Development Of Internet Of Things Research Articles

ASSESSING THE TECHNOLOGICAL PROGRESS OF THE INTERNET OF THINGS (IOT) IN POST-PANDEMIC PERIOD

IoT-based smart products such as smartphones and smartwatches, smart homes and cars, smart TVs and entertainment devices, beside healthcare devices, have generated a great deal of interest among customers. The global threat COVID-19, with the recent and future opportunities in IoT have made the companies even more exited and eager to exploit the technology. Although, there are some challenges regarding the security issues, returns of IoT mostly outweigh the pitfalls. The objective of this study is to analyze the literature, sta-tistics and predictions for IoT in different industries and sectors, in post-pandemic era. Sev-eral topics involving use and implementation of IoT during and after pandemic, main IoT opportunities for companies, main challenges related to adoption and further development of IoT are examined and presented with figures. Keywords: Internet of Things (IoT), digital technology, smart devices, post-pandemic, in-dustrial 4.0

Intrusion Detection in Healthcare 4.0 Internet of Things Systems via Metaheuristics Optimized Machine Learning

Rapid developments in Internet of Things (IoT) systems have led to a wide integration of such systems into everyday life. Systems for active real-time monitoring are especially useful in areas where rapid action can have a significant impact on outcomes such as healthcare. However, a major challenge persists within IoT that limit wider integration. Sustainable healthcare supported by the IoT must provide organized healthcare to the population, without compromising the environment. Security plays a major role in the sustainability of IoT systems, therefore detecting and taking timely action is one step in overcoming the sustainability challenges. This work tackles security challenges head-on through the use of machine learning algorithms optimized via a modified Firefly algorithm for detecting security issues in IoT devices used for Healthcare 4.0. Metaheuristic solutions have contributed to sustainability in various areas as they can solve nondeterministic polynomial time-hard problem (NP-hard) problems in realistic time and with accuracy which are paramount for sustainable systems in any sector and especially in healthcare. Experiments on a synthetic dataset generated by an advanced configuration tool for IoT structures are performed. Also, multiple well-known machine learning models were used and optimized by introducing modified firefly metaheuristics. The best models have been subjected to SHapley Additive exPlanations (SHAP) analysis to determine the factors that contribute to occurring issues. Conclusions from all the performed testing and comparisons indicate significant improvements in the formulated problem.

Prospects and Challenges of Different Geometries of TFET Devices for IoT Applications

Background: The applications based on IoT are nearly boundless, and the integration of the cyber world and the physical world can be done effortlessly. TFET Based IoT applications may be the future alternative to existing MOSFET-based IoT because of the faster switching speed of TFET devices. Objectives: Prospects and challenges in a simulation study of different Geometries of TFET devices for IoT Applications. Methods: In this manuscript, the detailed study of IoT evolution, IoT applications and challenges faced by IoT industries based on different TFET geometries have been elaborated and analyzed. Results: The Internet of Things (IoT) is a new prototype that provides a set of new services for new-generation technological innovations. IoT has seized the entire technological world as it can be used in every application like health, security, environmental and biomedical applications etc. The semiconductor TFET devices operating at low supply voltage and consuming the least power are most suitable for IoT applications. The devices like digital inverter, memory, adiabatic circuit, and different shaped TFET are explained as well as compared in tabular form thoroughly Conclusion: In next-generation devices, TFET can be widely used for low-power IoT applications because of the superior switching characteristics performance.

