Internet Of Things Communication Technologies Research Articles

Smart Home Automation using IoT: Prototyping and Integration of Home Devices

Smart homes are becoming a reality thanks to the Internet of Things (IoT) technology's quick progress, providing homeowners with never-before-seen levels of efficiency, convenience, and security. This abstract gives a summary of a project that combines prototyping and integration to turn a standard house into a modern smart home. The paper focuses on creating an extensive IoT ecosystem that seamlessly connects diverse household equipment, such as lighting controls, thermostats, and security cameras, to a single, intelligent network. We use cutting-edge IoT communication and protocol technologies to create strong connectivity between these devices, enabling homeowners to remotely monitor and control them from a central hub or their smartphones. Our smart home system's central controller, which includes cutting-edge sensors and AI algorithms, is its brain. To reduce energy usage, improve security, and accommodate resident preferences and routines, this controller gathers and examines data from the linked devices. It learns user patterns through machine learning and suggests automation procedures to make life easier. A smart home system prioritises security and privacy in addition to increasing convenience. We also place a strong emphasis on flexibility and scalability, which enable the incorporation of new hardware and features as the IoT landscape changes. For homeowners, tech enthusiasts, and developers interested in building their own smart houses, our project on prototyping and integration serves as a model. It highlights how IoT technology has the ability to upgrade conventional living quarters into intelligent, networked areas that improve our quality of life while fostering energy efficiency and security. In the end, this project advances the continued development of smart home automation by increasing everyone's access to and ability to customise it.

Research on Detection System for Machinery Parts Based on ZigBee Technology

ZigBee technology is a low-power, low-cost, short-range wireless communication technology for various IoT (Internet of Things) applications. Machinery parts detection system monitors the quality, size, shape, and other parameters of machinery parts in real time to ensure the accuracy and quality of the production process. In this article, we propose a machinery parts detection scheme based on ZigBee technology. By deploying wireless sensor networks, the detection data concerning machinery parts could be transmitted in real time, thus reducing the complexity of wiring and improving detection efficiency. ZigBee based machinery parts detection system would provide an efficient and convenient means of detection for the manufacturing industry, thus enjoying a wide range of application prospects.

Computer Hardware and Network Data Transmission based on Internet of Things Communication Technology

In order to meet the requirements of computer hardware and network data transmission security, a research based on Internet of Things communication technology is proposed. The main content of this research is the research based on the communication technology of the Internet of Things, through the description of the communication protocol of the Internet of Things, the system hardware design and implementation methods are used, and finally the research method based on the communication technology of the Internet of Things is constructed through experiments and analysis. The core technologies of 5G connectivity are being used to construct the IOT. As a result, the IOT might gain momentum. The experimental findings demonstrate that the delays are all within 200 Ms. When the message size is short (within 1KB), the transmission of diverse hardware is average, and the transmission quality standards of QoS1 are fulfilled. The transmission quality standards of QoS1 can match the communication reliability and security needs of the Internet of Things. This article evaluates the performance of data transfers with lengths of 20 byte, 30 byte, 50 byte, and 70 byte, respectively. This paper evaluates the efficiency of Wi-Fi access configuration by sending data packets of varying sizes i.e., 10 bytes, 30 bytes, 50 bytes, and 70 bytes over a distribution network. The results show that, on average, the network takes 0.6692s, 1.3546s, 2.8600s, and 4.7319s to deliver each packet, with success rates of 100% in each case. The system's increased network distribution efficiency is observed from the experimentation. The research based on the Internet of Things communication technology can meet the needs of computer hardware and network data transmission security.

