Traditional Internet Of Things Research Articles

Vibration IOT Control Algorithm for Steel Structures of Concrete Buildings with Elastic Boundary Constraints

Abstract Because of the influence of steel structure’s elastic properties in concrete buildings, the traditional vibration Internet of Things (IOT) control algorithm of steel structures has the problem of low control efficiency. Based on the research subject of concrete buildings, a corresponding steel structure model is established, and the corresponding vibration control standard is determined according to the characteristics of the model. In this model, the boundary elastic constraints of the steel structure are set according to its structural characteristics, and the vibration characteristics of the steel structure are analyzed under the constraints. The external vibration signal is simulated, and the response of the building’s steel structure under different signal excitations is observed. According to the response characteristics of the steel structure, the vibration controller is designed and installed, the real-time vibration signal is input into the controller, and finally the vibration control of steel structure of concrete building is realized. By comparison with the traditional vibration IOT control algorithm, it is concluded that the vibration control method designed by combining vibration frequency and vibration amplitude has smaller error and shorter time cost, that is, the designed vibration IOT control algorithm has more advantages in control efficiency.

Multi-attribute Feature Fusion Algorithm of IoT Communication Big Data Based on Ant Colony Neural Network

Abstract To address the issues of time-consuming and inaccurate feature fusion in traditional Internet of Things (IoT) communication big data multi-attribute fusion algorithms, a new algorithm based on the ant colony neural network is proposed. Modeling and feature decomposition processing is carried out on IoT communication big data, communication data information and data attribute characteristics are optimized into different data groups according to a data clustering algorithm, and a rough set calculation method is used to calculate information attribute characteristics. The genetic algorithm is used to improve the ant colony neural network, improve the search ability, extract the multi-attribute characteristics of IoT communication big data, filter the current big data’s characteristic attribute demand through the comparison method, and achieve multi-attribute feature fusion of IoT communication big data through the similarity measurement method. The experimental results show that the fusion error of the IoT communication big data multi-attribute feature fusion algorithm based on the ant colony neural network is small and relatively stable. During the 600 MB data fusion process, the data fusion processing time of the method in this paper is 150 ms, and the average energy consumption ratio is below 2 %, which reflects better IoT communication big data multi-attribute feature fusion performance.

FedRDR: Federated Reinforcement Distillation-Based Routing Algorithm in UAV-Assisted Networks for Communication Infrastructure Failures

Traditional Internet of Things (IoT) networks have limited coverage and may experience failures due to natural disasters affecting critical IoT devices, making it difficult for them to provide communication services. Therefore, how to establish network communication service more efficiently in the presence of fault points is the problem we solve in this paper. To address this issue, this study constructs a hierarchical multi-domain data transmission architecture for an emergency network with unmanned aerial vehicles (UAVs) employed as core communication devices. This architecture expands the functionality of UAVs as key network devices and provides a theoretical basis for their feasibility as intelligent network controllers and switches. Firstly, the UAV controllers perceive the network status and learn the spatio-temporal characteristics of air-to-ground network links. Secondly, a routing algorithm within the domain based on federated reinforcement distillation (FedRDR) is developed, which enhances the generalization capability of the routing decision model by increasing the training data samples. Simulation experiments are conducted, and the results show that the average communication data size between each domain controller and the server is approximately 45.3 KB when using the FedRDR algorithm. Compared to the transmission of parameters through federated reinforcement learning algorithms, FedRDR reduces the transmitted parameter size by approximately 29%. Therefore, the FedRDR routing algorithm helps to facilitate knowledge transfer, accelerate the training process of intelligent agents within the domain, and reduce communication costs in resource-constrained scenarios for UAV networks and has practical value.

Fog computing: a platform for big-data marketing analytics.

Marketing science embraces a wider variety of data types and measurement tools necessary for strategy, research, and applied decision making. Managing the marketing data generated by internet of things (IoT) sensors and actuators is one of the biggest challenges faced by marketing managers when deploying an IoT system. This short note shows how traditional cloud-based IoT systems are challenged by the large scale, heterogeneity, and high latency witnessed in some cloud ecosystems. It introduces researchers to one recent breakthrough, fog computing, an emerging concept that decentralizes applications, strategies, and data analytics into the network itself using a distributed and federated computing model. It transforms centralized cloud to distributed fog by bringing storage and computation closer to the user end. Fog computing is considered a novel marketplace phenomenon which can support AI and management strategies, especially for the design of "smart marketing".

