Blockchain: Structure, Uses, and Applications in IoT

One of the modern trends in the development of information and communication technologies that have evolved into the Internet of Things (IoT) paradigm is the progressive idea of using blockchain technology in IoT. This trend is described in a large number of modern literature sources, which point out the significant advantages of using blockchain, primarily related to decentralization, immutability, transparency and security. This allows us to conclude that the implementation of blockchain technology in IoT information and communication systems is highly relevant. However, the authors of different studies describe significant problems, including the problem of scalability of the blockchain itself, as well as the problems of energy efficiency and limited resources in IoT devices. Due to these problems, the implementation of blockchain technology in the Internet of Things is becoming a challenge and determines the relevance and feasibility of researching this topic and finding effective solutions related to the integration of two very powerful technologies in modern information and communication systems. The article presents an analytical overview of the issues of integrating blockchain technology into IoT, in particular, the use of the Proof-of-Work (PoW) consensus algorithm in IoT and the use of alternative blockchain protocols, including IOTA, Ethereum Light Client and Litecoin, which allow increasing the efficiency of performing tasks in IoT infrastructure, taking into account the limited resources of devices; existing problems and implementation methods, such as the use of light clients and proxy servers. The article also considers the feasibility of using a full blockchain node on IoT devices and ways to increase system efficiency by pre-processing data before sending it to the blockchain network. The article also highlights the problem of insufficient implementation of blockchain technology in various spheres of human life, as well as the search for the reasons for this problem. The results of the analytical review make it possible to substantiate the purpose and advantages of integrating blockchain technology into the Internet of Things, as well as to summarize the main issues and substantiate a number of tasks for relevant and progressive scientific research in the field of modern information and communication systems.

Under the background of prosperity of Internet of things (IoT), in order to accelerate the training of talented persons of China for IoT, we propose to design and develop a new course for Chinese students: Essential Technologies, Applications, and Commercial Patterns of Internet of Things. Aiming at three-dimensional target, which has dimensionalities of attitude and thoughts, knowledge and skills, process and methods, the contents of the course include the following parts: system and application architectures, key technologies of IoT, applications of IoT, commercial patterns of IoT, IoT industry and social significance etc. The course highlights the training of abilities of innovation, creativity, comprehensive analysis and practical operations. The construction of teaching resources, such as textbooks, lecture notes, teaching equipments, practice bases, are also emphasized in the process of development of this course.

The internet of things (IoT) is focused in offering new technologies which is changing the business environment by showing the potential in different sectors like retail, transportation, healthcare etc. Through IoT, the managers can gather and process data and information in an effective manner, also they can use them to automate in order to enhance productivity and efficiency. With the usage of such technologies, human resource managers can access information for possible candidates which can be accessed through IoT. The overall behaviour of potential candidate tends to help them in shortlisting and choosing the desirable ones. The application of IoT has emerged in enhancing the recruitment of candidates in search of candidates based on large volume of information, assist in screening the candidates, selecting the most suitable ones. The application of IoT technology can modify the HR roles, enable in changing the company perspective in enhancing recruitment process, source the candidates effectively and select them so as to meet the organisational requirements. The implementation of IoT driven technologies support in removing the biases in screening the candidates and aids in candidate selection with the support of other technologies like artificial intelligence, predictive analytics etc. Furthermore, IoT is also involved in better inventory management as it supports the organisation in converting the data which are sourced through RFID (Radio Frequency Identification) into more insights related to inventory data, location of the products, tracking the movement of goods until it reaches the hands of the customers. With the application of IoT inventory managers possess better control in managing the inventory through automated ordering request and thereby reduce manual time and cost for the business. This paper is focused in presenting a conceptual understanding on the application of environmental IoT in recruitment process and also the overall impact created by the technology in managing the inventory efficiently.KeywordsInternet of thingsRecruitment processInventory managementPredictive analytics