Ransomware-based Cyber Attacks: A Comprehensive Survey

<p>Internet of Things (IoT) and sensor devices have been connected due to the development of the IoT and Information Communication Technology (ICT). It offers automatic environments in smart city and IoT scenarios and describes investments in advanced resources in futuristic human lives as sustainable growth of quality-wise life with intelligent infrastructure. Nowadays, IoT devices are continuously increasing and utilized in advanced IoT applications, including Smart Homes, Smart Farming, Smart Enterprises, and others. However, security and privacy are significant challenges with Ransomware-based Cyber-attack detection in IoT due to the lack of security design and heterogeneity of IoT devices. In the last few years, various advanced paradigms and technologies have been utilized to mitigate the security issues with Ransomware attack detection in IoT devices and data. This paper comprehensively surveys Ransomware-based Cyber Attacks and discusses solutions based on advanced technologies such as Artificial Intelligence (AI), Blockchain, and Software Defined Networks (SDN). Then, we design service scenarios for ransomware-based cyber-attack detection. Finally, we summarize the open research challenges and future directions for ransomware in IoT.</p> <p> </p>

Smart ports: Sustainable smart business port operation schemes based on the Artificial Intelligence of Things and blockchain technologies

In recent years, the application and development of the Internet of Things (IoT) has increased significantly. In general, the IoT requires many technologies. Usually, a large amount of IoT sensor information is collected through IoT devices, and devices are connected to each other through IoT communication technology. The Internet exchanges and transmits information, issues instructions and commands to the device, and then conducts prediction and decision making by artificial intelligence (AI) after big data analysis, which is called the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AI of Things</i> ( <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">AIoT</i> ) system.

Cyber Secure Framework for Smart Agriculture: Robust and Tamper-Resistant Authentication Scheme for IoT Devices

Internet of Things (IoT) as refers to a network of devices that have the ability to connect, collect and exchange data with other devices over the Internet. IoT is a revolutionary technology that have tremendous applications in numerous fields of engineering and sciences such as logistics, healthcare, traffic, oil and gas industries and agriculture. In agriculture field, the farmer still used conventional agriculture methods resulting in low crop and fruit yields. The integration of IoT in conventional agriculture methods has led to significant developments in agriculture field. Different sensors and IoT devices are providing services to automate agriculture precision and to monitor crop conditions. These IoT devices are deployed in agriculture environment to increase yields production by making smart farming decisions and to collect data regarding crops temperature, humidity and irrigation systems. However, the integration of IoT and smart communication technologies in agriculture environment introduces cyber security attacks and vulnerabilities. Such cyber attacks have the capability to adversely affect the countries’ economies that are heavily reliant on agriculture. On the other hand, these IoT devices are resource constrained having limited memory and power capabilities and cannot be secured using conventional cyber security protocols. Therefore, designing robust and efficient secure framework for smart agriculture are required. In this paper, a Cyber Secured Framework for Smart Agriculture (CSFSA) is proposed. The proposed CSFSA presents a robust and tamper resistant authentication scheme for IoT devices using Constrained Application Protocol (CoAP) to ensure the data integrity and authenticity. The proposed CSFSA is demonstrated in Contiki NG simulation tool and greatly reduces packet size, communication overhead and power consumption. The performance of proposed CSFSA is computationally efficient and is resilient against various cyber security attacks i.e., replay attacks, Denial of Service (DoS) attacks, resource exhaustion.

AI-based modeling and data-driven evaluation for smart farming-oriented big data architecture using IoT with energy harvesting capabilities

The use of Internet of Things (IoT) networks offers great advantages over wired networks, especially due to their simple installation, low maintenance costs, and automatic configuration. IoT facilitates the integration of sensing and communication for various industries, including smart farming and precision agriculture. For several years, many researchers have strived to find new sources of energy that are always “cleaner” and more environmentally friendly. Energy harvesting technology is one of the most promising environment-friendly solutions that extend the lifetime of these IoT devices. In this paper, the state-of-art of IoT energy harvesting capabilities and communication technologies in smart agriculture is presented. In addition, this work proposes a comprehensive architecture that includes big data technologies, IoT components, and knowledge-based systems for innovative farm architecture. The solution answers some of the biggest challenges the agriculture industry faces, especially when handling small files in a big data environment without impacting the computation performance. The solution is built on top of a pre-defined big data architecture that includes an abstraction layer of the data lake that handles data quality following a data migration strategy to ensure the data's insights. Furthermore, in this paper, we compared several machine learning algorithms to find the most suitable smart farming analytics tools in terms of forecasting and predictions.

