smart healthcare, smart warehouses, smart transportation, smart waste management, smart communities, etc. Different implementation challenges towards the smart city concept exists, Fig. 6 and should be solved for various applications, ( Fig. 7 ).

Different challenges in Smart City concept ( Bhagya et al., 2018 ).

Various smart home management systems ( Zhou et al., 2016 ).

The most present implementation challenges are linked with the efficient integration of different sensing technologies, development of a suitable network infrastructure, education of population, investigation of the sustainability aspect, such as carbon footprint, etc.

The application of IoT technologies in smart homes, ( Moniruzzaman et al., 2020 ), within the smart city concept allows for an increase in the life quality within residential facilities, bringing novel and attractive technological solutions. Both, energy and fund savings could be reached with more efficient time management, which is a valuable feature in our present economic system. Different control options are possible within the smart home concept and enable an efficient integration of renewable energy technologies in homes ( Stavrakas and Flamos, 2020 ), and their efficient balancing (efficient supply and demand).

1.2.3. IoT in agriculture

Efficient agriculture production is a necessity for our population to prevent the potential lack of food resources in future terms caused by different factors, ( Hussain et al., 2020 ). The first factor is constant population growth, as already emphasized, the second is linked with climate change issues ( Yang et al., 2020 ), which is causing a reduction in the yields of important crops, or some areas are even becoming unsuitable for efficient agriculture production. The food waste issue is one of the major problems ( Keng et al., 2020 ), since it has become a global problem, especially in developed economies. It is estimated that more than 28% of available agriculture areas is ‘‘reserved’’ for food waste and unfortunately more than 800·10 6 people are currently hungry, ( Fao.org, 2020 ). The implementation of IoT technologies in agriculture can certainly help to secure sufficient food demands and increase the efficiency of agricultural production processes in general. Various useful data about crops could be collected and used for yield monitoring and the detection of potential diseases in advance that can significantly reduce the yields of specific crops. The monitoring of soil and nutrients would rationalize agricultural production processes and lead to water savings that are precious in some specific geographical regions, which could be utilized through smart irrigation systems, ( Xin et al., 2020 ). A more precise seeding could also be ensured and fertility crop management in general, Fig. 8. There are some issues linked with the efficient application of IoT technologies in agriculture production. Different sensing and monitoring technologies should be developed and a better education of farmers should be provided (i.e. development of standard education modules for farmers). Due to a large quantity of collected data, farmers could be potentially overwhelmed, ( Ec.europa, 2017 ). Therefore, there is a necessity for the development of standard trainings (education modules) for farmers coupled with the development of more user-friendly software solutions.

IoT in agricultural production from farmer’s perspective.

The application of IoT technologies in the agricultural sector would lead to advancements that could drastically modify current production procedures in agriculture, ( Shafi et al., 2020 ) ( Fig. 8 ).

1.2.4. IoT in waste management

Waste management towards a circular economy concept ( Fan et al., 2019 ) is a vital current population problem, where there is certainly a role for IoT technologies that could help provide more efficient waste management in specific areas ( Voca and Ribic, 2020 ) and recycling of different limited resources, ( Qiu et al., 2020 ). Currently, various technological solutions are being developed to support the smart waste management concept, ( Das et al., 2019 ). Some of them are already available on the market for wide implementation, ( Iot.farsite, 2020 ). The developed solutions are mostly directed towards the smart monitoring of waste bins ( Dhana Shree et al., 2019 ), i.e. bin filling level detection, waste temperature and fire detection, bin vibration occurrence and bin tilt, presence of waste operators, waste humidity, bin GPS location etc. In general, smart waste management systems, can be effectively supported by IoT devices, Fig. 9 . IoT technologies could also be used for the smart coordination of waste trucks ( Idwan et al., 2020 ) and efficiency waste utility companies could be ensured in that manner, which would be followed by a reduction of harmful emissions (pollutants) created by garbage trucks, ( Kozina et al., 2020 ). From the perspective of smart technologies, the proper and IoT based waste management of electronic waste is very important ( Kang et al., 2020 ) to secure sufficient raw resources to produce electronic equipment as already highlighted. IoT technologies could also be used for the reduction of food waste through intelligent appliances and a developed management structure in that sense, ( Liegeard and Manning, 2020 ).

IoT in smart waste management system, ( Quamtra, 2020 ).

Innovative IoT based technological solutions are expected to be developed in upcoming years, especially from a smart city concept perspective and that could support smart waste management systems and a circular economy concept.

1.2.5. IoT in healthcare

One challenging implementation field of IoT technologies has been detected in the healthcare system in general, through the e-health concept, ( Farahani et al., 2020 ). An increase in the service quality of healthcare systems could be utilized through IoT support (mainly collection of patient health data) and finally with the improvement of patient safety and care since it could also lead to an increase in patient life expectancy. There is an enormous potential in smart medical devices for different purposes ( Papa et al., 2020 ) that can be utilized for the monitoring of various vital and valuable human functions such as heart rate, skin temperature, movement monitoring, etc. Remote health monitoring is also an interesting perspective that could be utilized with the proper support of IoT devices and products. The prediction of different symptoms and prevention of potentially life hazardous states and diseases could generally be enabled, ( Muthu et al., 2020 ). Assistance to the elderly could also be ensured by monitoring a patient’s general health condition and nutrition status ( Nivetha et al., 2020 ), that would be supported via IoT devices. Rehabilitation after a serious disease could also be efficiently supported with IoT technologies, especially in cases of home rehabilitation circumstances, ( Bisio et al., 2019 ). One of the main issues and challenges in this specific IoT application field would be to ensure proper cyber safety due to potential attacks that could occur within healthcare monitoring systems, ( John et al., 2019 ). Significant progress in upcoming years is expected in the field of software development for health care systems, i.e. especially in hospitals. Namely, different devices could be linked via advanced software solutions as for example MRIs or CT devices and connected with laboratory data to create a smart hospital information system. The previously mentioned approach would allow for the better treatment of patients, detection of medical priorities and support for medical staff in monitoring and therapy decisions. IoT systems could also be used in hospitals for the efficient maintenance of a large number of medical devices ( Shamayleh et al., 2020 ). Equipment costs could be reduced in hospital systems due to the early detection of severe equipment malfunctions that could affect the accuracy of specific readings from medical devices. The development of smart and based IoT solutions in healthcare systems could also be very useful in the case of severe global pandemic states (data collection and fast data diversity, resources of medical staff and resources, medical triage, etc.), such as is the recent corona virus situation that has severely threatened the global population, ( WHO, 2020 ). The healthcare sector is probably one of the most challenging areas for IoT, thus important progress is expected in the upcoming year with serious benefits for the population.

1.2.6. IoT in transportation

Transportation modes will be significantly changed in upcoming decades, ( Jonkeren et al., 2019 ), especially due to the expected rising implementation of electric cars on the market, ( Capuder et al., 2020 ). The upcoming ban of Diesel based vehicles due to environmental issues ( Li et al., 2020c ) and finally development of alternative transportation technologies, such as hydrogen based vehicles for example ( Ajanovic and Haas, 2019 ), would change the shape of future transportation systems. In general, there is a demand for more environmentally suitable transportation options that are already being gradually developed with an expected penetration on the market. A necessary development of transportation infrastructure is needed for specific vehicle technologies to ensure desirable vehicle autonomy. Nowadays, the IoT emerged in the ‘‘internet of vehicles’’ concept ( Shen et al., 2020 ), which just proves its potential in this important area. The most significant IoT application area is in the case of the smart car (vehicles) concept, ( Chugh et al., 2020 ). The smart car concept considers the utilization and optimization of different internal functions in the car that are supported by IoT technologies. The application of IoT would upgrade driver experience and increase in comfort and safety. Specific data are collected in the smart car and associated with the main operating parameters such as tyre pressure, fuelling, early detection of potential failures, regular maintenance indicators, etc. In general, improved service as well as added value for customers could be obtained with a targeted utilization of IoT technologies, which finally can improve competition in the automobile industry between vehicle manufacturers. The challenging aspect of IoT application is in the case of autonomous vehicles, ( Padmaja et al., 2019 ). Location, direction as well as a planned path of the autonomous vehicle could be efficiently supported with IoT in general as well as the monitoring of safety systems for autonomous vehicles, ( Bylykbashi et al., 2020 ). The most important issue with autonomous vehicles is the prevention and avoidance of crash vehicle accidents, which could be solved with a targeted utilization of IoT devices, ( Abdou et al., 2019 ). Smart parking is also currently one of the most developing IoT areas when considering the transportation sector in general terms. Different research efforts are provided in that sense with the main goal being to enable the latest status of available parking space, control and monitoring of different useful parking space information in real time, ( Luque-Vega et al., 2019 ). Again, the development of sensor technologies, i.e. smart parking sensors is very important to enable efficient and accurate service, ( Perković et al., 2020a ). The maintenance and failure prevention of different vehicles could also be supported by IoT ( Saki et al., 2020 ), which could improve security and the lifetime of vehicles. Taking all the previously addressed into account, IoT technologies could completely change the driving experience and generally improve the quality of transportation systems from various aspects.

1.2.7. IoT in smart grids and power management

Energy transition ( Biresselioglu et al., 2020 ) has become a necessity due to the potential shortcomings of fossil fuel resources in future terms and for the reduction of different pollution impacts that are associated with the utilization of various fossil-based technologies, ( Bielski et al., 2020 ). Since a more intense implementation of renewable energy technologies has already been occurring, the efficient and advanced power management of electric grids has become an important aspect. Efficient demand side management with accurate and flexible smart metering technologies are key factors to enable smart power management in smart grids, ( Mendes et al., 2020 ). The most important role of IoT technologies in smart grids is to save electricity ( Rishav et al., 2019 ), with efficient distribution of electricity, Fig. 10 . The collection of specific grid data through IoT devices, and later their analysis with the proper software, could help improve grid reliability and efficiency. The economic aspect of electricity could also be improved with IoT due to the already mentioned efficiency improvement as previously highlighted. Useful benefits could be ensured both for customers and service providers.

Concept of smart grids ( Tuballa and Lochinvar Abundo, 2016 ),

A demand side management in households is also an important application area of IoT, ( Rahimi et al., 2020 ). Homes are typically equipped with different appliances that are becoming more advanced, creating the possibility for an efficient operation with the regulation of IoT, ( Tawalbeh et al., 2019 ). The efficient and smart forecasting of electricity demands for households could also be effectively supported by IoT technologies, ( Nils et al., 2020 ). An expected higher penetration of renewables in households through hybrid energy systems as an example ( Gagliano et al., 2019 ), would also require a smart operation strategy that could be utilized by IoT through integrated smart nano-grids, ( Kalair et al., 2020 ). A growth of IoT products and technologies in smart power management is expected to enable accurate forecasting and different load strategies in the case of renewable generation, ( Pawar et al., 2020 ). The elaborated main issues and challenges above just reflect the importance of IoT devices in smart grids and power management.

1.3. Review methodology

By addressing all the above raised general challenges towards an efficient and suitable implementation of IoT technologies, it is evident that more intense research efforts are needed to lead to further advancements in this dynamic research topic, with a strong application potential. A synergy of different research efforts in the field, mainly focused on the targeted topical area is needed. The main contribution and novelty of this review editorial is in line with that. Further main topical areas are addressed in the herein review introductory editorial;

• - IoT technologies in sustainable energy and environmental issues,
• - IoT enabled Smart City
• - E-health – Ambient assisted living systems
• - IoT technologies in Transportation and Low Carbon Products

The main objective of the herein presented review editorial is to address and discuss the latest advancements in the above specified and key IoT application areas. This review editorial serves as an introduction to the Virtual Special Issue (VSI) of JCLEPRO devoted to the 4th International Conference on Smart and Sustainable Technologies (SplTtech 2019) held on 18–21 June 2019, in Bol (Island of Brač) and Split, at the University of Split, (Croatia). The herein presented introductory review editorial was directed to the selected and accepted publications from the international conference SpliTech2019 and published papers were divided into four main topical areas as already specified above. Overall 38 papers were initially selected and invited for potential inclusion in the VSI SpliTech 2019. After conducted peer-review process, based on the JCLP procedures, 29 of them were selected for inclusion in the VSI SpliTech 2019. Authors from following countries have contributed VSI SpliTech 2019: China, India, Australia, Canada, Italy, Croatia, Serbia, Greece, Poland, Czech Republic, Spain, Cyprus, Turkey, Norway, Iran, Germany, Brazil, Malaysia, Pakistan, Dubai and United Kingdom. Besides the selected VSI SpliTech2019 works published in the JCLEPRO, the other relevant and latest works from the existing literature in the field were also addressed using the Scopus database, ( Scopus, 2020 ). Based on the conducted review as well as selected contributions in this VSI the key issues were identified, discussed and highlighted in the conclusion section.

2. IoT technologies in sustainable energy and environment

The rapid development of information technologies caused in one sense the necessity for ‘‘energy digitalization’‘. The increasing application of renewable energy technologies and development of efficient policies will be key points in upcoming decades to be able to secure global energy transition goals, ( Tzankova, 2020 ). Referring to the previous, the development of alternative renewable energy sources would also be valuable, ( Nižetić, 2010 ). Different energy scenarios or options have been considered in recent years involving a high share of renewables via hybrid energy options ( Nizetic et al., 2014 ), or for instance the possible application of alternative energy sources such as hydrogen technologies in different implementation fields ( El-Emam et al., 2020 ), or vehicle applications ( Matulić et al., 2019 ). The focus of the research is to investigate the techno-economic viability of different energy concepts in order to secure a suitable mix of energy technologies that would support an efficient energy transition. An improvement in the energy efficiency of different renewable energy technologies is also important, especially in the case of photovoltaics ( Grubišić-Čabo et al., 2019 ) and wind generation technologies ( Marinić-Kragić et al., 2020 ), to secure large scale projects. The efficiency of specific production processes ( Giama et al., 2020 ), is also vital and certainly needs to be carefully investigated and analysed, to reduce energy intensity and provide a circular economy concept in specific application areas, ( Xu et al., 2020 ). The main research efforts should be directed towards the upgrade of energy saving technologies followed with the increasing utilization of renewable energy sources, ( Klemeš et al., 2019 ). Recent technological progress in the field of IoT technologies has enabled different opportunities for the possible application of IoT concepts in the energy sector and environmental protection to secure a sustainable development.