LoRaWAPS: A Wide-Area Positioning System Based on LoRa Mesh

The positioning task of the Internet of Things (IoT) for outdoor environments requires that the node devices meet the requirements of low power consumption, long endurance, and low cost and that the positioning system can achieve high-precision positioning and wide-area coverage. Considering that traditional IoT positioning technology cannot balance the cost, energy consumption, and positioning performance well, a Wide-Area Positioning System Based on Long Range Mesh (LoRaWAPS), which is a low-cost and low-power outdoor positioning system with multi-anchor wireless mesh networking and multi-dimensional data fusion, is designed in this paper. To meet the need for a positioning system, a low-power consumption and high-reliability LoRa Mesh protocol is proposed. Aiming at the problem that the accuracy of LoRa ranging is easily affected by the non-line-of-sight (NLOS) path propagation of signals, a distance estimation algorithm based on the fusion of time of flight (TOF) and received signal strength indicator (RSSI) multi-sampling data is proposed. Furthermore, a position estimation algorithm is designed to minimize the posteriori RSSI error for multi-anchor cooperative estimation scenarios. Furthermore, the prototype of LoRaWAPS is built and tested in the campus environment. The experimental results show that the proposed system can provide reliable location service with low power and low cost.

Bio-Inspired Internet of Things: Current Status, Benefits, Challenges, and Future Directions.

There is no doubt that the involvement of the Internet of Things (IoT) in our daily lives has changed the way we live and interact as a global community, as IoT enables intercommunication of digital objects around us, creating a pervasive environment. As of now, this IoT is found in almost every domain that is vital for human survival, such as agriculture, medical care, transportation, the military, and so on. Day by day, various IoT solutions are introduced to the market by manufacturers towards making our life easier and more comfortable. On the other hand, even though IoT now holds a key place in our lives, the IoT ecosystem has various limitations in efficiency, scalability, and adaptability. As such, biomimicry, which involves imitating the systems found in nature within human-made systems, appeared to be a potential remedy to overcome such challenges pertaining to IoT, which can also be referred to as bio-inspired IoT. In the simplest terms, bio-inspired IoT combines nature-inspired principles and IoT to create more efficient and adaptive IoT solutions, that can overcome most of the inherent challenges pertaining to traditional IoT. It is based on the idea that nature has already solved many challenging problems and that, by studying and mimicking biological systems, we might develop better IoT systems. As of now, this concept of bio-inspired IoT is applied to various fields such as medical care, transportation, cyber-security, agriculture, and so on. However, it is noted that only a few studies have been carried out on this new concept, explaining how these bio-inspired concepts are integrated with IoT. Thus, to fill in the gap, in this study, we provide a brief review of bio-inspired IoT, highlighting how it came into play, its ecosystem, its latest status, benefits, challenges, and future directions.

Survey: An Overview of Lightweight RFID Authentication Protocols Suitable for the Maritime Internet of Things

The maritime sector employs the Internet of Things (IoT) to exploit many of its benefits to maintain a competitive advantage and keep up with the growing demands of the global economy. The maritime IoT (MIoT) not only inherits similar security threats as the general IoT, it also faces cyber threats that do not exist in the traditional IoT due to factors such as the support for long-distance communication and low-bandwidth connectivity. Therefore, the MIoT presents a significant concern for the sustainability and security of the maritime industry, as a successful cyber attack can be detrimental to national security and have a flow-on effect on the global economy. A common component of maritime IoT systems is Radio Frequency Identification (RFID) technology. It has been revealed in previous studies that current RFID authentication protocols are insecure against a number of attacks. This paper provides an overview of vulnerabilities relating to maritime RFID systems and systematically reviews lightweight RFID authentication protocols and their impacts if they were to be used in the maritime sector. Specifically, this paper investigates the capabilities of lightweight RFID authentication protocols that could be used in a maritime environment by evaluating those authentication protocols in terms of the encryption system, authentication method, and resistance to various wireless attacks.

