Designing a Solar-Powered IoT-Based Flood Early Warning System Prototype with Audio-Visual Alarm for Aceh Region
DOI:
https://doi.org/10.58477/dj.v4i1.386Keywords:
Flood Early Warning, IoT, Solar Power, Float Switch, Disaster Risk ReductionAbstract
Floods have repeatedly threatened the people of Aceh Province. Thousands of families lost their property and lives because the early warning information was delayed. This research designs a flood early warning system prototype based on IoT using renewable energy, which can operate on its own without PLN electricity. The system uses three IP68 float switch sensors to detect water levels at thresholds of 0.5m (normal), 1.0m (alert), and 1.5m (danger) combined with a 2-in-1 audio-visual alarm (strobe and siren) with a coverage distance of 100-150 meters. The energy design uses a solar panel of 50-100W with 12V DC voltage and has a minimum backup for 48 hours without sunlight. Hardware design, sensor accuracy testing, validation of the energy system, and testing the effectiveness of alarms are the research methods in this study which is conducted in Banda Aceh City. The results indicate that this system can run independently at low power consumption because float switch sensors are more effective than ultrasonic sensors under conditions where the water is turbid and full of debris as found in rivers in Aceh Province. This prototype is low-cost (less than Rp 2 million), requires minimal maintenance, and has high reliability; therefore, it can be adopted by communities that do not have many resources. This research provides a technical blueprint for developing an early warning system that fits geographically and climatically with Aceh Province which may be replicated in other flood-prone districts for disaster risk reduction programs.
Downloads
References
Abdelal, Q., & Al-Hmoud, A. (2021). Low-cost, low-energy, wireless hydrological monitoring platform: Design, deployment, and evaluation. Journal of Sensors, 2021(1), 8848955. https://doi.org/10.1155/2021/8848955
Adhikari, B. R., & Sitoula, N. R. (2018). Community based flash flood early warning system: A low-cost technology for Nepalese mountains. Bulletin of the Department of Geology, 87-92. https://doi.org/10.3126/bdg.v20i0.20728
Aprianti, E., Hamzah, S., Cahyadi, M. N., Kusumawardani, D., Widjajanti, N., & Apdin, S. C. F. (2025). The systematic disaster management approach to assessing early warning systems in South Sulawesi: A review. Engineering, Technology & Applied Science Research, 15(4), 24305-24310. https://doi.org/10.48084/etasr.9794
Cools, J., Innocenti, D., & O'Brien, S. (2016). Lessons from flood early warning systems. Environmental Science & Policy, 58, 117-122. https://doi.org/10.1016/j.envsci.2016.01.006
Danang, D., Suwardi, S., & Hidayat, I. A. (2019). Flood disaster mitigation using a disaster early warning and monitoring information system with an IoT-based Arduino microcontroller. Teknik, 40(1), 55-62. https://doi.org/10.14710/teknik.v40i1.23342
Fakhruddin, S. H. M., Kawasaki, A., & Babel, M. S. (2015). Community responses to flood early warning system: Case study in Kaijuri Union, Bangladesh. International Journal of Disaster Risk Reduction, 14, 323-331. https://doi.org/10.1016/j.ijdrr.2015.08.004
Islam, A. R. M. T., Al Mamun, A., Rahman, M. N., Akter, M. Y., Chisty, M. A., Alam, G. M., ... & Sohel, M. S. (2024). A cost-benefit analysis of flood early warning system: Evidence from lower Brahmaputra River Basin, Bangladesh. International Journal of Disaster Risk Reduction, 104, 104380. https://doi.org/10.1016/j.ijdrr.2024.104380
Iyekekpolo, U. B., Idachaba, F. E., & Popoola, S. I. (2018). Early flood detection and monitoring system based on wireless sensor network. In Proceedings of the International Conference on Industrial Engineering and Operations Management (Vol. 2018, pp. 1381-1394).