Energy and environment are two of the most important elements of Smart Cities and are very often closely interrelated concepts. The available challenges in energy management to use and generate energy in the most efficient manner possible, and the development of a sustainable energy structure can take advantage of Internet of Things (IoT) and Internet of Energy (IoE) technologies, Fig. 11 ( Mohammadian, 2019 ) or in the case of battery charging protocols ( Fachechi et al., 2015 ).

IoE architecture ( Mohammadian, 2019 ).

The climate change and global warming impose a paradigm shift in the exploitation of resources and in more efficient energy resource management: production, distribution and consumption, as an integral part of this vision. The energy transition must point to an infrastructure change at the center of which there are the so-called smart grids. With the advent of smart grids and new technologies, the energy industry is inexorably changing. The most interesting aspect is that smart grids ensure flexibility in demand and allow consumers to participate in the energy system, as prosumers. Smart grids exploit digital and innovative technologies to manage and monitor the transport of electricity from all sources of generation to promptly, quickly and effectively satisfy the demand of end users. Smart grids are raising reliability, system resilience and stability, and minimizing disruptions, costs and environmental impacts. Some of these new technologies such as Distributed Generation (DG) and microgrids provide energy locally, creating larger and more reliable networks and reducing the line overload. Energy storage complements the energy from renewable sources while microgrids help reduce any blackouts by providing energy locally. Unlike the existing power system of a unidirectional system, which distributes electricity generated from a power plant to the consumer, the microgrid is equipped with a local power supply and storage system centered on independent distributed power sources. It is an energy network that can connect with an existing power system as needed and the self-sufficiency of energy such as electricity and heat by using multiple distributed power sources independently. In addition to giving owners the ability to generate their own energy, microgrids also reduce the dependency on energy providers by helping reduce costs and avoid peak usage charges. The microgrid can produce revenue if it were to produce a surplus of power, which could be sold to the energy provider. Recent works in the energy related field are discussed in the upcoming section of the paper to highlight IoT implementation areas and clarify the benefits in specific engineering applications.

In microgrids, IoT technologies are introduced mainly to realize a smart system able to autonomously schedule loads and/or detect system faults and then improving the efficiency of the energy consumption. The work ( Nayanatara et al., 2018 ) proposes a renewable energy based microgrid management strategy to use renewable energy (solar energy from a photovoltaic panel and wind energy from a wind turbine) effectively reducing the energy usage from the power grid. IoT technologies are used to realizing a smart scheduling algorithm able to control schedulable loads as per the needs of the consumer. Authors demonstrate that the proposed energy management system installed in an institution enables low power consumption and reduced costs. In ( Sujeeth et al., 2018 ) an IoT-based automated system that constantly monitors the current and voltage flowing through various branches of a DC microgrid, detects and controls the fault clearance process during fault conditions that has been developed. The system is capable to alert the user during overcurrent faults, ground faults and short circuit faults. As the operation of a microgrid is automated, the need for human decision making is eliminated and the minimum reaction time to react to fault conditions is drastically reduced. The work ( Majee et al., 2018 ) is also focused on the issue of fault management within a microgrid exploiting the IoT. The concept of IoT is used to solve the issues of microgrid reconfiguration occurring due to faults, changing energy usage patterns and the inclusion and removal of distributed energy resources.

Smart grids can automatically monitor energy flows and adapt to changes in energy demand and supply in a flexible and real-time manner. These smart systems can benefit from technologies such as machine learning ( Chou et al., 2019 ) and artificial intelligence ( Bose, 2017 ) to perform predictive analyzes and better configure all the devices. To do this, however, smart grids require adequate and equally intelligent measuring instruments. Here, smart metering tools could be efficient solution, reaching the consumers and suppliers, providing them with information on consumption in real-time. With smart meters, consumers can adapt - in terms of time and volume - their energy consumption to different energy prices during the day, saving on their energy bills by consuming more energy in periods of lower prices. In this perspective, the possibilities generated by improved digitization and sensorization, utilizing to the Internet of Things solutions, has led many research works to focus on realizing innovative IoT-based hardware and software solutions. These solutions are capable of providing real-time information about the quality usage of appliances, data consumption, and energy flow information ( Morello et al., 2017 ). present an interesting study on the role of advanced smart metering systems in the electric grid of the future through the realization and the experimental validation of a smart meter, Fig. 12 . The cost effective three phase smart energy meter, IoT enabled, multi-protocol and modular, capable to collect, process, and transmit several electric energies related information, mainly focused on consumer-side, to any smart energy control system was proposed by ( Avancini et al., 2018 ), Fig. 13 .

Proposed smart power meter, ( Morello et al., 2017 ).

Photo of created IoT enabled smart energy meter ( Avancini et al., 2018 ).

Several solutions are also based on the use of the Arduino platform ( Arduino, 2020 ) and a few sensors for the realization of low-cost smart meters ( Patel et al., 2019 ) or for instance Arduino based solutions ( Saha et al., 2018 ). Although smart grids are fundamental elements when it comes to energy sustainability, it is reductive to identify the concept of smart energy only in them. In fact, smart buildings also play a crucial role. The energy efficiency of building structures using smart technologies provides an increasingly intelligent management of resources, avoiding waste, improving the life quality of people and making the buildings themselves more resilient in the face of current climate changes. Thanks to building automation and IoT not only individual buildings but also entire neighborhoods can be controlled remotely from an energy point of view and in terms of the security. For example, it is possible to carry out checks on air pollution remotely ( Becnel et al., 2019 ), monitor fire systems ( Cavalera et al., 2019 ) or, furthermore, immediately detect any intrusion by outsiders ( Dasari et al., 2019 ).

Smart buildings are able to monitor actual energy needs, optimizing consumption and therefore counting not only on green energy, but also on a high degree of energy efficiency. The virtuous process that passes from smart energy allows to count on Nearly (Net) Zero Energy Building (NZEB) ( Rushikesh Babu and Vyjayanthi, 2017 ) and on a wider energy sustainability.

The most common use of IoT for energy and environmental sustainability is in the home automation systems, which allow homeowners to live comfortably and manage energy consumption through connected devices. In this field, numerous applications have been implemented and, despite the common goal of creating an Energy Management System (EMS) for home, the techniques used to achieve it can be very different. For example ( Li et al., 2018 ), propose a self-learning home management system that exploits computational and machine learning technologies, Fig. 14 . The proposed system has been validated by collecting real-time power consumption data from a Singapore smart home. In ( Al-Ali et al., 2017 ), an EMS for smart home is realized exploiting off-the-shelf Business Intelligence (BI) and Big Data analytics software packages to better manage energy consumption and meet consumer demands. In this work, the proposed system has been validated realizing a case study based on the use of HVAC (Heating, Ventilation and Air Conditioning) Units. Smart energy solutions such as those analysed provide real-time visibility of consumption and billing data, helping consumers to save resources, while energy and service companies can better balance production to meet actual demands, reducing potential problems. As the main effect, the energy consumption of families is reduced, also decreasing our impact on climate change.

Self-learning home management system architecture ( Li et al., 2018 ).

In addition to buildings and homes, industrial facilities and enterprises also deal with the adoption of innovative energy efficiency solutions to optimize resource consumption and reduce costs, but they need to evaluate a high number of factors to adopt the best energy efficiency measures. The work ( Suciu et al., 2019 ) proposes an IoT and Cloud-based energy monitoring and simulation platform to help companies monitor energy production and consumption, forecast the energy production potential and simulate the economic efficiency for multiple investment scenarios.

The concept of sustainability is increasingly linked to that of circular economy, which is now considered the key to this new paradigm. Unlike the traditional linear economy, based on the so-called “take-make-dispose” scheme, which provides for a complete utilization of resources, the circular economy model promotes reparability, durability and recyclability. In practice, the circular economy aims to minimize waste through reuse, repair, refurbishment and recycling of existing materials and products, focusing attention on designs that last over time. In this system, the IoT is considered an essential element, as it offers new opportunities in various sectors, such as manufacturing, energy and public services, infrastructure, logistics, waste management, fishing and agriculture. Especially in the field of waste management, research has made great strides through the creation of innovative systems capable of concretizing the concept of digital economy. In the work ( De Fazio et al., 2019 ) the activities related to the research project called POIROT were discussed, which exploit innovative hardware and software technologies, aiming to realize a platform for the inertization and traceability of organic waste. In detail, the main project objective is to realize a targeted transformation, through technological processes, regarding the organic fraction of urban solid waste, into inert, odorless and sanitized material, identified and traced to be employed for building applications or as thermal acoustic insulator, Fig. 15 .

Architecture of proposed identification and traceability system, ( De Fazio et al., 2019 ).

Several works propose solutions to support waste management at a domestic level, simplifying the waste separation to avoid problems due to improper waste management including hazards for human health or environmental issues. For example ( Al-Masri et al., 2018 ), propose a server-less IoT architecture for smart waste management systems able to identify waste materials prior to the separation process. This allows reducing costs related to the waste separation process from hazardous materials such as paint or batteries ( Kumar et al., 2017 ). propose a hygienic electronic system of waste segregation. The proposed approach eases the segregation of wastes at source level and thereby reducing the human interaction and curbs the pollution caused by improper segregation and management of wastes at source level.

The role of IoT supported smart meters was considered in the work ( Mendes et al., 2020 ) to address different demand side management scenarios. The novel and adaptive compression mechanism was proposed in the same work to improve the communication infrastructure for the given case, i.e. complete controlling structure, Fig. 16 . The proposed mechanism can reduce the quantity of data sent to utility companies and can automatize energy consumption management.

Proposed general controlling structure ( Mendes et al., 2020 ).

The proposed and tested control solution showed to be efficient with respect to the considered application, since compression rates were satisfactory and the proposed concept showed potential for other applications. The demand side management of a hybrid rooftop photovoltaic system was discussed in ( Kalair et al., 2020 ) where the system was integrated in a smart Nano grid. The smart monitoring system was presented in detail for residential purposes, together with a developed experimental setup that contains specific electronic components, Fig. 17 . The developed controller can automatically detect any frequency and voltage changes and link them with specific loading patterns. The proposed solution demonstrated efficiency since the power supply reliability was up to 97%. The proposed home management system could lead to the reduction of carbon footprints in the case of residential facilities.

Experimental setup with pre-processing unit (a) and smart controller (b) ( Kalair et al., 2020 ).

A machine learning-based smart home energy system was investigated in ( Machorro-Cano et al., 2020 ), using big data with the support of IoT. The home automatization system was coupled with IoT devices that enabled energy savings for the given purpose. A machine learning algorithm was used to study user behaviour and was later linked with energy consumption, i.e., with the proposed approach, specific user patterns were revealed. The developed monitoring system, Fig. 18 allowed specific recommendations to lead towards an improvement of energy efficiency in households, which were somehow personalized for the specific household. The system was successfully validated via the provided case study where the main strength of the conducted research was the personalized approach for the specific household. A step further could be to network and balance other households in the specific building facility. The importance of the BIM (Building Information Modelling) systems was discussed and analysed in the review paper ( Pantelia et al., 2020 ). An overview of the recent works focused on the building smart operation was elaborated in detail with use of IoT technologies. In the same work the renovation projects were also tackled as well as interoperability problems caused by data sharing with respect to the BIM related applications.

Concept of proposed IoT supported smart home system ( Machorro-Cano et al., 2020 ).

An application of smart wearable sensors was reported in the study ( Pivac et al., 2019 ) that were used for the monitoring of thermal comfort data as well as for the modelling of occupant metabolic response in office buildings. The smart and IoT supported monitoring system allowed the collection of useful data from the wearable sensors. The readings helped for the better understanding of thermal comfort issues in office buildings from a personalized thermal comfort point of the view. The experimental readings were compared with a subjective response from the occupants, where a successful modelling of personal metabolic responses was enabled with an accuracy of over 90%. Industrial facilities could also be improved with the implementation of IoT technologies as already briefly addressed in the introduction section. Legislation support is important to ensure smart electricity utilization in the households, especially from the perspective of the smart city concept. Study ( Grycan, 2020 ) discussed legislative for electricity consumption for the case of the Polish residential sector. Lack of legislative was detected and mainly in the smart metering solutions that are slowing down development of the smart infrastructure. There is necessity for the new regulations to ensure adaptability to the novel desired goals towards smart cities. Development of the novel business models is important to ensure smart driven business in the energy sector. The case of the smart energy driven model was elaborated in ( Chasin et al., 2020 ) as well as implications and necessary changes in the energy sector. Eight smart business models were discussed with introduction of desired changes. Presented knowledge and development business scenarios could be useful guideline for energy utility companies. The possibility of IoT based smart solutions was discussed in the review paper ( Bagdadee et al., 2020 ), where the focus of the work was on IoT-based energy management systems in the industry. IoT based energy management systems were elaborated for industrial applications as well as for smart energy planning in industrial facilities. The energy management systems in factories were addressed from a perspective of energy demand and supply. The focus of IoT applications could also be used on a level of single or multiple devices or appliances. The scheduling and optimal power management of the transformers was analysed and discussed in ( Sarajčev et al., 2020 ). The Bayesian approach was applied to detect an optimal controlling strategy to ensure benefits for power utility companies. The proposed and demonstrated model can predict the transformer health index with an accuracy of about 90%. The solution could be applied on the fleet of the power transformers where with the application of IoT technologies, further savings could be ensured for the specific application. The efficiency of the lighting system could also be improved with IoT devices. The work ( Mukta et al., 2020 ) discussed and reviewed the possible application of IoT technologies for the energy efficiency improvement of highway lighting systems. The results of the conducted review revealed that the development of smart and IoT supported highway lighting systems lack a systematic approach, quality and comprehensiveness. Possible framework was proposed to bridge the mentioned gap and secure an efficient pathway for the improvement of energy efficiency in IoT based lighting smart and green highway systems. The necessity for the environmental suitability of the proposed smart lighting system was also raised in the same study and noted as an important factor that needs to be further investigated. Energy harvesting is also interesting topic and closely linked with the possible application of IoT technologies, especially since IoT devices require energy for their operation. An underwater piezoelectric energy harvesting system was discussed in ( Kim et al., 2020 ) for the case of autonomous IoT sensor production. The proposed solution was fully designed and provided in the form of a prototype and demonstrated an autonomous energy source that could be further linked with IoT devices. The harvesting of waste energy could also be considered with the implementation of IoT devices. The possibility for waste energy harvesting supported by IoT was addressed and discussed in ( Kausmally et al., 2020 ) for the case of an industrial chimney. The complete design procedure was reported, i.e. the conceptual approach for the waste heat recovery where the prototype was successfully developed and demonstrated. Energy storage systems are also interesting for the application of IoT technologies. A renewable energy storage system was analysed in ( Sathishkumar and Karthikeyan, 2020 ), where a power management strategy was supported by IoT. The optimal design of a hybrid energy system coupled with energy storage was discussed based on solar and wind renewable energy resources.

