Tiwari / Fegade / Kamal AI-Driven Environmental Pollution Management

Erscheinungsjahr 2025
ISBN: 978-3-031-96243-1
Verlag: Springer International Publishing
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 297 Seiten

Reihe: Earth and Environmental Science (R0)

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.

Zielgruppe

Professional/practitioner

Autoren/Hrsg.

Tiwari, Shashi Kant

Fegade, Atul

Kamal, Mustafa

Inhaltsverzeichnis

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

Über Autor(innen)

Dr. Shashi Kant Tiwari is a highly accomplished Professor and a dedicated researcher, holding a bachelor’s degree in mechanical engineering, a master’s in Computer Aided Design from the Vellore Institute of Technology, Vellore (2017), and Ph.D. from the Indian Institute of Technology (Indian School of Mines) Dhanbad. His pioneering research areas lie in Artificial Intelligence, Machine Learning, Deep Learning, Environmental Acoustics, and Data Science. Dr. Tiwari has an extensive publication record in esteemed journals (Environmental Science and Pollution Research, Applied Acoustics, Noise Mapping, NCEJ, MAPAN, IEEE Explore, serves as a reviewer for reputable publications such as Environmental Research, Scientific Report, ESPR, Measurement, and holds two registered design patents. Additionally, he is also associated in two projects of Saudi Electronics University, Saudi Arabia. He currently imparts his knowledge as a Senior Assistant Professor at Balaji Institute of Modern Management, Sri Balaji University, Pune, in subjects like Data Science, and Introduction to Python, Machine Learning, and Deep Learning inspiring the next generation of pioneers with his holistic perspective and impressive expertise.

Dr. Atul Fegade holds a PhD in Marketing Management from Savitribai Phule Pune University (2018), an MBA in Marketing Management from the same university (2004), and a BSc in Chemistry from Fergusson College, Pune (2002). He is UGC NET qualified and has over 15 years of experience in management education at both undergraduate and postgraduate levels. In addition, he has 4.5 years of industry experience, having held sales positions at reputable companies such as ICICI Lombard General Insurance Ltd., Novar India Pvt. Ltd. (part of the Honeywell Group), and GSK Pharmaceuticals Ltd. Dr. Fegade’s contributions to research and consultancy include authoring and presenting two papers at national and international conferences, as well as publishing seven research papers in reputable journals, including one in an ABDC B category publication and two indexed in Scopus. He has also published two book chapters indexed in Scopus. His consultancy work includes a marketing research project aimed at improving packaged cow milk sales for Kolhapur Zilla Doodh Utpadak Sangh (Gokul Milk) and completing a minor research project funded by BCUD, Savitribai Phule Pune University.

Dr. Mustafa Kamal currently employed as an Associate Professor in the Department of Basic Sciences, College of Science and Theoretical Studies, at Saudi Electronic University in Saudi Arabia. He received his Ph.D. in statistics from Aligarh Muslim University in India in 2013. Prior to assuming his current position, Dr. Kamal worked as a Research Project Fellow (From April 2012 to August 2014) in a Research Project (Code: 1206) of University Grants Commission SAP (DRS-I), Department of Statistics and Operations Research, Aligarh Muslim University, Aligarh. Over the years, Dr. Kamal has established himself as a prolific researcher, with an impressive record of more than 75 research papers published in high-impact, peer-reviewed international journals and conference proceedings. His main research interest includes Reliability theory, Accelerated Life testing, Survey Sampling and Distribution Theory. He has also contributed to interdisciplinary fields, exploring the integration of statistical techniques with emerging areas like Artificial Intelligence, Environmental Sciences, Statistical Economics, and Sustainable Developments. His work emphasizes the application of statistical tools to address global challenges such as environmental sustainability and economic growth and reflects his deep expertise and innovative approach to addressing complex problems across various domains.