Environmental science is a multidisciplinary field that addresses a wide range of issues related to the environment and its interactions with human activities. These issues are critical to understanding and mitigating the impact of human actions on the planet. Some of the key environmental science issues include climate change, air pollution, water pollution, natural disasters, etc. Environmental science plays a crucial role in understanding these challenges and developing solutions to ensure a sustainable and healthy planet for future generations.
In recent years, the emergence of two transformative technologies- Machine Learning (ML) and the Internet of Things (IoT), have ushered in a new era in environmental science. These technologies are revolutionizing the way humans observe, analyze, and respond to environmental issues, offering unprecedented insights and solutions. These technologies have revolutionized our ability to monitor, analyze, and address complex environmental challenges. This integration of ML and IoT in environmental science represents a powerful synergy between the digital and natural worlds. It empowers us to make informed decisions, protect the environment, and work towards a more sustainable and resilient future.
The book “Applications of Machine Learning and Internet of Things in Environmental Sciences" offers a comprehensive exploration of how these advanced technologies are reshaping the way we understand and manage our natural world. This book begins by providing readers with a solid foundation in ML and IoT concepts and their relevance to environmental science. This book covers the application of machine learning and the Internet of Things in environmental science and gives theoretical as well as practical knowledge to the readers. The main sections of the book cover a wide range of applications and case studies where ML and IoT are making a significant impact on the environmental sciences.