Wireless Communication Technologies for IoT in 5G: Vision, Applications, and Challenges

Communication technologies are developing very rapidly and achieving many breakthrough results. The advent of 5th generation mobile communication networks, the so-called 5G, has become one of the most exciting and challenging topics in the wireless study area. The power of 5G enables it to connect to hundreds of billions of devices with extreme-high throughput and extreme-low latency. The 5G realizing a true digital society where everything can be connected via the Internet, well known as the Internet of Things (IoT). IoT is a technology of technologies where humans, devices, software, solutions, and platforms can connect based on the Internet. The formation of IoT technology leads to the birth of a series of applications and solutions serving humanity, such as smart cities, smart agriculture, smart retail, intelligent transportation systems, and IoT ecosystems. Although IoT is considered a revolution in the evolution of the Internet, it still faces a series of challenges such as saving energy, security, performance, and QoS support. In this study, we provide a vision of the Internet of Things that will be the main force driving the comprehensive digital revolution in the future. The communication technologies in the IoT system are discussed comprehensively and in detail. Furthermore, we also indicated indepth challenges of existing common communication technologies in IoT systems and future research directions of IoT. We hope the results of this work can provide a vital guide for future studies on communication technologies for IoT in 5G.

Multi-Layered Energy Efficiency in LoRa-WAN Networks: A Tutorial

Emerging Internet-of-Things (IoT) applications are driving increasing demand for advanced services in wireless networks, prompting the development of new technologies to address the associated challenges. Energy efficiency of IoT standards is a key feature targeted by research efforts and industrial activities, leading to an extensive and growing number of innovative solutions. Low Power Wide Area Networks (LPWANs) define a class of wireless communication technologies seen as highly relevant for future IoT development given its long communication range, low-cost devices and interesting energy management. Long Range Wide Area Network (LoRaWAN) is acknowledged to be the dominant IoT communication technology. It has allowed broad deployment and unlocked new IoT applications such as smart cities, asset tracking, etc. This article provides a comprehensive tutorial on the LoRa standard, and surveys existing solutions, hot topics and future insights for building energy efficient IoT infrastructures and IoT devices. Indeed, energy efficiency is one of the key factors for successful and sustainable deployments of IoT applications. More precisely, this article discusses how to meet LoRa/LoRaWAN energy efficiency across physical layer, medium access control layer, and network layer. Subsequently, extensive pioneering solutions from related literature are compared and assessed. Finally, insightful conclusions are drawn, and open problems are listed at the end of this article.

A QoS-Aware Machine Learning-Based Framework for AMI Applications in Smart Grids

The Internet of things (IoT) enables a diverse set of applications such as distribution automation, smart cities, wireless sensor networks, and advanced metering infrastructure (AMI). In smart grids (SGs), quality of service (QoS) and AMI traffic management need to be considered in the design of efficient AMI architectures. In this article, we propose a QoS-aware machine-learning-based framework for AMI applications in smart grids. Our proposed framework comprises a three-tier hierarchical architecture for AMI applications, a machine-learning-based hierarchical clustering approach, and a priority-based scheduling technique to ensure QoS in AMI applications in smart grids. We introduce a three-tier hierarchical architecture for AMI applications in smart grids to take advantage of IoT communication technologies and the cloud infrastructure. In this architecture, smart meters are deployed over a georeferenced area where the control center has remote access over the Internet to these network devices. More specifically, these devices can be digitally controlled and monitored using simple web interfaces such as REST APIs. We modify the existing K-means algorithm to construct a hierarchical clustering topology that employs Wi-SUN technology for bi-directional communication between smart meters and data concentrators. Further, we develop a queuing model in which different priorities are assigned to each item of the critical and normal AMI traffic based on its latency and packet size. The critical AMI traffic is scheduled first using priority-based scheduling while the normal traffic is scheduled with a first-in–first-out scheduling scheme to ensure the QoS requirements of both traffic classes in the smart grid network. The numerical results demonstrate that the target coverage and connectivity requirements of all smart meters are fulfilled with the least number of data concentrators in the design. Additionally, the numerical results show that the architectural cost is reduced, and the bottleneck problem of the data concentrator is eliminated. Furthermore, the performance of the proposed framework is evaluated and validated on the CloudSim simulator. The simulation results of our proposed framework show efficient performance in terms of CPU utilization compared to a traditional framework that uses single-hop communication from smart meters to data concentrators with a first-in–first-out scheduling scheme.

