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Smart Solutions for Climate Resilience Harnessing Machine Learning and Sustainable WSNs
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Author(s): Rajesh Kanna Rajendran (Christ University, Bangalore, India), T. Mohana Priya (Christ University, Bangalore, India), Abdalla Ibrahim Abdalla Musa (Qassim University, Saudi Arabia), S. B. Mahalakshmi (Coimbatore Institute of Technology, India)and T. R. Anand (Dr. N.G.P. Arts and Science College, India)
Copyright: 2025
Pages: 20
Source title:
Machine Learning for Environmental Monitoring in Wireless Sensor Networks
Source Author(s)/Editor(s): Parikshit N. Mahalle (Department of Artificial Intelligence and Data Science, Vishwakarma Institute of Technology, Pune, India), Dattatray G. Takale (Vishwakarma Institute of Information Technology, India), Sachin Sakhare (Vishwakarma Institute of Information Technology, India)and Ganesh B. Regulwar (Vardhaman College of Engineering, India)
DOI: 10.4018/979-8-3693-3940-4.ch010
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Abstract
Smart Solutions for Climate Resilience: Harnessing Machine Learning and Sustainable WSNs presents a comprehensive examination of how cutting-edge technologies can fortify communities against the escalating impacts of climate change. The chapter explores the integration of machine learning techniques and energy-efficient Wireless Sensor Networks (WSNs) in environmental monitoring and climate prediction. It outlines strategies to optimize energy consumption within WSNs, emphasizing the utilization of sustainable power sources to support remote monitoring initiatives. Through real-world case studies, this chapter showcases the transformative potential of these technologies in fostering climate resilience and sustainable development, offering insights for researchers and practitioners alike.By elucidating the foundational principles of machine learning and WSNs, this chapter provides a roadmap for leveraging these technologies to confront the complex challenges posed by climate change.
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