This book consolidates and summarizes smart technologies like IoT, edge computing, and AI used in different aspects of waste material management, mitigation, and recycling for a sustainable environment. One of the cases explains how IoT-based systems and wireless sensors can be used to continuously detect common pollutants such as volatile organic compounds (VOCs), carbon monoxide, and particulate matter (PM) and how the data collected are used to assess the overall air quality and determine actions for improvements. A collection of practical case studies, this book provides a comprehensive knowledge in smart waste management to readers in universities, research centers, and industries.

The book studies emerging and sustaining technologies for applications of Industry 5.0 to develop technological solutions to address numerous real-life challenges to solve sustainable development-related issues. It identifies limitations, pitfalls, and open research questions in industry 5.0, discusses real-time problems, and challenges with equivalent solutions with a focus on sustainable growth to develop, humanization and environmentally friendly intelligent system applications. It analyses applications enabled by Industry 5.0 such as healthcare, supply chain, smart framing, remote sensing, production in manufacturing, and cloud manufacturing. It also includes the difficulties and problems posed by the organization between robots and humans on the assembly line to maintain sustainability. Addresses key challenges in implementing intelligent systems in IoT-based applications, including issues ranging from cost and energy efficiency to availability and quality of service Explores the technologies to allow human-machine association and its impact on consumption and sustainability Provides sustainable solutions to emerging industrial problems, especially in healthcare, manufacturing, remote sensing, environmental engineering Examines need for data pre-processing, classification & prediction, Cluster Analysis, Mining Multimedia, Text, and Web Data, Advanced machine learning techniques for scientific programming in Industry Presents success stories in the form of case studies of IIoT, IIoRT, Big Data, Intelligent Systems, Deep Learning in Industry 5.0 era The text is for postgraduate students, professionals, and academic researchers working in the fields of computer science and information technology, especially for professionals and researchers interested in the technological side of sustainable development.

This book explores the concepts and role of green computing and its recent developments for making the environment sustainable. It focuses on green automation in disciplines such as computers, nanoscience, information technology, and biochemistry. This book is characterized through descriptions of sustainability, green computing, their relevance to the environment, society, and its applications. Presents how to make the environment sustainable through engineering aspects and green computing Explores concepts and the role of green computing with recent developments Processes green automation linked with various disciplines such as nanoscience, information technology, and biochemistry Explains the concepts of green computing linked with sustainable environment through information technology This book will be of interest to researchers, libraries, students, and academicians that are interested in the concepts of green computing linked with green automation through information technology and their impacts on the future.

The rapid proliferation of connected devices in our daily lives, from smart homes to industrial sensors, has led to an explosion of data that requires processing before it is useful to experts. However, modern devices often have limited resources, making it challenging to decode and utilize this data effectively. Additionally, the need for real-time decision-making further complicates this issue, as traditional data processing methods take far too long to be able to keep up with the required volume and speed. Developments Towards Next Generation Intelligent Systems for Sustainable Development offers a comprehensive solution to these challenges by integrating novel technologies such as AI, edge computing, federated learning, quantum computing, and more. The book shows how intelligent systems can maximize computing power by leveraging these technologies to process large volumes of data efficiently and autonomously and make real-time decisions. The proposed architectures and frameworks focus on real-time analysis, faster decision-making, enhanced privacy, and efficient data processing.

Artificial intelligence and the use of computational methods to extract information from data are providing adequate tools to monitor and predict water pollutants and water quality issues faster and more accurately. Smart sensors and machine learning models help detect and monitor dispersion and leakage of pollutants before they reach groundwater. With contributions from experts in academia and industries, who give a unified treatment of AI methods and their applications in water science, this book help governments, industries, and homeowners not only address water pollution problems more quickly and efficiently, but also gain better insight into the implementation of more effective remedial measures. FEATURES Provides cutting-edge AI applications in water sector. Highlights the environmental models used by experts in different countries. Discusses various types of models using AI and its tools for achieving sustainable development in water and groundwater. Includes case studies and recent research directions for environmental issues in water sector. Addresses future aspects and innovation in AI field related to watersustainability. This book will appeal to scientists, researchers, and undergraduate and graduate students majoring in environmental or computer science and industry professionals in water science and engineering, environmental management, and governmental sectors. It showcases artificial intelligence applications in detecting environmental issues, with an emphasis on the mitigation and conservation of water and underground resources.

This book presents the proceedings of the 6th International Conference on Signal Processing and Information Communications (ICSPIC 2023), which was held in Singapore, on February 25-27, 2023. The conference aims to provide a leading international forum for researchers, practitioners, and professionals from the industry, academia and government to share their new ideas, progresses and achievements in signal processing and information communications. The contributions focus on the latest advances, trends and future challenges in analog and mixed signal processing, design and implementation of signal processing systems, compressive sensing, machine learning methods for communications and signal processing, multimedia signal processing, natural language processing, next generation mobile communications, nonlinear signal processing, optical communications, parallel and distributed processing, and more.

Currently, available technologies can help make a supply chain resilient in volatile times whilst also keeping it responsible. Environmentally Responsible Supply Chains in an Era of Digital Transformation focuses on the linkages between digital technologies and environmental sustainability research and outlines synergies for more resilient, efficient and transparent supply chain management practices.