A Microservice and Serverless Architecture for Secure IoT System

In cross-border transactions, the transmission and processing of logistics information directly affect the trading experience and efficiency. The use of Internet of Things (IoT) technology can make this process more intelligent, efficient, and secure. However, most traditional IoT logistics systems are provided by a single logistics company. These independent systems need to withstand high computing loads and network bandwidth when processing large-scale data. Additionally, due to the complex network environment of cross-border transactions, the platform’s information security and system security are difficult to guarantee. To address these challenges, this paper designs and implements an intelligent cross-border logistics system platform that combines serverless architecture and microservice technology. This system can uniformly distribute the services of all logistics companies and divide microservices based on actual business needs. It also studies and designs corresponding Application Programming Interface (API) gateways to solve the interface exposure problem of microservices, thereby ensuring the system’s security. Furthermore, asymmetric encryption technology is used in the serverless architecture to ensure the security of cross-border logistics data. The experiments show that this research solution validates the advantages of combining serverless architecture and microservices, which can significantly reduce the operating costs and system complexity of the platform in cross-border logistics scenarios. It allows for resource expansion and billing based on application program requirements at runtime. The platform can effectively improve the security of cross-border logistics service processes and meet cross-border transaction needs in terms of data security, throughput, and latency.

A Blockchain-based MQTT Protocol Optimization Algorithm

The communication protocol is an important support to realize the communication between equipment and Internet. And it covers all aspects of the IoT (Internet of things) system. To address the security problem of forging or tampering of key data in traditional IoT protocols, this paper designs an improved MQTT (message queue telemetry transmission) protocol that uses blockchain technology to ensure the security of transmitted data in the process of data transmission. Because the information in the blockchain is not tamperable, which in turn ensures that data stored in brokers are not maliciously tampered with. Through simulation experiments, it is proved that this scheme is lightweight, efficient and easy to implement, which helps to protect the security of IoT data.

Design and Implementation of Wireless Optical Access System for VLC-IoT Networks

With the development of information technology, the Era of the Internet of Everything led by the Internet of Things (IoT) has arrived. The development of traditional Internet of Things based on radio frequency (RF) communication is increasingly perfect, but it is difficult to apply in electromagnetic sensitive industries such as nuclear power plants, engine rooms, hospitals, and industrial control. Under the background of limited spectrum resources, crowded space is filled with a lot of RF communication waves, and the electromagnetic environment is extremely complex. Traditional IoT is also difficult to apply in the high secrecy industries. In these special scenarios, the development of the IoT based on visible light communication (VLC) is particularly important. To realize the VLC-IoT, in this paper, the crosstalk phenomenon in the full-duplex real-time VLC is studied, and the crosstalk phenomenon is suppressed by reducing beam angle and field angle, power isolation, and ground plane segmentation. And the transmitter and receiver in the full-duplex VLC system are integrated on a single printed circuit board (PCB). Combined with the existing mature network, a full-duplex real-time VLC system based on fast Ethernet is implemented, which can be also considered as the wireless optical access system for VLC-IoT networks. Among them, the combination of a red LED and APD430A/M (optical receiver designed by Thorlabs) can achieve 100 Mbps Ethernet transmission of 30 m, and the combination of a white LED with the same optical power and the receiver with a blue light filter designed in this paper can achieve 100 Mbps Ethernet transmission of 4 m. The change of communication distance is because the latter only uses the blue light component to transmit information, which leads to the decrease of signal optical power and the low responsivity of the optical receiver at short-wave strength. All the above wireless optical access systems for VLC-IoT networks have been tested for packet loss rate and communication rate. In the daily lighting environment, the above systems can realize the transmission of 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">8</sup> packets with zero packet loss and 94.9 Mbps transmission rate, in line with the characteristics of Fast Ethernet transmission rate, fully meeting the platinum user standard in the Carrier Ethernet. Based on this experiment, the key performance of the receivers is quantified in this paper. The noise equivalent power (NEP) of the receiver designed in this paper at peak response wavelength is 3.7 nW, which is better than the 5.5 nW of APD430A/M. With the help of the wireless optical access systems designed in this paper, a VLC-IoT networks experiment is realized, and multiple terminal devices can access the VLC-IoT networks at the same time by the wireless optical.

