Chinmay Chakraborty

Susmita Sharma

Swapnila Roy

Tien Anh Tran

This book covers the sustainability issues of a green environment towards economics and society in terms of alteration in industrial pollution levels, effect of reduced carbon emissions, changes in water bodies characteristics with respect to heavy metal contamination, monitoring of associated impact with respect to ecology and biodiversity, impact of reduced noise levels and air quality influences on human health, handling and management of biomedical waste. According to WHO, 80% of people living in urban areas are exposed to air exceeding safe limits. The advent of "sustainability‟ in development science has led planners to apply evolving notions of "sustainability‟ to the contemporary debate over how cities and regions should be revitalized, redeveloped, and reformed. Market allocation of resources, sustained levels of growth and consumption, an assumption that natural resources are unlimited and a belief that economic growth will „trickle down‟ to the poor have been its hallmarks. The recent advance technology helps to promote green and clean modern societies continuously. The Internet of things will be playing an important role in the upcoming years in environment protection and sustainable development. There is a focus on paradigm shift in the sustainable development for the green environment during the period of isolation of COVID-19. This is the moment for the mobilization against the climate crisis. The sudden fall in pollutants and subsequent blue skies signifies a dramatic shift for India and also other affected countries during this period. Fighting climate change requires a collaborative approach between all spheres of society unlike the former. It must heavily redirect resources towards local, sustainable activities, including education, health, sustainable agriculture and circular management of resources. The impact of COVID-19 pandemic which has resulted in the dramatic change in the different aspects of the environment. The global lockdown has led to a rejuvenation of nature, ecosystems, biodiversity. Even urban environments are discovering a degree of peace and serenity, which led to decrease in greenhouse gas emission.

Environmental Sustainability

The Impact of the COVID-19 Pandemic on Green Societies

Jerry Chun-Wei Lin

Mamoun Alazab

This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.

Trends and Advances

Data-Driven Mining, Learning and Analytics for Secured Smart Cities

Lalit Garg

Uttam Ghosh

Gautam Srivastava

This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives; Promotes an exchange of research across disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures; Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.

Intelligent Internet of Things for Healthcare and Industry

Jayanta Kumar Saha

Utpal Chakraborty

Amit Banerjee

Niloy Sarkar

This book presents the overall technology spectrum in artificial intelligence (AI) and the Fourth Industrial Revolution, which is set to revolutionize the world. It discusses their various aspects and related case studies from industry, academics, administration, law, finance, and accounting as well as educational technology. The contributors, who are experts in their respective fields and from industry and academia, focus on a gesture-recognition prototype for specially abled people; jurisprudential approach to AI and legal reasoning; automated chatbot for autism spectrum disorder using AI assistance; Big Data analytics and Internet of Things (IoT); role of AI in advancement of drug discovery; development, opportunities, and challenges of the Fourth Industrial Revolution; legal, ethical, and policy implications of AI; Internet of Health Things for smart healthcare and digital wellbeing; machine learning and computer vision; computer vision-based system for automation and industrial applications; AI-IoT in home-based healthcare; and AI in super-precision human brain and spine surgery. Buttressed with comprehensive theoretical, methodological, well-established, and validated empirical examples, the book covers the interests of a broad audience from basic science to engineering and technology experts and learners. It will be greatly helpful for CEOs, entrepreneurs, academic leaders, researchers, and students of engineering, biomedicine, and master’s programs in science as well as the vast workforce and students with technical or non-technical backgrounds. It also serves common public interest by presenting new methods to improve the quality of life in general, with a better integration into society.

Artificial Intelligence and the Fourth Industrial Revolution

This book discusses the innovative and efficient technological solutions for sustainable smart societies in terms of alteration in industrial pollution levels, the effect of reduced carbon emissions, green power management, ecology, and biodiversity, the impact of minimal noise levels and air quality influences on human health. The book is focused on the smart society development using innovative low-cost advanced technology in different areas where the growth in employment and income are driven by public and private investment into such economic activities, infrastructure and assets that allow reduced carbon emissions and pollution, enhanced energy, and resource efficiency and prevention of the loss of biodiversity and ecosystem services. The book also covers the paradigm shift in the sustainable development for the green environment in the post-pandemic era. It emphasizes and facilitates a greater understanding of existing available research i.e., theoretical, methodological, well-established and validated empirical work, associated with the environmental and climate change aspects.

Post Pandemic Era

Green Technological Innovation for Sustainable Smart Societies

G. R. Sinha

Varun Bajaj

This book examines the use of biomedical signal processing—EEG, EMG, and ECG—in analyzing and diagnosing various medical conditions, particularly diseases related to the heart and brain. In combination with machine learning tools and other optimization methods, the analysis of biomedical signals greatly benefits the healthcare sector by improving patient outcomes through early, reliable detection. The discussion of these modalities promotes better understanding, analysis, and application of biomedical signal processing for specific diseases. The major highlights of Biomedical Signal Processing for Healthcare Applications include biomedical signals, acquisition of signals, pre-processing and analysis, post-processing and classification of the signals, and application of analysis and classification for the diagnosis of brain- and heart-related diseases. Emphasis is given to brain and heart signals because incomplete interpretations are made by physicians of these aspects in several situations, and these partial interpretations lead to major complications. FEATURES Examines modeling and acquisition of biomedical signals of different disorders Discusses CAD-based analysis of diagnosis useful for healthcare Includes all important modalities of biomedical signals, such as EEG, EMG, MEG, ECG, and PCG Includes case studies and research directions, including novel approaches used in advanced healthcare systems This book can be used by a wide range of users, including students, research scholars, faculty, and practitioners in the field of biomedical engineering and medical image analysis and diagnosis.

Biomedical Signal Processing for Healthcare Applications

Chinmay Chakraborty

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