THE MAINTENANCE SYSTEM FOR A SMART BUILDING IN INDUSTRY 4.0 ENVIRONMENT

Buildings, where we spend the majority of our time, have been quickly altering in recent years. Building systems powering integrate consumer-grade Internet of things (IoT) sensors such as cameras with operational technology controllers and actuators to accommodate the increased complexity of building operations. This study discussed the idea of “smart buildings” and the comparison along with the technologies being developed for these structures and the implications for libraries and specialized smart building technology using various IoT approaches used in smart building categories. The research goal is to improve approaches which active in recent years and the gaps researchers have found in their investigations. As a result, smart buildings provide physical value by generating data intelligently to enhance operations and customer skills. Recent breakthroughs in IoT have piqued experts and engineers across the world. However, improvements are only possible if we consider the numerous flaws and mistakes in the present technology. IoT developers might consider many challenges and hurdles while designing a better model in this survey article. Significant IoT technology sectors in which IoT developers and academics are interested are frequently addressed. In addition to providing services, IoT captures a vast amount of data. Therefore, big data analytics is essential, trustworthy judgments can be made, and a more robust IoT framework can be created. This study compares the previous studies that focused on characteristics that a controlling and advanced approach to making buildings smarter with Maintenance to reduce greenhouse gas emissions and enhance the world's environment at a lower cost.

Edge Trusted Sharing: Task-Driven Decentralized Resources Collaborate in IoT

6G is committed to providing a fully connected world. The deployment and application of 6G technology in the Internet of Things (IoT) can efficiently collaborate IoT resources and realize resource sharing, which mainly encourages IoT development. However, due to the lack of trust between IoT resources, security and privacy become the main challenges. As an emerging technology, blockchain can solve the trust-absence issues and provide more benefits, but the introduction of blockchain also brings problems for IoT resource collaboration and sharing. This article first proposes a blockchain-enabled edge resource sharing (BEERS) architecture by combining blockchain and edge computing technology. Then, based on a typical resource sharing and collaboration scenario, the joint optimization problem of resource scheduling and task assignment (JRSTA) is constructed. We decompose JRSTA into a primal problem and a master problem and design a greedy-based task assignment (GBTA) algorithm to solve the primal problem. Based on the GBTA algorithm, the resource scheduling and task assignment (RSTA) algorithm is developed. Next, we design a layered parallel edge resource scheduling and task assignment (LPRSTA) mechanism to improve practicability. Finally, we analyze the security and the performance of our proposed architecture and algorithms. The results show that the proposed architecture can support the secure collaboration of IoT resources, and the proposed algorithm can achieve effective resource scheduling and task assignment.

IoT Inspired Brain Disorders Monitoring and Detection

Abstract: Today’s rapid changes in technology bring immense competition in work life that in effect perturb the work-personal life balance. This pampered disharmony involuntarily creates stress in human lives. Once the stress is uncontrolled, it will cause severe diseases including neurological disease, ageing effect, cardiovascular disease etc. Amongst these vulnerable diseases, brain disorder is considered more severe one as our control section when becomes scared, the entire body functions will be hampered from their equilibrium state. Most cited brain disorders are Alzheimer and Perkinson disease. There has been tireless effort to detect Azheirmer and Perkinson as well as bipolar diseases and their proper treatment for a decade but the befitted solution is under development. Also the busiest lifestyle may also discard human beings to keep in touch with their parents. The senior citizens are often suffered from these two diseases. In this regard, our aim is to investigate a realistic as well as compatible solution to administer the brain disorders. Internet of Things (IoT) is considered as most efficient and energy saving technology that can provide easy and remote monitoring of target problem. The number of sensors and IoT devices along with applications is used for monitoring the health condition of patients. These devices will monitor the movement of targeted patients at home or out of their homes. Based on their behavior and movement, the treatment will be provided to Alzheimer’s patients. In this review paper, we are trying to response the unanswered question “ Is Brain disorder properly detected and prevented?”. Our attempt is to figure out possible solutions using Internet of Things (IoT) over the problem. The paper will highlight recent development in IoT based brain disorder therpy and attempt to harbinger the process of way-out

An efficient algorithm for energy harvesting in IIoT based on machine learning and swarm intelligence

The Internet of Things (IoT) is a network of smart gadgets that are connected through the Internet, including computers, cameras, smart sensors, and mobile phones. Recent developments in the industrial IoT (IIoT) have enabled a wide range of applications, from small businesses to smart cities, which have become indispensable to many facets of human existence. In a system with a few devices, the short lifespan of conventional batteries, which raises maintenance costs, necessitates more replacements and has a negative environmental impact, does not present a problem. However, in networks with millions or even billions of devices, it poses a serious problem. The rapid expansion of the IoT paradigm is threatened by these battery restrictions, thus academics and businesses are now interested in prolonging the lifespan of IoT devices while retaining optimal performance. Resource management is an important aspect of IIoT because it's scarce and limited. Therefore, this paper proposed an efficient algorithm based on federated learning. Firstly, the optimization problem is decomposed into various sub-problems. Then, the particle swarm optimization algorithm is deployed to solve the energy budget. Finally, a communication resource is optimized by an iterative matching algorithm. Simulation results show that the proposed algorithm has better performance as compared with existing algorithms.

