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IoT has a wide range of applications in the health-care sector and has captured the interest of many academic and industrial communities. The health IoT devices suffer from botnet attacks as all the devices are connected to the internet. An army of compromised bots may form to launch a DDoS attack, steal confidential data of patients and disrupt the service, and hence detecting this army of bots is paramount. This study aims to detect botnet attacks in health IoT devices using the deep learning technique.

This paper focuses on designing a method to protect health IoT devices from botnet attacks by constantly observing communication network traffic and classifying them as benign and malicious flow. The proposed algorithm analyzes the health IoT network traffic through implementing Bidirectional long-short term memory, a deep learning technique. The IoT-23 data set is considered for this research as it includes diverse botnet attack scenarios.

The performance of the proposed method is evaluated using attack prediction accuracy. It results in the highest accuracy of 84.8%, classifying benign and malicious traffic.

The proposed method constantly monitors the health IoT network to detect botnet attacks and classifies the traffic as benign or attack. The system is implemented using the BiLSTM algorithm and trained using the IoT-23 data set. The diversity of attack scenarios of the IoT-23 data set demonstrates the proposed algorithm's competence in detecting botnet types in a heterogeneous environment.

Considering both the current opportunities of the Internet of things (IoT) and aviation, as well as the potential opportunities they may offer for the future, it is understood that they are among the important issues that need to be examined in the literature. This study aims to provide an idea by conducting bibliometric and visualization analyses of the current trends and development opportunities of IoT and aviation.

In this study, descriptive and bibliometric analyses within the framework of co-author, co-citation, bibliographic coupling, and keyword co-occurrence analysis were carried out for publications found to be published between 2007 and 2023 in the Web of Science (WoS) database related to IoT and aviation. VOSviewer (ver. 1.6.18) program and the Biblioshiny application were used to create bibliometric networks and provide visualization.

As a result of some descriptive and visualization analyses, the current trend of publications on IoT and aviation and future publication opportunities has been revealed. It has been understood that the subject of IoT and aviation is one of the subjects whose number of publications has increased in recent years and has not yet fully matured in terms of the number of publications and has the potential to make new publications.

In this study, bibliometric analysis of IoT and aviation, which could not be found examined before in the literature, and the creation of existing bibliometric networks by visualizing were carried out.

Internet of things (IoT) is essential in technical, social and economic domains, but there are many challenges that researchers are continuously trying to solve. Traditional resource allocation methods in IoT focused on the optimal resource selection process, but the energy consumption for allocating resources is not considered sufficiently. This paper aims to propose a resource allocation technique aiming at energy and delay reduction in resource allocation. Because of the non-deterministic polynomial-time hard nature of the resource allocation issue and the forest optimization algorithm’s success in complex problems, the authors used this algorithm to allocate resources in IoT.

For the vast majority of IoT applications, energy-efficient communications, sustainable energy supply and reduction of latency have been major goals in resource allocation, making operating systems and applications more efficient. One of the most critical challenges in this field is efficient resource allocation. This paper has provided a new technique to solve the mentioned problem using the forest optimization algorithm. To simulate and analyze the proposed technique, the MATLAB software environment has been used. The results obtained from implementing the proposed method have been compared to the particle swarm optimization (PSO), genetic algorithm (GA) and distance-based algorithm.

Simulation results show that the proper performance of the proposed technique. The proposed method, in terms of “energy” and “delay,” is better than other ones (GA, PSO and distance-based algorithm).

The paper presents a useful method for improving resource allocation methods. The proposed method has higher efficiency compared to the previous methods. The MATLAB-based simulation results have indicated that energy consumption and delay have been improved compared to other algorithms, which causes the high application of this method in practical projects. In the future, the focus will be on resource failure and reducing the service level agreement violation rate concerning the number of resources.

The proposed technique can solve the mentioned problem in the IoT with the best resource utilization, low delay and reduced energy consumption. The proposed forest optimization-based algorithm is a promising technique to help enterprises participate in IoT initiatives and develop their business.

The Cloud of Things (IoT) that refers to the integration of the Cloud Computing (CC) and the Internet of Things (IoT), has dramatically changed the way treatments are done in the ubiquitous computing world. This integration has become imperative because the important amount of data generated by IoT devices needs the CC as a storage and processing infrastructure. Unfortunately, security issues in CoT remain more critical since users and IoT devices continue to share computing as well as networking resources remotely. Moreover, preserving data privacy in such an environment is also a critical concern. Therefore, the CoT is continuously growing up security and privacy issues. This paper focused on security and privacy considerations by analyzing some potential challenges and risks that need to be resolved. To achieve that, the CoT architecture and existing applications have been investigated. Furthermore, a number of security as well as privacy concerns and issues as well as open challenges, are discussed in this work.

This research focuses on the challenges of establishing a better medical system that can detect and diagnose diseases earlier. Using such cutting-edge health systems, healthcare practitioners may quickly and effectively manage patients’ medical issues by providing the appropriate data at the right time about the right people. The advancement of technology has increased the usefulness of devices that routinely analyse health measurements or monitoring time-sensitive health-related data. Medical professionals and patients alike are downloading health-related mobile apps to better track and manage their health. The research evidences how Internet of Things (IoT) technology may be used to support health care.

