Landslide and Flood Predictor and Alert Dissemination System

This project proposes a machine learning-based system to predict landslides and floods using historicaland real-time climate data. Traditional models often rely on static threshold values, which limits theiraccuracy. By leveraging advanced ML techniques and algorithms, this system analyses environmentalfactors like rainfall, elevation, humidity, and river water levels to provide more reliable forecasts. Themodel is trained on past disaster records and continuously improves by learning from newly fed data. Auser-friendly website will display live updates and warnings, while an alert system will send SMSnotifications to at-risk residents. By integrating real-time weather APIs and optimizing predictiveaccuracy, this project aims to enhance disaster preparedness, reduces chances of false alarms, andpromotes resilience against natural hazards for the community.