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Original Article

Aqua Sentry: A Resilient Flood Intelligence System Built on Dual-Modal Risk Fusion for Urban Disaster Response

Sanchit Sanjay Vhajage1
Science, K.J. Somaiya Junior College of Science and Commerce, Mumbai, Maharashtra, India.

Published Online: September-December 2025

Pages: 195-197

Abstract

We developed Aqua Sentry, a native Android application designed to address a critical limitation in current flood warning systems: the “false safe” problem. This work was motivated by the 2025 Punjab floods, which affected nearly two million people and highlighted the urgent need for reliable, location-specific alerts. Aqua Sentry introduces a Dual-API Risk Fusion model that integrates global river discharge data (GloFAS) with locally predicted rainfall totals (Open-Meteo). This combined analysis enhances the accuracy of danger detection, allowing the system to recognize threats from both river overflows and sudden urban floods. From a technical standpoint, Aqua Sentry was built for maximum operational stability. The application employs Executor Service for concurrent network processing and applies defensive JSON parsing to minimize crashes during external data failures—a feature essential for life-critical systems. Testing demonstrated the system’s ability to avoid false safety conditions and achieve rapid response times of under 100 milliseconds when deploying evacuation routes through Google Maps. These findings indicate that Aqua Sentry provides a dependable, low-latency framework for mobile-based flood intelligence, capable of converting complex environmental data into timely and actionable safety guidance.

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