DisasterSense: AI-Powered Real-Time Disaster Alert and Resource Locator Using Web Scraping

DisasterSense is a disaster management application which uses webs crapping, machine learning and satellite API’s. It provides real time alert system. This Application can be accessed by citizens, Emergency responders and authorities. It provides timely disaster alerts and location based safety guidance. It creates an environment where information about disasters from different online sources are automatically gathered and analyzed to give early warning and for preparedness. This application includes disaster categories such as floods, earthquake, cyclones and storms. It can improve situational awareness, timely response and public safety. Information about Disasters are processed with NLP models such as BERT. Also predictive models like LSTM analyzes trends in severity. Satellite and weather API helps in validating the envi- ronment and also increases the reliability of alerts. Python based Flask backend ensures quick data processing and delivery and a flutter based mobile interface enhances usability and accessibility. The Application helps users find nearby shelters, hospitals and emergency camps through map. The Application turns raw data from different sources into actionable intelligence, supports disaster preparedness and allows quick mitigation. This project showcases a scalable AI-driven solution for modern disaster management and emergency response systems