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Machine Learning For Sustainable Development

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Machine Learning For Sustainable Development

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Author : Kamal Kant Hiran
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-07-19

Machine Learning For Sustainable Development written by Kamal Kant Hiran and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-19 with Computers categories.

The book will focus on the applications of machine learning for sustainable development. Machine learning (ML) is an emerging technique whose diffusion and adoption in various sectors (such as energy, agriculture, internet of things, infrastructure) will be of enormous benefit. The state of the art of machine learning models is most useful for forecasting and prediction of various sectors for sustainable development.

Machine Learning For Sustainable Development

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Author : Kamal Kant Hiran
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2021-07-19

Artificial Intelligence And Machine Learning For Sustainable Development

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Author : Pawan Whig
language : en
Publisher: CRC Press
Release Date : 2024-12-18

Artificial Intelligence And Machine Learning For Sustainable Development written by Pawan Whig and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-12-18 with Computers categories.

Artificial Intelligence and Machine Learning for Sustainable Development is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development. The book examines cutting-edge innovations, practical applications, and potential challenges in harnessing AI and ML to address global sustainability issues. It offers insights into how these technologies can optimize resource management, improve environmental monitoring, enhance decision-making processes, and promote equitable, eco-friendly solutions. This book would be of special interest to researchers, policymakers, and practitioners seeking to leverage cutting-edge technology for a more sustainable future.

Artificial Intelligence Machine Learning And Deep Learning For Sustainable Industry 5 0

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Author : Nitin Liladhar Rane
language : en
Publisher: Deep Science Publishing
Release Date : 2024-10-14

Artificial Intelligence Machine Learning And Deep Learning For Sustainable Industry 5 0 written by Nitin Liladhar Rane and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-14 with Computers categories.

This book offers an insight into the applications of Artificial Intelligence (AI)- Machine Learning Algorithms and Deep Learning (DL) in Bigdata Analytics to Industry 4.0/5.0 and Society 5.0 with transformative power responsibly. It has delved into how these technologies are disrupting industries, fostering innovation, and solving age-old social problems-so that readers have an understanding of where the digital world is headed. These chapters cover the big picture subjects of using AI with Big data analytics aimed mostly at increasing industrial efficiency, healthcare optimization, retail transformation, construction industry transformation, autonomous vehicles development and environmental sustainability improvement. The book covers each of these technologies extensively applied to full chapters devoted to detail studies, methodologies and practical usages. One of the central concepts in the book is how we evolve from industry 4.0 to industry 5.0. Therefore, Industry 4.0 relies on the automation and data exchange in manufacturing technologies using cyber-physical systems, the Internet of Things and cloud computing route to intelligent factories. During this phase, it improves operational efficiency, predictive maintenance and real-time monitoring which lowers down time and other operating costs by considerable amount. As industries move towards Industry 5.0, a lot has been noted-human-oriented solutions that combine human creativity and intelligence with highly automated and distributed technological tools. More cooperation between humans and machines during such times will, therefore, result in more customized production aimed at sustainable processes. The book details how, thanks to digital twins-that is, innumerable virtual replicas of physical systems-the further step is taken, allowing for real-time data analysis and, consequently innovative ways of manufacturing where the interests of the workers and customers come first. The present book discusses how AI and big data analytics transcend industrial applications to meet more societal ends as society ushers in its fifth revolution. Society 5.0 postulates that a super-smart digital society will drive transformation in all aspects of life, ranging from health and education to planning urban resources and infrastructure and ensuring public safety. The combination of AI with Big Data makes personalized healthcare services possible, competent resource planning in cities, and environmental sustainability in place via predictive analytics or simulation models. One such industry in which significant changes are coming, according to AI and Big Data analytics, is healthcare. This book shows how these technologies improve diagnostic accuracy, enable personalized treatment plans, and optimize resource allocations. Predictive insights can predict outbreaks and admissions, which helps better preparedness against diseases and also optimizes health resource utilization. AI in medical imaging and anomaly detection strengthens the efficiency of professional health experts, thus delivering better patient outcomes. AI and big data analytics have further remodelled the retail industry by providing retailers profound insights into consumer behaviour and preferences. With this information, retailers can adopt person-segmented marketing techniques and optimize inventory levels while enabling high levels of customer service using AI-fuelled chatbots and virtual assistants. These technologies help retailers stay competitive in an ever-developing market environment by offering solutions structured based on individual needs expressed by customers. AI and big data analytics combine to form one synergy connected with autonomous vehicles. It further goes on to discuss the huge amount of data needed for training these AI models and big data analytics in refining the accuracy and safety of autonomous driving systems. Another critical area in which AI and Big Data Analytics make a considerable impact is environmental sustainability. By applying these analyses to large data sets relating to climatic changes, energy consumption, and natural resources, AI models can establish trends and recognize patterns indicating future changes. This predictive ability equips organizations and governments with tools to develop lower environmental footprints and promote sustainable practices proactively. It further explains AI-enabled energy management systems that drive optimized energy use in buildings to reduce carbon emissions and save on associated costs. This certainly looks like something for a vast readership: it speaks more to academics, professionals working in the industry, and decision-makers-but, really, to anybody who seeks to grasp the transformative powerfulness of AI and big data analytics. This source will provide information on overall guidance and a rich source of inspiration in using these technologies to enable innovation and sustainable development across different sectors. Actual case examples and practical applications are given to convey the knowledge and elements that readers need to know as they go about using AI and big data analytics. This book also includes discussions concerning the dynamic policy and regulatory scenes of AI, pointing out that it is necessary to have standard policies that should be implemented to have ethical deployment of AI that reduces risks. This book also focuses on challenges in implementing AI for intelligent and sustainable industries, meaning technical, ethical, and operational barriers. It outlines high costs, low-quality data, and the need for skilled professionals; ethical concerns and robust cybersecurity measures become necessary. As such, this book will engross an audience ranging from academics to industry professionals and policymakers working toward understanding and using AI and big data for sustainable development and technological advancement.

