ICT Interventions in Landslide Prediction Runout Modeling, Early Warning and Mitigation

Landslides are one of the most destructive natural hazards, especially in mountainous regions, leading to severe loss of life, property damage, and ecosystem disruption. The complex nature of landslide prediction, influenced by geological, hydrological, topographical, and climatic factors, has long been a challenge. Consequently, Informatics based tools like run out modelling for forecasting, mitigation, and early warning have become crucial, utilizing technologies such as remote sensing, GIS, IoT, and AI/ML. This paper explores the effective application of Informatics especially its AI, ML components, in landslide risk management, with a focus on real-time data acquisition, numerical prediction models, and forecasting. Topics discussed include early warning systems utilizing IoT sensor networks, mobile applications for community mobilization and real-time alerts, Challenges such as data quality, infrastructure constraints, and gaps in public awareness are also discussed. The article stresses the role of informatics in improving the accuracy of disaster prediction and enhancing disaster preparedness and response through timely warnings.