Flood Alert Mapper: A Community-Powered Real-Time Flood Reporting and Rescue Location System

Abstract

Flooding remains one of the most destructive natural disasters affecting communities, particularly in urban and low-lying areas where delayed reporting and inaccurate information hinder effective emergency response operations. Traditional flood monitoring systems often rely on centralized reporting mechanisms that may not provide real-time situational awareness and community-based verification. This study aimed to develop a Flood Alert Mapper: A Community-Powered Real-Time Flood Reporting and Rescue Location System capable of supporting real-time flood monitoring, AI-assisted validation, community participation, and emergency notification dissemination. The study utilized a developmental-descriptive research design and adopted the Rapid Application Development (RAD) model in designing and implementing the proposed system. The developed web-based platform integrated real-time flood mapping, crowdsourced flood reporting, AI-assisted confidence scoring using MobileNetV2, community validation mechanisms, and automated notification features. The system computed report reliability using a weighted confidence formula combining AI-generated analysis and community validation results.