Energy Efficient Deep Learning Approaches In Iot Fog And Green Blockchain Revolution

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Energy Efficient Deep Learning Approaches In Iot Fog And Green Blockchain Revolution

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Author : Sathio, Anwar Ali
language : en
Publisher: IGI Global
Release Date : 2025-04-18

Energy Efficient Deep Learning Approaches In Iot Fog And Green Blockchain Revolution written by Sathio, Anwar Ali and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-18 with Technology & Engineering categories.

The convergence of Internet of Things (IoT), fog computing, and blockchain technology can be used to revolutionize energy efficiency and sustainability. The implementation of deep learning (DL) techniques may optimize the energy consumption of these interconnected systems. Thus, they can be used to create green, energy-efficient solutions for various industries, including smart cities, healthcare, finance, and industrial IoT (IIoT). Focusing on the energy efficiency and environmental impact of these technologies, they provide valuable insights into creating sustainable and scalable systems. Energy-Efficient Deep Learning Approaches in IoT, Fog, and Green Blockchain Revolution bridges the knowledge gap between traditional IoT and blockchain research and the emerging need for energy-efficient and green technologies. It influences future research directions, encourages collaboration across disciplines, and inspires innovations that prioritize sustainability. Covering topics such as software-defined networking (SDN), ecosystem conservation, and monitoring systems, this book is an excellent resource for computer scientists, policymakers, technologists, industry practitioners, engineers, environmentalists, sustainability advocates, professionals, researchers, scholars, academicians, and more.

Responsible Innovation In Smart Healthcare Ai Iot And Ethical Sustainability Practices

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Author : Sheih, Chich-Jen
language : en
Publisher: IGI Global
Release Date : 2025-07-25

Responsible Innovation In Smart Healthcare Ai Iot And Ethical Sustainability Practices written by Sheih, Chich-Jen and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-25 with Medical categories.

The advancement of smart healthcare technologies has transformed how medical services are delivered, monitored, and personalized. As these innovations improve patient outcomes, operational efficiency, and predictive care, they also raise critical ethical and sustainability concerns. Responsible innovation requires a balance between technological progress and the ethical, social, and environmental implications of intelligent tools. This includes ensuring data privacy, addressing algorithmic bias, promoting equitable access, and minimizing environmental impact. By integrating ethical sustainability practices into the design and usage of AI and IoT in healthcare, organizations can foster an inclusive, transparent, and resilient healthcare system. Responsible Innovation in Smart Healthcare: AI, IoT, and Ethical Sustainability Practices explores the integration of AI and IoT in smart healthcare systems, focusing on how these technologies improve care delivery and patient outcomes. It explains the importance of responsible innovation by addressing ethical, social, and environmental considerations to ensure sustainable and equitable healthcare solutions. This book covers topics such as machine learning, ethics and law, and patient monitoring, and is a useful resource for medical professionals, computer engineers, academicians, researchers, and scientists.

Emerging Technologies And The Application Of Wsn And Iot

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Author : Shalli Rani
language : en
Publisher: CRC Press
Release Date : 2024-04-30

Emerging Technologies And The Application Of Wsn And Iot written by Shalli Rani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-30 with Computers categories.

The Internet of Things (IoT) has numerous applications, including smart cities, industries, cloud-based apps, smart homes, and surveillance. The Internet of Things (IoT) enables smarter living by connecting devices, people, and objects. As networking became a crucial aspect of the Internet, rigorous design analysis led to the development of new research areas. The Internet of Things has revolutionized daily living in countless ways. It enables communication between buildings, people, portable gadgets, and vehicles, facilitating mobility. Smart cities and cloud-based data have transformed corporate practices. With billions of connected gadgets, everything will soon be able to communicate remotely. IoT networks, whether public or private, rely significantly on machine learning and software-defined networking. Indian and other governments have approved various research projects on IoT-based networking technologies. This field of study will significantly impact society in the future. Researchers are concerned about the many application areas and driving forces behind smart cities. The authors aim to provide insights into software-defined networking, artificial intelligence, and machine learning technologies used in IoT and networking. The framework focuses on practical applications and infrastructures. The book includes practical challenges, case studies, innovative concepts, and other factors that impact the development of realistic scenarios for smart surveillance. It also highlights innovative technology, designs, and algorithms that can accelerate the creation of smart city concepts. This resource includes real-world applications and case studies for smart city technology, enormous data management, and machine learning prediction, all with confidentiality and safety problems.

Computational Intelligence For Green Cloud Computing And Digital Waste Management

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Author : Kumar, K. Dinesh
language : en
Publisher: IGI Global
Release Date : 2024-02-27

Computational Intelligence For Green Cloud Computing And Digital Waste Management written by Kumar, K. Dinesh and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-27 with Computers categories.

