Location Based Disaster Report

Disasters of various types and magnitudes afflict regions worldwide, necessitating a comprehensive understanding of their causes, characteristics, and impacts. Preparedness measures are paramount in mitigating the fear and losses that accompany such events. This research addresses the imperative for disaster preparedness by developing a novel informatics approacha region-wise repository and prediction web application. The primary objective of this project is to lower the risk of disaster impact by creating a repository that not only catalogs the types of disasters but also recommends necessary precautions, contingent upon the user's location. Each geographical region's susceptibility to specific disasters is unveiled, facilitating informed decisions regarding housing construction and disaster resilience. Furthermore, this paper emphasizes the colossal human and economic toll of disasters and highlights the pivotal role of the web application in constructing a region-wise disaster repository. By favor of web scraping techniques and machine learning algorithms, this application generates detailed predictions and offers needed precautionary guidance. This research represents a significant advancement in disaster preparedness, empowering individuals and communities to proactively safeguard against the catastrophic consequences of unforeseen events.