Internet of Things (IoT) applications are generally developed in a vertical manner, i.e., each IoT application is developed for a certain scenario which generally does not share data with IoT applications for recommendation services. This leads to an inefficient exploitation of other IoT service applications. In fact, such recommendation services can be achieved with the help of Social IoT (SIoT) by using data generated by various IoT applications. SIoT builds a profile of objects based on IoT applications data that can be exchanged with SIoT network for accessible to other IoT applications. In this manner, the SIoT network provides recommendation services for reusability of IoT applications' data among various IoT applications, as well as adapting IoT services according to users' needs which improve user experience. Additionally, the profiles built by a SIoT network can also help a single IoT application by looking for similar conditions that have been addressed in the past for the same IoT application. We propose a concept for exploiting the SIoT for recommendation services among various IoT applications with the help of a sample application scenario that highlights how the SIoT can help by providing recommendations. We also provide some implementation challenges for this concept.

SummaryThe Internet of Things (IoT) is the future technology, whose glimpses are already visible in various fields today. IoT promises a connection of about 50 billion devices in the near future to enhance data sharing and analysis between many otherwise independent modules. Smart sensors, smart antennas, and intelligent processors form the backbone of IoT technology. IoT is about remote detection and control of devices which is dependent on the efficient communication system provided. This paper studies the IoT technology, along with its supportive systems, giving an emphasis to the communication module, enabled using microstrip patch antennas. The study takes a walk through the different improvement techniques implemented in patch antennas as DGS, MIMO, and arrays and further pins down the research gaps and objectives that can be taken up in this field with respect to the effective implementation of IoT services. Recent advances in the antenna systems employed in IoT environment are discussed, and the antennas employed in IoT devices and applications are reviewed in detail. Recently evolving technologies like LoRa and NB‐IoT and the ESP8266 module which is widely used in IoT applications are addressed. A good insight is given into the challenges faced in this field along with some recent case studies.

The correct implementation and behavior of Internet of Things (IoT) applications are seldom investigated in the literature. This paper shows how the simulation mechanism can be integrated well into an IoT application development platform for correct implementation and behavior investigation. We use an IoT application development platform called IoTtalk as an example to describe how the simulation mechanism called SimTalk can be built into this IoT platform. We first elaborate on how to implement the simulator for an input IoT device (a sensor). Then we describe how an output IoT device (an actuator) can be simulated by an animated simulator. We use a smart farm application to show how the simulated sensors are used for correct implementation. We use applications including interactive art (skeleton art and water dance) and the pendulum physics experiment as examples to illustrate how IoT application behavior investigation can be achieved in SimTalk. As the main outcome of this paper, the SimTalk simulation codes can be directly reused for real IoT applications. Furthermore, SimTalk is integrated well with an IoT application verification tool in order to formally verify the IoT application configuration. Such features have not been found in any IoT simulators in the world.

As a major agricultural province in China, Shandong Province has always played an important role. At the same time, it is also closely related to the strong support of science and technology. As a new technology, the Internet of things (IoT) has made positive contributions. Agricultural IoT is a mode that uses information technology, wireless communication technology and radio frequency automatic identification technology to share the identified agricultural information to the network. The application of agricultural IoT is a major change in agricultural development, which provides convenient conditions for the development of agriculture, provides a favorable environment for the agricultural products, promotes the transformation of agricultural technology, realizes the informatization of agricultural production, improves the efficiency of rural land, integrates agricultural resources and provides a foundation for food safety. In this paper, the application of IoT in the field of agriculture in Shandong Province is described from two practical cases. One is about how to use wireless sensor network technology to transmit data in the big data platform based on the Bohai granary project. The other describes how to use IoT for food quality and safety traceability. It takes pigs as the research object, runs through all links of the whole industrial chain of pig breeding, breeding, slaughtering, processing, logistics and sales, collects the data of the whole industrial chain with the help of IoT, and realizes the information tracking and traceability of the whole industrial chain. At the end of the paper, it discusses the countermeasures.

