Integrating AI enhanced remote sensing technologies with IOT networks for precision environmental monitoring and predicative ecosystem management

Abstract

Detection of hazardous substances in the environment is paramount in safeguarding human health and ecosystems. With the continuous advancement of technology, artificial intelligence (AI) has emerged as a promising tool in the development of sensors capable of efficiently detecting and analyzing these substances. Environmental monitoring, modeling, and management are very essential for gaining a deeper insight into the fundamental processes and methodologies employed in handling environmental transformations. Hence, the objective of this study is to investigate recent progress in the utilization of AI, sensors, and IoT devices for monitoring environmental pollution, while considering the challenges associated with predicting and monitoring these variations due to the dynamic nature of the environment. The integration of these systems is actively revolutionizing environmental monitoring and enhancing our understanding of how to implement a comprehensive approach to the management of natural resources and ecological processes that are crucial for our societal, economic, and cultural well-being. Consequently, we are able to uncover the transformative impact of this collaborative effort on our comprehension of Earth, as it tackles obstacles, conducts in-depth analysis of long-term environmental data monitoring, and lays the foundation for a promising future.