Artificial Intelligence And Machine Learning Applications For Sustainable Development

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Author : A. J. Singh
language : en
Publisher: CRC Press
Release Date : 2025-01-28

Artificial Intelligence And Machine Learning Applications For Sustainable Development written by A. J. Singh and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-01-28 with Technology & Engineering categories.

The book highlights how technologies including artificial intelligence and machine learning are transforming renewable energy technologies and enabling the development of new solutions. It further discusses how smart technologies are employed to optimize energy production and storage, enhance energy efficiency, and improve the overall sustainability of energy systems. This book: Discusses artificial intelligence-based techniques, namely, neural networks, fuzzy expert systems, optimization techniques, and operational research Showcases the importance of artificial intelligence and machine learning in the energy market, demand analysis, and forecasting of renewable energy applications Illustrates strategies for sustainable development using artificial intelligence and machine learning applications Presents applications of artificial intelligence in the domain of electronics transformation and development, smart cities, and renewable energy utilization Highlights the role of artificial intelligence in solving problems such as image and signal processing, smart weather monitoring, smart farming, and distributed energy sources It is primarily written for senior undergraduates, graduate students, and academic researchers in diverse fields, including electrical, electronics and communications, energy, and environmental engineering.

Sustainable Development Through Machine Learning Ai And Iot

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Author : Pawan Whig
language : en
Publisher: Springer Nature
Release Date : 2023-11-18

Sustainable Development Through Machine Learning Ai And Iot written by Pawan Whig and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-18 with Computers categories.

This book constitutes the revised selected papers of the First International Conference, ICSD 2023, virtually held in Delhi, India, during July 15–16, 2023. The book comprises 31 full papers that were selected from a total of 129 submissions. It provides insights into the latest research and advancements in sustainable development through the integration of machine learning, artificial intelligence, and IoT technologies. It serves as a valuable resource for researchers, practitioners, and policymakers working in the field of sustainable development.

