Intelligent Environmental Surveillance

Microplastics polluting the world are a threat to both environmental and human health, and monitoring in this case needs new approaches. The use of various artificial intelligence technologies in enhancing the detection, monitoring, and evaluation of microplastic pollution in distinct ecosystems is also discussed in this book chapter. This book chapter explores how machine learning and computer vision technology can advance state-of-the-art environmental surveillance systems through a discussion of current difficulties in microplastic detection and the application of AI. This study reviews current deployments of AI-based monitoring systems and establishes best practices for AI-based monitoring system deployment in the field. Our study shows that with the use of an AI-based system, it is possible to detect microplastics with up to 95% accuracy and at a much lower cost and time than can be accomplished by using conventional methods. The solutions proposed in the study also include a discussion of the sustainability of the developed products as well as the possibility of integration into the networks of the global monitoring of the environment. Offering a solution on how to improve microplastic monitoring utilizing modern AI technologies together with environmental science, this study offers automation of microplastic identification for improving efficiency. Finally, this chapter presents specific recommendations for implementation and defines the directions of further research concerning the contemporary environmental problem systematically analyzed.