Smart Learning using IOT Technology

Information and communication technologies (ICT) and the ongoing integration of new technologies into institutional learning have led to the development of smart education, which is now a common component in education. The goal of the smart classroom is to help students learn new skills, adapt to new situations, and use technology in a way that results in improved learning outcomes and big data. A new technology known as the internet of things (IoT) enables devices with sensors, actuators, and processors to connect with one another and carry out useful tasks. Designing under these circumstances might be challenging because of the quick evolution of technology. IoT application design is a difficult problem. The current standardisation efforts frequently duplicate IoT development. The reference architecture offers a remedy for superfluous design tasks in smart education. This chapter's goal is to examine the prerequisites and architectural frameworks for smart education. A scalable and adaptable IoT architecture for smart education (IoTASE) is being presented

In Situ IoT Development and Application for Continuous Water Monitoring in a Lentic Ecosystem in South Brazil

The monitoring of water resources through conventional methods, related to a manual process when performing the sample collection, followed by laboratory analysis, presents some difficulties concerning the logistics of the process, such as access to the interior of a lake, in addition to often being based on a small number of samples. The concept of the internet of things (IoT) is used here to collect data through five parametric probes contained in the floating station located inside a lake and inform them in real time continuously. The main objective of this research is to demonstrate the applicability of the IoT concept in the continuous monitoring of water in a lentic environment. Therefore, it is necessary to develop a tool for this. Upon reaching this objective, the advantages observed in this research confirmed that the IoT paradigm is an essential resource, justifying a natural tendency to establish itself when there is a need to collect data efficiently and continuously. Furthermore, the experimental result proves the IoT concept’s efficiency, agility, and reliability to environmental issues, especially regarding the most significant natural and indispensable resource for the planet, water.

Collaborative Intelligent Confident Information Coverage Node Sleep Scheduling for 6G-Empowered Green IoT

The Internet of Things (IoT) enabled by 6G increases the number of devices and users exponentially. 6G IoT will cover the overall domain of the world. Due to the limited resources in the IoT environment, greener and smarter networks are indispensable for the sustainable development of the 6G IoT. In this paper, the issue of improving resource efficiency and extending network lifetime is studied. We propose a novel Confidence Information Coverage (CIC) node sleep scheduling algorithm based on reinforcement learning (CICRL). In CICRL, collaborative intelligence is achieved through Q-learning to meet the coverage rate with the least active nodes, thus balancing the energy consumption and prolonging the network lifetime. Compared with the Coordination Algorithm based on Reinforcement Learning (COORD), Low-Energy Adaptive Clustering Hierarchy (LEACH) and Sleep Scheduling Approach based on Learning Automata (PCLA), the simulation results demonstrate that the proposed algorithm satisfies coverage with fewer active nodes and improves the network lifetime substantially.