The IoT approach allows successful monitoring and managing of complex energy systems. The main advantage of IoT for the considered application is the energy efficiency improvement, better synchronization of different energy systems and improvement of the economic aspect. A significant development of IoT products would lead to a rapid increase of big data that are usually processed by data centres. The energy load of data centres is increased, so efficiency improvements are necessary in the case of data centres to minimize load power as well as utilization of other limited resources. The issue related to data centres, power demands and the possible application of IoT technologies in order to reduce the mentioned unwanted impacts was discussed in ( Kaur et al., 2020 ). The authors proposed a specific framework in the same work that is applicable for data centres and could lead to efficiency improvement of over 27% (proposed approach was based on empirical evaluations).

IoT technologies could also be successfully implemented in a circular economy concept as above already mentioned, especially in smart waste management systems and environment protection as already mentioned. The role of IoT technologies in e-waste was discussed in ( Kang et al., 2020 ) for the case of the Malaysian recycling sector. A novel smart waste collection box was designed together with a user friendly mobile application, Fig. 19 . The concept was successfully demonstrated. The developed solution could be further optimized and fitted for possible market implementation. A discussion of possible IoT framework, based on the developed IoT supported smart e-waste bin was elaborated for the Sunway city in Malaysia. The proposed approach could be a helpful guideline for other cities. The remaining issue with the proposed concept is its economic feasibility that should be further investigated via a detailed user survey, detecting user willingness for the acceptance of the proposed concept. The innovative IoT supported platform for the transformation of organic waste into inert and sterilized material was reported in ( Ferrari et al., 2020 ). The specific Arduino-electronic platform was developed to control process parameters and link them with user responses and traceability. Novel and low cost sensors were developed and successfully applied for the given purpose. The proposed prototype of the device was presented and was used for the mechanical treatment of waste. The developed IoT supported framework for the identification and traceability of products was presented in Fig. 20 .

Prototype of smart e-waste bin ( Kang et al., 2020 ).

Conceptual IoT supported framework for waste processing ( Ferrari et al., 2020 ).

The implementation of IoT technologies in a circular supply chain framework was elaborated in ( Garrido-Hidalgo et al., 2020 ) for the waste management of Li-ion battery packs from used electric vehicles. A novel and IoT supported supply chain framework was proposed, which is compatible with the information infrastructure. The approach could be further used for the recovery process of Li-ion batteries. Due to a planned increase in electric car fleets globally, intensive research was also directed for the potential usage of IoT technologies for the smart charging of electric vehicles. Real time IoT based forecasting applications were proposed in ( Savari et al., 2020 ) for a more efficient charging process of electric vehicles. The application allowed better scheduling management where the waiting time was minimized, which improved the overall charging economy as well as charging time.

Environmental protection and sustainable behaviour could also be improved with the targeted application of IoT technologies. In the study ( Irizar-Arrieta et al., 2020 ), long-term field investigation was presented with the main goal being to investigate how IoT technologies could help ensure the sustainable behaviour of users in office building facilities. The results of the conducted directed study could lead to the improvement of energy efficiency at workplaces with IoT utilization in different aspects. The impact of IoT technologies on a sustainable perspective and society was addressed in ( Mahmood et al., 2020 ). The study was focused on addressing the impacts of home systems on the environment and sustainability in general. A survey was conducted for specific users and the investigation showed that the impact of home automatization on sustainability and environment is significant. However, the environmental effects should be discussed in more detail and quantified to get realistic indicators that would later be used for sustainable planning.

Besides the obvious potential impact of IoT technologies to the environment, IoT products could on the other side be used for environmental protection. The design and concept of a systematic framework for the massive deployment of IoT-based PM (Particulate Matter) sensing devices was elaborated in ( Chen et al., 2020c ). The proposed framework was applied for the monitoring of air quality. Compressed spatiotemporal data were used and that allowed for the efficiency improvement of air quality monitoring systems, energy savings and improved data saving ratio. In order to improve the interoperability between different sensor networks, as well as data sources, a novel IoT data framework was proposed in ( Duy et al., 2019 ). The proposed analytical framework was used as a useful tool to improve the data management of environmental monitoring systems. The developed framework enabled a more efficient utilization of the gathered environmental data and improved knowledge extraction later. IoT platforms could also be used for environmental planning as it was demonstrated in the study ( Wu et al., 2019 ). In the conducted research, a building information model was integrated successfully with IoT and used for environmental planning for environmental protection reasons. Moreover, the system was used for environmental protection in a specific construction project (tunnel utility). Different impacts to the environment were monitored during the construction project such as dust falling control, temperature monitoring, visual monitoring etc. The overall findings directed that the proposed IoT supported system showed to be effective for the considered application. The application of an IoT based data logger was presented in ( Mishra et al., 2020 ), for the monitoring of equipment for environmental protection. The developed monitoring system ensured accurate and reliable work of the equipment used for the environmental protection. Potential equipment faults were detected in advance (prevention of serious failure), the equipment energy consumption was rationalized and scheduled maintenance was enabled. The accurate prediction of particulate matter (PM 2.5 ) concentrations is very important, especially in urban areas. Usually, there is a network of sensors used for the monitoring of PM 2.5 concentrations but they are not well connected and harmonized in some situations, which is vital. An IoT framework was used, together with a fusion technique, to improve the data utilization from the PM measuring stations in the work ( Lin et al., 2020 ). A novel multi-sensor space-time data fusion framework was proposed that ensured better accuracy, i.e. a more reliable model was ensured with a higher spatial-temporal resolution. Regarding the current progress of specific application areas in IoT devices for environmental protection, it can be conducted that the studies were mostly focused on air quality monitoring. Water-Energy-Carbon (WEC) nexus was analysed in detail for EU27 countries, in the recent work ( Wang et al., 2020 ) by implementation of the Environmental Input-Output model (EIO). Study was important since contributed to the better understanding of the environmental performance in EU27 and could serve as important basis for future considerations or planning for policymakers.

Based on the previously conducted overview of latest research findings related to the application of IoT technologies in sustainable energy and environment, the further main findings could be highlighted:

• - IoT technologies are intensively investigated from a perspective of smart monitoring in different devices or engineering components that are associated with energy applications. Better usage and networking of various collected data could lead to noticeable efficiency improvements, energy savings, improved safety, improved equipment maintenance and finally the general improved operation of devices in different engineering applications,
• - The economic aspect associated with the application of IoT technologies was not addressed in most studies, which is a significant drawback,
• - The environmental impacts associated with the implementation of IoT technologies for specific use were not addressed, which is serious and an important issue that should be carefully considered and investigated when discussing specific IoT concepts. Moreover, an integral techno-economic-environmental conceptual approach (TEE) should be applied when considering an IoT application for specific cases,
• - The main advantages (benefits) of IoT technologies enable a personalized approach in specific engineering applications such as smart homes (level of single user), which lead to different possibilities for both energy and fund savings,
• - There is significant potential in IoT technologies for environmental protection; however, rare studies have been conducted in that sense. More intense research efforts are needed in that direction to be able to utilize all the potential benefits of IoT technologies and improve the environmental suitability of IoT in one sense,
• - The waste management and circular economy concept could be well supported with IoT technologies, where the main issue is the development of integral and conceptual smart waste management frameworks that would efficiently support the circular economy concept in different economies.

3. IoT enabled smart city

To enable the IoT-based smart city concept, Fig. 21 , is described in the form of a tree that can be considered to further understand what the possible applications or functionalities the IoT-enabled Smart City can provide. The branches of the given tree are dedicated to applications, wherein the leaves of the given branch are dedicated to the functionalities that each application can have. As the more leaves a branch contains, the more functionalities it has. Fig. 16 represents the different functionalities of a smart parking system for instance. Further on, for example, smart homes can have many functionalities: smart metering (electricity, water consumption, gas monitoring), smart lock control, smart room temperature monitoring, smart kitchens and other appliances, etc. The root of the given tree (enabler and information source of these systems) is dedicated to the hardware whose system uses to accomplish any of the given possible functionalities. This section considers an overview of the most important hardware technologies, and software architectures that can enable and present functionalities for different applications in the smart city concept.

Generalized concept of IoT enabled Smart City Architecture ( Perković et al., 2020b ).

3.1. Hardware overview and state-of-the-art

To enable Smart Cities, an infrastructure that uses sensing hardware acting as an information source is of crucial importance. As this sensing hardware is located in remote areas, often without access to an electrical network, an almost zero-energy use is needed and therefore can prolong battery lifetime and possibly enable self-powering through ambient power sources, e.g. solar cells. This is crucial for improving the usability of the whole system as a battery replacement in these circumstances is difficult, expensive and a time-consuming activity. To understand power consumption issues, an overview of state-of-the-art technologies to build the hardware is provided.

A standard sensing node, presented in Fig. 22 is consisted of a sensor component that delivers the sensed information to a microcontroller unit (MCU) for its further processing. To reduce power needs, the node is usually equipped with a related power management unit, while there is a given power source. Once the MCU acquires the data from the sensor, it gives data to a radio unit that uses an antenna to transmit the data over a wireless channel. In the next sections, the components are described in depth by referencing the relevant literature, while the specific original work was done in current technology investigations that can enable these functionalities.

Block scheme of standard sensing node architecture in IoT enabled Smart City.

Sensors vary in terms of design and functionalities. A good overview of sensing technologies, and its power consumption is given in Fig. 23 . It can be noticed that each of them has its own power consumption pattern, where the more functionalities they have, the more consumption will appear. Using it in an optimal way is of the highest importance for reducing battery lifetime.

Most popular sensors and their power requirements in active and power-down (i.e. sleep mode, Perković et al., 2020b ).

3.2. Efficient IoT radio units

To achieve data transmission, a critical part is to deliver the data in an efficient manner. For this, the major idea and enabler is to provide data links between sensing nodes and receiving stations for transmitted data. To satisfy different applications and related functionalities, it is important that these radios can timely transmit the data over larger distances while consuming less energy. The major competitors in this area are Low-Power Wide Area Networks (LPWAN) with their technology competitors: LoRa, NB-IoT and Sigfox. According to Fig. 24 LPWAN can satisfy long ranges wherein the data rate is sacrificed, just suitable for sensorial application. In these cases, sensor devices send several data packets containing only the sensed information.

Overview of technologies that can satisfy different usage scenarios ( Mekki et al., 2019 ).

When considering LPWANs, the competitive technologies are also orthogonal in terms of different application points of view. A good overview of these technologies is given in Fig. 25 and Fig. 26 , also by providing the costs for each of them. In addition, Figs. 25 and ​ and26 26 give the technological comparison between each of them, so the deployers can understand which technology better fits which need. These mostly refer to which kind of infrastructure is required to match needs, what distance can be covered, what the overall system latency is when considering the number of nodes, etc.

Overview of performances and deployment costs for different LPWAN technologies ( Mekki et al., 2019 ).

Pros and cons for each of LPWAN competitors ( Mekki et al., 2019 ).

3.3. Power management

The basic mechanism that allows for the long lifetime of battery-operated devices (up to a couple of years) is to keep the device in low-power state during inactive periods. IoT devices, especially battery-operated ones, spend only a small fraction of time within active state, in which MCU performs sensor readings, and communicates data over wireless channels using a radio peripheral, while during inactive periods, the MCU along with other components is kept in deep-sleep state. Such a period between two active states, i.e. active - sleep - active is referred to as a duty cycle. Intuitively, to increase the lifetime of an IoT device, it is necessary to minimize its consumption during inactive periods. Logically, within inactive periods, it is necessary to place all active components into sleep. Some components, such as sensors, and radio modules, already come with libraries that support low-power consumption in sleep state (around 1uA per component or less). Using built-in functions, the MCU triggers external components to enter sleep once the sensor reading and radio transmission is done. On the other hand, the MCU also has to be kept in deep-sleep during the sleep period. However, to trigger the MCU waking from deep-sleep, some form of interrupt has to be sent to it. This is usually accomplished with some form of low-power timer. Depending on the MCU that is used in the implementation of an IoT device, there are many ways to accomplish this.

