FLOOD DETECTION SYSTEM USING IOT: DESIGN, IMPLEMENTATION AND PERFORMANCE ANALYSIS

Abstract

Floods remain one of the most destructive natural disasters, causing extensive damage to human life, property, and infrastructure worldwide. Conventional flood-monitoring approaches rely heavily on manual observation, which is slow, labour-intensive, and often results in delayed warnings. This paper presents the design and implementation of a low-cost, real-time Flood Detection System based on the Internet of Things (IoT). The system employs an ESP32 microcontroller interfaced with an ultrasonic sensor for water-level measurement, a float sensor for critical-level detection, a rain sensor for precipitation monitoring, and a DHT11 sensor for temperature and humidity sensing. Sensor data is processed locally on the ESP32 and transmitted over Wi-Fi to the Blynk IoT cloud platform, enabling continuous remote monitoring through a mobile dashboard. When the measured water level crosses a predefined threshold, the system automatically triggers a multi-channel alert comprising an audible buzzer, a visual LED indicator, and a push notification to the user's smartphone. Experimental evaluation shows that the proposed system reliably tracks environmental parameters with minimal latency and correctly activates alerts under simulated critical conditions. Owing to its low cost, simple architecture, and dual suitability for rural and urban deployment, the proposed system offers a practical and scalable solution for early flood warning and disaster-risk reduction.