Internet of Things for Agricultural Applications: The State of the Art

The advent of the Internet of Things (IoT) inspired various new and enhanced sets of applications in multiple domains including agriculture. The recent drive in the adoption of IoT technologies offers a major enhancement for the agricultural sectors in terms of efficiency and scalability. In this article, we investigate the specific issues and challenges associated with IoT, and review various IoT architectures, communication, middleware, and information processing technologies. We, then, discuss few IoT applications for agriculture-presenting various case studies to thoroughly analyze the solutions along with their design and implementation related parameters. Consequently, we provide a comprehensive review of the available simulation tools, data sets, and testbeds which provisions experimentation with IoT in agriculture. We enumerate open issues and challenges present in enabling IoT for agriculture. Finally, this article concludes while giving directions for future research.

Effective policies to overcome barriers in the development of smart cities

The world is facing substantial challenges related to population growth and the derived pressure on environment, energy, and other natural resources. Cities contribute to these problems due to the ever-increasing urbanization. As a solution, smart cities are managed and optimized across traditional boundaries and through the exchange of information between physical objects, citizens, and stakeholders. However, there are barriers in the development of smart cities that should be overcome in order to meet these challenges through smart cities. The main barriers identified in this work are poor private-public participation, utilization of fossil fuels, lack of attention to the environment, insufficient internet technology (IT) infrastructure, and old technology throughout the cities. To overcome these barriers, policies must be implemented to improve private-public participation by encouraging public investments and a wider adoption of electrical vehicles that may act as storage device and provide ancillary services to the electricity grid; reduce the use of private cars; strengthen IT infrastructure, deployment of smart technology to allow residents to monitor and control their energy consumption, installation of roof-top solar panels, and better mobility and efficient public services supported by smart technologies such as IoT (Internet of Things) and information and communication technology (ICT) to enhance the interconnection among smart city systems.

Improved Image Security in Internet of Thing (IOT) Using Multiple Key AES

Image is an important digital information that used in many internet of things (IoT) applications such as transport, healthcare, agriculture, military, vehicles and wildlife. etc. Also, any image has very important characteristic such as large size, strong correlation and huge redundancy, therefore, encrypting it by using single key Advanced Encryption Standard (AES) through IoT communication technologies makes it vulnerable to many threats, thus, the pixels that have the same values will be encrypted to another pixels that have same values when they use the same key. The contribution of this work is to increase the security of transferred image. This paper proposed multiple key AES algorithm (MECCAES) to improve the security of the transmitted image through IoT. This approach is evaluated via applying it on RGB bmp images and analyzing the results using standard metrics such as entropy, histogram, correlation, Peak Signal-to-Noise Ratio (PSNR) and Mean Square Error (MES) metrics. Also, the time for encryption and decryption for the proposed MECCAES is the same time consumed by original single key AES is 12 second(the used image size is 12.1MB therefore time is long). The performance experiments show that this scheme achieves confidentiality also it encourages to use effectively in a wide IoTs fields to secure transmitted image.

