Artificial Intelligence For Sustainable Development
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Author |
: Aboul Ella Hassanien |
Publisher |
: Springer Nature |
Total Pages |
: 310 |
Release |
: 2020-08-31 |
ISBN-10 |
: 9783030519209 |
ISBN-13 |
: 3030519201 |
Rating |
: 4/5 (09 Downloads) |
Synopsis Artificial Intelligence for Sustainable Development: Theory, Practice and Future Applications by : Aboul Ella Hassanien
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 |
: Henrik Skaug Sætra |
Publisher |
: CRC Press |
Total Pages |
: 121 |
Release |
: 2022-02-23 |
ISBN-10 |
: 9781000542813 |
ISBN-13 |
: 1000542815 |
Rating |
: 4/5 (13 Downloads) |
Synopsis AI for the Sustainable Development Goals by : Henrik Skaug Sætra
What is artificial intelligence? What are the Sustainable Development Goals (SDGs)? How does AI affect the SDGs? Artificial Intelligence has a real impact on our lives and on our environment, and the Sustainable Development Goals enable us to evaluate these impacts in a systematic manner. This book shows that doing so requires us to understand the context of AI – the infrastructure it is built on, who develops it, who owns it, who has access to it, who uses it, and what it is used for – rather than relying on an isolationist theory of technology. By doing so, we can analyze not only the direct effects of AI on sustainability, but also the indirect – or second-order – effects. AI for the Sustainable Development Goals shows how AI potentially affects all SDGs – both positively and negatively.
Author |
: Krishna Kumar |
Publisher |
: Academic Press |
Total Pages |
: 418 |
Release |
: 2022-03-18 |
ISBN-10 |
: 9780323914284 |
ISBN-13 |
: 0323914284 |
Rating |
: 4/5 (84 Downloads) |
Synopsis Sustainable Developments by Artificial Intelligence and Machine Learning for Renewable Energies by : Krishna Kumar
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 |
Total Pages |
: 214 |
Release |
: 2021-07-19 |
ISBN-10 |
: 9783110702514 |
ISBN-13 |
: 3110702517 |
Rating |
: 4/5 (14 Downloads) |
Synopsis Machine Learning for Sustainable Development by : Kamal Kant Hiran
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 |
: Zakaria Boulouard |
Publisher |
: Springer Nature |
Total Pages |
: 638 |
Release |
: 2022-01-31 |
ISBN-10 |
: 9783030906184 |
ISBN-13 |
: 3030906183 |
Rating |
: 4/5 (84 Downloads) |
Synopsis AI and IoT for Sustainable Development in Emerging Countries by : Zakaria Boulouard
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 |
: Abdalmuttaleb M. A. Musleh Al-Sartawi |
Publisher |
: Springer Nature |
Total Pages |
: 637 |
Release |
: 2022-01-01 |
ISBN-10 |
: 9783030934644 |
ISBN-13 |
: 3030934640 |
Rating |
: 4/5 (44 Downloads) |
Synopsis Artificial Intelligence for Sustainable Finance and Sustainable Technology by : Abdalmuttaleb M. A. Musleh Al-Sartawi
This book shows latest research on artificial intelligence for sustainable technology. ICGER 2021 was organized by the Accounting, Finance and Banking Department at Ahlia University, Bahrain, and was conducted on the 15th and 16th of September. The strategic partners included the University of Jordan, the Bahrain Economists Society, the Association of Chartered Certified Accountants: ACCA, Al-Barka Banking Group and the International Computer Auditing Education Association: ICAEA . The theme of the ICGER 2021 centered around artificial intelligence for sustainable finance and sustainable technology. Accordingly, the papers presented at the conference provided a holistic view of sustainable finance, sustainability, AI, financial technology, cybersecurity, blockchain, CSR, and governance. This book, unlike ever before, brings together intelligence applications of new technologies and the sustainability requirements in the era of the digital economy, with special attention given to the opportunities, challenges, for education, business growth, and economic progression of nations which will help societies (economists, financial managers, engineers, ICT specialists, digital managers, data managers, policymakers, regulators, researchers, academics, and students) to better understand, use, and control AI applications and financial technologies to develop future strategies and to achieve sustainable development goals.
