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An IoT-Based Seismic Sensor Network for Earthquake Prediction and Early Warning

Students & Supervisors

Student Authors
Koushik Biswas Arko
Bachelor of Science in Computer Science & Engineering, FST
Sadia Afrin
Bachelor of Science in Computer Science & Engineering, FST
Md Anjir Jaman
Bachelor of Science in Computer Science & Engineering, FST
Hasibul Islam
Bachelor of Science in Computer Science & Engineering, FST
Supervisors
Md. Mortuza Ahmmed
Associate Professor, Faculty, FST
Bishwajit Banik Pathik
Assistant Professor, Faculty, FE

Abstract

This study combines the Internet of Things (loT), embedded systems, and disaster management technology. The project aims to develop a decentralized seismic monitoring network with real-time data collected from sensors for early detection and the issuance of a warning in earthquake zones. Objectives The purpose of this study is to create an ecosystem of scalable earthquake monitoring systems in real time based on Internet of Things (IoT) technology. The proposed system will improve disaster preparedness and response by accurately sensing ground vibrations, analytics, and automated alerts. Methodology The system will be built on ESP32 microcontrollers that house MEMS accelerometers (MPU6050/ADXL345) and GPS modules to record three-axis motion on the ground. Sensor nodes will send their data via Wi-Fi using MQTT/HTTP protocols to a cloud-based server (of which none is specific, but will use Arduino Cloud to serve as testing). The data will be logged in InfluxDB and visualized on Grafana dashboards. Alerts will be generated based on vibration thresholds and via mobile notifications or publicly activated sirens. Local data logging can be done on SD cards as well. The system will be powered by rechargeable batteries using solar panels to allow outdoor development without the need for external auxiliary power. Results and Analysis The system will recognize low-frequency ground motion, and data will be transferred to a dashboard with a mean latency of 1.6 seconds. Time synchronization with GPS capabilities ensure integrity between nodes. Data integrity will be kept solid during short connectivity issues as the system uses SD backups to retain data at each node. Seismic Sensor Node (ESP32 + Accelerometer) Wi-Fi Transmission Cloud Server + Database Dashboard & Alert System Mobile / Siren Alerts Figure 1: System Flowchart of the IoT-Based Seismic Network All solar-powered nodes will be on and running for at least 72 hours. Through the dashboard, clear visualization will be demonstrated with the ability to add or remove widgets to view only relevant data. Modularity, scalability, and low cost are the key attributes of the system. Transient ambient noise captured by the sensors, which may produce false alerts, can be reduced with machine learning-based filters in future increments of the testing. References [1] A. Goap, S. Sarkar, A. Roy, C. R. Krishna, and S. Kumar, “An IoT-Based Architectural Framework for EarthquakeWarning System Using Low-cost Heterogeneous Seismic Sensors,” Arabian Journal for Science and Engineering, May 2025, doi: 10.1007/s13369-025-10221-x. [2] I. Muthahhari and M. D. Firdaus, “IoT-Based Seismic Sensor Network Design for Early Warning System in Kalimantan: Literature Review,” JoCPES, vol. 4, no. 2, Mar. 2025, doi: 10.63581/JoCPES.v4i2.02."

Keywords

Seismic IoT Sensors Detection Monitoring

Publication Details

  • Type of Publication: Conference 
  • Conference Name: IEEE CS BDC Summer Symposium 2025
  • Date of Conference: 18/07/2025 - 18/07/2025
  • Venue: Hajee Mohammad Danesh Science and Technology University (HSTU), Dinajpur
  • Organizer: Faculty of Computer Science and Engineering
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