Emerging Integration of Artificial Intelligence of Things (AIoT) in Air Pollution Monitoring and Management

The integration of the artificial intelligence of things (AIoT) in monitoring air pollution is transforming industrial strategy for managing pollutants. It combines artificial intelligence (AI) with IoT to gather real‐time data for precise and cost‐effective air quality management. Traditional monitoring stations face challenges in dynamic data collection and analysis. Key benefits include real‐time monitoring and alerting of air pollutants, while predictive modeling helps forecast pollution trends. AI‐powered air sensors, being smaller and portable compared to fixed stations, are easier to deploy. Through AIoT integration, communities and governments can implement data‐driven regulations and controls to reduce pollution exposure and identify emission hotspots. However, ensuring sensor accuracy remains challenging, requiring ongoing calibration and AI model training. Further work is needed to meet regulatory standards and integrate with existing infrastructure. The AIoT promotes sustainable development, regulatory compliance, and improved health outcomes. This chapter explores AIoT's role in real‐time air pollution monitoring using AI technologies and addresses how it enhances regulatory compliance through emissions monitoring and anomaly detection, along with ethical considerations and future perspectives.