Real-Time Flood Resource Allocation & Rescue Coordination System

Abstract

Floods are one of the most catastrophic natural calamities that usually cause widespread and devastation along with loss of life. The allocation of resources during the emergencies should be precise and timely. Unfortunately, the existing systems of managing these disasters have several manual steps which result in issues due to lack of effective communication, absence of real-time information, and data, making critical aid slow and poorly allocated. This project proposes an automated disaster relief management model powered by AI, which utilizes classified data, geospatial nuances, and machine learning to enhance the allocation of basic needs which include food, water, medical assistance, and even rescuing services. The system implements user data along with real time data concerning floods, the infrastructure of the area and the infrastructure’s condition, enabling automatic resource allocation and goal showing through an interactive dashboard. The solution functions in regions lacking the internet due to offline communication through mesh networks and satellite links. The proposed platform is set to transform the flood relief logistics for improved decision making, increased transparency during the operations and decreased response time.