Artificial Intelligence And Data Science For Sustainability
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Artificial Intelligence And Data Science For Sustainability Applications And Methods
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Author : Syafrudin, Muhammad
language : en
Publisher: IGI Global
Release Date : 2025-02-07
Artificial Intelligence And Data Science For Sustainability Applications And Methods written by Syafrudin, Muhammad and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-07 with Computers categories.
The integration of artificial intelligence (AI) and data science (DS) into sustainability efforts is increasingly crucial as the world faces environmental and resource challenges. By leveraging advanced AI and DS techniques, we can create innovative solutions for sectors like energy, agriculture, and waste management, promoting long-term sustainability. These technologies have the potential to optimize processes, reduce environmental footprints, and support smarter decision-making across industries. Ultimately, AI and DS are key to advancing both the efficiency and impact of sustainability efforts, contributing to a more sustainable future for society at large. Artificial Intelligence and Data Science for Sustainability: Applications and Methods explores the application of AI and DS techniques and methodologies in addressing various sustainability challenges. It brings together cutting-edge research, case studies, and practical applications that demonstrate how AI can be leveraged to promote sustainable development across diverse domains. Covering topics such as structural optimization, drone imagery, and development financing, this book is an excellent resource for computer scientists, computer engineers, urban planners, sustainability professionals, government officials, policymakers, researchers, professionals, scholars, academicians, and more.
Artificial Intelligence For A More Sustainable Oil And Gas Industry And The Energy Transition
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Author : Mohammadali Ahmadi
language : en
Publisher: Elsevier
Release Date : 2024-07-13
Artificial Intelligence For A More Sustainable Oil And Gas Industry And The Energy Transition written by Mohammadali Ahmadi and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-13 with Technology & Engineering categories.
Artificial Intelligence for a More Sustainable Oil and Gas Industry and the Energy Transition: Case Studies and Code Examples presents a package for academic researchers and industries working on water resources and carbon capture and storage. This book contains fundamental knowledge on artificial intelligence related to oil and gas sustainability and the industry's pivot to support the energy transition and provides practical applications through case studies and coding flowcharts, addressing gaps and questions raised by academic and industrial partners, including energy engineers, geologists, and environmental scientists. This timely publication provides fundamental and extensive information on advanced AI applications geared to support sustainability and the energy transition for the oil and gas industry. - Reviews the use and applications of AI in energy transition of the oil and gas sectors - Provides fundamental knowledge and academic background of artificial intelligence, including practical applications with real-world examples and coding flowcharts - Showcases the successful implementation of AI in the industry (including geothermal energy)
Artificial Intelligence And Information Technologies
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Author : Arvind Dagur
language : en
Publisher: CRC Press
Release Date : 2024-07-31
Artificial Intelligence And Information Technologies written by Arvind Dagur and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Computers categories.
This book contains the proceedings of a non-profit conference with the objective of providing a platform for academicians, researchers, scholars and students from various institutions, universities and industries in India and abroad to exchange their research and innovative ideas in the field of Artificial Intelligence and information technologies. It begins with exploring the research and innovation in the field of Artificial Intelligence and information technologies, including secure transaction, monitoring, real time assistance and security for advanced stage learners, researchers and academicians has been presented. It goes on to cover: Broad knowledge and research trends about Artificial Intelligence and information technologies and their role in today’s digital era Depiction of system model and architecture for clear picture of Artificial Intelligence in real life Discussion on the role of Artificial Intelligence in various real-life problems such as banking, healthcare, navigation, communication and security Explanation of the challenges and opportunities in Artificial Intelligence-based healthcare, education, banking and related industries Recent information technologies and challenges in this new epoch This book will be beneficial to researchers, academicians, undergraduate students, postgraduate students, research scholars, professionals, technologists and entrepreneurs.
Artificial Intelligence And Sustainability
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Author : Mohamed Ahmed Alloghani
language : en
Publisher: Springer Nature
Release Date : 2023-11-25
Artificial Intelligence And Sustainability written by Mohamed Ahmed Alloghani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-25 with Technology & Engineering categories.
This book gives readers the tools to craft AI systems that don't just thrive today, but endure sustainably into the future. Whether a trailblazer or an aspiring innovator, this book enables readers to resonate with the ambitions of software developers, data scientists, and AI practitioners. The author covers the latest techniques and best practices for energy efficiency, reducing carbon footprints, and ensuring fair and ethical AI. The book also addresses important issues such as AI governance, managing risks, and ensuring transparency. Topics covered include understanding the relationship between AI and sustainable development, strategies for building efficient AI systems, and ethical considerations in AI development, among others. The author includes case studies of companies and organizations that have successfully implemented sustainable AI software development practices. Therefore, this book will be of interest to AI practitioners, academics, researchers, and lecturers in computer science, artificial intelligence, machine learning and data sciences.