Kalyanapu, A., Owusu, C., Wright, T., & Datta, T. (2023). Low-cost real-time water level monitoring network for Falling Water River watershed: A case study. Geosciences, 13(3), 65. https://doi.org/10.3390/geosciences13030065
Kamali, M. A., Utami, C. T., Ma'ady, M. N. P., & Amifia, L. K. (2023, December). IoT-based flood early warning system for remote deployment and an integrated social media. In 2023 IEEE Asia-Pacific Conference on Geoscience, Electronics and Remote Sensing Technology (AGERS) (pp. 215-219). IEEE. https://doi.org/10.1109/AGERS61027.2023.10490838
Kharisma, R. S., & Puspitaningrum, N. A. (2025). Design and implementation of an IoT-based real-time water level monitoring system of Belik River at Yogyakarta City. Journal of Soft Computing Exploration, 6(3), 206-214. https://doi.org/10.52465/joscex.v6i3.621
Ma'Ti, M. A. N. B., Isa, R. M., Kasran, F. A. M., Hassan, S. L. M., Zakaria, W. N. W., & Ismadi, M. H. N. M. (2025, August). Smart IoT-based flood detection and alert system with real-time data logging. In 2025 IEEE 16th Control and System Graduate Research Colloquium (ICSGRC) (pp. 7-12). IEEE. https://doi.org/10.1109/ICSGRC65918.2025.11159736
Malek, K., Rodríguez, E. O., Lee, Y. C., Murillo, J., Mohammadkhorasani, A., Vigil, L., ... & Moreu, F. (2023). Design and implementation of sustainable solar energy harvesting for low-cost remote sensors equipped with real-time monitoring systems. Journal of Infrastructure Intelligence and Resilience, 2(3), 100051. https://doi.org/10.1016/j.iintel.2023.100051
Mamat, N. H., Othman, M. H., Othman, W. Z., & Noor, M. F. M. (2021, April). Internet of things in flood warning system: An overview on the hardware implementation. In Proceedings of the 1st International Conference on Electronics, Biomedical Engineering, and Health Informatics: ICEBEHI 2020, 8-9 October, Surabaya, Indonesia (pp. 269-279). Springer. https://doi.org/10.1007/978-981-33-6926-9_23
Mandal, R., Nishant, N., Chutia, D., Aggarwal, S. P., & Sharma, B. (2024, February). LoRa enabled IoT sensor framework for monitoring urban flood in Guwahati City. In NIELIT's International Conference on Communication, Electronics and Digital Technologies (pp. 55-76). Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3604-1_5
Masoudimoghaddam, M., Yazdi, J., & Shahsavandi, M. (2025). A low-cost ultrasonic sensor for online monitoring of water levels in rivers and channels. Flow Measurement and Instrumentation, 102, 102777. https://doi.org/10.1016/j.flowmeasinst.2024.102777
Megawati, T. F., Labib, M. F., Jaima, Z. T., Islam, M. A., & Jubair, H. (2025). Design and implementation of a solar-powered IoT flood detection system with dual online-offline connectivity and a two-tier alert mechanism using LoRa communication. Authorea Preprints. https://doi.org/10.22541/au.173548620.51633036/v1
Meléndez-Landaverde, E. R., & Sempere-Torres, D. (2025). Design and evaluation of a community and impact-based site-specific early warning system (SS-EWS): The SS-EWS framework. Journal of Flood Risk Management, 18(1), e12860. https://doi.org/10.1111/jfr3.12860
Mercado, R. J. M. (2016, November). Design of wireless sensor networks using embedded Programmable System-on-Chip (PSoC) as applied to community-based flood early warning systems (CBFEWS). In 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES) (pp. 214-223). IEEE. https://doi.org/10.1109/ICAEES.2016.7888041
Mihajlovic, Z., Joza, A., Milosavljevic, V., Rajs, V., & Zivanov, M. (2015, September). Energy harvesting wireless sensor node for monitoring of surface water. In 2015 21st International Conference on Automation and Computing (ICAC) (pp. 1-6). IEEE. https://doi.org/10.1109/IConAC.2015.7313997
Mousa, M., Oudat, E., & Claudel, C. (2015, October). A novel dual traffic/flash flood monitoring system using passive infrared/ultrasonic sensors. In 2015 IEEE 12th International Conference on Mobile Ad Hoc and Sensor Systems (pp. 388-397). IEEE. https://doi.org/10.1109/MASS.2015.61
Mousa, M., Zhang, X., & Claudel, C. (2016). Flash flood detection in urban cities using ultrasonic and infrared sensors. IEEE Sensors Journal, 16(19), 7204-7216. https://doi.org/10.1109/JSEN.2016.2592359
Mydlarz, C., Sai Venkat Challagonda, P., Steers, B., Rucker, J., Brain, T., Branco, B., ... & Silverman, A. I. (2024). FloodNet: Low-cost ultrasonic sensors for real-time measurement of hyperlocal, street-level floods in New York City. Water Resources Research, 60(5), e2023WR036806. https://doi.org/10.1029/2023WR036806
Perera, D., Agnihotri, J., Seidou, O., & Djalante, R. (2020). Identifying societal challenges in flood early warning systems. International Journal of Disaster Risk Reduction, 51, 101794. https://doi.org/10.1016/j.ijdrr.2020.101794
Prakash, C., Barthwal, A., & Acharya, D. (2022). FLOODWALL: A real-time flash flood monitoring and forecasting system using IoT. IEEE Sensors Journal, 23(1), 787-799. https://doi.org/10.1109/JSEN.2022.3223671
Prastyo, D., Mursyidin, I. H., & Irawan, D. (2025). An IoT-ML based flood early warning prototype for disaster risk mitigation. bit-Tech, 8(2), 2452-2461. https://doi.org/10.32877/bt.v8i2.3269
Ringo, J., Sabai, S., & Mahenge, A. (2024). Performance of early warning systems in mitigating flood effects: A review. Journal of African Earth Sciences, 210, 105134. https://doi.org/10.1016/j.jafrearsci.2023.105134
Rogers, D., & Tsirkunov, V. (2011). Costs and benefits of early warning systems. Global Assessment Report on Disaster Risk Reduction. United Nations International Strategy for Disaster Reduction.