An MCU such as ATmega328P, found on Arduino boards, comes with a built-in Watchdog timer (WDT), with consumption up to couple of Ua, ( ATmega328P, 2020 ). Some external timers, like TPL5010 come with Watchdog functionalities, however, with nA scale consumption ( TPL5010, 2020 ). Unfortunately, the maximum time WDT can hold the MCU in low-power mode is around 8 s ( Tutorial - Atmega328p, 2020 ). One way to increase sleep time using WDT would require a loop that periodically triggers the MCU waking up every 8 s, after which the MCU immediately enters deep-sleep. Within deep-sleep period, the consumption of MCU and WDT is only a few uA. To increase sleep time for ATmega328P, an external RTC clock could be employed, such as a cheap and precise RS3231 RTC clock, with ±2 ppm stability and 1uA of consumption (Datasheet - RTC3231, 2020 ). Other MCUs, such as STM32 or SAMD21, already come with built-in RTC clocks that can be used to trigger an alarm for waking up from deep sleep (Libraries - Arduino low-power, 2020 ), ( STM32, 2020 ). All these components (MCU, sensor, RTC clock, radio peripheral, voltage regulators, capacitors, etc.), although in low-power mode, combined may consume tens to even couple of hundred of uA while being placed in deep-sleep. Moreover, it may happen that some boards equipped with components that adopt low-power modes have a hardware problem that prevent them from achieving low deep-sleep currents, such as found in MKRWAN1300 (Arduino LoRa with SAMD21) and ( MKRWAN1300, 2020 ).

To reduce even more consumption regarding all components, it is suggested to use an external timer component that will completely cut-off power for predefined periods. The TPL5110 is a low power timer where an alarm clock is regulated with resistors, allowing for the duration of sleep mode to be up to 2 h ( TPL5110, 2020 ). Within the sleep period, the TPL5110 simply cuts-off power from other components leaving overall consumption to be equal to the consumption of the timer only. Since the TPL5110 is low power by nature, the overall consumption falls to only 50 nA. The drawback of such a solution is that the MCU is no longer in deep-sleep but is instead powered off, which means that possible variables that were held in volatile memory during deep-sleep will not be available to the MCU when it wakes up. For this reason, it is suggested to use EEPROM or flash memory to write the variables before cutting off power from the MCU. A Tega328P may use built-in EEPROM, while STM32 or SAMD21 can use flash memory or RTC backup RAM ( Flash storage, 2020 ). The RS3231 RTC clock has an EEPROM that can be used for saving variables. The main drawback of EEPROM and flash memory is the limited number of writes (around 10,000), hence some external EEPROM or flash memory may be used with a larger number of writings, or either an external specialized chip like ATECC508A ( ATECC508A, 2020 ) that supports secure storage (of key for example) (ATEC). It must be noted that when the MCU wakes from deep-sleep, the code runs from where it left off, which usually requires a couple of mS. On the other hand, powering the MCU with an external timer such as TPL5110 requires a fresh restart of code, which in some scenarios may indicate running the bootloader. For ATmega328P, by default it may take up to 2 s for the bootloader to start ( Tutorial - Low-power nodes, 2020 ). Hence, to reduce consumption, it is suggested to either completely wipe out the bootloader or flash faster bootloader ( Bootloader, 2020 ). It must be mentioned that battery capacity, along with its input voltage may vary during sensor lifetime or could be larger than the operating voltage of some components. A good quality voltage regulator that may deliver enough current to a sensor device while consuming itself small current is required. For example, MCP1700 ( MCP1700, 2020 ) is a family of CMOS low dropout (LDO) voltage regulators that can deliver up to 250 mA of current while consuming only 1.6 μA, with input operating ranging from 2.3V to 6.0V, making it ideal for battery operated devices.

3.4. Microcontrollers for IoT: scouting and comparison

The Microcontroller (MCU hereafter) is the core of any Internet of Things (IoT) device and embedded system. Indeed, its role is to coordinate, according to a specific pre-programmed logic, all the peripherals of the IoT node thus providing sensing, actuation, and connectivity in an as low power mode as possible. In other words, the MCU sets the “smart-ability” of a certain object in relation with its cost, computational capability, power consumption, memory, communication interfaces and other features to accurately select during the design phase. It is worth highlighting that a “perfect” microcontroller does not exist, but just the most suitable one for the specific application. For this reason, the role of the designer in selecting the microcontroller for a specific IoT application is never simple. Some “universal” microcontroller key features are useful to drive the designer towards the right choice according to the requirements of the considered IoT application.

The proposed analysis aims at comparing some microcontrollers as potentially useful for the IoT by considering the following objective parameters.

• • Register Memory Bits : This parameter refers to the number of internal register bits and buffer. The higher the number of MCU bits, the higher the number of operations that the MCU itself can sustain. This parameter sets different families of Microcontrollers.
• • Maximum Clock Frequency: is the maximum frequency on the internal/external clock of the microcontroller. It is useful because it sets the number of operations of an MCU in a single time unit.
• • RAM : RAM is the volatile memory of an MCU which is useful for performing quick operations, actions or data buffering. The absence of powering resets this kind of memory
• • Flash Type : It is the static memory of an MCU that retains data in the absence of power. The quality of this memory in terms of writing operation figures and writing/reading speed determines a consistent part of the microcontroller cost.
• • Number and Type of GPIOs : GPIO is the acronym of a general-purpose input/output interface. It is referred to as the presence of pins that can be configured to act as the analog or digital input/output of the MCU. The higher the number of MCU GPIOs, the higher the number of external devices (sensors, actuators, transceivers) that can be controlled.
• • Serial Bus : Presence of an SPI/I2C bus for communication
• • Integrated Wireless Connectivity Interfaces: This key feature is useful in the IoT to wirelessly connect the MCU by using Wi-Fi, Ethernet, or BLE interfaces.
• • Power Consumption: Power Consumption is the most important aspect of IoT-oriented Microcontrollers. This parameter should be optimized by controlling the Active time and Sleeping time of the MCU according to the specific application.
• • Development board/Launchpad: The availability of a development board is helpful during the design phase to test the targeted IoT solution before realizing a prototype. Providing this board is an added value for MCUs.
• • Arduino IDE Programming Interface: Multi-brand MCUs implement an Arduino-compatible convergence programming language useful to simplify the programming operations and modular implementation of IoT applications.
• • Cost: IoT applications are often cost-sensitive. In many cases, functionalities could not be implemented to maintain a low-cost IoT system design. Generally, both MCUs and the presence of specific sensors determine the cost of the whole solution.

In addition to the above-mentioned parameters, the computational capability of a microcontroller can be evaluated by considering the presence of an on-board Operating System. If supported, this feature helps in managing complex IoT embedded applications where several peripherals must be managed. In this regard, three different typologies of microcontrollers can be summarized:

• • No-Operating system: The operating system is not present. In this case the microcontroller can be programmed in a “canonical” manner, by developing a code for low-level operations (Assembler of C are the main programming languages). A software-level connection cannot be implemented, however, the cost-effectiveness of these kinds of microcontrollers as well as reduced power consumption, make this MCU typology quite diffused.
• • RTOS : namely “Real-Time Operating System”. An RTOS Operating system enables a multi-task approach by introducing priority levels among the tasks running under the operating system. Moreover, this Operating System guarantees the correct timing of single events.
• • Linux/UNIX : This feature allows high-level programming in a way similar to a canonical computer. Open source software can be run on the MCU thus enabling connectivity and port management. Real-time and low-power operations are never guaranteed so that this kind of MCU is often not compatible with IoT applications, except for hi-level management IoT node systems.

Underneath, selected multi-brand MCUs will be compared by using the above-mentioned metrics in order to have a quick perspective useful in selecting the right MCU for a specific IoT application. After a quick overview of the microcontrollers based on manufacturer descriptions, which is useful to understand the different categories, a table summarizing their main features will be provided. Being low-power, “No-Operating system” devices will be considered in this comparison, Fig. 27 .

Comparison of microcontroller devices.

3.4.1. Texas instruments G series MSP430G2x13 and MSP430G2x53

The MSP430G2x13 and MSP430G2x53 series are ultra-low-power microcontrollers with built-in 16-bit timers, up to 24 I/O capacitive-touch enabled pins, a versatile analog comparator, and built-in communication capability using a universal serial communication interface. In addition, the MSP430G2x53 family members have a 10-bit analog-to-digital (A/D) converter. This is an entry-level microcontroller useful for general purpose low-power and low-cost IoT applications. The availability of a development board for the MSP43G2553 MCU, called “Launchpad”, makes the design easy for simple IoT sensing nodes.

3.4.2. Texas instruments F series MSP430F552x

The MSP430F5529, MSP430F5527, MSP430F5525, and MSP430F5521 microcontrollers have an integrated USB and PHY supporting USB 2.0, four 16-bit timers, a high-performance 12-bit analog-to-digital converter (ADC), two USCIs, a hardware multiplier, DMA, an RTC module with alarm capabilities, and 63 I/O pins. The MSP430F5528, MSP430F5526, MSP430F5524, and MSP430F5522 microcontrollers include these peripherals but have 47 I/O pins. This MCU family is compatible with low-power hi-performance IoT applications where hi-speed communication, port availability, and USB connectivity is required. Also in this case, the availability of a “Launchpad”, for the MSP430F5529 MCU makes the design easy for rather advanced and low-cost IoT smart nodes.

3.4.3. Texas instruments FR series MSP430FR572x and MSP430FR59xx

The TI MSP430FR572x and MSP430FR59xx families of ultra-low-power microcontrollers consist of multiple devices that feature an embedded FRAM nonvolatile memory, ultra-low-power 16-bit MSP430™ CPU, and different peripherals targeted for various applications. The architecture, FRAM, and peripherals, combined with seven low-power modes, are optimized to achieve extended battery life in portable and wireless sensing applications. FRAM is a new nonvolatile memory that combines the speed, flexibility, and endurance of SRAM with the stability and reliability of flash, all at lower total power consumption. Peripherals include a 10-bit ADC, a 16-channel comparator with voltage reference generation and hysteresis capabilities, three enhanced serial channels capable of I2C, SPI, or UART protocols, an internal DMA, a hardware multiplier, an RTC, five 16-bit timers, and digital I/Os.

3.4.4. Microchip PIC18F family PIC18F26K22

The PIC18 microcontroller family provides PICmicro® devices in 18-to 80-pin packages, that are both socket and software upwardly compatible to the PIC16 family. The PIC18 family includes all the popular peripherals, such as MSSP, ESCI, CCP, flexible 8- and 16-bit timers, PSP, 10-bit ADC, WDT, POR and CAN 2.0B Active for a maximum flexible solution. Most PIC18 devices will provide a FLASH program memory in sizes from 8 to 128 Kbytes and data RAM from 256 to 4 Kbytes; operating from 2.0 to 5.5 V, at speeds of DC to 40 MHz. Optimized for high-level languages like ANSI C, the PIC18 family offers a highly flexible solution for complex embedded applications.

3.4.5. Microchip PIC24F family PIC24F16KA102

The PIC24F is a cost-effective, low-power family of microcontrollers (MCUs) based on eXtreme Low Power (XLP) technology and 16-bit architecture. The flash memory ranges from 16 KB to 1 MB. The PIC24F family is a suitable solution for many space-constrained, low-power, cost-sensitive industrial, IoT and consumer applications.

3.4.6. STMicroelectronics STM32L0 family – STM32L053x8

The STM32L053x6/8 devices provide high power efficiency for a wide range of IoT applications. It is achieved with a large choice of internal and external clock sources, an internal voltage adaptation and several low-power modes. The STM32L053x6/8 devices offer several analog features, one 12-bit ADC with hardware oversampling, one DAC, two ultra-low-power comparators, several timers, one low-power timer (LPTIM), three general-purpose 16-bit timers and one basic timer, one RTC and SysTick which can be used as time bases. The MCU is provided with SPI, I2C, UART and USB 2.0 busses. This kind of MCU is studied for Ultra Low Power IoT applications and is provided with an effective development Arduino-compatible modular kit, called NUCLEO, allowing for easy interconnection with connectivity (BLE, Wi-Fi, Lo-Ra, etc) modules for IoT.

Taking into the account the above elaborated recent works, application scenarios and the enabling technology overview, following can be emphasized:

• - all kinds of services that are used to enable smart cities highly depend on the deployed hardware sensing infrastructure. Less infrastructure implies limited functionalities for given application scenarios. On contrary, many different application scenarios can be considered but this increases implementation and maintenance costs,
• - many different sensing techniques were proposed, and research community is intensively working to provide more reliable and cost-effective sensing technologies that can be easily implemented in IoT sensing nodes,
• - to enable different functionalities of the given application scenarios it is important to have the technology which can deliver sensed data on a greater distance, while preserving the energy in order to improve battery lifetime. For their products, many vendors specify 2–10 years of lifetime for their products, and it can be concluded that the battery lifetime depends on how frequently data is sensed and sent to the receiving station. Two-years span can certainly be considered as not enough, ten years’ horizon could be enough as by then, new technologies may arise and substitute currently implemented technologies. In any case, providing new technologies from any point of view: radios, MCUs, sensing techniques that can preserve battery lifetime is of crucial interest for both current and future IoT deployment,
• - currently available radios can fulfil today’s needs in terms of delivering data from remote areas in smart cities/villages. The NB-IoT, LoRa and Sigfox are overlapping in part, but can be considered as orthogonal for specific use-cases. Smart usage of given radios can further improve battery lifetime. However, it is always of the high interest to consume even less energy and provide larger communication distances and it provides the space for further analysis and technology improvements.

4. E-health – ambient assisted living systems

In recent years, the exploitation of new assisted living technologies has become necessary due to a rapidly aging society. In fact, it is estimated that 50% of the population in Europe will be over 60 years old in 2040, while in the USA it is estimated that one in every six citizens will be over 65 years old in 2020 ( Corchado et al., 2008 ). In addition, in 75-year-olds, the risk of Mild Cognitive Impairment (MCI) and frailty increases and people over 85 years of age usually require continuous monitoring. This suggests that taking care of elderly people is a challenging and very important issue. People with limited mobility are increasingly looking for innovative services that can help their daily activities. Ambient Assisted Living (AAL) encompasses technological systems to support people in their daily routine to allow an independent and safe lifestyle as long as possible. AAL (or simply assisted living) solutions can provide a positive influence on health and quality of life, especially with the elderly. An AAL approach is the way to guarantee better life conditions for the aged and people with limited mobility, chronic diseases and in recovery status with the development of innovative technologies and services.

