Download or read book Machine Learning for Sustainable Development written by Kamal Kant Hiran and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-07-19 with total page 214 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Artificial Intelligence for Sustainable Development Theory Practice and Future Applications written by Aboul Ella Hassanien and published by Springer Nature. This book was released on 2020-08-31 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies written by Krishna Kumar and published by Academic Press. This book was released on 2022-03-18 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Artificial Intelligence and Machine Learning for Sustainable Development written by Pawan Whig and published by CRC Press. This book was released on 2024-12-18 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: AI and ML for Sustainable Development: Innovations, Challenges, and Applications is a comprehensive exploration of how artificial intelligence (AI) and machine learning (ML) technologies are revolutionizing the field of sustainable development.
Download or read book Artificial Intelligence for Sustainable Development written by Anandakumar Haldorai and published by Springer Nature. This book was released on with total page 492 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Digital Cities Roadmap written by Arun Solanki and published by John Wiley & Sons. This book was released on 2021-04-13 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: DIGITAL CITIES ROADMAP This book details applications of technology to efficient digital city infrastructure and its planning, including smart buildings. Rapid urbanization, demographic changes, environmental changes, and new technologies are changing the views of urban leaders on sustainability, as well as creating and providing public services to tackle these new dynamics. Sustainable development is an objective by which the processes of planning, implementing projects, and development is aimed at meeting the needs of modern communities without compromising the potential of future generations. The advent of Smart Cities is the answer to these problems. Digital Cities Roadmap provides an in-depth analysis of design technologies that lay a solid foundation for sustainable buildings. The book also highlights smart automation technologies that help save energy, as well as various performance indicators needed to make construction easier. The book aims to create a strong research community, to have a deep understanding and the latest knowledge in the field of energy and comfort, to offer solid ideas in the nearby future for sustainable and resilient buildings. These buildings will help the city grow as a smart city. The smart city has also a focus on low energy consumption, renewable energy, and a small carbon footprint. Audience The information provided in this book will be of value to researchers, academicians and industry professionals interested in IoT-based architecture and sustainable buildings, energy efficiency and various tools and methods used to develop green technologies for construction in smart cities.
Download or read book Data Science Applied to Sustainability Analysis written by Jennifer Dunn and published by Elsevier. This book was released on 2021-05-11 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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
Download or read book Machine Learning for Ecology and Sustainable Natural Resource Management written by Grant Humphries and published by Springer. This book was released on 2018-11-05 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ecologists and natural resource managers are charged with making complex management decisions in the face of a rapidly changing environment resulting from climate change, energy development, urban sprawl, invasive species and globalization. Advances in Geographic Information System (GIS) technology, digitization, online data availability, historic legacy datasets, remote sensors and the ability to collect data on animal movements via satellite and GPS have given rise to large, highly complex datasets. These datasets could be utilized for making critical management decisions, but are often “messy” and difficult to interpret. Basic artificial intelligence algorithms (i.e., machine learning) are powerful tools that are shaping the world and must be taken advantage of in the life sciences. In ecology, machine learning algorithms are critical to helping resource managers synthesize information to better understand complex ecological systems. Machine Learning has a wide variety of powerful applications, with three general uses that are of particular interest to ecologists: (1) data exploration to gain system knowledge and generate new hypotheses, (2) predicting ecological patterns in space and time, and (3) pattern recognition for ecological sampling. Machine learning can be used to make predictive assessments even when relationships between variables are poorly understood. When traditional techniques fail to capture the relationship between variables, effective use of machine learning can unearth and capture previously unattainable insights into an ecosystem's complexity. Currently, many ecologists do not utilize machine learning as a part of the scientific process. This volume highlights how machine learning techniques can complement the traditional methodologies currently applied in this field.
Download or read book Disruptive Technologies for Sustainable Development written by G. Nagappan and published by CRC Press. This book was released on 2024-06-07 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: We feel greatly honoured to have been assigned the job of organizing the AICTE Sponsored International Conference on Application of AI, ML, DL, Big Data on Recent Societal Issues (ICARSI’2023) on April 21 & April 22,2023 at Saveetha Engineering College. The international conference is a platform that brings together the brightest minds from across the globe to share their ideas and insights on the recent societal issues with Artificial intelligence, Machine Learning, Deep Learning, Big data and emerging technologies. With an aim to promote collaboration and foster innovation, this conference promises to be a melting pot of ideas and knowledge sharing.