Investigation of Self-Powered IoT Sensor Nodes for Harvesting Hybrid Indoor Ambient Light and Heat Energy.

Sensor nodes are critical components of the Internet of Things (IoT). Traditional IoT sensor nodes are typically powered by disposable batteries, making it difficult to meet the requirements for long lifetime, miniaturization, and zero maintenance. Hybrid energy systems that integrate energy harvesting, storage, and management are expected to provide a new power source for IoT sensor nodes. This research describes an integrated cube-shaped photovoltaic (PV) and thermal hybrid energy-harvesting system that can be utilized to power IoT sensor nodes with active RFID tags. The indoor light energy was harvested using 5-sided PV cells, which could generate 3 times more energy than most current studies using single-sided PV cells. In addition, two vertically stacked thermoelectrical generators (TEG) with a heat sink were utilized to harvest thermal energy. Compared to one TEG, the harvested power was improved by more than 219.48%. In addition, an energy management module with a semi-active configuration was designed to manage the energy stored by the Li-ion battery and supercapacitor (SC). Finally, the system was integrated into a 44 mm × 44 mm × 40 mm cube. The experimental results showed that the system was able to generate a power output of 192.48 µW using indoor ambient light and the heat from a computer adapter. Furthermore, the system was capable of providing stable and continuous power for an IoT sensor node used for monitoring indoor temperature over a prolonged period.

Data Interworking Model and Analysis for Harmonization of Smart Metering Protocols in IoT-Based AMI System

In the energy sector, since the adoption of remote device management for massive advanced metering infrastructure (AMI) devices and Internet of Things (IoT) technology using a representational state transfer (RESTful) architecture, a blurred boundary has been developed between traditional AMI and IoT. With respect to smart meters, the standard-based smart metering protocol, called the device language message specification (DLMS) protocol, still has a predominant role in the AMI industry. Thus, we aim to propose a novel data interworking model in this article that embraces the DLMS protocol in AMI using the most promising IoT protocol, the so-called lightweight machine-to-machine (LwM2M) protocol. We provide a 1:1 conversion model using the correlation of the two protocols with an analysis of the object modeling and resource management methods of both the LwM2M and DLMS protocols. The proposed model utilizes a complete RESTful architecture, which is the most beneficial in the LwM2M protocol. It improves the average packet transmission efficiency and packet delay on the plaintext and encrypted text (session establishment and authenticated encryption) by 52.9%p and 9.9%p, respectively, and by 11.86 ms for both cases, compared to the encapsulation method of the LwM2M protocol, KEPCO's current approach. This work provides the key idea to unify the protocol for the remote metering and device management of field devices into the LwM2M protocol, and it is expected that this work will improve the efficiency in the operation and management of KEPCO's AMI system.

Using Quantum Nodes Connected via the Quantum Cloud to Perform IoT Quantum Network

Computer networks consist of millions of nodes that need constant protection because of their continued vulnerability to attacks. Classical security methods for protecting such networks will not be effective enough if quantum computers become widespread. On the other hand, we can exploit the capabilities of quantum computing and communications to build a new quantum communication network. In this paper, we focused on enhancing the performance of the classical client–server Internet application. For this sake, we introduced a novel Internet of Things (IoT) quantum network that provides high security and Quality of Service (QoS) compared with the traditional IoT network. This can be achieved by adding quantum components to the traditional IoT network. Quantum counterpart nodes, channels, and servers are used. In order to establish a secure communication between the quantum nodes and the quantum server, we defined a new Communication Procedure (CP) for the suggested IoT quantum network. The currently available quantum computer has a small qubit size (from 50 to 433 qubits). The proposed IoT quantum network allows us to overcome this problem by concatenating the computation efforts of multiple quantum nodes (quantum processors).