Salleh, M. A. M., Telly, M. J., Abidin, Z. Z., & Ghazali, N. B. (2025). Solar-powered flood early monitoring system with IoT technology in Parit Raja. Multidisciplinary Applied Research and Innovation, 6(2), 80-88.
Saparudin, F. A., Halim, M. S., Ibrahim, N. S. A., & Baharom, M. F. (2024, September). Real-time flood monitoring using mobile LoRaWAN IoT gateway: A case study of the Muar River catchment. In 2024 IEEE 1st International Conference on Communication Engineering and Emerging Technologies (ICoCET) (pp. 1-4). IEEE. https://doi.org/10.1109/ICoCET63343.2024.10730107
Schismenos, S., Stevens, G., Emmanouloudis, D., Georgeou, N., Shrestha, S., Katopodes, N., & Wali, N. (2022). Humanitarian engineering for renewable energy and flood early warning in remote communities: A scoping review of enabling factors and sustainability. Journal of Sustainable Development of Energy, Water and Environment Systems, 10(3), 1-27. https://doi.org/10.13044/j.sdewes.d9.0406
Shrestha, M. S., Gurung, M. B., Khadgi, V. R., Wagle, N., Banarjee, S., Sherchan, U., ... & Mishra, A. (2021). The last mile: Flood risk communication for better preparedness in Nepal. International Journal of Disaster Risk Reduction, 56, 102118. https://doi.org/10.1016/j.ijdrr.2021.102118
Silverman, A. I., Brain, T., Branco, B., Sai Venkat Challagonda, P., Choi, P., Fischman, R., ... & Toledo-Crow, R. (2022). Making waves: Uses of real-time, hyperlocal flood sensor data for emergency management, resiliency planning, and flood impact mitigation. Water Research, 220, 118648. https://doi.org/10.1016/j.watres.2022.118648
Smith, C., Satme, J., Martin, J., Downey, A. R., Vitzilaios, N., & Imran, J. (2022). UAV rapidly-deployable stage sensor with electro-permanent magnet docking mechanism for flood monitoring in undersampled watersheds. HardwareX, 12, e00325. https://doi.org/10.1016/j.ohx.2022.e00325
Soegoto, E. S., Fauzi, F. A., & Luckyardi, S. (2021, February). Internet of things for flood and landslide early warning. In Journal of Physics: Conference Series (Vol. 1764, No. 1, p. 012190). IOP Publishing. https://doi.org/10.1088/1742-6596/1764/1/012190
Sufri, S., Dwirahmadi, F., Phung, D., & Rutherford, S. (2020). A systematic review of community engagement (CE) in disaster early warning systems (EWSs). Progress in Disaster Science, 5, 100058. https://doi.org/10.1016/j.pdisas.2019.100058
Syed, M. A., Shrestha, M. S., & Khadgi, V. (2021). Last mile communication of multihazard early warning—A case study on Bangladesh. In Disaster resilience and sustainability (pp. 725-765). Elsevier. https://doi.org/10.1016/B978-0-323-85195-4.00002-0
Tyagi, V., Rawat, N., & Ram, M. (2021). Reliability modelling and sensitivity analysis of IoT based flood alerting system. Journal of Quality in Maintenance Engineering, 27(2), 292-307. https://doi.org/10.1108/JQME-01-2020-0001
Uranus, H. P., Adhinugroho, N. R., Yulian, D. H., & Mangunsong, R. (2022). Design and realization of solar-powered IoT-based flood early warning system with telegram messaging, auto-restart watchdog, and power management. GCISTEM Proceeding, 1, 96-108. https://doi.org/10.56573/gcistem.v1i.4
Vimala, M., Kumar, P. R., & Ramasamy, S. (2025, May). Early flood detection using IoT: For flood risk management. In 2025 7th International Conference on Inventive Material Science and Applications (ICIMA) (pp. 1379-1384). IEEE. https://doi.org/10.1109/ICIMA64861.2025.11074094
Visconti, P., Orlando, C., & Primiceri, P. (2016, June). Solar powered WSN for monitoring environment and soil parameters by specific app for mobile devices usable for early flood prediction or water savings. In 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC) (pp. 1-6). IEEE. https://doi.org/10.1109/EEEIC.2016.7555638
Wisudawan, H. N. P. (2021). Design and implementation of real-time flood early warning system (FEWS) based on IoT Blynk application. ELKHA: Jurnal Teknik Elektro, 13(2), 113-121. https://doi.org/10.26418/elkha.v13i2.49003
Zakaria, M. I., Jabbar, W. A., & Sulaiman, N. (2023). Development of a smart sensing unit for LoRaWAN-based IoT flood monitoring and warning system in catchment areas. Internet of Things and Cyber-Physical Systems, 3, 249-261. https://doi.org/10.1016/j.iotcps.2023.04.005.
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2026 Design Journal
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.