To develop an Artificial Intelligence (AI) / Machine Learning (ML) based system for identification, classification, and prediction of different tropical cyclone patterns using multi-source satellite data.
Dense winter radiation fog across the Indo-Gangetic Plains (Delhi, Punjab, UP, Bihar) disrupts hundreds of flights, passenger trains, and highway freight operations daily with low-visibility conditions (<50 meters) that existing numerical models fail to forecast accurately at sub-kilometer scales. Build an AI/ML-based high-resolution fog and visibility nowcasting system combining satellite land surface temperature, boundary layer humidity sensors, and Ceilometer backscatter to forecast Runway Visual Range (RVR) up to 12 hours in advance.
Smart India Hackathon 2026 Problem Statement PS-26070: "To develop an Artificial Intelligence (AI) / Machine Learning (ML) based system for identification, classification, and prediction of different tropical cyclone patterns using multi-source satellite data.", Ministry: Ministry of Earth Sciences (MoES). Strategy & Architecture via SIH ONE (https://sihone.pages.dev/ps/26070)
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