Sustainable Development Through Machine Learning Ai And Iot

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Author : Pawan Whig
language : en
Publisher: Springer Nature
Release Date : 2024-09-24

This book constitutes the refereed proceedings of the Second International Conference on Sustainable Development through Machine Learning, AI and IoT, ICSD 2024, held in Virtual Event, during April 27–28, 2024. The 38 full papers presented here were carefully reviewed and selected from 167 submissions. These papers have been categorized into the following sections: This volume encompassing a diverse array of topics at the intersection of cutting-edge technologies and practical applications. Each chapter delves into innovative approaches and solutions, providing valuable insights into contemporary challenges and opportunities in various domains. Here, we explore the realms of blockchain, data science, machine learning, artificial intelligence, and more, offering in-depth analyses and practical implementations.

Machine And Deep Learning Solutions For Achieving The Sustainable Development Goals

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Author : Ruiz-Vanoye, Jorge A.
language : en
Publisher: IGI Global
Release Date : 2025-03-07

Machine And Deep Learning Solutions For Achieving The Sustainable Development Goals written by Ruiz-Vanoye, Jorge A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-07 with Computers categories.

Achieving the United Nations' Sustainable Development Goals (SDGs) requires innovative solutions that address global challenges such as climate change, poverty, and social inequality. Artificial intelligence (AI), machine learning, and data-driven technologies offer transformative potential by optimizing resource management, improving healthcare outcomes, and enhancing decision-making processes. However, integrating AI into sustainable development efforts presents ethical, technical, and policy-related challenges that must be carefully navigated. A multidisciplinary approach is essential to ensure these technologies are applied inclusively and responsibly, maximizing their positive societal impact. Machine and Deep Learning Solutions for Achieving the Sustainable Development Goals enhances understanding and application of machine learning, deep learning, data mining and AI technologies in the context of the SDGs. It fills the gap by linking theory and practice and addresses both the opportunities and challenges inherent in this intersection. Covering topics such as demand side management, agricultural productivity, and smart manufacturing, this book is an excellent resource for engineers, computer scientists, practitioners, policymakers, professionals, researchers, scholars, academicians, and more.

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.

Harnessing Automation And Machine Learning For Resource Recovery And Value Creation

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Author : Kishor Kumar Sadasivuni
language : en
Publisher: Elsevier
Release Date : 2025-03-31

Harnessing Automation And Machine Learning For Resource Recovery And Value Creation written by Kishor Kumar Sadasivuni and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-31 with Technology & Engineering categories.

Harnessing Automation and Machine Learning for Resource Recovery and Value Creation: From Waste to Value provides a comprehensive understanding of how automation and machine learning technologies can be used to convert waste into valuable resources. This book gives insight in the opportunities offered by automation and machine learning technologies in waste management and how they can help address the challenges associated with waste management and to discuss the benefits and potential of automation technologies. It examines the potential of machine learning algorithms in analyzing waste management data, identifying patterns, predicting future waste generation, and optimizing waste management processes. Moreover, this book showcases case studies from different industries and regions, highlighting the revolutionary applications of automation and machine learning in waste management. This book is an indispensable resource for researchers, waste management professionals, and policymakers interested in learning more about how automation and machine learning can contribute to waste management and the creation of a sustainable future. - Provides insights into the potential of automation and machine learning in waste management inspiring readers to adopt sustainable waste management practices - Offers a comprehensive understanding of how waste management can be transformed into a profitable business by adopting innovative and sustainable solutions - Offers an opportunity to explore case studies from different industries and regions to showcase the revolutionary applications of automation and machine learning in waste management - Provides guidance for waste management professionals, policymakers, and business leaders to optimize waste management processes and improve their bottom line

Machine Learning For Sustainable Development

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