Modern assistive technologies constitute a wide range of technological solutions aimed at improving the well-being of the elderly, Fig. 28 . These technologies are used for personalized medicine, smart health, health tracking, telehealth, health-as-a-service (HaaS), smart drugs and multiple other applications ( Maskeliunas et al., 2019 ).

IoT technology applications for AAL domain, ( Maskeliunas et al., 2019 ).

AAL technologies can also provide more safety for the elderly, offering emergency response mechanisms ( Lin et al., 2013 ), fall detection solutions ( Kong et al., 2018 ), and video surveillance systems ( Meinel et al., 2014 ). Other AAL technologies were designed in order to provide support in daily life, by monitoring the activities of daily living (ADL) ( Reena and Parameswari, 2019 ), by generating reminders ( Uribe et al., 2011 ), as well as by allowing older adults to connect with their families and medical staff. The recent advancements in mobile and wearable sensors helped the vision of AAL to become a reality. All novel mobile devices are equipped with different sensors such as accelerometers, gyroscopes, a Global Positioning System (GPS) and so on, which can be used for detecting user mobility. In the same way, recent advances in electronic and microelectromechanical sensor (MEMS) technology promise a new era of sensor technology for health ( Vohnout et al., 2010 ). Researchers have already developed noninvasive sensors in the form of patches, small holter-type devices, wearable devices, and smart garments to monitor health signals. For example, blood glucose, blood pressure, and cardiac activity can be measured through wearable sensors using techniques such as infrared or optical sensing. User localization is another key concept in AAL systems because it allows tracking, monitoring, and providing fine-grained location-based services for the elderly. While GPS is the most widespread and reliable technology to deal with outdoor localization issues, in indoor scenarios it has a limited usage due to its limited accuracy due to the impact of obstacles on the received signals. The number of alternative indoor positioning systems have been proposed in the literature ( Mainetti et al., 2014 ) that can be exploited in order to support AAL systems. Among all technologies, Bluetooth (BT) technology represents a valid alternative for indoor localization ( Yapeng et al., 2013 ) or specifically in museums ( Alletto et al., 2015 ). It is able to guarantee a low cost since it is integrated in most of daily used devices such as tablets and smart phones. The spread of the emerging Bluetooth Low Energy (BLE) technology makes the BT also energy-efficient, which is a key requirement in many indoor applications. An interesting investigation regarding the state-of-the-art and adaptive AAL platforms for older adult assistance was provided in ( Duarte et al., 2018 ). The authors present an overview of AAL platforms, development patterns, and main challenges in this domain.

In recent years, a large number of solutions have been proposed in the literature in order to create smart environments and applications to support elderly people. The main purpose is to provide a level of independence at home and improve elderly quality of life. In ( Dobre et al., 2018 ), an architecture which constitutes the base for the development of an integrated Internet of Things (IoT) platform to deliver non-intrusive monitoring and support for older adults to augment professional healthcare giving is presented, Fig. 29 . The proposed architecture integrates proven open-data analytics technology with innovative user-driven IoT devices to assist caregivers and provide smart care for older adults at out-patients clinics and outdoors.

Proposed modular architecture, ( Dobre et al., 2018 ).

A solution for monitoring patients with specific diseases such as diabetes using mobile devices is discussed in ( Villarreal et al., 2014 ). The proposed system provides continuous monitoring and real time services, collecting the information from healthcare and monitoring devices located in the home environment which are connected to BT mobile devices. The sensor data are transmitted to a central database for medical server evaluation and monitoring via 3G and Wi-Fi networks. An ad hoc application, installed on a mobile phone, allows the remote control of a patient’s health status whilst the patient can receive any notifications from the health care professionals via the application running on her/his mobile phone, Fig. 30 .

Proposed system for continuous monitoring and real time services, ( Villarreal et al., 2014 ).

The work ( Villarrubia et al., 2014 ) proposes a monitoring and tracking system for people with medical problems whose system architecture is shown in Fig. 31 . The solution includes a system for performing biomedical measurements, locomotor activity monitoring through accelerometers and Wi-Fi networks. The interactive approach involves the user, through a smart TV. The locomotor activity of the elderly is deduced through the analysis of Received Signal Strength Indication (RSSI) measurements, i.e. through an algorithm, the received signal power from different access points located in the house is determined. Mobile accelerometers are used to analyze the movement of users and detect steps. Single board computers, such as Raspberry Pi, are used to collect data coming from the different sensors wirelessly connected to obtain real-time context-aware information such as gas, temperature, fire, etc. or to get information from biomedical sensors such as, oxygen meter, blood pressure, ECG, accelerometer, etc. The Raspberry Pi can be connected to a TV to transmit warnings or notifications coming from health care professionals.

Virtual organization of system, ( Villarrubia et al., 2014 ).

The work ( Mainetti et al., 2016 ) proposes an AAL system for elderly assistance applications able to provide both outdoor and indoor localization by using a single wearable device. A prototypal device has been developed exploiting GPS technology for outdoor localization and BLE technology for indoor localization. The proposed system is also able to collect all information coming from heterogeneous sensors and forward it towards a remote service that is able to trigger events (e.g., push notifications to families or caregivers and notifications to the same indoor environment that will change its status). In an enriched work ( Mainetti et al., 2017 ), presents an architecture that exploits IoT technologies to capture personal data for automatically recognizing changes in the behaviour of elderly people in an unobtrusive, low-cost and low-power manner, Fig. 32 . The system allows performing a behavioral analysis of elderly people to prevent the occurrence of MCI and frailty problems.

Overall logical architecture ( Mainetti et al., 2017 ).

Based on the recent analysed research works on the use of IoT technologies in the e-health and for the creation of AAL systems, it is possible to draw the following general observations:

• - an extensive research is aimed at creating AAL systems intended primarily for the elderly or for people with physical or mental diseases,
• - current challenges deal with the use of IoT technologies in order to capture the habits of the people monitored both in indoor and outdoor environments for behavioral analysis purposes. The behavioral analysis can be useful for monitoring people, scheduling interventions and providing notifications directly to the user,
• - increasing efforts are needed in order to unobtrusively capture habits by favoring the use of wearable devices.

5. IoT technologies in Transportation and Low Carbon Products

The issue of security and traceability of goods is increasingly important in the logistics sector, with repercussions in terms of supply chain management and goods transport. In this case, information technologies and in particular the IoT can offer valuable support, increasing the degree of visibility and control over the entire supply chain. Transportation is a good example of how IoT technologies can bring value. In fact, this sector needs systems that on the one hand allow for the planning, management and optimization of flows (both along the supply chain and within complex logistics hubs such as intermodal ones) and, on the other hand, allow for the traceability of goods (products or containers) in real time along the entire supply chain. A further requirement concerns the check of goods integrity. In this context, it is clear how IoT technologies can contribute to the remote monitoring of flows and assets, providing a series of information useful for their management and optimization. This is possible through identification (e.g., via RFID or barcode), location (e.g., via GPS), monitoring of parameters and status variables of the assets (e.g., via sensors) and their transmission (e.g., via Wi-Fi or GSM/GPRS network).

The advent of IoT technologies allows to organize, automate and control processes remotely and from any device connected to the Internet. By definition, an efficient supply chain is responsible for delivering the goods, from the manufacturer to the end user, at the agreed time and under the specified conditions. Through the use of IoT technologies, it is possible to track the entire process in real time, promoting speed and efficiency in automated processes, reducing time and personnel costs. IoT technologies such as sensors, embedded and mobile devices, and cloud storage systems allow for the connection of “things” (warehouses, vehicles or goods) to the Internet so that the manufacturer, the logistics service provider and even the end user can thoroughly know at any time the status of products, their location and estimated delivery time.

Logistics can benefit from the use of IoT technologies in all the following sectors:

• • efficient inventory and warehouse management
• • automation of internal business processes
• • fast and efficient delivery of products (e.g., route planning)
• • conservation and quality of transported goods (e.g., monitoring of cold chain)
• • location, monitoring and tracking of vehicle fleets
• • interactive communication between vehicles and manufacturers/distributors of goods
• • certification of both deliveries and transport phases

The basic principles of logistics always remain valid: transfer the right product, in the right quantity and condition, at the right time and right price, in the right place and to the right customer. As carrying out each of these tasks has become much more complicated in an increasingly globalized and interconnected world, the need for innovative solutions to achieve these objectives also increases. As mentioned above, the IoT is revolutionizing the logistics sector, offering many advantages and opportunities. Supply chain monitoring, vehicle tracking, inventory management, secure transport and process automation are the cornerstones of IoT applications as well as the main elements of interconnected logistics systems.

In the logistics sector, the IoT allows creating smart location management systems, which allow companies to easily monitor driver activities, vehicle location and delivery status, ( Brincat et al., 2019 ). This solution is indispensable in the planning of deliveries and the organization of timetables and reservations. It is possible to detect any changes in real time and this is precisely the reason behind the success of the IoT: the ability to improve the management of good movement and therefore streamline business processes. Inventory and warehouse management is another important element of the connected logistics ecosystem. The positioning of small sensors allows companies to easily track items in warehouses, monitor their status, position and create a smart control system. In fact, with the help of IoT technology, employees will be able to successfully prevent any loss, ensure the safe storage of goods and efficiently locate the product needed. Even the minimization of human error becomes possible thanks to the IoT. In this scenario ( Wang et al., 2015 ), proposes a layered architecture for the realization of an automation enterprise asset management system using IoT and RFID technologies, Fig. 33 .

Layered architecture of proposed automation enterprise asset management system ( Wang et al., 2015 ).

The sustainable and IoT supported business model was discussed in ( Gao and Li, 2020 ) for the case of the bike-sharing services. Novel framework was developed that links sustainable indicators as well as social aspects of the business concept. The case studies for dockless bike-sharing services were discussed and presented for China and UK. Practical findings extended knowledge needed for improvement of the sharing economy to achieve sustainably goals through IoT enabled support. The work ( Zhang et al., 2016 ) proposes an inventory management system for a warehousing company. The system adopts the concept of IoT using RFID technology to track the material and provide messages or warnings when incorrect behaviors are detected. In particular, it integrates RFID technology and a self-Adaptive distributed decision support model for inbound and outbound actives, inventory location suggestions and incident handling. In ( Guptha et al., 2018 ), the authors design an IoT architecture for order picking processes in a warehouse that allows the inventory real time tracking and visibility into the reduction of warehouse operation costs, improved safety and reduced theft. IoT and RFID technologies are again exploited in ( Valente et al., 2017 ) to improve productivity in the value chain of a steel mill. In this work, an existing RFID solution architecture based on the reference EPCGlobal/GS1 framework was modified in order to be extended to the IoT domain, Fig. 34 .

RFID/IoT solution architecture for steel mill (Valente et al., 2017).

The internet-connected devices collect large amounts of data which can be transmitted to a central system for further analysis. In this context, the integration between IoT and predictive analysis systems can help companies to create effective business development strategies, improve decision-making and manage risks. In the logistics sector, this integration finds application to plan routes and deliveries as well as identify various defects before something goes wrong. An integrated framework to track and monitor shipped packages, Fig. 29 was proposed in ( Proto et al., 2020 ). Framework relies on a network of IoT-enabled devices, called REDTags, allowing courier employees to easily collect the status of package at each delivery step. The framework provides back-end functionalities for smart data transmission, management, storage, and analytics. A machine-learning process is included to promptly analyze the features describing event-related data to predict the potential breaks of goods in the packages ( Fig. 35 ).

Framework architecture, ( Proto et al., 2020 ).

Ensuring product quality and integrity is an interesting challenge that in recent years has led to the creation of smart systems that integrate IoT solutions and block chain technology. The Blockchain technology associated with IoT sensors could allow the creation of a temporal “stamp” inside which a series of information is kept such as product delivery date, product characteristics and status, and origin of product. By positioning the sensors, for example, it is possible to monitor parameters such as product temperature and humidity, vehicle position and phases of the transport process and save this data in the block chain. Block chain infrastructure can also revolutionize company logistics in the field of document management (i.e., invoices, transport documents, etc.), traceability of goods (origin of products, monitoring of vehicle fleets, etc.), and play a substantial role in fighting counterfeiting. Imeri and Khadraoui (2018) showed a conceptual approach to the security and traceability of shared information in the process of dangerous goods transportation using block chain technology based on smart contracts. IoT and block chain technologies are exploited in ( Arumugam et al., 2018 ) where a smart logistics solution encapsulating smart contracts, logistics planner and condition monitoring of the assets in the supply chain management area is presented, Fig. 36 . Moreover, a prototype of the proposed solution is implemented.

High-level architecture of proposed solution, ( Arumugam et al., 2018 ).

The block chain-IoT-based food traceability system (BIFTS) to integrate the novel deployment of block chain, IoT technology, and fuzzy logic into a total traceability shelf life management system for the managing of perishable food, Fig. 37 was proposed in ( Tsang et al., 2019 ). Challenges in the adoption of the proposed framework in the food industry are analysed and future research planned to improve the proposed work.

Modular framework of BIFTS, ( Tsang et al., 2019 ).

Taking into account above discusses recent research findings further main findings could be highlighted:

• - The studies analysed previously show how the hardware and software technologies enabling the Internet of Things are leading to a digital transformation process that aims at an intelligent and advanced management of the entire logistics and transportation system.
• - The main scientific challenges in this field aim to use sensors in order to monitor the status of the goods transported, to ensure traceability and above all to safely and reliably collect telemetry data and offer them to Artificial Intelligence modules for advanced processing.
• - Furthermore, recently the interest has focused on the next generation of blockchain systems (the so-called blockchain 3.0) which aims to apply the benefits of the classic blockchain in typical scenarios of the Internet of Things, such as logistic and transportations.

