11th International Conference on ICT for Sustainable Development

Authors - Lokesh Khedekar, Atharva Kassa, Kartavya Sharma,Tejas Kedar, Sarthak Kasar, Kaustubh Kelgandre, Sharad Kasralikar
Abstract - Natural Disasters have been a major threat to the living beings, environment and the infrastructure, in mainly areas where they have poor access to early warnings systems. This paper provides AI-based Natural Disaster Response System which helps to evaluate the impact of natural disasters and gives better of the existing systems. The system has historical Geographic Information System (GIS) datasets with real-time data from Internet of Things (IoT) sensors and predictive modeling to check out the natural disaster’s magnitude, area of impact, and resources. The methodology includes data preprocessing, feature extraction, and machine learning model training to achieve effective predictive accuracy. A Convolutional Neural Model (CNN) model was created and tested which further achieved 93% accuracy of predicting the impact of the disaster incident. The system was then compared with other machine learning models, then was proved to be more effective. The suggested method gives efficient, cost-effective and scalable way of utilizing the emergency resources at the maximum.