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Zombro72928 April 30, 2023 Comment

The information era is coming. As a popular technology in the information age, Internet of Things (IoT) can collect various types of information in real time, realize the ubiquitous connection between things and people, and process the intelligent perception, identification, and management of things, processes, and information, and environment protection through various network access methods. Applying IoT to various fields is like wrapping the Earth with a layer of “digital skin” (Gubbi et al., 2013; Bauwens et al., 2020; Li and Da Xu, 2020). Moreover, under the trend of global warming, the emergence of the theme of Energy Saving and Emission Reduction (ESER) undoubtedly poses new challenges to the development of IoT.

When IoT is widely used in various life scenarios, its main purpose is to provide intelligent services and environments. IoT applications can connect any sensing device to the Internet for data transmission, so as to realize intelligent identification, tracking, positioning, and monitoring of sensing devices. In addition, IoT contains many types of Wireless Sensor Networks (WSN), which, as a part of IoT sensing layer, can meet the actual needs of people to obtain reliable data in special environments (Sadowski and Spachos, 2020). WSN is a multi-hop network which is self-organized by many sensor nodes. It has the characteristics of flexibility, fault tolerance, high awareness, low cost, strong survivability, and fast layout. Therefore, IoT has a wide range of applications, such as environmental monitoring, agriculture, military, and medical care, and can collect, process, and disseminate collected data deployed in various environments (Aman et al., 2020; Fortino et al., 2020). However, for some special scenes, many sensor nodes are often placed in areas that cannot be accessed by human beings. While enjoying the convenience brought by WSN, people are also faced with the problems that illegal personnel obtain illegitimate interests by intercepting the monitoring data transmitted in the public channel. Therefore, the attention to security issues in IoT cannot be ignored.

With the increasing commercial scope of 5th Generation Mobile Communication Technology (5G) communication technology in cities, the application of IoT in power, construction, industry, intelligent transportation, agriculture, logistics, intelligence, high efficiency, and ESER is being promoted (Verma et al., 2020). Of course, applying IoT is also inseparable from the combination of 5G communication, Cloud Computing (CC), Edge Computing (EC), blockchain, AI, and other technologies. IoT can collect many data from the environment, effectively monitor, analyze, and manage energy consumption, and reasonably improve IoT by identifying and analyzing opportunities of energy efficiency improvement (Khan et al., 2020; Liao et al., 2020; Saračević et al., 2020).

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In summary, in today’s high-speed 5G communication technology, IoT is widely applied, and guaranteeing its performance is of high significance. Therefore, taking the practical application of IoT as the theme, this work explores the application of intelligent power, intelligent building, intelligent industry, intelligent transportation, intelligent agriculture, and intelligent logistics. In addition, it analyzes the intelligent prospect of IoT application based on the intelligent Information Security (IS) of IoT system and CE (carbon emission) reduction under the cooperation of Artificial Intelligence (AI), so as to provide a theoretical reference for the intelligent development of smart cities (SC) and social system and ESER.

With the penetration of “everyone connected” to “everything connected” in various industries, IoT is well-known as a symbol of SC in the Internet + era. IoT can equip Radio Frequency Identification Tag (RFID), sensors, two-dimensional code, and other types of sensors to a variety of real objects, through the interface and wireless network connection, and then run the original program for remote control or direct communication among objects, so as to realize the interconnection and dialogue between people and objects, and objects and objects, so that the urban environment realizes self-perception, and lays a foundation for data collection, mining analysis, and decision support (Abd El-Latif et al., 2020; Wang T et al., 2020). When IoT is applied in SC, its architecture is designed based on the initial three-tier architecture (Figure 1).

IoT system is mainly composed of collection, transmission, and application layers. Its terminal data-collection layer contributes to the construction of SC and IoT information system. The application layer is a critical component to give full play to the system function, and network transmission layer to connect the SC information system.

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Therefore, the application of IoT system in all walks of life is described respectively for SC construction. It mainly classifies the applications of IoT in intelligent power, intelligent building, intelligent industry, intelligent transportation, intelligent agriculture, intelligent logistics, and other fields (Figure 2).

