Second International Conference on Emerging Trends in IOT and Computing Technologies (ICEICT – 2023) is organised with a vision to address the various issues to promote the creation of intelligent solution for the future. It is expected that researchers will bring new prospects for collaboration across disciplines and gain ideas facilitating novel concepts. Second International Conference of Emerging Trends in IoT and Computer Technologies (ICEICT-2023) is an inventive event organised in Goel Institute of Technology and Management, Lucknow, India, with motive to make available an open International forum for the researches, academicians, technocrats, scientist, engineers, industrialist and students around the globe to exchange their innovations and share the research outcomes which may lead the young researchers, academicians and industrialist to contribute to the global society. The conference ICEICT- 2023 is being organised at Goel Institute of Technology and Management, Lucknow, Uttar Pradesh, during 12-13 January 2024. It will feature world-class keynote speakers, special sessions, along with the regular/oral paper presentations. The conference welcomes paper submissions from researcher, practitioners, academicians and students will cover numerous tracks in the field of Computer Science and Engineering and associated research areas.

This book includes the proceedings of the International Conference on Emerging Trends in IoT and Computing Technologies (ICEICT-2022) held at Goel Institute of Technology & Management, Lucknow, India.

The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.

This book constitutes the refereed proceedings of the 25th International Computer Symposium on New Trends in Computer Technologies and Applications, ICS 2022, which took place in Taoyuan, Taiwan, in December 2022. ICS is one of the largest joint international IT symposia held in Taiwan. Founded in 1973, it is intended to provide a forum for researchers, educators, and professionals to exchange their discoveries and practices, and to explore future trends and applications in computer technologies. The biannual symposium offers a great opportunity to share research experiences and to discuss potential new trends in the IT industry. The 58 full papers and one invited paper presented in this volume were carefully reviewed and selected from 137 submissions. The papers have been organized in the following topical sections: Invited Paper; Algorithms, Bioinformatics, and Computation Theory; Cloud Computing and Big Data; Computer Vision and Image Processing; Cryptography and Information Security; Electronics and Information Technology; Mobile Computation and Wireless Communication; Ubiquitous Cybersecurity and Forensics.

PUBLISHED BY CO-TEXT PUBLISHERS IN ASSOCIATION WITH DEPARTMENT OF COMPUTER SCIENCE SACRED HEART COLLEGE (AUTONOMOUS) THEVARA, KOCHI-682013, KERALA, INDIA

"Advancements and Emerging Trends in AI, ML, DS, and IoT" provides an exhaustive examination of the state-of-the- art progressions that are influencing the domains of IoT, Data Science, Artificial Intelligence (AI), and Machine Learning (ML). Designed for a wide readership including professionals, researchers, students, and enthusiasts, this book provides a systematic guide to comprehending the profound possibilities that these interrelated fields hold. The text provides an in-depth exploration of the most recent developments in the field, encompassing fundamental concepts as well as sophisticated implementations. Such developments include federated learning, edge computing, and deep learning. Insightful case studies and expert contributions shed light on the practical implications of this concept in various sectors, including finance, healthcare, and smart cities. An exhaustive examination is conducted on ethical considerations pertaining to bias, privacy, and accountability, thereby guaranteeing a comprehensive outlook on the societal ramifications of these technologies. Furthermore, the book provides a view into the future by examining forthcoming disruptive innovations, opportunities, and challenges. An invaluable resource, "Advancements and Emerging Trends in AI, ML, DS, and IoT" offers a well-balanced combination of theoretical insights and practical wisdom. It effectively guides readers through the ever-changing realm of technological innovation and motivates them to delve deeper into the subject matter.

The adoption of cloud and IoT technologies in both the industrial and academic communities has enabled the discovery of numerous applications and ignited countless new research opportunities. With numerous professional markets benefiting from these advancements, it is easy to forget the non-technical issues that accompany technologies like these. Despite the advantages that these systems bring, significant ethical questions and regulatory issues have become prominent areas of discussion. Social, Legal, and Ethical Implications of IoT, Cloud, and Edge Computing Technologies is a pivotal reference source that provides vital research on the non-technical repercussions of IoT technology adoption. While highlighting topics such as smart cities, environmental monitoring, and data privacy, this publication explores the regulatory and ethical risks that stem from computing technologies. This book is ideally designed for researchers, engineers, practitioners, students, academicians, developers, policymakers, scientists, and educators seeking current research on the sociological impact of cloud and IoT technologies.

The Internet of Things (IoT) has made revolutionary advances in the utility grid as we know it. Among these advances, intelligent medical services are gaining much interest. The use of Artificial Intelligence (AI) is increasing day after day in fighting one of the most significant viruses, COVID-19. The purpose of this book is to present the detailed recent exploration of AI and IoT in the COVID-19 pandemic and similar applications. The integrated AI and IoT paradigm is widely used in most medical applications, as well as in sectors that deal with transacting data every day. This book can be used by computer science undergraduate and postgraduate students; researchers and practitioners; and city administrators, policy makers, and government regulators. It presents a smart and up-to-date model for COVID-19 and similar applications. Novel architectural and medical use cases in the smart city project are the core aspects of this book. The wide variety of topics it presents offers readers multiple perspectives on a variety of disciplines. Prof. Dr. Fadi Al-Turjman received his PhD in computer science from Queen’s University, Kingston, Ontario, Canada, in 2011. He is a full professor and research center director at Near East University, Nicosia, Cyprus.

Book describes online experimentation, using fundamentally emergent technologies to build the resources and considering the context of IoT.Online Experimentation: Emerging Technologies and IoT is suitable for all who is involved in the development design and building of the domain of remote experiments.

Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.