6. Concluding remarks and future directions in the field

This review paper discussed and presented latest research findings that were included within the JCELPRO VSI SpliTech2019 and dedicated to the 4th International Conference on Smart and Sustainable Technologies (SpliTech 2019). The contributions as well as herein presented knowledge is summarized and discussed in upcoming sections.

The Intense digitalization in recent years has allowed for different technological possibilities that have already gradually been changing the main economic sectors and societies in general. Digitalization in different economic sectors enabled various possibilities for advancements and for a more efficient utilization of limited resources, systems or processes. The main driver for an efficient digitalization in various sectors is information technology, i.e., IoT supported smart technologies. In the previous sense, the energy sector is one of the key sectors where ‘‘energy digitalization’’ has already been rapidly developing in various energy related fields. Currently, one of the most progressing implementation areas of IoT technologies is related to the energy sector. The developing solutions are focused on smart homes, i.e. advanced automatization of home energy systems, development of smart and adaptive micro-grids, or advancements in efficient demand-side management of power systems. A circular economy concept has also been intensively worked on where various concepts have been investigated, which can support smart waste management and help bridge one of the main challenges in society. Recently, different concepts have been tested where IoT technologies could be used for environmental protection, primarily for the monitoring of air quality, which is a big potential in that sense.

Healthcare systems can also be significantly improved with the application of IoT devices, i.e. via the E-health concept. An improved quality of services and patient safety could be enabled with an advanced IoT supported monitoring system. The prediction of life threatening states could be efficiently detected with a better treatment of patients, such as timely therapy decisions and qualitative rehabilitation. In general, large healthcare systems could also benefit from IoT, both in efficiency and from a cost aspect, which is important for hospitals. The current pandemic state with COVID-19 allowed for the consideration of different IoT applications or devices that could help in efficiently monitoring and controlling the pandemic, which proves the added value of IoT products.

The transportation sector is currently in gradual transition where a mix of transportation vehicle technologies is expected in upcoming decades with the involvement of electric vehicles primarily along with hybrid or hydrogen based vehicles. The main advancements of IoT in transportation are the support of the smart car concept where different vehicle operating parameters can be monitored in an efficient manner. The main advantage is early detection of severe failures, then regular maintenance, improved fuelling and finally improvement of safety and driving experience in general. The most challenging IoT application area is in the case of autonomous vehicles, where safety is the main goal and in that sense, significant research advancements are expected to occur in the near future.

The smart city concept is the most progressing IoT application area since cities have been vastly populated, which causes severe infrastructural issues. The main benefit of IoT technologies in the smart city concept is to bridge severe infrastructural challenges in highly populated cities. The improvement of life quality in cities is also expected thanks to the efficiency improvement of various convectional services in cities. The early detection of various and common daily problems in cities could be efficiently solved with IoT as with transportation issues, energy and water shortage supplies, security issues, etc. The biggest challenge in the smart city concept is directed to the efficient networking and operation of different sensing technologies, which must be followed with the proper education of the population.

Each technology that is rapidly progressing has got specific potential drawbacks that need to be carefully analysed and addressed. Since IoT devices are measured in billions, and with large potential impacts on the population, specific challenges need to be addressed, which were detected based on the herein conducted review. The main goal is to secure a sustainable and balanced development of IoT technologies. Therefore, further issues are briefly discussed below and should be carefully considered during the further development of IoT technologies:

• - the rapid development of IoT technologies causes fast consumption of raw materials to produce different electronic devices where unfortunately some of raw materials are already rare or becoming,
• - electronic devices are becoming more economically acceptable where a potentially large population would be affected. High production volumes are expected which can finally cause a rebound effect and a more rapid unwanted utilization of already limited resources,
• - the sustainability aspect and long-term effects of IoT technologies are not clear and insufficiently investigated. A noticeable amount of energy would be needed to operate IoT devices and the electronic industry is leaving different unfavourable environmental footprints that also need to be carefully investigated,
• - electronic waste will become one of the major issues caused with the planned rise of IoT products. Recycling rates must be improved and better e-waste management should be secured,
• - IoT technologies can cause social impacts in specific industrial branches or businesses since working labour could be reduced and direct social contacts have also been reduced. In that sense, the application of IoT technologies should be carefully considered taking the raised issues into account,
• - significant advancements in both specific electronic components as well as user-friendly software solutions are required,
• - further development in sensing technologies and advanced data acquisition systems is also required,
• - the minimization of energy consumption in IoT devices is a crucial target, i.e. reduction of energy supply.

From the herein addressed recent research findings within the VSI SpliTech 2019, it is obvious that developments in various IoT application sectors are promising but further advancements are expected and that are mainly focused on maximizing the efficiency of specific IoT supported processes or technologies, minimizing resource utilization (raw materials and energy) and environmental footprints. IoT technologies are an opportunity for humanity and can bring important as well as useful benefits to the population. The authors contributions within the JCLEPRO VSI SpliTech2019 provided quality discussion and presentation of the latest advancements in the field, and most important, they contributed to the better understanding of IoT application areas, technological possibilities, but also potential drawbacks and issues that should be carefully monitored in future terms. The crucial and important aspects are linked with sustainability where the rapid developments in IoT technologies must be carefully monitored from a resource and environmental point of view to ensure balanced and sustainable development of IoT products. Herein presented knowledge and published works in the Journal of Cleaner Production are serving as important foundations for researchers dealing with this challenging and dynamic research field.

CRediT authorship contribution statement

Sandro Nižetić: Conceptualization, Methodology, Supervision. Petar Šolić: Conceptualization, Methodology, Supervision. Diego López-de-Ipiña González-de-Artaza: Supervision. Luigi Patrono: Conceptualization, Methodology, Supervision.

Declaration of competing interest

We wish to confirm that there are no known conflicts of interest associated with this publication in Journal of Cleaner Production ( Internet of Things (IoT): Opportunities, issues and challenges towards a smart and sustainable future ) and there has been no significant financial support for this work that could have influenced its outcome.

We confirm that the manuscript has been read and approved by all named authors and that there are no other persons who satisfied the criteria for authorship but are not listed. We further confirm that the order of authors listed in the manuscript has been approved by all of us.

We confirm that we have given due consideration to the protection of intellectual property associated with this work and that there are no impediments to publication, including the timing of publication, with respect to intellectual property. In so doing we confirm that we have followed the regulations of our institutions concerning intellectual property.

We understand that the Corresponding Author is the sole contact for the Editorial process (including Editorial Manager and direct communications with the office). He is responsible for communicating with the other authors about progress, submissions of revisions and final approval of proofs. We confirm that we have provided a current, correct email address which is accessible by the Corresponding Author and which has been configured to accept email from ( [email protected] ).

Acknowledgments

This work has been supported in part by Croatian Science Foundation under the project “Internet of Things: Research and Applications”, UIP-2017-05-4206, Croatia.

Handling editor: Cecilia Maria Villas Bôas de Almeida

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The Internet of Things: Definitions, Key Concepts, and Reference Architectures

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• Theo Lynn 7 ,
• Patricia Takako Endo 8 , 9 ,
• Andrea Maria N. C. Ribeiro 10 ,
• Gibson B. N. Barbosa 10 &
• Pierangelo Rosati 7  

Part of the book series: Palgrave Studies in Digital Business & Enabling Technologies ((PSDBET))

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This chapter introduces the Internet of Things (IoT) and presents definitions and a general framework for conceptualising IoT. Key concepts and enabling technologies are summarised followed by a synthesis and discussion of the current state-of-the-art in IoT Reference Architectures.

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Internet of Things

• Internet of things
• IoT Reference Architecture

1.1 Introduction

The Internet has evolved in a series of waves (Cisco 2012 ). The first three waves were device-centric. In the first wave, we went to a device, typically a desktop PC, to access the Internet. As mobile computing evolved, soon we brought our own devices with us and could access the Internet anywhere anytime. Today, we are in the midst of the so-called Internet of Things (IoT) where devices (things) are connected to the Internet and each other. These things comprise a multitude of heterogeneous devices ranging from consumer devices, such as mobile phones and wearables, to industrial sensors and actuators. Gartner ( 2017 ) estimated only 8.4 billion things were connected in 2017 representing just over 0.5% of the total estimated connectable physical objects worldwide.

This objective of this chapter is to introduce readers to the Internet of Things. The remainder of the chapter is organised as follows. First, we will explore perspectives on the definition of the Internet of Things (IoT) followed by key constructs and concepts underlying IoT including a general research framework for conceptualising IoT. Then, we will delve into a further level of granularity and present a selection of IoT Reference Architectures before concluding.

1.2 Defining the Internet of Things

The Internet of Things (IoT) has rapidly grown in prominence in the last ten years and, yet, it means different things to different people. Indeed Whitmore et al. ( 2015 ) note that there is no universal definition of IoT. Two main conceptualisations exist—the technical and socio-technical perspectives. The first, the pure technical perspective, views IoT as an assemblage and ecosystem of technical artefacts. It is defined by reference to these artefacts and their capabilities. These range in detail. For example, Weyrich and Ebert 2016 , p. 1) define IoT as being “ […] about innovative functionality and better productivity by seamlessly connecting devices. ” In contrast, Tarkoma and Katasonov ( 2011 , p. 2) is significantly more detailed defining IoT as a “ global network and service infrastructure of variable density and connectivity with self-configuring capabilities based on standard and interoperable protocols and formats [which] consists of heterogeneous things that have identities, physical and virtual attributes, and are seamlessly and securely integrated into the Internet. ” Similarly, Whitmore et al. ( 2015 , p. 1) define the IoT as “ a paradigm where everyday objects can be equipped with identifying, sensing, networking and processing capabilities that will allow them to communicate with one another and with other devices and services over the Internet to achieve some objective. ” Unsurprisingly, given the nature of these definitions, they dominate Computer Science literature.

The socio-technical perspective of IoT recognises not only the technical artefacts but also the associate actors and processes with which the IoT interacts. For example, Haller et al. ( 2009 ) recognises the role of the connected objects as active participants in business processes. They define the IoT as “ a world where physical objects are seamlessly integrated into the information network, and where the physical objects can become active participants in business processes. Services are available to interact with these ‘smart objects‘ over the Internet, query their state and any information associated with them, taking into account security and privacy issues ” (Haller et al. 2009 , p. 15). Shin ( 2014 , p. 25) argues that the IoT is part of “ wider, socio-technical systems, comprising humans, human activity, spaces, artefacts, tools and technologies. ” Indeed, Shin et al. note that in some instances, a biological entity may, in fact, be considered the connected thing, for example a human with a heart monitor implant or a farm animal with a biochip transponder.

This perspective taken in this book is not particularly concerned with a specific IoT-related definition or problem. Figure 1.1 below presents a general research framework for conceptualising IoT research. It is general in that it is capable of being used to understand IoT related problems and research questions in conjunction with widely accepted levels of generalisation (abstraction) in both the social sciences (nano, micro, meso, macro) and computer sciences (computation, algorithmic/representational, physical/implementation). Furthermore, it provides a sufficiently general abstraction of the IoT in that it facilitates sense making without getting in to a non-generalisable level of granularity.

A general framework for conceptualising big data research in the Internet of Things

In this framework, five core entities are identified and defined—social actors, things, data, networks, and events. Each of these entities has a myriad of characteristics that may change and evolve over time and inflect our understanding of how value can be generated and captured at different units of analysis:

Social Actors (S) , while typically human, need not be; the framework is flexible enough to accommodate the emerging concept of computers as social actors (Lynn et al. 2015 ; Zhao 2003 ).

Things (T) are primarily physical however they may also be virtual and exist in augmented and/or virtual reality. Two key functional requirements of things in IoT and IoE are data sensing (collating data) and network connectivity.

Data (D) here are discrete artefacts that can connect to other entities including other data and may be sourced from first party, second party, or third party sources. It recognises the existence of an IoT data chain. For example, Radio frequency identification (RFID) enables the tracking of objects through an electronic product code (EPC) serving serves as a link to data about the object that can queried over the Internet (Haller et al. 2009 ).

Networks (N) are systems of interconnected entities and are both conduits and entities in themselves. Our framework accommodates networks between different types of IoT entities and those of the same type, for example machine-to-machine (M2M) networks.

Events (E) are occurrences of interest at given time and/or physical or virtual space.

Processes (P) are obviously critical to how entities interoperate in the IoT and comprise general (e.g. communication) and domain-specific processes. They are essential to how value is created, captured, and delivered in the IoT.

All entities and processes take place in an infrastructural setting and the framework recognises that in the IoT, additional data and metadata is created and collated at the infrastructural level. For example, depending on the networking, processing, and storage capabilities of a given device, these activities may be centralised (in the cloud), at the edge (at the device), or in an intermediary layer (the fog) and not only store or process this data but also may extract other hardware, software, functional use, or other ambient data that can provide different and/or new insights. Finally, each IoT use case is situated in space (physical or virtual) and time and it is against this context that different types of events occur and impact the IoT.

As the IoT can be explored from numerous perspectives, we argue that such a research framework can play an important role for researchers to make sense of a complex and dynamic environment and isolate the major constituents of the IoT experience. In addition, the proposed framework can be used as a general-purpose scaffold for crafting research agendas on the IoT and avoiding duplicated and unfocussed research endeavours.

1.3 Key Concepts and Constructs

IoT revolves around a number key concepts and enabling technologies including object (thing) identification (e.g. IPv6), information sensing (e.g. RFID, sensors, GPS, etc.), communications technologies for data exchange, and network integration technologies (Shin 2014 ).

