Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies PDF Download
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Author: Krishna Kumar
Publisher: Elsevier
ISBN: 0323912281
Category : Science
Languages : en
Pages : 416
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Book Description
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum Addresses the advanced field of renewable generation, from research, impact and idea development of new applications
Author: Krishna Kumar
Publisher: Elsevier
ISBN: 0323912281
Category : Science
Languages : en
Pages : 416
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Book Description
Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies analyzes the changes in this energy generation shift, including issues of grid stability with variability in renewable energy vs. traditional baseload energy generation. Providing solutions to current critical environmental, economic and social issues, this book comprises various complex nonlinear interactions among different parameters to drive the integration of renewable energy into the grid. It considers how artificial intelligence and machine learning techniques are being developed to produce more reliable energy generation to optimize system performance and provide sustainable development. As the use of artificial intelligence to revolutionize the energy market and harness the potential of renewable energy is essential, this reference provides practical guidance on the application of renewable energy with AI, along with machine learning techniques and capabilities in design, modeling and for forecasting performance predictions for the optimization of renewable energy systems. It is targeted at researchers, academicians and industry professionals working in the field of renewable energy, AI, machine learning, grid Stability and energy generation. Covers the best-performing methods and approaches for designing renewable energy systems with AI integration in a real-time environment Gives advanced techniques for monitoring current technologies and how to efficiently utilize the energy grid spectrum Addresses the advanced field of renewable generation, from research, impact and idea development of new applications
Author: Kamal Kant Hiran
Publisher: Walter de Gruyter GmbH & Co KG
ISBN: 3110702517
Category : Computers
Languages : en
Pages : 216
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Book Description
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.
Author: Aboul Ella Hassanien
Publisher: Springer Nature
ISBN: 3030519201
Category : Technology & Engineering
Languages : en
Pages : 310
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Book Description
This book highlights the latest advances in the field of artificial intelligence and related technologies, with a special focus on sustainable development and environmentally friendly artificial intelligence applications. Discussing theory, applications and research, it covers all aspects of artificial intelligence in the context of sustainable development.
Author: Pawan Whig
Publisher: CRC Press
ISBN: 1040228771
Category : Computers
Languages : en
Pages : 287
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Book Description
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.
Author: Adam Bohr
Publisher: Academic Press
ISBN: 0128184396
Category : Computers
Languages : en
Pages : 385
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Book Description
Artificial Intelligence (AI) in Healthcare is more than a comprehensive introduction to artificial intelligence as a tool in the generation and analysis of healthcare data. The book is split into two sections where the first section describes the current healthcare challenges and the rise of AI in this arena. The ten following chapters are written by specialists in each area, covering the whole healthcare ecosystem. First, the AI applications in drug design and drug development are presented followed by its applications in the field of cancer diagnostics, treatment and medical imaging. Subsequently, the application of AI in medical devices and surgery are covered as well as remote patient monitoring. Finally, the book dives into the topics of security, privacy, information sharing, health insurances and legal aspects of AI in healthcare. - Highlights different data techniques in healthcare data analysis, including machine learning and data mining - Illustrates different applications and challenges across the design, implementation and management of intelligent systems and healthcare data networks - Includes applications and case studies across all areas of AI in healthcare data
Author: Nitin Liladhar Rane
Publisher: Deep Science Publishing
ISBN: 8198127186
Category : Computers
Languages : en
Pages : 185
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Book Description
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.