A Topical Review on Machine Learning, Software Defined Networking, Internet of Things Applications: Research Limitations and Challenges

In recent years, rapid development has been made to the Internet of Things communication technologies, infrastructure, and physical resources management. These developments and research trends address challenges such as heterogeneous communication, quality of service requirements, unpredictable network conditions, and a massive influx of data. One major contribution to the research world is in the form of software-defined networking applications, which aim to deploy rule-based management to control and add intelligence to the network using high-level policies to have integral control of the network without knowing issues related to low-level configurations. Machine learning techniques coupled with software-defined networking can make the networking decision more intelligent and robust. The Internet of Things application has recently adopted virtualization of resources and network control with software-defined networking policies to make the traffic more controlled and maintainable. However, the requirements of software-defined networking and the Internet of Things must be aligned to make the adaptations possible. This paper aims to discuss the possible ways to make software-defined networking enabled Internet of Things application and discusses the challenges solved using the Internet of Things leveraging the software-defined network. We provide a topical survey of the application and impact of software-defined networking on the Internet of things networks. We also study the impact of machine learning techniques applied to software-defined networking and its application perspective. The study is carried out from the different perspectives of software-based Internet of Things networks, including wide-area networks, edge networks, and access networks. Machine learning techniques are presented from the perspective of network resources management, security, classification of traffic, quality of experience, and quality of service prediction. Finally, we discuss challenges and issues in adopting machine learning and software-defined networking for the Internet of Things applications.

Research on the Construction of Intelligent Fire Protection Virtual Simulation Teaching Platform Based on Internet of Things

Aiming at the teaching challenge of cultivating integrated talents of Internet of things worldwide, and combining with the social background of fire rescue and management problems, We propose a virtual simulation teaching platform for the Internet of Things under the background of intelligent fire protection application. Based on the overall structure of the Internet of Things, different fire scenarios that cannot be simulated in real life are constructed through virtual simulation technology. OMNet++ technology is adopted to carry out virtual deployment of fire nodes for the overall structure of the building, and experiments such as cluster routing simulation, communication transmission simulation and wireless sensor node data acquisition simulation are designed. Meanwhile, a 3D fire data model is established using big data to simulate the best fire extinguishing scheme and the best escape strategy. From aspects of the Internet of Things system design and development, sensor principle and application, Internet of Things communication technology and Internet of Things data storage and application, we have realized the efficiency, innovation and challenge of the Internet of Things teaching.The virtual simulation teaching platform we built has been deployed and put into practical teaching, which has received positive response from students and achieved excellent teaching effect.

A Multidimensional Internet of Things Testbed System: Development and Evaluation

The technological breakthrough of the Internet of Things (IoT) drives the emergence of a wide scope of smart IoT solutions in different domains. Advancing the different technological aspects of these solutions requires effective IoT implementations and experimentations. This is widely addressed following low-cost and scalable methods such as analytical modeling and simulation. However, such methods are limited in capturing physical characteristics and network conditions in a realistic manner. Therefore, this paper presents an innovative IoT testbed system which facilitates practical experimentation of different IoT solutions in an effective environment. The testbed design was developed towards a general-purpose multidimensional support of different IoT properties including sensing, communication, gateway, energy management, data processing, and security. The implementation of the testbed was realized based on integrating a set of robust hardware components and developing a number of software modules. To illustrate its effectiveness, the testbed was utilized to experiment with energy efficiency of selected IoT communication technologies. This resulted in lower energy consumption using the Bluetooth Low Energy (BLE) technology compared to the Zigbee and 6LoWPAN technologies. A further evaluation study of the system was carried out following the Technology Acceptance Model (TAM). As the study results indicated, the system provides a simple yet efficient platform for conducting practical IoT experiments. It also had positive impact on users’ behavior and attitude toward IoT experimentation.

