Artificial Intelligence Driven Models For Environmental Management
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Artificial Intelligence-Driven Models for Environmental Management
Author: Shrikaant Kulkarni
language: en
Publisher: John Wiley & Sons
Release Date: 2025-08-19
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.
Prospects of Artificial Intelligence in the Environment
Author: Ajitanshu Vedrtnam
language: en
Publisher: Springer Nature
Release Date: 2025-07-19
This book gives readers insight into the state-of-the-art use of artificial intelligence for the environment. It encompasses most of the significant facets of current breakthroughs in the fields of conceptions, methodologies, resources, and leading artificial intelligence solutions for the environment. This book presents research at the forefront on applications of artificial intelligence in combating climate change, natural hazards, and textile dyeing pollution (water pollution), for forecasting, assessing air quality trends, and air pollution monitoring. It explains how machine learning can prove to be an efficient technique to forecast the consumption of energy and how AI can be effective for renewable energy systems. Research in this book widens its scope to present the problems, opportunities, and directives for the application of AI systems in engine exhaust prediction. One of the new and interesting things explored is to provide and predict the rate of decay of human lung tissue (due to Particulate Matter exposure) with the help of AI in this book. Likewise, the book opens its scope to various environmental problems and focuses on giving the best solutions with an application of artificial intelligence; this feature makes this book an indispensable guide for environmental scientists and AI researchers of all levels. The book is written comprehensively so that engineering professionals, programmers, environmentalists, graduates, postgraduates, and researchers from beginning/intermediate level to advance level can be enlightened.
Artificial Intelligence Applications for Sustainable Construction
Artificial Intelligence Applications for Sustainable Construction presents the latest developments in AI and ML technologies applied to real-world civil engineering concerns. With an increasing amount of attention on the environmental impact of every industry, more construction projects are going to require sustainable construction practices. This volume offers research evidence, simulation results, and case studies to support this change. Sustainable construction, in fact, not only uses renewable and recyclable materials when building new structures or repairing deteriorating ones, but also adopts all possible methods to reduce energy consumption and waste.The concisely written but comprehensive, practical knowledge put forward by this international group of highly specialized editors and contributors will prove to be beneficial to engineering students and professionals alike. - Presents convincing "success stories that encourage application of AI-powered tools to civil engineering - Provides a wealth of valuable technical information to address and resolve many challenging construction problems - Illustrates the most recent shifts in thinking and practice for sustainable construction