AI-Driven Early Warning Systems for Natural Disaster Prediction

Alladi Deekshith

Abstract


Predicting natural disasters accurately is essential for minimizing loss of life and property. This paper introduces an AI-driven early warning system that integrates satellite imagery, weather data, and geospatial information to predict disasters such as floods, hurricanes, and wildfires. The system employs deep learning models for pattern recognition and anomaly detection, providing timely alerts to authorities and communities. Case studies on historical disaster events demonstrate the system's effectiveness in early prediction and risk mitigation. The findings highlight the transformative potential of AI in disaster management and resilience planning.

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