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AI-driven environmental pollution management

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	AI-driven environmental pollution management edited by Shashi Kant Tiwari, Atul Fegade, Mustafa Kamal.
其他作者:	Tiwari, Shashi Kant.
出版者:	Cham :Springer Nature Switzerland :2025.
面頁冊數:	xvii, 297 p. :ill., digital ;24 cm.
Contained By:	Springer Nature eBook
標題:	PollutionData processing.
電子資源:	https://doi.org/10.1007/978-3-031-96243-1
ISBN:	9783031962431$q(electronic bk.)

AI-driven environmental pollution management
AI-driven environmental pollution management [electronic resource] /edited by Shashi Kant Tiwari, Atul Fegade, Mustafa Kamal. - Cham :Springer Nature Switzerland :2025. - xvii, 297 p. :ill., digital ;24 cm. - Climate risks and solutions,3005-1673. - Climate risks and solutions..

Understanding Environmental Pollution -- Advanced Monitoring Techniques -- Artificial Intelligence In Pollution Management -- Economic And Sustainable Solutions -- Technological Innovations For Sustainability -- Index.

This book provides a comprehensive overview of the challenges caused by environmental pollution on a global scale, and delves into the intricate sources of air, water, and noise pollution. It discusses cutting-edge technologies such as IoT-based systems and AI integration for pollution detection and monitoring networks. With a focus on machine learning and deep learning models, the book provides insights into assessing, predicting, and mitigating the impact of pollution. Furthermore, it examines the implementation of AI-driven strategies for pollution control and reduction, alongside considerations for urban planning and sustainable infrastructure development. This indispensable resource navigates the social, policy, and economic implications of employing AI in environmental governance, emphasizing the importance of global cooperation for effective pollution management. The book will help readers to:1. Understand the adverse effect of environmental pollution in the era of new age. 2. Implement advanced management techniques that integrate sustainability into various environmental business economics.3. Explore effective environmental control and mitigation strategies using Internet of Things technologies and data analytics.4. Leverage AI/ML/DL for accurate environmental monitoring, modelling, prediction and decision-making.5. Navigate the complexities of Industry 4.0 to achieve sustainable development goals.

ISBN: 9783031962431$q(electronic bk.)

Standard No.: 10.1007/978-3-031-96243-1doiSubjects--Topical Terms:

1003591
Pollution
--Data processing.

LC Class. No.: TD174

Dewey Class. No.: 363.73028563

AI-driven environmental pollution management
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