Author |
: Adam Bohr |
Publisher |
: Academic Press |
Total Pages |
: 385 |
Release |
: 2020-06-21 |
ISBN-10 |
: 9780128184394 |
ISBN-13 |
: 0128184396 |
Rating |
: 4/5 (94 Downloads) |
Synopsis Artificial Intelligence in Healthcare by : Adam Bohr
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 |
: Peter Dauvergne |
Publisher |
: MIT Press |
Total Pages |
: 278 |
Release |
: 2020-09-15 |
ISBN-10 |
: 9780262359580 |
ISBN-13 |
: 0262359588 |
Rating |
: 4/5 (80 Downloads) |
Synopsis AI in the Wild by : Peter Dauvergne
Examining the potential benefits and risks of using artificial intelligence to advance global sustainability. Drones with night vision are tracking elephant and rhino poachers in African wildlife parks and sanctuaries; smart submersibles are saving coral from carnivorous starfish on Australia's Great Barrier Reef; recycled cell phones alert Brazilian forest rangers to the sound of illegal logging. The tools of artificial intelligence are being increasingly deployed in the battle for global sustainability. And yet, warns Peter Dauvergne, we should be cautious in declaring AI the planet's savior. In AI in the Wild, Dauvergne avoids the AI industry-powered hype and offers a critical view, exploring both the potential benefits and risks of using artificial intelligence to advance global sustainability.
Author |
: Ghislain Landry Tsafack Chetsa |
Publisher |
: Apress |
Total Pages |
: 140 |
Release |
: 2021-08-14 |
ISBN-10 |
: 1484272137 |
ISBN-13 |
: 9781484272138 |
Rating |
: 4/5 (37 Downloads) |
Synopsis Towards Sustainable Artificial Intelligence by : Ghislain Landry Tsafack Chetsa
So far, little effort has been devoted to developing practical approaches on how to develop and deploy AI systems that meet certain standards and principles. This is despite the importance of principles such as privacy, fairness, and social equality taking centre stage in discussions around AI. However, for an organization, failing to meet those standards can give rise to significant lost opportunities. It may further lead to an organization’s demise, as the example of Cambridge Analytica demonstrates. It is, however, possible to pursue a practical approach for the design, development, and deployment of sustainable AI systems that incorporates both business and human values and principles. This book discusses the concept of sustainability in the context of artificial intelligence. In order to help businesses achieve this objective, the author introduces the sustainable artificial intelligence framework (SAIF), designed as a reference guide in the development and deployment of AI systems. The SAIF developed in the book is designed to help decision makers such as policy makers, boards, C-suites, managers, and data scientists create AI systems that meet ethical principles. By focusing on four pillars related to the socio-economic and political impact of AI, the SAIF creates an environment through which an organization learns to understand its risk and exposure to any undesired consequences of AI, and the impact of AI on its ability to create value in the short, medium, and long term. What You Will Learn See the relevance of ethics to the practice of data science and AI Examine the elements that enable AI within an organization Discover the challenges of developing AI systems that meet certain human or specific standards Explore the challenges of AI governance Absorb the key factors to consider when evaluating AI systems Who This Book Is For Decision makers such as government officials, members of the C-suite and other business managers, and data scientists as well as any technology expert aspiring to a data-related leadership role.
Author |
: Yo-Ping Huang |
Publisher |
: Springer Nature |
Total Pages |
: 655 |
Release |
: 2020-10-27 |
ISBN-10 |
: 9783030623241 |
ISBN-13 |
: 3030623246 |
Rating |
: 4/5 (41 Downloads) |
Synopsis Computational Intelligence Methods for Green Technology and Sustainable Development by : Yo-Ping Huang
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.