Intelligent Systems for Pollution Detection and Control

The industrialization and urbanization have occurred as rapidly as this and thus, has accompanied the increase in pollution which has been a life threat to the life of people and the ecological system is caught in a spiral of decline. The chapter under discussion is Introduction of artificial intelligence (AI) in the creation of intelligent systems that will identify and manage pollution in real time within the urban and industrial setting. AI-based technologies, including machine and deep learning, computer vision and Internet of things (IoT) are researched, synthesized and reviewed concerning air, water and soil contaminants surveillance. The data generated by the distributed sensor networks, and satellite imagery through such intelligent systems are used to reach the provision of real-time and automated pollution mapping, proactive analysis and at-the-point intervention measures. Moreover, controlling industrial emissions through AI models is also a topic of the paper which includes pollution forecasting and the identification of the pollution sources. Besides that, the study addresses the challenges emerging with the implementation of AI systems such as data quality, scalability of the system, and regulatory consideration. There are some present smart city and green industrial projects that are described as case studies showing implementations and solutions that are practical. This chapter outlines the benefits of combined AI and the infrastructure of environmental surveillance apparatuses in achieving the control of pollution, to its end, sustainable development improvement and ecology lifestyle.