Telegram bot-based Flood Early Warning System with WSN Integration


Abdul Wahid(1*); Jumadi Mabe Parenreng(2); Welly Chandra Kusumah Kusnandar(3); Puput Dani Prasetyo Adi(4); Dendy Mahabror(5); Ros Sariningrum(6);

(1) Universitas Negeri Makassar
(2) Universitas Negeri Makassar
(3) Universitas Negeri Makassar
(4) BRIN-RI
(5) BRIN-RI
(6) BRIN-RI
(*) Corresponding Author

  

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.

Keywords


Alert; Early Warning System; Flood; Water Level Detection; Wireless Sensor Network

  
  

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doi  https://doi.org/10.33096/ilkom.v16i2.1699.151-160 		  

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