DESIGN AND IMPLEMENTATION OF A FIREBASE-INTEGRATED IOT-BASED FLOOD DETECTION AND EARLY WARNING SYSTEM FOR PAKISTAN - Naeem Akbar Channar; Mushkar Afzal Mughal; Amna Talpur; Anjum Khalique (Spectrum of Engineering Sciences, 2025)
Pakistan is a country that is very susceptible to floods due to its geographical and climatic conditions. Poor urban planning, weak infrastructure, and no early warning systems make it even more deadly. Destructive monsoon floods break every year, homes, agriculture, and the transport system apart not to mention the loss of human life. Climate change has already had an impact on increasing the frequent severity of flooding; hence there is a strong requirement for modern technology-based solutions. This study presents a low-cost scalable IoT-based flood detection and early warning system suitable for flood-prone areas within Pakistan utilizing ultrasonic water level sensors, rain sensors plus water flow sensors integrated with NodeMCU(ESP8266) microcontroller continuously monitoring environmental parameters realtime data being uploaded to Firebase Realtime Database where it gets visualization through a custom-built web application. These sensors continuously monitor the environmental parameters and upload the data in real time to Firebase Realtime Database where it gets visualized through a custom-built web application. Instantly, based on thresholds, alerts are sent to warn emergency responders. The system has been prototyped and tested to validate its responsiveness and accuracy. Future integration with predictive models will advance system capabilities.