Agriculture Food Supply Chain Management System based on BlockChain and IOT

In agriculture supply chain management block chain distributed ledger underpinning cryptocurrncies bit coin, represent, new innovative technological approach to realizing system. they provide fault-tolerance, immutability, transparency and full tractability of stored transaction record, as well as coherent Digital representation of physical assets and autonomous transaction execution. Trace-ability is critical in managing food quality and safety. Traditional Internet of Things (IoT) trace-ability systems offer viable solutions for food supply chain quality monitoring and trace-ability. However, majority of IOT solution rely on the centralized server-client paradigm, which makes is difficult for consumers to obtain all transaction information and track the origins of product. Block chain is an innovative technology that has potential to significance improve tracebility performance by providing security and complete transparency. However, the current literature does not fully explore benefit ,challenges and development method block chain based food traceability systems. As result ,the to identify block chain and IOT based solutions for food tracebility.

A Smart Design Based on User Experience for Lighting System in Smart Home

Smart home and the Internet of Things (IoT) have become integral parts of our daily lives. This paper provides an overview of the concept, development history, application scenarios, and future trends of smart home and IoT. The paper introduces the fundamental concepts of smart home and IoT, including the use of sensors, communication technology, and cloud computing. It presents the design of a highly automated smart home lighting system that incorporates traditional smart home technology and IoT technology, allowing the system to use big data to determine when to turn on the lights. The proposed method is tested through a mathematical model and theoretical simulations, followed by an actual simulation using a 51 microcomputer. The paper discusses potential future developments in the field of smart home and IoT, such as the integration of artificial intelligence and machine learning.

Next-Generation IoT Devices: Sustainable Eco-Friendly Manufacturing, Energy Harvesting, and Wireless Connectivity

This invited paper presents potential solutions for tackling some of the main underlying challenges toward developing sustainable Internet-of-things (IoT) devices with a focus on eco-friendly manufacturing, sustainable powering, and wireless connectivity for next-generation IoT devices. The diverse applications of IoT systems, such as smart cities, wearable devices, self-driving cars, and industrial automation, are driving up the number of IoT systems at an unprecedented rate. In recent years, the rapidly-increasing number of IoT devices and the diverse application-specific system requirements have resulted in a paradigm shift in manufacturing processes, powering methods, and wireless connectivity solutions. The traditional cloud-centering IoT systems are moving toward distributed intelligence schemes that impose strict requirements on IoT devices, e.g., operating range, latency, and reliability. In this article, we provide an overview of hardware-related research trends and application use cases of emerging IoT systems and highlight the enabling technologies of next-generation IoT. We review eco-friendly manufacturing for next-generation IoT devices, present alternative biodegradable and eco-friendly options to replace existing materials, and discuss sustainable powering IoT devices by exploiting energy harvesting and wireless power transfer. Finally, we present (ultra-)low-power wireless connectivity solutions that meet the stringent energy efficiency and data rate requirements of future IoT systems that are compatible with a batteryless operation.

Secure and Lightweight User Authentication Scheme for Cloud-Assisted Internet of Things

Cloud-assisted Internet of Things (IoT) overcomes the resource-constrained nature of the traditional IoT and is developing rapidly in such fields as smart grids and intelligent transportation. In a cloud-assisted IoT system, users can remotely control the IoT devices and send specific instructions to them. If the users’ identities are not verified, adversaries can pretend as legitimate users to send fake and malicious instructions to IoT devices, thereby compromising the security of the entire system. Thus, a sound authentication mechanism is indispensable to ensure security. At the same time, it should be noted that a gateway may connect to massive IoT devices with the exponential growth of interconnected devices in a cloud-assisted IoT system. The efficiency of authentication schemes is easily impacted by the computation capability of the gateway. Recently, several schemes have been designed for cloud-assisted IoT systems, but they have problems of one kind or another, making them not very suitable for cloud-assisted IoT systems. In this paper, we take a typical scheme (proposed at IEEE TDSC 2020) as an example to identify the common weaknesses and challenges of designing a user authentication scheme for cloud-assisted IoT systems. In addition, we propose a new secure user authentication scheme with lightweight computation on gateways. The proposed scheme provides secure access between remote users and IoT devices with many ideal attributions, such as forward secrecy and multi-factor security. Meanwhile, the security of this scheme is proved under the random-oracle model, heuristic analysis, the ProVerif tool and BAN logic. Compared with ten state-of-the-art schemes in security and performance, the proposed scheme achieves all the listed twelve security requirements with minimum computation and storage costs on gateways.

