(Chhatrapati Shivaji Institute of Technology (CSIT), India.)
Dr. Ravi Mishra is a Professor in the Department of Computer Science and Engineering at Chhatrapati Shivaji Institute of Technology (CSIT), Durg, Chhattisgarh, India. His academic interests include computer science, Artificial Intelligence, and intelligent data-driven systems. He contributes to the application of Agentic AI for real-time air pollution monitoring and prediction.
Ravi Mishra, Swati Chaitandas Hadke. In: Agentic Artificial Intelligence: Intelligent Autonomous Systems and Real-World Applications — ISBN: 978-81-69935-67-8. Pages: 113 - 135
Air pollution constitutes a multifaceted environmental issue shaped by factors such as traffic, industrial operations, energy generation, construction, agricultural methods, weather patterns, and urban expansion.This chapter introduces a cohesive structure for utilising Agentic AI in the real-time observation and forecasting of air pollution. It addresses environmental sensing, IoT-driven data collection, sensor calibration, data quality evaluation, pollutant prediction, spatiotemporal modelling, meteorological integration, anomaly detection, pollution source analysis, adaptive monitoring, intelligent alert generation, edge-cloud intelligence, UAV-based monitoring, satellite data integration, and multi-agent environmental systems. The section additionally explores elucidation, uncertainty assessment, cybersecurity measures, data management, human-in-the-loop decision processes, and evaluative techniques. A conceptual agentic framework is established wherein specialised agents cooperate with sensors, predictive models, databases, geographic information systems, meteorological services, and decision-support systems. The chapter wraps up by exploring prospective avenues related to multimodal environmental foundation models, digital twins, federated learning, autonomous environmental observatories, and collaborative multi-agent systems. The primary aim is to develop Agentic AI as a regulated and comprehensible computational system for ongoing environmental intelligence instead of an unbounded autonomous decision-maker.