The emerging technologies of the Fourth Industrial Revolution are transforming various industries, including agriculture. Unaware, young male and female farmers leave the agriculture profession as they perform unsustainable practices. Precision agriculture using the Internet of Things (IoT) is a solution to sustainable agriculture. Extension professionals are at the heart of disseminating agricultural advisory agricultural services in India. The discourse on the IoT is entering the space of extension advisory services (EASs) and social sciences. Thus, the present paper seeks to review the application of IoT in Indian agriculture, its challenges and its effect on EASs. The conceptual framework is drawn from disruptive and surveillance capitalist theories.

Online literature review was conducted on electronic e-book Ebsco, Google scholar, PubMed, Jane, j gate, research4life, springer journal and Mendeley databases for full-text repositories, textbook, thesis, web articles, newspaper articles, reports, blogs for the year 1990 to May 2021 using keywords “IoT application in agriculture,” “emerging technologies in agriculture,” “challenges in IoT application,” “extension advisory services sources of information,” “big data and extension advisory, “IoT and extension advisory in India.” Only publications in the English language were included.

IoT aids progressive farmers and small farmers alike. Drones, robotics, precision irrigation, livestock tracking and crop disease surveillance are examples of IoT applications in agriculture. Only large corporations and governments access IoT, and for them, big data storage is an issue. Privacy and security concerns demand upgrades in IoT systems. Solutions to the convergence of IoT with the cloud will leverage agricultural EASs, resulting in fast computing, precise and proactive up-to-date problem solving. Hence, the need for communication between firms and clients has ceased. Thus, the jobs of extension agents are replaced.

The competence of future human extension agents lies in reskilling as a “knowledge broker” of relationships and expertise, as s/he cannot have all multidisciplinary knowledge.

Although IoT applications in agriculture are available from a technological standpoint, there remains an awareness gap regarding the impact of IoT applications in agricultural EASs. This study will aid in a better comprehension of IoT applications from current and prospective EASs.

Digital transformation using Industry 4.0 technologies can address various challenges in food supply chains (FSCs). However, the integration of emerging technologies to achieve digital transformation in FSCs is unclear. This study aims to establish how the digital transformation of FSCs can be achieved by adopting key technologies such as the Internet of Things (IoTs), cloud computing (CC) and big data analytics (BDA).

A systematic literature review (SLR) resulted in 57 articles from 2008 to 2022. Following descriptive and thematic analysis, a conceptual framework based on the diffusion of innovation (DOI) theory and the context-intervention-mechanism-outcome (CIMO) logic is established, along with avenues for future research.

The combination of DOI theory and CIMO logic provides the theoretical foundation for linking the general innovation process to the digital transformation process. A novel conceptual framework for achieving digital transformation in FSCs is developed from the initiation to implementation phases. Objectives and principles for digitally transforming FSCs are identified for the initiation phase. A four-layer technology implementation architecture is developed for the implementation phase, facilitating multiple applications for FSC digital transformation.

The study contributes to the development of theory on digital transformation in FSCs and offers managerial guidelines for accelerating the growth of the food industry using key Industry 4.0 emerging technologies. The proposed framework brings clarity into the “neglected” intermediate stage of data management between data collection and analysis. The study highlights the need for a balanced integration of IoT, CC and BDA as key Industry 4.0 technologies to achieve digital transformation successfully.

As the size of the population is growing and the capacity of the planet Earth is limited, human beings are searching for sustainable and technology-enabled solutions to support society, ecology and economy. One of the solutions has been developing smart sustainable cities. Smart sustainable cities are cities as systems, where their infrastructure, different subsystems and different functional domains are virtually connected to the information and communication technologies (ICT) and internet via sensors and devices and the Internet of Things (IoT), to collect and process real-time Big Data and make efficient, effective and sustainable solutions for a democratic and liveable city for its various stakeholders. This chapter explores the concepts and practices of sustainable smart cities across the globe and explores the use of technologies such as IoT, Blockchain technology and Cloud computing, etc. their challenges and then presents a view on business models for sustainable smart cities.

The 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.

Bibliometric 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.

The 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.

Documents 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.

The 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.

The 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.

This study aims to identify blockchain-related innovation trends that can improve trust networks in a smart city's transport and supply chain networks. Trust networks are crucial in building and maintaining the trust of citizens in smart cities. By promoting transparency and accountability, facilitating collaboration and innovation, enhancing citizen participation and protecting privacy and security, trust networks can help to ensure that smart cities are developed and implemented in a responsible and sustainable way. A systematic literature review identifies 60 conceptual and empirical studies. This research focuses on the current problems and developing procurement and supply chain strategy and the potential benefits of using blockchain in these areas. It suggests ways for the smart city's transport and supply chain networks to utilise blockchain to improve operations and supply chain strategy and identifies innovation trends related to blockchain. The study also includes a systematic literature review and Blockchain Transformation and Influence model as the basis to enhance trust networks in the supply chain.