Harnessing the Power of IoT and AI for Human Evolution

The internet of things (IoT) and artificial intelligence (AI) are two of the most transformative technologies of the modern era. They have the potential to change how we live, work, and interact with each other. This paper explores the impact of IoT and AI on human evolution, including the challenges and opportunities they present. Through a review of relevant literature, this paper identifies the potential benefits of IoT and AI, such as improving healthcare, increasing productivity, and promoting sustainability. However, this paper also highlights the ethical and social issues that need to be addressed to ensure that these technologies benefit humanity. (Manyika, et al., 2015)The Internet of Things (IoT) and Artificial Intelligence (AI) are two transformative technologies that are revolutionizing the way we live, work, and interact with each other. Together, they have the potential to enable unprecedented levels of connectivity, automation, and intelligence, leading to significant improvements in various aspects of human life, from healthcare and education to transportation and energy. In this research paper, we explore the latest developments in IoT and AI and their potential impact on human evolution. We examine how these technologies are being applied in different fields, such as smart homes, cities, factories, and healthcare, and we discuss the opportunities and challenges associated with their adoption. We also explore how IoT is being employed in agriculture to enhance crop yields and in transportation to optimize traffic flow and reduce emissions. We also investigate how AI is transforming the field of healthcare by enabling personalized treatments and improving patient outcomes, as well as how it is being used in education to provide customized learning experiences. Additionally, we discuss the role of IoT and AI in creating smart cities that are more efficient, sustainable, and liveable, and how they are being used in industry to optimize production processes and reduce waste. Through these examples, we demonstrate the potential of IoT and AI to drive human evolution and shape the future of our society. Moreover, we explore the ethical and societal implications of IoT and AI and provide recommendations for their responsible and sustainable development. Ultimately, we argue that harnessing the power of IoT and AI can contribute to human evolution by enhancing our ability to understand and address complex problems, enabling us to live healthier, safer, and more fulfilling lives, and empowering us to create a more equitable and sustainable world.

Bibliometric analysis, scientometrics and metasynthesis of Internet of Things (IoT) in smart buildings

PurposeThe Internet of Things has made the shift to the digital era possible, even though the Architecture, Engineering and Construction (AEC) sector has not embraced nor integrated it within the core functions compared to other sectors. The need to enhance sustainable construction with the adoption of Internet of Things in this sector cannot be overemphasized. However, the real-world applications of Internet of Things in smart buildings remain relatively unexplored in the AEC sector due to several issues related to deployment and energy-saving potentials. Given these challenges, this paper proposes to identify the present state of development and research in Internet of Things and smart buildings, identify Internet of Things clusters and applications in smart buildings.Design/methodology/approachBibliometric analyses of papers from 2010 to 2023 using the Scopus database and scientometric evaluations using the VosViewer software were undertaken. The proper search keyword was identified by using the phrases “ Internet of Things” and “Smart Building”. A total of 1158 documents in all, written by 3540 different writers, representing 2285 different institutions from 97 different countries were looked at. A metasynthesis was conducted and a system of Internet of Things applications in a smart building is illustrated.FindingsThe development of IoT and Smart Buildings is done in two phases: initiation (2010–2012) and development phase (2013–2023). The IoT clusters comprised Internet of things, energy efficiency, intelligent buildings, smart buildings and automation; while the most commonly used applications were analysed and established. The study also determined the productive journals, documents, authors and countries.Research limitations/implicationsDocuments published in the Scopus database from 2010 to 2023 were considered for the bibliometric analysis. Journal articles, conference papers, reviews, books and book chapters written in English language represent the inclusion criteria, while articles in press, conference reviews, letters, editorials, undefined sources and all medical and health publications were excluded.Practical implicationsThe results of this study will be used by construction stakeholders and policymakers to identify key themes and applications in IoT-enabled smart buildings and to guide future research in the policymaking process of asset management.Originality/valueThe study utilised bibliometric analysis, scientometrics and metasynthesis to investigate Internet of things applications in smart buildings. The study identified Internet of things clusters and applications for smart building design and construction.

A REVIEW OF INTEGRATED RADIO FREQUENCY ENERGY HARVESTING AND COGNITIVE RADIO FOR THE INTERNET OF THINGS

In recent decades, there has been significant growth in interconnected communication devices, with the Internet of Things (IoT) being one of the most intensively developed wireless communication appliances. This concept can be implemented in several areas, including smart cities, transportation, telemedicine, agriculture, and wearable applications. However, this increase in connectivity demand can lead to spectrum shortages in the future. In addition, in the development of future green communications, it is crucial to incorporate self-powered systems using energy harvesting technologies. In this review, it is shown that the integration of cognitive radio and radio frequency energy harvesting into IoT development can address the spectrum shortages and energy issues mentioned earlier. The findings indicate that the operating model works based on the slotted approach and state consideration, and the system’s performance metric can be optimised by adjusting parameters such as harvesting time, sensing time, transmit time, transmission power, interference level, and others. This review provides a comparative summary of several focus domains, such as RF harvesting, spectrum sensing and utilisation, operating models, and some open research issues for further work.