It is important to note that legacy computing and telecommunications architectures were not designed with the IoT in mind. The scale of heterogeneous devices and an unprecedented volume, variety and velocity of data combined with an extreme variation in use context require new paradigms in computing. Depending on the use case and service level requirements, IoT devices may require processing and storage locally, in the cloud or somewhere in between. In addition cloud computing, edge, fog, and dew computing are three new computing paradigms designed to support IoT. While beyond the scope of this chapter, it is useful to be aware of these concepts and technologies when consider the architectures in Sect. 1.4 . Table 1.1 provides a brief definition for technology.

1.4 IoT Reference Architectures

IoT devices are being used in a wide range of domains such as health, agriculture, smart cities, and process automation. The ‘things’ used can be characterised by their heterogeneity in terms of computing resources (processing, memory, and storage), network connectivity (communication protocols and standards) and software development (high degree of distribution, parallelisation, dynamicity). While such heterogeneity enables the depth and breadth of applications and use cases, it also introduces complexity, particularly with respect to expected service level requirements, for example, user and device mobility, software dependability, high availability, scenario dynamicity, and scalability. As such, an abstraction layer to promote interoperability amongst IoT devices is needed. However, lack of standardisation means that such interoperability is lacking (Cavalcante et al. 2015 ). Reference Architectures can help IoT software developers to understand, compare, and evaluate different IoT solutions following a uniform practice.

Several Reference Architectures have been proposed in order to standardise concepts and implementation of IoT systems in different domains. Breivold ( 2017 ), for instance, conducted a comparative study with eleven different Reference Architectures. This chapter focuses on the those Reference Architectures that enable IoT integration with cloud computing and/or fog and edge computing i.e. across the cloud to thing (C2T) continuum. Figure 1.2 shows the timeline containing the main Reference Architectures that support IoT across the C2T continuum, namely IoT Architectural Reference Model (IoT ARM), IEEE P2413 (IEEE P2413 2014 ), Industrial Internet Reference Architecture (IIRA) (Lin et al. 2019 ), WSO2 IRA, Intel SAS, Azure IRA, and SAT-IoT.

Timeline of selected IoT Reference Architectures

Each of the architectures below can be explored through the lens of the framework presented in Sect. 1.2 and embodies the key concepts and constructs discussed in Sect. 1.3 .

1.4.1 Internet of Things Architectural Reference Model (IoT ARM)

The IoT-A project (IoT-A 2019 ) groups the specificities of IoT functionalities and defines the IoT Architectural Reference Model (IoT ARM) to support the usage, the development and the analysis of different IoT systems, from communication to service level.

According to Bauer et al. ( 2013 ), the main contributions of the IoT ARM are twofold: (a) the Reference Model itself, which contains a common understanding of the IoT domain and definitions of the main IoT entities and their basic relationships and interactions; and (b) the Reference Architecture per se , which provides views and perspectives to generate IoT architectures adapted to one’s specific requirements. This way, the Reference Model and the Reference Architecture provide abstraction levels (models, views and perspectives) to derive concrete IoT solutions (i.e. IoT ARM compliant IoT architectures and systems) (Fig. 1.3 ).

Derivation from each IOT ARM step

The Reference Architecture is independent from a specific use-case or application and includes three views: (a) functional, (b) information, and (c) deployment and operation. The functional view describes the function components of a system; these include components’ responsibilities, default functions, interfaces, and interactions. The architecture is composed of five longitudinal functionality groups (FGs), namely service organisation, IoT process management, virtual entity, IoT services, communication, and two transversal FGs, namely management and security.

The information view covers the information life cycle in the IoT system, providing an overview of the information structures and flows (i.e. how information is defined, structured, exchanged, processed, and stored), and the list of the components involved in the process.

Lastly, the deployment and operation view has an important role in the realisation of IoT systems as they are bringing together a number of devices, each of which has different resources and connection interfaces, which can be interconnected in numerous ways. The deployment and operation view provides a set of guidelines for system design, covering different aspects of technologies, communication protocols, services, resources, and information storage.

According to Bauer et al. ( 2013 ), evolution and interoperability, availability and resilience, trust, security and privacy, and performance and scalability are the most important for perspectives for IoT systems.

Bauer et al. ( 2013 ) also present a reverse mapping to demonstrate how the concepts of the IoT ARM can be presented to existing architectures and to validate their proposal. One of the use cases was based on the use of RFID for tracing the towels before, during, and after the surgery to avoid towels being left on the patient’s abdomen. This use case was also based on the use of a cloud infrastructure for data storing. Even though the authors argue that the IoT ARM mapping was successfully done, there is no way to say that it can be applied to any existing concrete architecture.

1.4.2 IEEE Standard for an Architectural Framework for the Internet of Things (P2413)

To avoid silos in domain-specific standards, P2413 is a unified architectural framework for IoT. As well as defining the framework, it includes descriptions of various IoT domains, definitions of IoT domain abstractions, and identification of commonalities between different IoT domains (energy, media, home, transport etc.). It provides a reference model that defines relationships among various IoT verticals and common architecture elements. In this way it has similar design principles to IoT ARM. The Reference Architecture covers the definition of basic architectural building blocks and their ability to be integrated into multi-tiered systems. The Reference Architecture also addresses how to document and mitigate architecture divergence. P2413 also includes a blueprint for data abstraction and addresses the need for trust through protection, security, privacy, and safety. Applying P2413, the architectural transparency of IoT systems can be improved to provide benchmarking, safety, and security assessments.

The P2413.1 is the Standard for a Reference Architecture for Smart City (RASC) (P2413.1 2019 ). The RASC provides an architectural design for the implementation of a smart city, enabling interaction and interoperability between domains and system components. The smart city applications may include water management, waste management, street lighting, smart parking, environmental monitoring, smart community, smart campus, smart buildings, e-health, e-government, etc. The RASC includes the Intelligent Operations Center (IoC) and IoT.

The P2413.2 is the Standard for a Reference Architecture for Power Distribution IoT (PDIoT) (P2413.2 2019 ). Following a similar idea of RASC, the PDIoT also provides an architectural design but for implementing power distribution systems, covering different domains, such as legacy grid systems, IoT and cloud computing. This standard defines a cloud based power distribution which supports microservices and migration from legacy systems to IoT based platforms.

1.4.3 Industrial Internet Reference Architecture (IIRA)

The term ‘Industrial Internet’ is largely attributed to General Electric (GE). In a joint report, Accenture and GE (2014, p. 7) define the industrial internet as an architecture that:

[…] enables companies to use sensors, software, machine-to-machine learning and other technologies to gather and analyse data from physical objects or other large data streams—and then use those analyses to manage operations and in some cases to offer new, value-added services.

Today, the Industrial Internet has evolved in to the Industrial Internet of Things (IIoT). IIoT is defined Boyes et al. ( 2018 , p. 3) as:

A system comprising networked smart objects, cyber-physical assets, associated generic information technologies and optional cloud or edge computing platforms, which enable real-time, intelligent, and autonomous access, collection, analysis, communications, and exchange of process, product and/or service information, within the industrial environment, so as to optimise overall production value.

Somewhat like IoT ARM and P2413, the Industrial Internet Reference Architecture (IIRA) (Lin et al. 2019 ) is an architecture framework to develop interoperable IIoT systems for diverse applications across industrials verticals.

IIRA is composed of one frame and different representations (Fig. 1.4 ). According to (Lin et al. 2019 ), a frame is a collection of concepts represented by stakeholders (individual, team, organisation having interest in a system), concerns (any topic of interest pertaining to the system), and viewpoints (conventions framing the description and analysis of specific system concerns). Representations are defined as views and models, which are collections of the results obtained through the application of the architecture frame to abstracted or concrete systems. These models and views are chosen for addressing a specific concern at an appropriate level of abstraction (Lin et al. 2019 ).

Industrial internet Reference Architecture. (Adapted from Lin et al. 2019 )

The IIRA identifies the main architectural concerns found in IIoT systems and classifies them into viewpoints related to their respective stakeholders. Viewpoints are critical components in the IIRA; there are four different viewpoints (Fig. 1.5 ). Firstly, the Business Viewpoint is responsible for inserting the vision, values, and objectives of business stakeholders in the commercial and regulatory context. Secondly, the Usage Viewpoint describes how an IIoT system realises its key capabilities, by providing the sequence of activities that coordinates the system components. Thirdly, the Functional Viewpoint relates the functional and structural capabilities of an IIoT system and its components. It is decomposed into five main functional domains: control domain, operation domain, information domain, application domain and business domain. Finally, the Implementation Viewpoint provides (1) a description the general architecture of an IIoT system, (2) a technical description of its components, (3) an implementation map of the activities identified in the Usage Viewpoint; and (4) an implementation map for the key system characteristics (Lin et al. 2019 ).

IIRA viewpoints. (Adapted from Lin et al. 2019 )

By adopting IIRA, industries can integrate best practices into their processes, use a generic architecture and common framework and as a result reduce operation expenditure. It should be noted that IIRA provides architectural patterns for both cloud and edge computing.

1.4.4 WSO2 IoT Reference Architecture (WSO2 IRA)

WSO2 is a US-based open source integration vendor. The WSO2 IoT Reference Architecture (WSO2 IRA) is illustrated in Fig. 1.6 and supports IoT device monitoring, management, and interaction, covering the communication process between the IoT and the cloud (Fremantle 2015 ). The WSO2 IRA comprises five horizontal layers (client/external communication, event processing and analytics, aggregation layer, transports, and devices) and two cross-cutting layers (device management and identity and access management). Table 1.2 provides a brief definition of each layer.

WSO2 IoT Reference Architecture. (Adapted from Fremantle 2015 )

1.5 Intel System Architecture Specifications (Intel SAS)

The purpose of the Intel System Architecture Specifications (SAS) is to connect any type of device to the cloud considering five key items: (1) C2T management, (2) real time analytics, (3) interoperability, (4) service and device discovery and provisioning, and (5) security (Intel 2015 ). Intel SAS has two distinct versions that co-exist in order to cover different infrastructure maturity levels: version 1.0 for connecting the unconnected and version 2.0 for smart and connected things. Version 1.0 specifies how legacy devices that were not originally designed to be connected to the cloud can use an IoT gateway to be online. Version 2.0 specifies how to integrate heterogeneous smart things focusing on security, manageability and real time data sharing between things and cloud (Fig. 1.7 ).

Intel system architecture specifications. (Adapted from Intel 2015 )

Intel SAS recommends a layered architecture that encompasses horizontal layers (users, runtime, and developers) and vertical layers (business and security). The data flow involves through eleven steps including analogue-to-digital conversion (ADC), gateways and reaching the cloud. Intel also recommends software components and interfaces to connect legacy devices with no connectivity functionality. The software components are located at endpoint devices and in the cloud. Basically, the cloud software components receive data collected by on-premise components and are responsible for analysis, storage, and service orchestration.

1.5.1 Azure IoT Reference Architecture (Azure IRA)

The Azure IoT Reference Architecture (Azure IRA) represented in Fig. 1.8 relies on Microsoft Azure platform to connect sensors to intelligent services at the cloud. The main goal of Azure IRA is to take actions on business insights that are generated through gathering data from IoT applications (‘things’) (Microsoft 2018 ). The reference document proposes a recommended IoT architecture, describing foundational concepts and principals, IoT subsystems details and solution design considerations. Azure IRA is focused on flexibility. As such, IoT solutions are cloud native and microservice-based. As deployable services are independent of each other, they suggest that it is better for scaling, updating individual IoT subsystems, and flexibility in the selection of technologies per IoT subsystem.

Azure IoT Reference Architecture. (Adapted from Microsoft 2018 )

Figure 1.8 shows the recommended Azure IRA covering both hybrid cloud and edge solution integration. In orange, one can see the core IoT subsystems: IoT devices, cloud gateway (IoT Hub), stream processing, and user interface. The IoT device should be able to register with the cloud gateway, which is responsible for managing the devices. The stream processor consumes and stores the data, and integrates with the business process. For each subsystem, the Azure IRA recommends a specific technology based on Azure services. There is also a set of optional IoT subsystems (in blue): IoT edge devices, data transformation, machine learning, and user management. The edge devices are able to aggregate and/or transform and process the data on premise, while the data transformation (at the cloud) can manipulate and translate telemetry data. The machine learning subsystem allow the IoT system to learn from past data and act properly, such as firing alert to predictive maintenance. Finally, the user management subsystem provides functionality for users to manage the devices.

1.5.2 SAT-IoT

SAT IoT is a platform (Fig. 1.9 ) developed by Spanish company, SATEC, as part of the Horizon 2020 RECAP project. Footnote 1 Smart cities is a primary use case for SAT IoT. As such it needed an architecture that could (1) manage the smart city data network topology at run time, (2) use optimisation techniques that support processing aggregated data by geographical zones, and (3) monitor the IoT system and the optimisation process in run time (Peña and Fernández 2019 ).

The SAT-IoT Architecture. (Adapted from Peña and Fernández 2019 )

Edge/cloud computing location transparency is a core feature of the platform allowing data to be shared between different zones (geographically and from the cloud to the edge), and thus to be processed at any of the edge nodes, mid nodes, or cloud nodes. This is realised by two of the entities in the SaT IoT architecture—the IoT Data Flow Dynamic Routing Entity and the Topology Management Entity. Together, they enable SAT IoT to manage the network topology at run time while also providing the necessary monitoring capabilities to understand the usage pattern and capacity limitations of the infrastructure. The IoT Data Flow Dynamic Routing Entity and the Topology Management Entity are augmented by the integration of the RECAP Application Optimiser in to SAT IoT, which derive the best possible placement of the data processing logic. Figure 1.9 shows the SAT-IoT architecture composed of Physical Layer, Smart Device Entity, IoT Data Flow Collector Entity, IoT Data Flow Dynamic Routing Entity, IoT Topology Management Entity, IoT Visualisation Entity, IoT Cloud Entity, Platform Access Entity, Security and Privacy, and Embedded IoT Applications.

