Machine Learning for Environmental Monitoring in Wireless Sensor Networks

Today, data fuels everything we do in a highly connected world. However, traditional environmental monitoring methods often fail to provide timely and accurate data for effective decision-making in today's rapidly changing ecosystems. The reliance on manual data collection and outdated technologies results in gaps in data coverage, making it challenging to detect and respond to environmental changes in real time. Additionally, integration between monitoring systems and advanced data analysis tools is necessary to derive actionable insights from collected data. As a result, environmental managers and policymakers face significant challenges in effectively monitoring, managing, and conserving natural resources in a rapidly evolving environment. Machine Learning for Environmental Monitoring in Wireless Sensor Networks offers a comprehensive solution to the limitations of traditional environmental monitoring methods. By harnessing the power of Wireless Sensor Networks (WSNs) and advanced machine learning algorithms, this book presents a novel approach to ecological monitoring that enables real-time, high-resolution data collection and analysis. By integrating WSNs and machine learning, environmental stakeholders can gain deeper insights into complex ecological processes, allowing for more informed decision-making and proactive management of natural resources. Key features of the book include an in-depth exploration of the principles, methodologies, and applications of WSNs and machine learning in environmental monitoring, real-world case studies and projects illustrating successful implementations, and a discussion on energy-efficient strategies for optimizing the sustainability of WSN deployments. Emphasis is placed on interdisciplinary collaborations among environmental scientists, engineers, data scientists, policymakers, and other stakeholders to foster innovative solutions for sustainable ecological monitoring. This book, tailored for researchers, practitioners, policymakers, and environmental enthusiasts, is an invaluable resource for leveraging cutting-edge technologies to address environmental monitoring and conservation challenges.

Dattatray Takale is Assistant Professor, Department of Computer Engineering at Vishwakarma Institute of Information Technology, Pune, India. Dr. Dattatray G. Takale obtained his Ph.D. in computer science and engineering. He has 10 + years of teaching and research experience. His research interests include Machine Learning, Data science, Wireless sensor Network, Natural lang. processing, data warehousing, mining, computer networks, and network security. He is currently employed by VIIT Pune, as an Assistant Professor. His has more than 6 years of teaching experience and 3 years industry experience. He has 21 patents, 20+ research publications, and authored/edited 4+ books with Springer, CRC Press, local and international publisher.

Sachin R. Sakhare is working as a Professor and Head of the Computer Engineering Department at Vishwakarma Institute of Information Technology, Pune, India. He has 27 Years of experience in engineering education. He is recognised as PhD guide by Savitribai Phule Pune University and currently guiding 8 PhD scholars. He is a life member of CSI, ISTE and IAEngg. He has Published 51 research communications in national, international journals and conferences, with around 370 citations and H-index 7. He has authored 6 books which is published by Springer Nature, CRC Press and IGI Global. He worked as a reviewer of journals published by Elsevier, Wiley, Hindawi, Springer, Inder science, and IETE. He worked as a reviewer for various conferences organised by IEEE, Springer, and ACM. He worked as a member of Technical and Advisory Committees for various international conferences. Dr. Sachin has Delivered invited talks at various Conferences, FDP’s and STTP’s as well as to PG and PhD students. He has guided 26 PG students. He has filed and published 07 patents out of which 01 Indian, 03 Australian and 02 south African patents are granted. Dr. Sachin is associated with international universities also. He was invited as Guest Faculty at Amsterdam University of Applied Sciences (AUAS), Netherlands to conduct sessions on data Structures and Internet of things. He has also visited Aalborg University, Copenhagen, Denmark and RWTH Aachen university, Germany for academic collaboration. He has availed the research workshop grants from AICTE, BCUD, Pune University. He has delivered various sessions on Outcome Based Education and NBA accreditations. He has completed the course on ABET accreditation.

Ganesh Bhaiyya Regulwar has obtained his B.E degree in Computer Science and Engineering from Sant Gadge Baba Amravati University, Amravati, India M.E. degree in Information Technology from Sant Gadge Baba Amravati University, Amravati, India He has completed his Ph. D in Information Technology specialization in Software Engineering from Sant Gadge Baba Amravati University, Amravati, India He has more than 19 years of teaching and research experience. He is recognised as PhD guide by Sant Gadge Baba Amravati University, Amravati and currently guiding 4 PhD scholars. He is a life member of CSI, ISTE and IAEngg. He has Published 30 research communications in national, international journals and conferences, with around 370 citations and H-index 7. He has authored 1 books which is published by Springer Nature, CRC Press and IGI Global. He worked as a member of Technical and Advisory Committees for various international conferences. Dr. Sachin has Delivered invited talks at various Conferences, FDP’s and STTP’s as well as to PG and PhD students. He has guided 20 PG students. He has filed and published 07 patents out of which 01 Indian, 03 Australian and 02 south African patents are granted.