ResQ – Intelligent Real-Time Disaster Management Using Machine Learning and IoT
N. Duraimurugan, A Reshma, S. Reshma
Abstract
The project, therefore, is to be a ResQ using deep learning capabilities for an enhanced response and coordination in cases of disaster. The best sources of real-time data on the weather services, government alerts, and user reports then integrate into critical updates and predictions during a disaster. The ResQ has such as features: real-time alerts, access to emergency contact information, route optimization evacuation, resource mapping, user-generated incident reports, first aid tips, offline functionality, volunteer coordination, and multi-language support. Deep learning algorithms in fact enhance predicting capabilities and thereby improve better management of disasters and effective allocation of resources. It is a means through which the effects of disasters will be reduced, rationalizing rescue procedures and saving more lives in the long term.