IoT Based Agriculture Monitoring System using Arduino Uno and Node MCU

Indian agriculture is diverse ranging from impoverished farm villages to developed farms utilizing modern agricultural technologies. Promoting application of modern information technology in agriculture will solve a series of problems facing by farmers. This system provides an intelligent monitoring platform framework and system structure to facilitate agriculture’s ecosystem based on IOT. This will be a Catalyst for the Transition from Traditional Farming to Modern Farming. This also provides opportunity for creating new technology and service development in IOT (Internet of things) farming application. In INDIA, the population has tripled, but food grain production had more than quadrupled, thus as there has been a substantial increase in available food grain per capita. Modern agriculture practices have a great promise for the economic development of a nation. So we have brought-in this innovative project for the welfare of Farmers and also for the Best Quality of Crops. There are no such restrictions of Day and Night in our project. Using this Project, Farming can be done at any time.

Internet of Things Energy Consumption Optimization in Buildings: A Step toward Sustainability

The internal components of a smart building interact through a compatible fabric and logic. A smart building integrates systems, structure, services, management, and their interrelationships to create a dynamic and cost-efficient environment. Smart buildings reduce the amount of cooling and heating load required to cool and heat spaces, thereby lowering operating costs and energy consumption without sacrificing occupant comfort. Smart structures are an Internet of Things (IoT) concern. The Internet of Things is a global network that virtualizes commonplace objects. The Internet of Things infuses non-technical objects with technology. IoT development has led to the creation of new protocols based on architectures for wireless sensor networks. Energy conservation extends the life and improves the performance of these networks, while overcoming the limitations of IoT node batteries. This research seeks to develop a data transmission model for routing IoT data in smart buildings. Utilization of intelligent object clustering and particle swarm optimization (PSO), chaotic particle swarm optimization (CPSO), and fractional chaotic order particle swarm optimization (FCPSO) optimization methods. Using the proposed algorithm to minimize energy consumption in the IoT is possible due to the algorithm’s ability to mitigate the problem by considering the number of parameters that can have a significant impact on performance, which is the goal of many optimization approaches.

Digital Hash Data Encryption for IoT Financial Transactions using Blockchain Security in the Cloud

Blockchain security via the Internet of Things (IoT) will reshape the decision-making function of the data-driven incumbent smart enterprise, providing the vision of the connected world of things. Enterprise IoT development of devices, personnel, and systems in such a way that they may connect and communicate with each other through the Internet. Blockchain is an enterprise financial transaction, and its digital network is distributed transaction ledger. Today, enterprises need the massive global data management and rapid trading volume to keep things going and growing. It creates enterprise business challenges of different types of security, transparency, and complexity of the problem. Enterprise architecture offers several advantages for the thief to obtain a specific user account, application, and access to the device. This is, will doesn't be to provide the necessities of security. The proposed Digital Hash Data Encryption (DHDE) is used to secure the transaction data-based embedded system people and blockchain. Blockchain and IoT technology integration may bring numerous benefits to mention. Therefore, the proposed DHDE algorithm comprehensively discusses the blockchain technology integration system. The proposed DHDE algorithm encrypts the transaction data for an unauthorized person who cannot access the enterprise transaction data based on embedded system people and blockchain.

