A Multi-Node, Sensor-Fusion-Based Smart Flood Electrical Hazard Detection and Adaptive Warning System

Abstract

Floodwater that becomes electrically energized through damaged underground cables, fallen conductors, or compromised distribution infrastructure poses a severe and largely invisible public-safety hazard, since energized water is visually indistinguishable from safe water. Existing mitigation approaches rely predominantly on manual utility inspection or single-parameter voltage sensing, both of which are slow, spatially limited, and prone to false alarms or missed detections. This paper proposes JALRAKSHAK, a distributed, solar-powered, ESP32-based Internet of Things (IoT) system that detects electrically hazardous floodwater through a multi-parameter sensor-fusion methodology combining electrical potential measurement, leakage current estimation, water conductivity sensing, and environmental condition monitoring (rainfall intensity and water level). Readings from three spatially distributed sensing nodes are aggregated at a central controller, which computes a quantitative Flood Electrical Hazard Index (0-100) and applies spatial correlation logic to estimate hazard location, severity, approximate spread, and a safe direction of pedestrian movement. The computed hazard level drives an adaptive four-tier warning response, ranging from a passive visual indicator to automated notification of utility and emergency authorities. The proposed architecture is designed to operate autonomously during storm-related grid outages using a solar-battery power subsystem. This work presents the sensing methodology, hazard-index algorithm, distributed architecture, and warning logic in sufficient technical depth to serve as the basis for a future IEEE conference submission and an Indian patent application, while explicitly distinguishing the proposed contributions from existing single-parameter detection approaches.