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@article{201389,
        author = {Ansh Nimablkar and Advait Nagar and Rohak Thakur and Shivam Mhamane and Mayuresh Gulame and Aarti Pimpalkar},
        title = {AI-Based Early Warning System for Glacial Lake Outburst Floods Using UAVs and Rovers},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {9851-9856},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201389},
        abstract = {Glacial Lake Outburst Floods (GLOFs) are abrupt, catastrophic releases of water impounded by glacial or moraine dams, posing danger to millions in high-mountain regions. Climate-induced glacier retreat has accelerated lake growth and hazard levels globally. Conventional early warning systems frequently fail because the rapid onset of GLOFs leaves insufficient time to warn downstream populations. This paper proposes an AI-based Early Warning System (EWS) integrating Unmanned Aerial Vehicles (UAVs) and an autonomous amphibious rover with onboard machine learning. The UAV monitors glacial lakes using high-resolution optical, thermal, and LiDAR sensors; the rover tracks moraine-dam stability using GPS, geophones, and inertial sensors. A hybrid CNN+LSTM model processes imagery and time-series data to detect precursors such as lake expansion and dam cracking. A secure cloud architecture provides real-time dashboards, multi-channel alerting, and cryptographic data integrity. Simulations achieved over 90% lake segmentation accuracy and 85% precision in forecasting rapid lake-level rises. A case study modeled on the 2023 Sikkim GLOF demonstrated 2–3 days of additional warning lead time. This work presents a comprehensive, scalable framework addressing critical gaps in current GLOF monitoring.},
        keywords = {Glacial Lake Outburst Flood (GLOF); Early Warning System; UAV; Autonomous Rover; Machine Learning;Remote Sensing; Edge AI; IoT; Cybersecurity; Cloud Dashboard.},
        month = {May},
        }