Landslide early warning systems: a perspective from the internet of things

<span lang="EN-US">Populations located in the vicinity of slopes and soils derived from volcanic ash are constantly at risk due to the possibility of landslides. Such is the case of the city of Manizales, Colombia, which, due to its geomorphological characteristics, has experienced a significant number of landslides that have caused human and economic losses. The Internet of things (IoT) has allowed important technological advances for monitoring, thanks to the low cost and wide coverage of IoT-based systems. Slope monitoring and the development of landslide early warning systems (EWS) have been positively impacted by IoT developments, which shows a relationship. The objective of this article is to review, from the scientific production, the relationship between IoT and EWS. For this purpose, a fragmenting-deriving-combining methodology is applied to focus on a research trends analysis of the subject, from macro-areas such as IoT and EWS to micro areas such as EWS by IoT-based landslides. Finally, the analysis concluded that the conceptual models of IoT and EWS for landslides have some correspondence in some of their layers.</span>

A Survey on Blockchain-Based Trust Management for Internet of Things

Internet of Things (IoT) aims to create a vast network with billions of things that can seamlessly create and exchange data, establishing intelligent interactions between people and objects around them. It is characterized with openness, heterogeneity, and dynamicity, which inevitably introduce severe security, privacy, and trust issues that hinder the widespread application of IoT. Trust management (TM) holds great promise in identifying malicious nodes, maintaining trust relationships, and enhancing system security. Traditional TM systems (TMSs) can be classified into centralized, semi-centralized, and distributed ones, all three of which suffer from critical challenges and thus are not sufficient for facilitating IoT development. Blockchain, as a disruptive technology, can help addressing the challenges of TM in IoT, thanks to its advanced features, such as decentralization, consistency, and tamper-proofing. As a result, blockchain-based TM (BC-TM) has been extensively studied in recent years to achieve decentralized TM in IoT. However, it still lacks a comprehensive survey on the current state of the arts. To fill this gap, in this article, we conduct a serious survey on BC-TM in IoT. We first propose a set of evaluation criteria that should be met by a TMS in IoT. Then, we propose a taxonomy of TMSs and continue with a thorough review on BC-TM in IoT by employing the proposed criteria. In the end, based on the review, a series of open issues are identified, and future research directions are suggested.

Constrained IoT-Based Machine Learning for Accurate Glycemia Forecasting in Type 1 Diabetes Patients.

Individuals with diabetes mellitus type 1 (DM1) tend to check their blood sugar levels multiple times daily and utilize this information to predict their future glycemic levels. Based on these predictions, patients decide on the best approach to regulate their glucose levels with considerations such as insulin dosage and other related factors. Nevertheless, modern developments in Internet of Things (IoT) technology and innovative biomedical sensors have enabled the constant gathering of glucose level data using continuous glucose monitoring (CGM) in addition to other biomedical signals. With the use of machine learning (ML) algorithms, glycemic level patterns can be modeled, enabling accurate forecasting of this variable. Constrained devices have limited computational power, making it challenging to run complex machine learning algorithms directly on these devices. However, by leveraging edge computing, using lightweight machine learning algorithms, and performing preprocessing and feature extraction, it is possible to run machine learning algorithms on constrained devices despite these limitations. In this paper we test the burdens of some constrained IoT devices, probing that it is feasible to locally predict glycemia using a smartphone, up to 45 min in advance and with acceptable accuracy using random forest.

An evidence-based roadmap for IoT software systems engineering

Context:The Internet of Things (IoT) has brought expectations for software inclusion in everyday objects. However, it has challenges and requires multidisciplinary technical knowledge involving different areas that should be combined to enable IoT software systems engineering. Goal:To present an evidence-based roadmap for IoT development to support developers in specifying, designing, and implementing IoT systems. Method:An iterative approach based on experimental studies to acquire evidence to define the IoT Roadmap. Next, the Systems Engineering Body of Knowledge life cycle was used to organize the roadmap and set temporal dimensions for IoT software systems engineering. Results:The studies revealed seven IoT Facets influencing IoT development. The IoT Roadmap comprises 117 items organized into 29 categories representing different concerns for each Facet. In addition, an experimental study was conducted observing a real case of a healthcare IoT project, indicating the roadmap applicability. Conclusions:The IoT Roadmap can be a feasible instrument to assist IoT software systems engineering because it can (a) support researchers and practitioners in understanding and characterizing the IoT and (b) provide a checklist to identify the applicable recommendations for engineering IoT software systems.