Prototipe Alat Deteksi Banjir Berbasis ESP32, TinyML, dan Notifikasi Telegram

Laily Rahmad Fauzi; Imam Suharjo

doi:10.53863/kst.v8i01.2115

Authors

Laily Rahmad Fauzi Universitas Mercu Buana Yogyakarta, Sleman, Indonesia
Imam Suharjo Universitas Mercu Buana Yogyakarta, Sleman, Indonesia

DOI:

https://doi.org/10.53863/kst.v8i01.2115

Keywords:

IoT, ESP32, TinyML, water level, flood warning

Abstract

Floods are among the most frequent hydrometeorological disasters in Indonesia and cause significant impacts on public safety, economic activities, and community infrastructure. To support improved preparedness, a water level monitoring system that operates in real time, provides accurate measurements, and is easy to implement in the field is required. This study aims to develop a prototype of an Internet of Things (IoT)-based water level monitoring and classification system using an ESP32 microcontroller, an HC-SR04 ultrasonic sensor, and a Tiny Machine Learning (TinyML) model that performs on-device inference. Water condition determination is based on predefined criteria and water level thresholds established during the analysis stage, which are subsequently used for data labeling and TinyML model development. The system is equipped with LED indicators (green, yellow, red), a 0.96-inch I2C OLED display for local monitoring, and an automatic notification mechanism via the Telegram application as a remote early warning system. The research adopts a Research and Development (R&D) approach using the ADDIE model, which includes needs analysis, system design, hardware and software development, prototype implementation, and system performance evaluation. Experimental results show that the system is able to measure water levels stably with a maximum error of 0.2 cm. A Mean Absolute Error (MAE) of 0.025 cm was obtained from eight experimental trials within a test range of 0–22.5 cm. The system successfully classified water conditions into “Safe,” “Alert,” and “Flood” categories using the TinyML model, achieving 100% agreement with test scenarios across ten test conditions. Furthermore, the Telegram notification mechanism operated as designed, with warning messages sent during all tested warning status transitions (five out of five scenarios) and not sent under stabel safe conditions. These findings indicate that the integration of IoT and TinyML has strong potential to support responsive and efficient flood monitoring and early warning systems, suitabel for small- to medium-scale prototype deployment in residential areas prone to inundation with measurable water level variations.

References

Banbury, C. R., Reddi, V. J., Lam, M., Fu, W., Fazel, A., Holleman, J., Huang, X., Hurtado, R., Kanter, D., Lokhmotov, A., Patterson, D., Pau, D., Seo, J., Sieracki, J., Thakker, U., Verhelst, M., & Yadav, P. (2021). Benchmarking TinyML Systems: Challenges and Direction. http://arxiv.org/abs/2003.04821

Fauziyah, A., Saleh, I., & Usman, I. (2024). Pengembangan prototipe sistem monitoring level ketinggian air menggunakan sensor ultrasonik berbasis internet of things. Jurnal Aplikasi Fisika, 20(02), 1–8. https://doi.org/10.62749/jaf.v20i02.p1-8

Hamzah, S. A., Dalimin, M. N., Som, M. M., Zainal, M. S., Ramli, K. N., Ikhsan, M. H. S., Yusop, A., Ishak, M., Rahman, R. A., Sidek, A., Utomo, W. M., Jamil, A. A., Talib, R., Yusoff, N. A., & Mustapa, M. S. (2024). Flood Level Detection System using Ultrasonic Sensor and ESP32 Camera: Preliminary Results. Journal of Advanced Research in Applied Mechanics, 119(1), 162–173. https://doi.org/10.37934/aram.119.1.162173

Hasibuan, A., Zahiri, M., Jannah, M., Roid, F., Almunadiansyah, R., Abta, A., & Nrartha, I. M. A. (2025). Design of flood warning prototype using ESP32 module-based ultrasonic sensors. International Journal of Reconfigurable and Embedded Systems (IJRES), 14(1), 126. https://doi.org/10.11591/ijres.v14.i1.pp126-135

Kurniawan, M. D., & Budjianto, A. (2025). Implementasi Sistem Programable Timer Menggunakan Esp32-C3 Supermini Dengan Tampilan Oled Dan Indikator Buzzer. Jurnal Mahasiswa Teknik Informatika), 9(6), 9950–9956.

Lengkong, A. G., Salaki, D. T., & Alfonsius, E. (2025). Implementation of An Internet of Things (IoT)-Based Water Level Early Warning System with Telegram Notification. 6(2), 196–207. https://doi.org/10.33365/jatika.v6i2.349

Mahardhika, P., Sari, Z., & Akbi, D. R. (2025). Rancang Bangun Prototype Sistem Monitoring Ketinggian Air Sungai Berbasis Mikrokontroler ESP32 dan Telegram Sebagai Upaya Deteksi Banjir Secara Dini. Jurnal Repositor, 7(4 SE-Sistem dan keamanan jaringan). https://doi.org/10.22219/repositor.v7i4.40639

Oktarian, A. R., Tasmi, Antony, F., & Verano, D. A. (2023). RANCANG SISTEM MONITORING KUALITAS DAN KETINGGIAN AIR BERBASIS INTERNET OF THINGS (IOT). JINI GLOBAL, 1(2), 75–83. https://doi.org/10.36982/jinig.v1i2.3649

Ovid, A., Yandani, E., & Asril. (2025). Prototype Sistem Pemantauan Tinggi Muka Air Berbasis Esp32 Untuk Sistem Pringatan Dini Banjir Melalui Telegram. JEKIN (Jurnal Teknik Informatika), 5(3), 1081–1089. https://doi.org/10.58794/jekin.v5i3.1634

Permana, I., & Irawati, R. (2025). Pengembangan Early Warning System Untuk Mitigasi Bencana Banjir Rob Di Indonesia. Journal of Information Technology, 5(2 SE-Articles), 300–307. https://doi.org/10.46229/jifotech.v5i2.1039

Rienandie, N. F., & Pramudita, R. (2025). DESIGN OF AN INTERNET OF THINGS-BASED WATER LEVEL MONITORING SYSTEM. JURTEKSI (Jurnal Teknologi Dan Sistem Informasi), 11(2), 265–272.

Samanta, R., Saha, B., & Ghosh, S. K. (2025). A Low-Power Low-cost System for Disaster Locations Detection using ESP32 CAM and TinyML. 2025 17th International Conference on COMmunication Systems and NETworks (COMSNETS), 907–910. https://doi.org/10.1109/COMSNETS63942.2025.10885754

Setiawan, I. P. E., Desnanjaya, I. G. M. N., Supartha, K. D. G., Ariana, A. A. G. B., & Putra, I. D. P. G. W. (2024). Implementation of Telegram Notification System for Motorbike Accidents Based on Internet Of Things. Jurnal Galaksi, 1(1), 1–11. https://doi.org/10.70103/galaksi.v1i1.1

Wikantama, P. T., & Puspitasari, R. (2023). Perancangan Perangkat Pengukur Ketinggian Banjir dengan ESP32 dan Telegram Berbasis IoT. Elektriese: Jurnal Sains Dan Teknologi Elektro, 13(02), 107–114. https://doi.org/10.47709/elektriese.v13i02.3108

Zakariah, M. A., Alfriani, V., & Zakariah, K. M. (2020). Metodologi Penelitian Kualitatif, Kuantitatif, Mix Method. Research and Development. In Madani Media. Yayasan Pondok Pesantren Al Mawaddah Warrahmah Kolaka.