Download or read book Sustainable Intelligent Systems written by Amit Joshi and published by Springer Nature. This book was released on 2021-03-06 with total page 282 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses issues related to ICT, intelligent systems, data science, AI, machine learning, sustainable development and overall their impacts on sustainability. It provides an overview of the technologies of future. The book also discusses novel intelligent algorithms and their applications to move from a data-centric world to sustainable world. It includes research paradigms on sustainable development goals and societal impacts. The book provides an overview of cutting-edge techniques toward sustainability and ideas to help researchers who want to understand the challenges and opportunities of using smart management perspective for sustainable society. It serves as a reference to wide ranges of readers from computer science, data analysts, AI technocrats and management researchers.
Download or read book Sustainable Development through Machine Learning AI and IoT written by Pawan Whig and published by Springer Nature. This book was released on 2023-12-20 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
Download or read book Sustainable Development through Machine Learning AI and IoT written by Pawan Whig and published by Springer Nature. This book was released on with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Artificial Intelligence for Smart and Sustainable Energy Systems and Applications written by Miltiadis D. Lytras and published by MDPI. This book was released on 2020-05-27 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: Energy has been a crucial element for human beings and sustainable development. The issues of global warming and non-green energy have yet to be resolved. This book is a collection of twelve articles that provide strong evidence for the success of artificial intelligence deployment in energy research, particularly research devoted to non-intrusive load monitoring, network, and grid, as well as other emerging topics. The presented artificial intelligence algorithms may provide insight into how to apply similar approaches, subject to fine-tuning and customization, to other unexplored energy research. The ultimate goal is to fully apply artificial intelligence to the energy sector. This book may serve as a guide for professionals, researchers, and data scientists—namely, how to share opinions and exchange ideas so as to facilitate a better fusion of energy, academic, and industry research, and improve in the quality of people's daily life activities.
Download or read book Computational Intelligent Data Analysis for Sustainable Development written by Ting Yu and published by CRC Press. This book was released on 2016-04-19 with total page 443 pages. Available in PDF, EPUB and Kindle. Book excerpt: Going beyond performing simple analyses, researchers involved in the highly dynamic field of computational intelligent data analysis design algorithms that solve increasingly complex data problems in changing environments, including economic, environmental, and social data. Computational Intelligent Data Analysis for Sustainable Development present
Download or read book Linking Aid to the Sustainable Development Goals a Machine Learning Approach written by Arnaud Pincet and published by . This book was released on 2019 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Deep Learning for Sustainable Agriculture written by Ramesh Chandra Poonia and published by Academic Press. This book was released on 2022-01-09 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: The evolution of deep learning models, combined with with advances in the Internet of Things and sensor technology, has gained more importance for weather forecasting, plant disease detection, underground water detection, soil quality, crop condition monitoring, and many other issues in the field of agriculture. agriculture. Deep Learning for Sustainable Agriculture discusses topics such as the impactful role of deep learning during the analysis of sustainable agriculture data and how deep learning can help farmers make better decisions. It also considers the latest deep learning techniques for effective agriculture data management, as well as the standards established by international organizations in related fields. The book provides advanced students and professionals in agricultural science and engineering, geography, and geospatial technology science with an in-depth explanation of the relationship between agricultural inference and the decision-support amenities offered by an advanced mathematical evolutionary algorithm. Introduces new deep learning models developed to address sustainable solutions for issues related to agriculture Provides reviews on the latest intelligent technologies and algorithms related to the state-of-the-art methodologies of monitoring and mitigation of sustainable agriculture Illustrates through case studies how deep learning has been used to address a variety of agricultural diseases that are currently on the cutting edge Delivers an accessible explanation of artificial intelligence algorithms, making it easier for the reader to implement or use them in their own agricultural domain
Download or read book Sustainable Development in AI Blockchain and E Governance Applications written by Kumar, Rajeev and published by IGI Global. This book was released on 2024-02-09 with total page 295 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the age of immediate technical expansion, our world faces a multifaceted challenge: ensuring the sustainability of our digital transformation. Governments and organizations have wholeheartedly embraced innovative technologies such as artificial intelligence, blockchain, and e-governance, but in doing so, they have encountered a complex web of issues. These range from cybersecurity concerns in an increasingly digitalized world to the need for intelligent systems capable of managing automation infrastructure and interconnected environments. Sustainable Development in AI, Blockchain, and E-Governance Applications offers a forward-thinking approach that harnesses the synergy between intelligent systems, machine learning, deep learning, and blockchain methods. It explores data-driven decision-making, automation infrastructure, autonomous transportation, and the creation of connected buildings, all aimed at crafting a sustainable digital future. By delving into topics like machine learning for smart parking, disease classification through neural networks, and the Internet of Things (IoT) for smarter cities, this book equips academic scholars with the tools they need to navigate the complex terrain of technology and governance. Academic scholars and researchers in technology, governance, and sustainability will find this book to be an indispensable resource. It caters to those seeking a comprehensive understanding of current and future trends in the integration of intelligent systems with cybersecurity applications.