Author: Zakaria Boulouard
Publisher: Springer Nature
ISBN: 3030906183
Category : Technology & Engineering
Languages : en
Pages : 638
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Book Description
This book comprises a number of state-of-the-art contributions from both scientists and practitioners working in a large pool of fields where AI and IoT can open up new horizons. Artificial intelligence and Internet of Things have introduced themselves today as must-have technologies in almost every sector. Ranging from agriculture to industry and health care, the scope of applications of AI and IoT is as wide as the horizon. Nowadays, these technologies are extensively used in developed countries, but they are still at an early stage in emerging countries. AI and IoT for Sustainable Development in Emerging Countries—Challenges and Opportunities is an invaluable source to dive into the latest applications of AI and IoT and how they have been used by researchers from emerging countries to solve sustainable development-related issues by taking into consideration the specifities of their countries. This book starts by presenting how AI and IoT can tackle the challenges of sustainable development in general and then focuses on the following axes: · AI and IoT for smart environment and energy · Industry 4.0 and intelligent transportation · A vision towards an artificial intelligence of medical things · AI, social media, and big data analytics. It aspires to provide a relevant reference for students, researchers, engineers, and professionals working in these particular areas or those interested in grasping its diverse facets and exploring the latest advances on their respective fields and the role of AI and IoT in them.
Author: Jennifer Dunn
Publisher: Elsevier
ISBN: 0128179775
Category : Science
Languages : en
Pages : 312
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Book Description
Data Science Applied to Sustainability Analysis focuses on the methodological considerations associated with applying this tool in analysis techniques such as lifecycle assessment and materials flow analysis. As sustainability analysts need examples of applications of big data techniques that are defensible and practical in sustainability analyses and that yield actionable results that can inform policy development, corporate supply chain management strategy, or non-governmental organization positions, this book helps answer underlying questions. In addition, it addresses the need of data science experts looking for routes to apply their skills and knowledge to domain areas. - Presents data sources that are available for application in sustainability analyses, such as market information, environmental monitoring data, social media data and satellite imagery - Includes considerations sustainability analysts must evaluate when applying big data - Features case studies illustrating the application of data science in sustainability analyses
Author: Yo-Ping Huang
Publisher: Springer Nature
ISBN: 3030623246
Category : Technology & Engineering
Languages : en
Pages : 655
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Book Description
This book is a selected collection of 54 peer-reviewed original scientific research papers of the 5th International Conference on Green Technology and Sustainable Development (GTSD2020) organised in Vietnam in 2020. It highlights the importance of sustainability as well as promotes up-to-date innovation and research for green development in technologies, economics and education among countries. The conference provides an international platform for researchers, practitioners, policymakers and entrepreneurs to present their advances, knowledge and experience on various interdisciplinary topics related to the theme of “Green technology and sustainable development in industrial revolution 4.0”. The book is a valuable resource for researchers, analysts, engineers, practitioners and policymakers who are interested in the latest findings in artificial intelligence, cyber systems, robotics, green energy and power systems, mechanical and computational mechanic models and advanced civil engineering. This book has 05 sessions consisting of both theoretical and practical aspects, and numerical and experimental analyses in various engineering disciplines.
Author: Pardeep Kumar
Publisher: John Wiley & Sons
ISBN: 1119761646
Category : Technology & Engineering
Languages : en
Pages : 484
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Book Description
The Smart Cyber Ecosystem for Sustainable Development As the entire ecosystem is moving towards a sustainable goal, technology driven smart cyber system is the enabling factor to make this a success, and the current book documents how this can be attained. The cyber ecosystem consists of a huge number of different entities that work and interact with each other in a highly diversified manner. In this era, when the world is surrounded by many unseen challenges and when its population is increasing and resources are decreasing, scientists, researchers, academicians, industrialists, government agencies and other stakeholders are looking toward smart and intelligent cyber systems that can guarantee sustainable development for a better and healthier ecosystem. The main actors of this cyber ecosystem include the Internet of Things (IoT), artificial intelligence (AI), and the mechanisms providing cybersecurity. This book attempts to collect and publish innovative ideas, emerging trends, implementation experiences, and pertinent user cases for the purpose of serving mankind and societies with sustainable societal development. The 22 chapters of the book are divided into three sections: Section I deals with the Internet of Things, Section II focuses on artificial intelligence and especially its applications in healthcare, whereas Section III investigates the different cyber security mechanisms. Audience This book will attract researchers and graduate students working in the areas of artificial intelligence, blockchain, Internet of Things, information technology, as well as industrialists, practitioners, technology developers, entrepreneurs, and professionals who are interested in exploring, designing and implementing these technologies.
