Ai-driven environmental pollution management / Shashi Kant Tiwari, Atul Fegade and Mustafa Kamal, editors.
Series: Climate Risks and Solutions Published by : Springer Nature Switzerland AG, (Cham, Switzerland : ) Physical details: 1 online resource, xvii, 298 pages : illustrations (some color). ISBN: 9783031962424 . Year: 2025| Item type | Location | Collection | Call number | Status | Date due | Barcode |
|---|---|---|---|---|---|---|
Electronic Books
|
E-Resource Section | E-Books | 628.5 Ai2881 2025 (Browse shelf) | Available |
Includes bibliograpical references and 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.
There are no comments for this item.