ILKOM Jurnal Ilmiah, Vol 16, No 2 (2024)

Telegram bot-based Flood Early Warning System with WSN Integration

Abdul Wahid, Jumadi Mabe Parenreng, Welly Chandra Kusumah Kusnandar, Puput Dani Prasetyo Adi, Dendy Mahabror, Ros Sariningrum

Abstract


Indonesia experiences frequent flooding, with data from the National Disaster Management Agency (BNPB) revealing that floods account for 41% of all natural disasters (1,441 incidents) recorded in 2021. These floods cause significant property damage and casualties. To address this challenge, we have developed a prototype flood early warning system. This system utilizes ultrasonic sensors for real-time water level detection. Sensor data is transmitted to designated personnel through a website interface. Additionally, the system leverages a Telegram bot to deliver flood early warnings directly to the community residing in flood-prone areas. The sensor data comparison test yielded an error rate of only 0.6175% with an average difference of 1 cm, demonstrating the system's accuracy and functionality. Furthermore, a notification test conducted ten times achieved 100% accuracy. The Telegram bot successfully sent text message alerts (alert 1, alert 2, alert 3) with an average delivery time of 4.07 seconds. This prototype offers a promising solution for flood mitigation. By providing real-time water level data and issuing timely alerts via a user-friendly Telegram bot, the system empowers communities to prepare for potential flooding and minimize associated risks.