Ubiquitous power IoT applies the IoT in power systems. Its essence is the resource-sharing of all professional perception layers, the aggregation and collaborative application of all kinds of data, the real-time online combination of data accommodation and businesses, the promotion of regional energy autonomy, and the better support of resource allocation, business collaboration, and risk prevention and control, to form a physical entity with self-perception and intelligent active operation (Adi and Kitagawa, 2019). Application of IoT in electric power has been studied extensively. Niu et al. (2019) proposed a power IoT load distribution mechanism for EC, which further realized the optimal distribution of workload. Balanced Initialization, Resource Allocation, and Task Allocation (BRT) algorithms were presented. The simulation results showed that this mechanism could minimize the service delay compared with Simulated Annealing Algorithm (SAA), LoAd Balancing (LAB), and Latency-awarE orkload offloaDing (LEAD). Fu et al. (2020) put forward a distributed User Cluster (UC) algorithm for clustering IoT devices into multiple UC and a system optimization model to lower the power consumption. Finally, many simulations suggested the effectiveness of the algorithm (Fu et al., 2020). Gomez et al. (2020) (Gomez et al., 2020) introduced the Static Context Header Compression and Fragmentation (SCHC) to solve insufficient self-adaption based on 6LoWPAN. Kaur et al. (2021), Lee et al. (2021) used transfer learning algorithm to deal with challenges related to data storage and processing and computational complexity in power IoT system, and finally found that the technology could bring innovation and higher productivity to intelligent changes in power systems.

It is found that most scholars optimize the performance of power systems based on the IoT, but there are few studies on fault occurrence, efficiency reduction, and function failure in power IoT system. Moreover, the accuracy and adaptability of operation state evaluation and Life Cycle (LC) prediction of complex power equipment in physical space are difficult to meet. It is unknown whether the industrial Big Data (BD) shared by various sensing equipment information and communication information is fully utilized in the power IoT. In view of the possible problems and faults in the power IoT mentioned above, the Digital Twins (DTs) technology is applied to it. The specific DTs-based power IoT system is shown in Figure 3.

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The intelligent management system of DTs-based power IoT engine monitors the bearing vibration and rotating shaft speed of the entity in real time using current power sensors and angular speed sensors. The system uses DTs technology to map the specification data, stored historical data, and real-time collected data in the physical entity of power IoT engine into the virtual space (Kaur et al., 2021), then fuses and extracts the data, transmits the data features to the cloud platform, and describes the components of the engine from multiple dimensions such as physics, information, and behavior. The engine entity and its DTs information model operate together, and the twinning data generated includes the data perceived during operation, as well as the simulation data of shafting wear, torsional vibration, thermal stress, and other data generated by the information model (Montazerolghaem and Yaghmaee, 2020; Rahman et al., 2020). Finally, it is applied to the condition monitoring, fault diagnosis, optimized operation, and maintenance guidance services of power IoT engine.

In the construction field, as the “brain” of the intelligent control of the whole building, the IoT system can comprehensively and centrally manage and control each separate intelligence, including air conditioning, fresh air, lighting systems, energy metering monitoring, and PM 2.5 concentration monitoring, so as to realize intelligent, healthy, safe, efficient, and sustainable development (Spachos et al., 2018). Many scholars have explored using IoT in architecture. Plageras et al. (2018) put forward a new system for collecting and managing sensor data in operating intelligent buildings in the IoT environment. The results showed that the proposed solution for collecting and managing sensor data could lead to energy-saving intelligent buildings and green intelligent buildings. Kumar et al. (2018) mainly focused on the application of IoT sensor actuators in intelligent buildings, such as air quality, lighting, and heating/cooling, and proved that the system could understand the importance of various factors in intelligent buildings. Jia et al. (2019) summarized the current technologies of IoT applied to buildings and related fields, including three different levels based on the traditional IoT architecture, and discussed the priorities and challenges of successful seamless IoT integration in intelligent buildings. In addition, issues were discussed to promote the implementation of IoT in the construction and operation stages. Yu K et al. (2020) proposed a IoT-based intelligent building architecture, and found that the data aggregation of indoor