Telegram-Based Earthquake Early Warning

Authors

Arfanda Anugrah Siregar , Erwinsyah Simanungkalit , Nasrudin

DOI:

10.29303/jppipa.v11i5.11080

Published:

2025-05-25

Issue:

Vol. 11 No. 5 (2025): May

Keywords:

Early warning system, Earthquake, Internet of Things (IoT), MPU 6050 sensor

Research Articles

Downloads

How to Cite

Siregar, A. A., Simanungkalit, E., & Nasrudin. (2025). Telegram-Based Earthquake Early Warning. Jurnal Penelitian Pendidikan IPA, 11(5), 85–94. https://doi.org/10.29303/jppipa.v11i5.11080

Downloads

Download data is not yet available.

Metrics

Metrics Loading ...

Abstract

Earthquakes are one of the natural disasters whose arrival cannot be ascertained and have a very detrimental impact, both in terms of property losses and lives. Indonesia, with its very active tectonic plate conditions, often experiences earthquakes, so it needs an effective early warning system. BMKG has developed an early warning system that informs of earthquake events through various media. However, this system still has weaknesses in the speed of delivering information to the public. This research aims to design and make a prototype of an earthquake early warning tool that can send information in the form of notifications and warning alarms using the Telegram application. The use of Telegram as a medium for conveying information was chosen because of its high-speed, security, and accessibility. This research was carried out at the Telecommunications Laboratory, Politeknik Negeri Medan starting from the system design process, system implementation, MPU6050 sensor testing, LoRa SX1278 testing, microcontroller ESP32 testing, and Telegram BOT testing to detect earthquake vibrations and send earthquake scale notifications via the Telegram. It produced a prototype of an earthquake early warning tool that uses Telegram for the dissemination of warning information in real-time, so that people can more quickly take self-rescue actions.

References

Abdalzaher, M. S., Krichen, M., & Falcone, F. (2024). Emerging technologies and supporting tools for earthquake disaster management: A perspective, challenges, and future directions. Progress in Disaster Science, 23(March), 100347. https://doi.org/10.1016/j.pdisas.2024.100347

Abdalzaher, M. S., Krichen, M., Yiltas-Kaplan, D., Ben Dhaou, I., & Adoni, W. Y. H. (2023). Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey. Sustainability (Switzerland), 15(15), 1–38. https://doi.org/10.3390/su151511713

Allen, R. M., & Melgar, D. (2019). Earthquake early warning: Advances, scientific challenges, and societal needs. Annual Review of Earth and Planetary Sciences, 47, 361–388. https://doi.org/10.1146/annurev-earth-053018-060457

Chan, H. ., & Tsai, M. . (2023). Alert notifications for governmental disaster response via instant messaging applications. International Journal of Disaster Risk Reduction, 96, 103984. https://doi.org/10.1016/j.ijdrr.2023.103984

Cheng, Z., Peng, C., & Chen, M. (2023). Real-Time Seismic Intensity Measurements Prediction for Earthquake Early Warning: A Systematic Literature Review. Sensors, 23(11), 1–23. https://doi.org/10.3390/s23115052

Cremen, G., & Galasso, C. (2020). Earthquake early warning: Recent advances and perspectives. Earth-Science Reviews, 205, 103184. https://doi.org/10.1016/j.earscirev.2020.10318

Damaševičius, R., Bacanin, N., & Misra, S. (2023). From Sensors to Safety: Internet of Emergency Services (IoES) for Emergency Response and Disaster Management. Journal of Sensor and Actuator Networks, 12(3). https://doi.org/10.3390/jsan12030041

El Anshori, Y. T., Kunda, R. M., & Manuhutu, F. (2025). Design and Construction of a Real-Time Air Quality Monitoring System Using IoT-Based ESP32 to Strengthen Environmental Policies. Jurnal Penelitian Pendidikan IPA, 11(2), 145–152. https://doi.org/10.29303/jppipa.v11i2.9820

Esposito, M., Palma, L., Belli, A., Sabbatini, L., & Pierleoni, P. (2022). Recent Advances in Internet of Things Solutions for Early Warning Systems: A Review. Sensors, 22(6). https://doi.org/10.3390/s22062124

Finazzi, F. (2020). The Earthquake Network Project: A Platform for Earthquake Early Warning, Rapid Impact Assessment, and Search and Rescue. Frontiers in Earth Science, 8(July), 1–7. https://doi.org/10.3389/feart.2020.00243

Hiden, H., Minardi, S., Yasin, S., Sukrisna, B., & Ardianto, T. (2022). Determination and Mapping of the Causes of High Risk of Earthquake Hazards Using Geoelectrical Data in Bengkaung, Batu Layar, West Lombok Indonesia. Jurnal Penelitian Pendidikan IPA, 8(4), 2404–2410. https://doi.org/10.29303/jppipa.v8i4.2206

Kanata, B., Rosmaliati, Zubaidah, T., Yadnya, M. S., Zainuddin, A., Ratnasari, D., Fitratunnisa, N., & Akbar, M. F. (2024). Unraveling the Seismic Signal Anomaly at Mount Rinjani Station: In-Depth Exploration with the Detrended Fluctuation (DFA) Analysis Method in Connection with the 2018 Big Earthquake on Lombok Island, West Nusa Tenggara. Jurnal Penelitian Pendidikan IPA, 10(1), 116–123. https://doi.org/10.29303/jppipa.v10i1.6263

Khan, A., Gupta, S., & Gupta, S. K. (2020). Multi-hazard disaster studies: Monitoring, detection, recovery, and management, based on emerging technologies and optimal techniques. International Journal of Disaster Risk Reduction, 47, 101642. https://doi.org/10.1016/j.ijdrr.2020.10164.

