Earthquake prediction is a crucial area of research aimed at mitigating the risks associated with seismic disas ters. This project proposes a system that combines seismic wave generation and detection with real time data analysis for improved earthquake monitoring. The setup utilizes an L298 motor driver to generate controlled vibrations that simulate seismic waves, allowing us to study ground motion behavior in a controlled environment. An accelerometer and a vibration sensor are employed to detect and measure these vibrations, capturing precise data on ground movements and potential disturbances.

The collected seismic data is processed and analyzed to identify patterns that could indicate imminent seismic activity. The system is designed to operate efficiently, with sensor data being transmitted to an Android application in real time. This mobile application provides a user-friendly interface for monitoring seismic activity, visualizing data trends, and receiving alerts for potential earthquakes. The real-time accessibility ensures that users are always informed of any concerning activity, enabling them to take timely action to ensure safety.

By leveraging the L298 motor, accelerometer, and vibration sensors, the project offers a cost-effective and scalable solution for earthquake monitoring. The integration of mobile technology through the Android app makes the system highly practical, bringing advanced seismic analysis capabilities directly to users. This approach not only enhances community preparedness but also demonstrates the potential of combining hardware and software solutions to address significant challenges in natural disaster prediction and management.