Artificial Intelligence Driven Models For Environmental Management
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Author : Shrikaant Kulkarni
language : en
Publisher: John Wiley & Sons
Release Date : 2025-08-19
Artificial Intelligence Driven Models For Environmental Management written by Shrikaant Kulkarni 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 2025-08-19 with Science categories.
Step-by-step guidelines for the development of artificial neural network-based environmental pollution models Artificial Intelligence-Driven Models for Environmental Management delves into the application of AI across a plethora of areas in environmental management, including climate forecasting, natural resource optimization, waste management, and biodiversity conservation. This book shows how AI can help in monitoring, predicting, and mitigating environmental impacts with tremendous accuracy and speed by leveraging machine learning, deep learning, and other data-driven models. The methodologies explored in this volume reflect a synthesis of computational intelligence, data science, and ecological expertise, underscoring how AI-driven systems have been making strides in managing and preserving our planet's natural resources. The text is structured to guide readers through numerous AI models and their practical environmental management applications, showcasing theoretical foundations as well as case studies. This book also addresses the challenges and ethical considerations related to deploying AI in ecological contexts, underscoring the importance of transparency, inclusivity, and alignment with sustainability goals. Sample topics discussed in Artificial Intelligence-Driven Models for Environmental Management include: Tools and methods for monitoring and predicting environmental pollutants faster and more accurately AI technology for the protection of water supplies from contamination to produce healthier foods Use of AI for the evaluation of the impacts of environmental pollution on human health AI and waste management technologies for sustainable agriculture and soil management The role of AI in environmental research and sustainability and key social and economic aspects of natural resource management through AI Artificial Intelligence-Driven Models for Environmental Management is a timely, forward-thinking resource for a diverse readership, including researchers, policymakers, environmental scientists, and AI practitioners.
Data Science Applied To Sustainability Analysis
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Author : Jennifer Dunn
language : en
Publisher: Elsevier
Release Date : 2021-05-11
Data Science Applied To Sustainability Analysis written by Jennifer Dunn and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-05-11 with Science categories.
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
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 Data Science And Applications
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Author : Yousef Farhaoui
language : en
Publisher: Springer Nature
Release Date : 2024-03-04
Artificial Intelligence Data Science And Applications written by Yousef Farhaoui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-03-04 with Computers categories.
This book is to provide a comprehensive reference for professionals in the field of data science and applications: artificial intelligence, big data, IoT, and blockchain. In summary, this book is expected to function as a helpful resource and manual, enabling readers to navigate the intricate domain of artificial intelligence, the Internet of things (IoT), and blockchain in smart environments. This book covers many topics related to integrating AI, IoT, blockchain, and smart environments. It begins by laying a solid foundation, introducing each technology's fundamental concepts and principles. Subsequent chapters explore applications and real-world use cases, demonstrating how AI, IoT, and blockchain can effectively address critical challenges within data science and applications.
Intersection Of Artificial Intelligence Data Science And Cutting Edge Technologies From Concepts To Applications In Smart Environment
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Author : Yousef Farhaoui
language : en
Publisher: Springer Nature
Release Date : 2025-05-02
Intersection Of Artificial Intelligence Data Science And Cutting Edge Technologies From Concepts To Applications In Smart Environment written by Yousef Farhaoui and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-02 with Computers categories.
This book explores the integration of AI, data science, and emerging technologies to create innovative, practical solutions for smart environments. This book offers a comprehensive framework that combines theoretical concepts with real-world applications, focusing on how these technologies intersect to transform various domains such as healthcare, urban planning, and sustainable development. The book's novel approach emphasizes interdisciplinary methods and problem-solving in dynamic, data-driven environments, with case studies illustrating practical impacts and advancements in smart city infrastructure, IoT, and predictive analytics. It is designed for researchers, practitioners, and advanced students interested in AI and data science applications within smart systems, as well as professionals seeking actionable insights to apply these technologies in complex environments.
Artificial Intelligence And Machine Learning In Management Science Emerging Research And Applications
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Author : Ms. Meenu Shukla
language : en
Publisher: NC Publishers
Release Date : 2025-07-01
Artificial Intelligence And Machine Learning In Management Science Emerging Research And Applications written by Ms. Meenu Shukla and has been published by NC Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Antiques & Collectibles categories.
As the global business environment continues to evolve, artificial intelligence (AI) and machine learning (ML) have emerged as powerful tools for enhancing decision-making, optimizing operations, and fostering innovation across various sectors. This book brings together a collection of scholarly contributions from researchers and practitioners who are at the forefront of integrating these technologies with managerial practices. The chapters offer both theoretical insights and practical applications, covering domains such as operations research, strategic planning, supply chain optimization, marketing analytics, financial forecasting, and human resource management.