Chuan-Ming Liu – författare

This book discusses the technological aspects for the implementation of Society 5.0. The foundation and recent advances of emerging technologies such as artificial intelligence, data science, Internet of Things, and Big Data for the realization of Society 5.0 are covered. Practical solutions to existing problems, examples, and case studies are also offered.

Society 5.0 and the Future of Emerging Computational Technologies: Practical Solutions, Examples, and Case Studies discusses technologies such as machine learning, artificial intelligence, and Internet of Things for the implementation of Society 5.0. It offers a firm foundation and understanding of the recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management. Applications and implementations are highlighted along with the correlation between technologies. Examples and case studies are presented throughout the book to augment text.

This book can be used by research scholars in the engineering domain who wish to gain knowledge and contribute towards a modern and secure future society. The book will also be useful as a reference at universities for postgraduate students who are interested in technological advancements.

This book discusses the technological aspects for the implementation of Society 5.0. The foundation and recent advances of emerging technologies such as artificial intelligence, data science, Internet of Things, and Big Data for the realization of Society 5.0 are covered. Practical solutions to existing problems, examples, and case studies are also offered.

Society 5.0 and the Future of Emerging Computational Technologies: Practical Solutions, Examples, and Case Studies discusses technologies such as machine learning, artificial intelligence, and Internet of Things for the implementation of Society 5.0. It offers a firm foundation and understanding of the recent advancements in various domains such as data analytics, neural networks, computer vision, and robotics, along with practical solutions to existing problems in fields such as healthcare, manufacturing industries, security, and infrastructure management. Applications and implementations are highlighted along with the correlation between technologies. Examples and case studies are presented throughout the book to augment text.

This book can be used by research scholars in the engineering domain who wish to gain knowledge and contribute towards a modern and secure future society. The book will also be useful as a reference at universities for postgraduate students who are interested in technological advancements.

Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment.

The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier.

Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare.

Audience

The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.

Encapsulates different case studies where green-IOT and machine learning can be used for making significant progress towards improvising the quality of life and sustainable environment.

The Internet of Things (IoT) is an evolving idea which is responsible for connecting billions of devices that acquire, perceive, and communicate data from their surroundings. Because this transmission of data uses significant energy, improving energy efficiency in IOT devices is a significant topic for research. The green internet of things (G-IoT) makes it possible for IoT devices to use less energy since intelligent processing and analysis are fundamental to constructing smart IOT applications with large data sets. Machine learning (ML) algorithms that can predict sustainable energy consumption can be used to prepare guidelines to make IoT device implementation easier.

Green Internet of Things and Machine Learning lays the foundation of in-depth analysis of principles of Green-Internet of Things (G-IoT) using machine learning. It outlines various green ICT technologies, explores the potential towards diverse real-time areas, as well as highlighting various challenges and obstacles towards the implementation of G-IoT in the real world. Also, this book provides insights on how the machine learning and green IOT will impact various applications: It covers the Green-IOT and ML-based smart computing, ML techniques for reducing energy consumption in IOT devices, case studies of G-IOT and ML in the agricultural field, smart farming, smart transportation, banking industry and healthcare.

Audience

The book will be helpful for research scholars and researchers in the fields of computer science and engineering, information technology, electronics and electrical engineering. Industry experts, particularly in R&D divisions, can use this book as their problem-solving guide.

This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the International Conference on Communication, Devices and Networking (ICCDN 2019), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 9–10 December 2019. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals, it will help young and experienced scientists and developers alike to explore new perspectives, and offer them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking. 

This book covers the latest technological advances in neuro-computational intelligence in biological processes where the primary focus is on biologically inspired neuro-computational techniques. The theoretical and practical aspects of biomedical neural computing, brain-inspired computing, bio-computational models, artificial intelligence (AI) and machine learning (ML) approaches in biomedical data analytics are covered along with their qualitative and quantitative features. The contents cover numerous computational applications, methodologies and emerging challenges in the field of bio-soft computing and bio-signal processing. The authors have taken meticulous care in describing the fundamental concepts, identifying the research gap and highlighting the problems with the strategical computational approaches to address the ongoing challenges in bio-inspired models and algorithms. Given the range of topics covered, this book can be a valuable resource for students, researchersas well as practitioners interested in the rapidly evolving field of neurocomputing and biomedical data analytics.

This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the International Conference on Communication, Devices and Networking (ICCDN 2020), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 19–20 December 2020. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals, it helps young and experienced scientists and developers alike to explore new perspectives, and offer them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking.

This book provides both the developers and the users with an awareness of the challenges and opportunities of advancements in healthcare paradigm with the application and availability of advanced hardware, software, tools, technique or algorithm development stemming the Internet of Things. The book helps readers to bridge the gap in their three understanding of three major domains and their interconnections: 

Hardware tested and software APP development for data collection, intelligent protocols for analysis and knowledge extraction. 

Medical expertise to interpret extracted knowledge towards disease prediction or diagnosis and support. Security experts to ensure data correctness for precise advice. 

This book covers recent trends in the field of devices, wireless communication and networking. It gathers selected papers presented at the 7th International Conference on Communication, Devices and Networking (ICCDN 2024), which was organized by the Department of Electronics and Communication Engineering, Sikkim Manipal Institute of Technology, Sikkim, India, on 19–20 January 2024. Gathering cutting-edge research papers prepared by researchers, engineers and industry professionals helps young and experienced scientists and developers alike to explore new perspectives and offers them inspirations on how to address real-world problems in the areas of electronics, communication, devices and networking.