Real-Time IoT-Based Flood Detection Using ESP32 a Scalable and Low-Power Solution for Risk Mitigation

Justin Phinni Jose, Jogimol Joseph

Abstract: The ESP32 microcontroller is used in this study's Internet of Things-based flood detection system to allow for real-time environmental state monitoring. The system combines flow, temperature, humidity, ultrasonic, raindrop, and water level sensors. Data is sent over Wi-Fi to the ThingSpeak cloud platform for analysis and visualization. Authorities and people receive early warnings from automated alerts that are based on sensor thresholds. High sensor precision, dependable data transmission, and low power consumption are confirmed by experimental findings. Scalability and deployment in various flood-prone areas are supported by the modular architecture. Future developments include real-world field testing, alternative communication protocols like LoRaWAN, and AI-driven predictive analytics, providing a reliable and affordable flood risk reduction solution.

Keywords: Flood Monitoring, IoT, Water Level Sensor, ESP32, Real-Time Data