Research on site selection of agricultural internet of things nodes based on rapid terrain sampling

With the development of Internet of Things (IoT) technology, modern agriculture is moving in the direction of 4.0. The Agricultural IoT is inseparable from wireless communication. However, in traditional agricultural IoT router and gateway site selection, the influence of the actual terrain on transmission loss is not considered, which results in node power wastage and increased maintenance costs. Based on a multi-sensor fusion algorithm, a fast terrain sampler is designed in this study to collect point-cloud data of the experimental site terrain. A reasonable objective function is then designed under the premise of consideration of the electromagnetic wave free-space and diffraction losses, and the locations of the routers and gateway are optimized based on k-means and particle swarm optimization (PSO) algorithm. Simulations show that the running time of the PSO algorithm is very sensitive to the changes in the execution parameters, and the improved PSO algorithm converges faster than the genetic algorithm (GA) in all three initialization methods. After collecting field terrain data, five interpolation methods were compared, and the nearest-neighbor algorithm is used to obtain the terrain model. On-site collection of received signal-strength indication (RSSI) shows that the communication quality of the optimal point selected via this algorithm is significantly higher than those of nearby points. At the same time, it is proved that the RSSI data has serious discontinuities, so the traditional gradient descent method is not suitable for solving the objective function in this work. Therefore, the algorithm used herein is of great significance for the site selection of agricultural Internet of Things nodes. However, since there are many ways to calculate the diffraction loss, the objective function of this work still needs more correction studies. The tool proposed in this work can obtain a 3D model of farmland faster than traditional surveying and mapping methods. With future research, the 3D model may be applied to soil moisture analysis, rainfall and moisture direction inversion, and plant light exposure prediction.

An Examination of Multi-Key Fully Homomorphic Encryption and Its Applications

With the rapid development of the Internet of Things (IoT) technology, the security problems it faces are increasingly prominent and have attracted much attention in industry and the academy. Traditional IoT architecture comes with security risks. Illegal intrusion of attackers into the network layer disrupts the availability of data. The untrusted transmission environment increases the difficulty of users sharing private data, and various outsourced computing and application requirements bring the risk of privacy leakage. Multi-key fully homomorphic encryption (MKFHE) realizes operations between ciphertexts under different key encryption and has great application potential. Since 2012, the first MKFHE scheme LTV12 has been extended from fully homomorphic encryption (FHE) and has ignited the enthusiasm of many cryptographic researchers due to its lattice-based security and quantum-resistant properties. According to its corresponding FHE scheme, the MKFHE schemes can be divided into four kinds: Gentry–Sahai–Water (GSW), number theory research unit (NTRU), Brakerski–Gentry–Vaikuntanathan (BGV), and FHE over the tour (TFHE). Efficiency and cost are urgent issues for MKFHE. New schemes are mainly improved versions of existing schemes. The improvements are mostly related to the four parts of MKFHE: security assumption, key generation, plaintext encryption, and ciphertext processing. We classified MKFHE schemes according to the improved partial schemes, and we present some improved techniques and the applications of MKFHE.

A Step toward Next-Generation Advancements in the Internet of Things Technologies.

The Internet of Things (IoT) devices generate a large amount of data over networks; therefore, the efficiency, complexity, interfaces, dynamics, robustness, and interaction need to be re-examined on a large scale. This phenomenon will lead to seamless network connectivity and the capability to provide support for the IoT. The traditional IoT is not enough to provide support. Therefore, we designed this study to provide a systematic analysis of next-generation advancements in the IoT. We propose a systematic catalog that covers the most recent advances in the traditional IoT. An overview of the IoT from the perspectives of big data, data science, and network science disciplines and also connecting technologies is given. We highlight the conceptual view of the IoT, key concepts, growth, and most recent trends. We discuss and highlight the importance and the integration of big data, data science, and network science along with key applications such as artificial intelligence, machine learning, blockchain, federated learning, etc. Finally, we discuss various challenges and issues of IoT such as architecture, integration, data provenance, and important applications such as cloud and edge computing, etc. This article will provide aid to the readers and other researchers in an understanding of the IoT’s next-generation developments and tell how they apply to the real world.