1.5.3 Summary of Architectural Features

Table 1.3 summarises the key functional features addressed in each IoT Reference Architecture, that is interoperability, scalability, security and privacy, data management, analytics, data visualisation and user interface, and supported computing paradigms.

By system interoperability, we mean that the architecture should address connectivity, data management and automatic integration in a transparent way for the end user. Scalability refers to the architecture’s ability to handle increases in the number of IoT devices and endpoints. Security and privacy capability ensures that the information be where it should be and prevents data leakage to unauthorised persons. Data management refers to both the management and exchange of data between architectural components. Analytics refers to the ability of the architecture to capture useful data from the deluge of data that travels on the network. Data visualisation and user interface is related to whether the architecture provides a human interface. Finally, computing paradigm refers to whether the architecture addresses support for new computing paradigms and specifically cloud, fog, edge, and dew computing.

Table 1.3 summarises the key features of different IoT Reference Architectures. It clearly emerges that only two functionalities are met by all Reference Architecture proposals—interoperability and security and privacy. Another common area of focus, unsurprisingly, is data management. Obviously, the primary value driver in the IoT is data and systems are required to manage the volume, velocity and variety of this data, not least where its stored and processes. The IEEE P2413 Reference Architecture presents less functionality; however this is due to the nature of such a standard. It is however the basis for a related smart cities standard (RASC).

When considering the IoT from a business, technical, or research perspective, each of these architecture features should be considered and addressed.

1.5.4 Conclusion

The chapter introduced two perspectives of the Internet of Things—a purely technical and a socio-technical perspective. The Internet of Things is not merely a technical phenomenon. It has the potential to transform how society operates and interacts. As such, it is critical to have a sufficiently general abstraction of the Internet of Things that facilitates sense making without getting in to a non-generalisable level of granularity. We present such an abstraction organised around five entities—social actors, things, data, networks, and events—and the processes that occur between them, all situated in time and space. We provided a brief overview of some of the key enabling technologies and new computing paradigms. Section 1.4 presented seven Reference Architectures for the Internet of Things and compared them across seven dimensions. This provides a further lens with which to consider the Internet of Things.

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Lynn, T., Endo, P.T., Ribeiro, A.M.N.C., Barbosa, G.B.N., Rosati, P. (2020). The Internet of Things: Definitions, Key Concepts, and Reference Architectures. In: Lynn, T., Mooney, J., Lee, B., Endo, P. (eds) The Cloud-to-Thing Continuum. Palgrave Studies in Digital Business & Enabling Technologies. Palgrave Macmillan, Cham. https://doi.org/10.1007/978-3-030-41110-7_1

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What is the Internet of Things (IoT)?

Does your house have a smart thermostat? Or maybe you’re one of the one in three Americans who wears a fitness tracker to help you stay physically active. If you do, you are tapping into the Internet of Things, or IoT. It’s become embedded in our lives, as well as in the way organizations operate.

Get to know and directly engage with senior McKinsey experts on the Internet of Things.

Cindy Levy is a senior partner in McKinsey’s London office; Enno de Boer is a senior partner in the New Jersey office; Gérard Richter is a senior partner in the Frankfurt office; Mark Patel  is a senior partner in the Bay Area office; and Matteo Mancini is a senior partner in the Riyadh office.

IoT uses a variety of technologies to connect the digital and physical worlds. Physical objects can be embedded with sensors and actuators. Sensors monitor things like temperature or motion, or really any change in environment. Actuators receive signals from sensors and then react to the reported changes. Sensors and actuators communicate with computing systems via wired (for example, Ethernet) or wireless (for example, Wi-Fi or cellular) networks; these computers can monitor or manage the health and actions of connected objects and machines.

The constant connectivity that IoT enables, combined with data and analytics, provides new opportunities for companies to innovate products and services, as well as to increase operational efficiency. Indeed, IoT has emerged  as one of today’s most significant trends in the digital transformation of business and economies. Challenges abound, particularly when it comes to IoT cybersecurity, but we estimate the total value potential for the IoT ecosystem could reach $12.6 trillion  by 2030.

What is an IoT device?

An IoT device is any object that has sensors and actuators embedded within it that communicate to an external network. Broadly, IoT devices are used in the following nine fields :

• Human bodies. Devices can be attached to or implanted in the human body, including wearable or ingestible devices that monitor or maintain health and wellness , assist in managing diseases such as diabetes, and more.
• Homes. Homeowners can install devices such as home voice assistants, automated vacuum cleaners , or security systems.
• Retail environments. Devices can be installed in stores , banks, restaurants, and arenas to facilitate self-checkout, extend in-store offers, or help optimize inventory.
• Offices. IoT applications in offices could entail energy management  or security for buildings.
• Standardized production environments. In such settings, including manufacturing plants , hospitals, or farms, IoT applications are usually aimed at increasing operating efficiencies or optimizing equipment use.
• Custom production environments. In customized settings, like those in mining, construction, or oil and gas exploration and production, IoT applications might be used in predictive maintenance  or health and safety efforts .
• Vehicles. IoT can help with condition-based maintenance, usage-based design, or presales analytics for cars and trucks , ships, airplanes, and trains.
• Cities. IoT applications can be used for adaptive traffic control, smart meters, environmental monitoring, or managing resources .
• Outside. In urban environments or other outdoor settings, such as railroad tracks, autonomous vehicles, or flight navigation, IoT applications could involve real-time routing, connected navigation, or shipment tracking.

Other real-world examples abound . IoT solutions are being used in a wide variety of settings: in refrigerators, to help restaurants optimize their food compliance processes; in fields and farms, to track livestock; in offices, to track how many and how often meeting rooms are used; and more.

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What is the economic potential of IoT?

The potential value of IoT is large and growing. By 2030, we estimate it could amount to up to $12.5 trillion globally . That includes the value captured by consumers and customers of IoT products and services.

The potential economic value of IoT varies by usage context. IoT applications in factories and in human health contexts represent outsize shares of this total. IoT in factories alone could generate up to $3.3 trillion by 2030, or just over a quarter of the total value potential. IoT economic impact in human health settings could reach about one sixth of the total estimated value.

Another way of looking at IoT’s value is to explore use case clusters , or similar uses adapted to different settings. The following common use cases account for a sizable share of IoT’s potential economic value:

• optimizing operations, or making the various day-to-day management of assets and people more efficient (41 percent)
• healthcare applications (15 percent)
• human productivity (15 percent)
• condition-based maintenance (12 percent)

Other clusters include sales enablement, energy management, autonomous vehicles (the fastest-growing cluster), and safety and security.

What are IoT platforms?

To get value from IoT, it helps to have a platform  to create and manage applications, to run analytics, and to store and secure your data. Essentially, these platforms do a lot of things in the background to make life easier and less expensive for developers, managers, and users. They handle issues like connecting and extracting data from many different end points, which might be in inconvenient locations with spotty connectivity.

Which IoT platform you select should depend on what your company is trying to achieve with IoT. Here are five things to consider when evaluating IoT platforms :

• Applications environment. Here, you might examine questions like: Can the platform develop, test, and maintain multiple applications? Can it connect easily to the applications my company already uses?
• Data management. It’s helpful to understand if the platform can structure and join multiple unfamiliar data sets, for example.
• Ownership of cloud infrastructure. Does the infrastructure provider own and operate its own data centers, or which public cloud provider does it use? (See “ What is cloud computing? ” for more on this topic.)
• Security. What commercial-grade authentication, encryption, and monitoring capabilities does the platform have, and are they distinctive?
• Edge processing and control. Here, you could examine whether the platform can do edge analytics without first bringing data into the cloud, or whether it can be easily configured to control local assets without human intervention.

What are the key factors for a seamless IoT experience?

A seamless IoT experience meets the following six requirements , spanning enterprise and consumer use cases:

• Hyperconnected. Connectivity is seamless across a vast number of devices and sensors sharing data.
• Integrated. Integration within and across networks of devices is effortless, with simultaneous use of multiple connectivity standards, platforms, and back-end systems.
• Secure and trusted. Dynamic cybersecurity enables a high degree of trust in handling the multilayered complexity of both new and legacy solutions.
• Intelligent. Devices and systems have the intelligence—enabled by AI and machine learning—to draw insights from data and make real-time decisions. This allows for a leap from monitored to automated implementation.
• Mobile. Devices and networks require minimal maintenance, are battery efficient, and have a persona to allow for futuristic experiences.
• Hyperpersonalized. There are personalized experiences across platforms and scenarios.

What should I know about IoT security?

The billions of IoT devices in use have naturally created new vulnerabilities for companies. As more “things” get connected, the number of ways to attack them mushrooms. Pre-IoT, a large corporate network might have had 50,000 to 500,000 endpoints vulnerable to attack; IoT may involve a network with millions or tens of millions of these endpoints. In the 2022 McKinsey B2B IoT Survey, IoT solution suppliers and buyers ranked cybersecurity as the top impediment to IoT adoption.

Overcoming the cybersecurity obstacle may be the determining factor  in whether IoT will be able to transition to a truly integrated network—and achieve its massive value potential.

It’s important to address customer privacy concerns  vis-à-vis connected devices. But managing IoT cybersecurity  is also about protecting critical equipment, such as pacemakers or entire manufacturing plants—which, if attacked, could put customers’ health or companies’ production capabilities at risk.

Six recommendations can help CEOs and other leaders tackle IoT cybersecurity:

• understand what IoT security means for your industry and business model
• set clear roles and responsibilities for IoT security in your supply chain
• hold strategic conversations with other industry players, including regulators
• prioritize cybersecurity for the entire product life cycle
• transform mindsets and skills
• create a point-of-contact system for external security researchers and implement a postbreach response plan

Learn more about our Digital McKinsey ,  Technology, Media & Telecommunications , Risk & Resilience , and People & Organizational  Practices.

What is IIoT?

The Industrial Internet of Things , or IIoT, is among the advanced manufacturing technologies collectively referred to as Industry 4.0 , or the Fourth Industrial Revolution.

What are some benefits of IIoT technologies? They can drastically reduce downtime, open up new business models, and improve customer experiences—and they can also make organizations more resilient. In the COVID-19 era, for example, digital management tools and constant connectivity allowed some companies to quickly respond to market changes by adjusting production capacity and simultaneously supporting remote operations.

Companies using IIoT for digital transformation  in manufacturing can follow seven guideposts to align their business, organization, and technology spheres to reap the full benefits from IIoT:

• identify and prioritize use cases
• focus on plant rollout and enablement
• monitor change and performance management
• build capabilities and embrace new ways of working
• attend to IIoT and data infrastructure, with a focus on core platform design and cybersecurity
• choose an IIoT cloud platform
• monitor the tech ecosystem

What could affect IoT adoption?

When it comes to getting more value from IoT, there are tailwinds as well as headwinds that will affect IoT adoption.

Three factors could accelerate the adoption and impact of IoT solutions:

• Perceived value proposition. Customers see value in IoT and the way it enables digital transformation and sustainability efforts.
• Technology. Affordable technology, which enables IoT deployments at scale, exists for the vast majority of IoT applications. Progress in hardware can be coupled with developments in analytics, AI, and machine learning, which can enable more granular insights and faster decision making.
• Networks. These are the backbone of IoT, and higher-performing 4G and 5G  networks are now available to more people.

Conversely, a variety of factors could constrain adoption. These include the need for new avenues of collaboration across functions, interoperability issues, and installation challenges, as well as concerns about cybersecurity  and individual privacy.

If your organization is just getting started, it can be helpful to consider what could accelerate enterprise IoT journeys . In a McKinsey interview, Wienke Giezeman, a serial tech entrepreneur and initiator of The Things Network, offers insight on what can drive action: “We’ve seen this in the industry again and again—you cannot solve IoT problems with money. It’s so tempting to try to solve these problems with cash, but really, it’s the creativity and pushing for simplicity that leads to the solution.”

Learn more about our Digital McKinsey ,  Technology, Media & Telecommunications , and  Operations  Practices.

How can IoT efforts be scaled?

To really see the benefits of IoT, companies should embrace the technology at scale, rather than make one-off efforts. If your organization is adopting IoT, here are seven useful actions for scaling IoT :

• Decide who owns IoT in the organization
• Design for scale from the start
• Don’t dip your toe in the water—deploying multiple use cases can be a forcing mechanism in transforming operating models, workflows, and processes
• Invest in technical talent
• Change the entire organization, not just the IT function
• Push for interoperability
• Proactively shape your environment by building and controlling IoT ecosystems

For more in-depth exploration of these topics, see McKinsey’s Insights on the Internet of Things . Learn more about IoT consulting —and check out IoT-related job opportunities  if you’re interested in working at McKinsey.

Articles referenced:

• “ Cloud-powered technologies for sustainability ,” November 9, 2023, Bernardo Betley, Tommaso Cariati, Fan Gao , Eric Hannon , Cindy Levy , Francesco Parente, and Julyeon Seo
• “ Cybersecurity for the IoT: How trust can unlock value ,” April 7, 2023, Jeffrey Caso, Zina Cole, Mark Patel , and Wendy Zhu
• “ IoT comes of age ,” March 7, 2022, Michael Chui  and  Mark Collins
• “ IoT value set to accelerate through 2030: Where and how to capture it ,” November 9, 2021, Michael Chui , Mark Collins , and Mark Patel
• “ A manufacturer’s guide to scaling Industrial IoT ,” February 5, 2021, Andreas Behrendt ,  Enno de Boer , Tarek Kasah, Bodo Koerber,  Niko Mohr , and  Gérard Richter  
• “ Industry 4.0 adoption with the right focus ,” October 21, 2021, Matteo Mancini ,  Gustavo Marteletti ,  Alpesh Patel ,  Laura Requeno , and  Tingfeng Ye

This article was updated in May 2024; it was originally published in August 2022.

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