This research presents a cutting-edge approach that combines chemical engineering principles with artificial intelligence (AI) to enhance battery maintenance in Internet of Things (IoT) applications. The study develops predictive maintenance models capable of accurately forecasting battery degradation, thereby optimizing usage patterns and extending battery life. By integrating electrochemical data with AI-driven predictive analytics, the project enables real-time monitoring of battery health, achieving over 90% accuracy in anticipating maintenance needs, which reduces unplanned downtime and lowers operational costs. Employing machine learning frameworks, data analysis tools, and chemical engineering simulation software, the focus is on lithium-ion and solid-state batteries, commonly used in IoT networks across sectors such as smart cities, agriculture, and healthcare. Key results include a 20−30% increase in battery lifespan and a 15% improvement in energy efficiency, significantly reducing electronic waste and environmental footprint. This interdisciplinary approach provides a foundation for sustainable battery technology in IoT technology, paving the way for future advancements in AI-augmented predictive maintenance and chemical engineering models for next-generation applications. The integration of AI with chemical engineering principles allows for the development of models that adapt to the unique electrochemical behavior of different battery types, such as lithium-ion and solid-state batteries. By analyzing lifecycle data and device usage patterns, predictive models can account for variables that influence battery performance over time, including temperature fluctuations and charging cycles. This project utilizes neural networks and reinforcement learning algorithms to train models capable of learning from historical data, enhancing their predictive capabilities. A significant aspect of this research involves the preprocessing of battery lifecycle data to ensure high data quality, which is critical for accurate model training and validation.

Nowadays, monitoring health systems in robust technology has been extensively applied in the sports field. Even though massive utilization of wearable device technologies aims to quantify athlete performance, inconsistent performance still exists between training sessions and competition. The rigorous discussion about the latest research in monitoring technological systems will help trainers obtain accurate data about athlete performance. This paper focuses on the athlete monitoring system in terms of psychological and physiological parameters and applications in individual sports based on Internet of Things (IoT) Technology. The study incorporates three factors: the parameters that affect athlete performance, multiple device sensors in sports health monitoring, and IoT technology’s application for athletes. Based on analysis and observation, efficient sports health monitoring can effectively enhance athlete performance in physiological and psychological conditions. An IoT system encompasses four main aspects: sensing, networking, data processing and application layer. These aspects provide real-time information on the athlete’s body condition during training and games. Therefore, this monitoring system greatly assists coaches in designing practical training and activities for athletes. It is highlighted that wearable health monitoring systems by IoT technology will be further built based on athlete requirements.

The Internet of Things (IoT) technology will soon become an integral part of our daily lives to facilitate the control and monitoring of processes and objects and revolutionize the ways that human interact with the physical world. For all features of IoT to become fully functional in practice, there are several obstacles on the way to be surmounted and critical challenges to be addressed. These include, but are not limited to cybersecurity, data privacy, energy consumption and scalability. The Blockchain decentralized nature and its multi-faceted procedures offers a useful mechanism to tackle several of these IoT challenges. However, applying the Blockchain protocols to IoT without considering their tremendous computational loads, delays, and bandwidth overhead can let to a new set of problems. This review evaluates some of the main challenges we face in the integration of Blockchain and IoT technologies and provides insights and high level solutions that can potentially handle the shortcomings and constraints of both IoT and Blockchain technologies.

With the advancement of computing technology, we are witnessing the dawn of a new era of the Internet of Things (IoT) paradigm in which objects equipped with sensors, actuators and processing capabilities communicate with each other to serve a given goal. The IoT’s intrinsic nature, which uses heterogeneous devices, resources and different communication protocols, complicates IoT applications’ design, development, and validation. Reducing the complexity of building IoT applications is one of the current challenges in this area.To address this challenge, we focus on a model-driven approach to support IoT systems’ management and the development of IoT applications. In particular, we propose the FloWare approach and its toolchain, which combine Software Product Line and Flow-Based Programming paradigms to manage the complexity in the various stages of the IoT application development process. An automatic transformation procedure generates the final IoT application, an executable Node-RED flow, starting from a configuration of the designed Feature Models.KeywordsIoTModel-drivenFeature modelFlow-based programmingNode-RED