IoT-Enabled Smart Sustainable Cities: Challenges and Approaches

The ongoing diffusion of Internet of Things (IoT) technologies is opening new possibilities, and one of the most remarkable applications is associated with the smart city paradigm, which is continuously evolving. In general, it can be defined as the integration of IoT and Information Communication Technologies (ICT) into city management, with the aim of addressing the exponential growth of urbanization and population, thus significantly increasing people’s quality of life. The smart city paradigm is also strictly connected to sustainability aspects, taking into account, for example, the reduction of environmental impact of urban activities, the optimized management of energy resources, and the design of innovative services and solution for citizens. Abiding by this new paradigm, several cities started a process of strong innovation in different fields (such as mobility and transportation, industry, health, tourism, and education), thanks to significant investments provided by stakeholders and the European Commission (EC). In this paper, we analyze key aspects of an IoT infrastructure for smart cities, outlining the innovations implemented in the city of Parma (Emilia Romagna region, Italy) as a successful example. Special attention is dedicated to the theme of smart urban mobility.

Split Channel Two-Tone On-Off Keying for Internet of Things Communication in Fading Channel

In medical treatment, healthcare and home appliances, the demand for Internet of Things (IoT) services is increasing in urban areas. However, in fading environments of urban area, the existing IoT communication system can degrade severely. The purpose of this paper is to develop a new IoT communication technology that improves communication performance in fading channels. IoT communication systems are aiming at low power long distances. In addition, the amount of data transmission is small due to the service requirements. To achieve this goal, existing IoT communication modems are designed with narrowband signals. However, narrowband signals may cause performance degradation in a frequency selective fading channel environments in urban area. In this paper, we propose a split channel two tone OOK (SC-TT-OOK) that implements on-off keying (OOK) using two tones. Unlike the existing OOK by using one tone, SC-TT-OOK uses spaced two tones to improve communication performance in fading channels. The conventional OOK method has a similar characteristic to that of the existing IoT modems with a narrow bandwidth spectrum. The proposed SC-TT-OOK is OOK using two separated tones. Since the proposed modulation uses two tones, it requires twice the frequency resources of the conventional OOK. However, if the frequencies of the two tones are sufficiently spaced apart, frequency diversity gain can be achieved in the frequency selective fading channels, and communication reliability can be improved in urban environments. The proposed SC-TT-OOK is examined through computer simulation. The simulation results show that the proposed scheme outperforms the conventional scheme in the frequency selective fading channel. Therefore, the proposed method can be used as an alternative technique for IoT modem in urban environments.

Emerging Wireless Sensor Networks and Internet of Things Technologies-Foundations of Smart Healthcare.

Future smart healthcare systems—often referred to as Internet of Medical Things (IoMT) – will combine a plethora of wireless devices and applications that use wireless communication technologies to enable the exchange of healthcare data. Smart healthcare requires sufficient bandwidth, reliable and secure communication links, energy-efficient operations, and Quality of Service (QoS) support. The integration of Internet of Things (IoT) solutions into healthcare systems can significantly increase intelligence, flexibility, and interoperability. This work provides an extensive survey on emerging IoT communication standards and technologies suitable for smart healthcare applications. A particular emphasis has been given to low-power wireless technologies as a key enabler for energy-efficient IoT-based healthcare systems. Major challenges in privacy and security are also discussed. A particular attention is devoted to crowdsourcing/crowdsensing, envisaged as tools for the rapid collection of massive quantities of medical data. Finally, open research challenges and future perspectives of IoMT are presented.

Cognitive solution for IoT communication technologies – emphasis on 5G

Abstract The 5G cellular network technology, in collaboration with Internet of Things (IoT), is envisaged to connect the world together through a flawless Internet connection between devices and sensors. The things in IoT term can be of any smart devices or Internet-enabled sensors that can share information in order to perform a task collectively or individually. On the other hand, Cognitive Internet of Things plays a vital role in utilizing available spectrum for 5G networks. Addition of cognitive feature to the things can allow decision making capability, thereby reducing the overall traffic congestion and improving the efficiency of the whole IoT system. Therefore, it is of great concern to develop an intelligent network to address a few challenges such as heterogeneity and volume of devices in 5G. The aim of this article is to provide a critical review of existing IoT communication Technologies and highlight several challenges and their potential solutions associated with Cognitive IoT based 5G networks.