Kurniawan, M. A., Wijaya, S. K., & Hanifa, N. R. (2023). Convolutional Neural Network for Earthquake Ground Motion Prediction Model in Earthquake Early Warning System in West Java. Jurnal Penelitian Pendidikan IPA, 9(11), 1004–1010. https://doi.org/10.29303/jppipa.v9i11.3514

Li, Z. (2021). Recent advances in earthquake monitoring I: Ongoing revolution of seismic instrumentation. Earthquake Science, 34(2), 177–188. https://doi.org/10.29382/eqs-2021-0011

Minson, S. E., Meier, M. A., Baltay, A. S., Hanks, T. C., & Cochran, E. S. (2018). The limits of earthquake early warning: Timeliness of ground motion estimates. Science Advances, 4(3), 1–10. https://doi.org/10.1126/sciadv.aaq0504

Mufarida, B. (2024). BMKG: 7.358 Gempa Bumi Guncang Indonesia Sepanjang 2024. Inews.Id. Retrieved from https://www.inews.id/news/nasional/bmkg-7358-gempa-bumi-guncang-indonesia-sepanjang-2024

Muthahhari, I., & Firdaus, M. D. (2024). IoT-Based Seismic Sensor Network Design for Early Warning System in Kalimantan : Literature Review. Journal of Computation Physics and Earth Science, 4(2), 39–46. https://doi.org/10.63581/JoCPES.v4i2.02

Pierleoni, P., Concetti, R., Marzorati, S., Belli, A., & Palma, L. (2023). Internet of Things for Earthquake Early Warning Systems: A Performance Comparison Between Communication Protocols. IEEE Access, 11(May), 43183–43194. https://doi.org/10.1109/ACCESS.2023.3271773

Pwavodi, J., Ibrahim, A. U., Pwavodi, P. C., Al-Turjman, F., & Mohand-Said, A. (2024). The role of artificial intelligence and IoT in prediction of earthquakes: Review. Artificial Intelligence in Geosciences, 5, 100075. https://doi.org/10.1016/j.aiig.2024.100075

Rosca, C. M., & Stancu, A. (2024). Earthquake Prediction and Alert System Using IoT Infrastructure and Cloud-Based Environmental Data Analysis. Applied Sciences (Switzerland), 14(22). https://doi.org/10.3390/app142210169

Rudyanto, A., Wijaya, A., Widiyantoro, S., Sahara, D. P., Rosalia, S., Wibowo, A., Pramono, S., & Putra, A. S. (2024). Performance test of pilot Earthquake Early Warning system in western Java, Indonesia. International Journal of Disaster Risk Reduction, 115, 105010. https://doi.org/10.1016/j.ijdrr.2024.105010

Sharma, K., Anand, D., Sabharwal, M., Tiwari, P. K., Cheikhrouhou, O., & Frikha, T. (2021). A Disaster Management Framework Using Internet of Things-Based Interconnected Devices. Mathematical Problems in Engineering, 9916440. https://doi.org/10.1155/2021/9916440

Topan Indra, A., Harmadi, H., & Marzuki, M. (2023). Prototype of Forest and Land Fire Monitoring and Detection System Using IoT-Based WSN Technology. Jurnal Penelitian Pendidikan IPA, 9(12), 11837–11845. https://doi.org/10.29303/jppipa.v9i12.5736

Wu, Y. M., & Mittal, H. (2021). A review on the development of earthquake warning system using low-cost sensors in taiwan. Sensors, 21(22). https://doi.org/10.3390/s21227649

Zambrano, A. ., Perez, I., Palau, C., & Esteve, M. (2017). Technologies of Internet of Things applied to an Earthquake Early Warning System. Future Generation Computer Systems, 75, 206–215. https://doi.org/10.1016/j.future.2016.10.009

Author Biographies

Arfanda Anugrah Siregar, Politeknik Negeri Medan

Erwinsyah Simanungkalit, Politeknik Negeri Medan

Nasrudin, Politeknik Negeri Medan

License

Copyright (c) 2025 Arfanda Anugrah Siregar, Erwinsyah Simanungkalit, Nasrudin

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors who publish with Jurnal Penelitian Pendidikan IPA, agree to the following terms:

  1. Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution 4.0 International License (CC-BY License). This license allows authors to use all articles, data sets, graphics, and appendices in data mining applications, search engines, web sites, blogs, and other platforms by providing an appropriate reference. The journal allows the author(s) to hold the copyright without restrictions and will retain publishing rights without restrictions.
  2. Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgment of its initial publication in Jurnal Penelitian Pendidikan IPA.
  3. Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).