In the digital age, the relentless growth of data centers and cloud computing has given rise to a pressing dilemma. The power consumption of these facilities is spiraling out of control, emitting massive amounts of carbon dioxide, and contributing to the ever-increasing threat of global warming. Studies show that data centers alone are responsible for nearly eighty million metric tons of CO2 emissions worldwide, and this figure is poised to skyrocket to a staggering 8000 TWh by 2030 unless we revolutionize our approach to computing resource management. The root of this problem lies in inefficient resource allocation within cloud environments, as service providers often over-provision computing resources to avoid Service Level Agreement (SLA) violations, leading to both underutilization of resources and a significant increase in energy consumption. Computational Intelligence for Green Cloud Computing and Digital Waste Management stands as a beacon of hope in the face of the environmental and technological challenges we face. It introduces the concept of green computing, dedicated to creating an eco-friendly computing environment. The book explores innovative, intelligent resource management methods that can significantly reduce the power consumption of data centers. From machine learning and deep learning solutions to green virtualization technologies, this comprehensive guide explores innovative approaches to address the pressing challenges of green computing. Whether you are an educator teaching about green computing, an environmentalist seeking sustainability solutions, an industry professional navigating the digital landscape, a resolute researcher, or simply someone intrigued by the intersection of technology and sustainability, this book offers an indispensable resource.

Fog Data Analytics For Iot Applications

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Author : Sudeep Tanwar
language : en
Publisher: Springer Nature
Release Date : 2020-08-25

Fog Data Analytics For Iot Applications written by Sudeep Tanwar and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-08-25 with Technology & Engineering categories.

This book discusses the unique nature and complexity of fog data analytics (FDA) and develops a comprehensive taxonomy abstracted into a process model. The exponential increase in sensors and smart gadgets (collectively referred as smart devices or Internet of things (IoT) devices) has generated significant amount of heterogeneous and multimodal data, known as big data. To deal with this big data, we require efficient and effective solutions, such as data mining, data analytics and reduction to be deployed at the edge of fog devices on a cloud. Current research and development efforts generally focus on big data analytics and overlook the difficulty of facilitating fog data analytics (FDA). This book presents a model that addresses various research challenges, such as accessibility, scalability, fog nodes communication, nodal collaboration, heterogeneity, reliability, and quality of service (QoS) requirements, and includes case studies demonstrating its implementation. Focusing on FDA in IoT and requirements related to Industry 4.0, it also covers all aspects required to manage the complexity of FDA for IoT applications and also develops a comprehensive taxonomy.

Grazing In Future Multi Scapes From Thoughtscapes To Landscapes Creating Health From The Ground Up

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Author : Pablo Gregorini
language : en
Publisher: Frontiers Media SA
Release Date : 2022-09-27

Grazing In Future Multi Scapes From Thoughtscapes To Landscapes Creating Health From The Ground Up written by Pablo Gregorini and has been published by Frontiers Media SA this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-27 with Technology & Engineering categories.

This Research Topic is hosted in partnership with the "Grazing in Future Multi-Scapes" international workshop. The workshop will be held online, 30th May - 5th June 2021. Throughout different landscapes of the world, “grazing” herbivores fulfill essential roles in ecology, agriculture, economies and cultures including: families, farms, and communities. Not only do livestock provide food and wealth, they also deliver ecosystem services through the roles they play in environmental composition, structure and dynamics. Grazing, as a descriptive adjective, locates herbivores within a spatial and temporal pastoral context where they naturally graze or are grazed by farmers, ranchers, shepherds etc. In many cases, however, pastoralism with the single objective of maximizing animal production and/or profit has transformed landscapes, diminishing biodiversity, reducing water and air quality, accelerating loss of soil and plant biomass, and displacing indigenous animals and people. These degenerative landscape transformations have jeopardized present and future ecosystem and societal services, breaking the natural integration of land, water, air, health, society and culture. Land-users, policy makers and societies are calling for alternative approaches to pastoral systems; a call for diversified-adaptive and integrative agro-ecological and food-pastoral-systems designs that operate across multiple scales and ‘scapes’ (e.g. thought-, social-, land-, food-, health-, wild-scapes), simultaneously. There needs to be a paradigm shift in pastoral production systems and how grazing herbivores are managed –grazed- within them, derived initially from a change in perception of how they provide wealth. The thoughtscapes will include paradigm shifts where grazers move away from the actual archetype of pastoralism, future landscapes are re-imagined, and regenerative and sustainable management paradigms are put in place to achieve these visions. From this will come a change in collective thinking of how communities and cultures (socialscapes) perceive their relationships with pastoral lands. The landscapes are the biotic and abiotic four-dimensional domains or environments in need of nurture. Landscapes are the tables where humans and herbivores gain their nourishment, i.e. foodscapes. Foodscapes and dietary perceptions, dictate actions and reactions that are changing as developed countries grapple with diseases related to obesity, and people starve in developing countries. Societies are demanding healthscapes and nutraceutical foodscapes, and paradoxically, some are moving away from animal products. While indigenous species of animals, including humans (wildscapes), have been displaced from many of their lands by monotonic pastoralism, multifunctional pastoral systems can be designed in view of dynamic multi-scapes of the future. The purpose of this Research Topic is to influence future mental and practical models of pastoralism in continually evolving multi-scapes. We seek a collection of papers that will cultivate such a shift in thinking towards future models of sustainable multipurpose pastoralism. The contributions will be synthesized to establish how multifunctional pastoral systems can be re-imagined and then designed in view of the integrative dynamics of sustainable future multi-scapes.