SummaryIn recent years, applying Internet of Things (IoT) applications has significantly increased to facilitate and improve quality of human life activities in various fields such as healthcare, education, industry, economics, etc. The energy aware cloud‐edge computing paradigm has developed as a hybrid computing solution to provide IoT applications using available cloud service providers and fog nodes for the smart devices and mobile applications. Since the IoT applications are developed in the form of several IoT services with various quality of service (QoS) metrics which can deploy on the cloud‐edge providers with different resource capabilities, finding an efficient placement solution as one of challenging topics to be measured for IoT applications. The service placement issue arranges IoT applications on the cloud‐edge providers with various capabilities of atomic services though sufficient different QoS factors to support service level agreement (SLA) contracts. This paper presents a technical analysis on the cloud‐edge service placement approaches in IoT systems. The key point of this technical analysis is to identify substantial studies in the service placement approaches which need additional consideration to progress more efficient and effective placement strategies in IoT environments. In addition, a side‐by‐side taxonomy is proposed to categorize the relevant studies on cloud‐edge service placement approaches and algorithms. A statistical and technical analysis of reviewed existing approaches is provided, and evaluation factors and attributes are discussed. Finally, open issues and forthcoming challenges of service placement approaches are presented.

Blockchain technology has been regarded as a paradigm that enables enterprises to deploy decentralized Internet of things (IoT) applications, which require security, mutual truthfulness, privacy, and data reliability. However, the adoption of blockchain technology on IoT applications has been limited due to the lack of blockchain's capability to process a huge amount of transaction requests from IoT devices. In this paper, we propose a new transaction processing mechanism, called Accelerator, which improves the performance of blockchain-based IoT applications in terms of transaction throughput and latency. Two key design ideas of Accelerator lie in: (i) independent modular structure that can be implemented without changing the incumbent blockchain network and (ii) adaptive multi-batch scheduling engine for robust performance. We first provide a mathematical analysis that is used to choose the parameters of Accelerator to maximize the performance. Moreover, we implement Accelerator on a decentralized blockchain network using Hyperledger Fabric and perform the extensive test using Hyperledger Caliper. We show that Accelerator achieves 8x transaction throughput improvement without sacrificing latency.

The Blockchain technology provides a way to record transactions or any digital interaction that is designed to be secure, tamper-proof, transparent, highly resistant to outages, traceable and auditable. The Internet of Things (IoT) technology is able to link computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers (UIDs) and provides the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction. These features encourage us to explore the combined application of IoT and Blockchain-based technology. In this paper, we propose a system architecture of blockchain and IoT based intellectual property protection system, which can process three types of intellectual property: 1) Patents, Copyrights, Trademarks etc.; 2) Industrial design, Trade dress, Craft works, Trade secrets etc.; and 3) Plant variety rights, Geographical indications etc. Using blockchain P2P network and IoT devices, the system can help us to establish a trusted, self-organized, open and ecological intellectual property protection system. To the best of our knowledge, this is the first work that applying blockchain technology and IoT technology on traditional intellectual property protection and trade ecosystem.

Bitcoin and Ethereum's low transaction per second (TPS) rate has prohibited the adoption of Blockchain in areas such as Internet of Things (IoT) and Internet of Medical Things (IoMT). Despite these constraints, there is considerable research in this area, outlining the benefits of employing Blockchain in IoT applications. Such benefits relate to ensuring that the applications and their data are secure, and integrity is maintained. However, the relatively low TPS rate is still an impediment for the widespread adoption of Blockchain in IoT. This research seeks to explore whether Solana, a new Blockchain technology designed to have a high TPS rate, can overcome this challenge. Can the Solana Blockchain achieve a TPS rate higher than that achieved in other works in the literature? Can a sufficient rate be achieved that could help Blockchain technologies become an enabler in the IoT industry? These are the questions that this research aims to answer. Our experiments conducted on an application coded in Rust on Solana Blockchain demonstrated that it can successfully achieve a 663 TPS rate. Consequently, we conclude that Solana, by overcoming the aforementioned TPS rate issue, could advance the further adoption of Blockchain in IoT context.