Machine Learning Approaches For Convergence Of Iot And Blockchain

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Author : Krishna Kant Singh
language : en
Publisher: John Wiley & Sons
Release Date : 2021-07-16

Machine Learning Approaches For Convergence Of Iot And Blockchain written by Krishna Kant Singh and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-16 with Computers categories.

MACHINE LEARNING APPROACHES FOR CONVERGENCE OF IOT AND BLOCKCHAIN The unique aspect of this book is that its focus is the convergence of machine learning, IoT, and blockchain in a single publication. Blockchain technology and the Internet of Things (IoT) are two of the most impactful trends to have emerged in the field of machine learning. Although there are a number of books available solely on the subjects of machine learning, IoT and blockchain technology, no such book has been available which focuses on machine learning techniques for IoT and blockchain convergence until now. Thus, this book is unique in terms of the topics it covers. Designed as an essential guide for all academicians, researchers, and those in industry who are working in related fields, this book will provide insights into the convergence of blockchain technology and the IoT with machine learning. Highlights of the book include: Examines many industries such as agriculture, manufacturing, food production, healthcare, the military, and IT Security of the Internet of Things using blockchain and AI Developing smart cities and transportation systems using machine learning and IoT Audience The target audience of this book is professionals and researchers (artificial intelligence specialists, systems engineers, information technologists) in the fields of machine learning, IoT, and blockchain technology.

Green Internet Of Things And Machine Learning

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Author : Roshani Raut
language : en
Publisher: John Wiley & Sons
Release Date : 2022-01-10

Green Internet Of Things And Machine Learning written by Roshani Raut and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-10 with Computers categories.

Health Economics and Financing 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.

Convergence Of Deep Learning And Artificial Intelligence In Internet Of Things

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Author : Ajay Rana
language : en
Publisher: CRC Press
Release Date : 2022-12-27

Convergence Of Deep Learning And Artificial Intelligence In Internet Of Things written by Ajay Rana and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-27 with Computers categories.

This book covers advances and applications of smart technologies including the Internet of Things (IoT), artificial intelligence, and deep learning in areas such as manufacturing, production, renewable energy, and healthcare. It also covers wearable and implantable biomedical devices for healthcare monitoring, smart surveillance, and monitoring applications such as the use of an autonomous drone for disaster management and rescue operations. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology. • Covers concepts, theories, and applications of artificial intelligence and deep learning, from the perspective of the Internet of Things. • Discusses powers predictive analysis, predictive maintenance, and automated processes for making manufacturing plants more efficient, profitable, and safe. • Explores the importance of blockchain technology in the Internet of Things security issues. • Discusses key deep learning concepts including trust management, identity management, security threats, access control, and privacy. • Showcases the importance of intelligent algorithms for cloud-based Internet of Things applications. This text emphasizes the importance of innovation and improving the profitability of manufacturing plants using smart technologies such as artificial intelligence, deep learning, and the Internet of Things. It further discusses applications of smart technologies in diverse sectors such as agriculture, smart home, production, manufacturing, transport, and healthcare.

Deep Learning Technologies For The Sustainable Development Goals

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Author : Virender Kadyan
language : en
Publisher: Springer Nature
Release Date : 2023-02-01

Deep Learning Technologies For The Sustainable Development Goals written by Virender Kadyan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-01 with Technology & Engineering categories.

This book provides insights into deep learning techniques that impact the implementation strategies toward achieving the Sustainable Development Goals (SDGs) laid down by the United Nations for its 2030 agenda, elaborating on the promises, limits, and the new challenges. It also covers the challenges, hurdles, and opportunities in various applications of deep learning for the SDGs. A comprehensive survey on the major applications and research, based on deep learning techniques focused on SDGs through speech and image processing, IoT, security, AR-VR, formal methods, and blockchain, is a feature of this book. In particular, there is a need to extend research into deep learning and its broader application to many sectors and to assess its impact on achieving the SDGs. The chapters in this book help in finding the use of deep learning across all sections of SDGs. The rapid development of deep learning needs to be supported by the organizational insight and oversight necessary for AI-based technologies in general; hence, this book presents and discusses the implications of how deep learning enables the delivery agenda for sustainable development.