The impacts of natural disasters can be far-reaching and devastating, affecting not only the immediate environment but also the lives of individuals and entire communities. These disasters, such as earthquakes, floods, and wildfires, can cause widespread destruction of infrastructure, homes, and agricultural lands, leading to significant economic losses and loss of life. Some of these disasters, such as wildfires sparked by human activity, can be prevented in some cases by taking certain proactive measures. But other events, like earthquakes, are entirely out of our control.
When prevention is not possible, the next best thing is early detection. Early warning systems for earthquakes allow people to flee structures that could be hazardous when the ground starts shaking. These systems also allow us to take other steps that can minimize the damage caused by an earthquake. Naveen Kumar believes that if early earthquake detection systems were more common, a great many tragedies could be avoided. For that reason, Kumar decided to build a prototype system that demonstrates how inexpensive and accessible this technology can be.
Kumar’s earthquake detection system is built around the Particle M-SoM LTE-M/2G + Wi-Fi, a multi-radio module with a 200MHz Arm Cortex-M33 microcontroller, 16MB of flash memory, and 4.5MB of RAM. This choice ensures fast processing of sensor data and reliable communication over a variety of wireless networks. It is mounted on a Particle M.2 SoM Breakout Board, which provides connectivity options for external sensors and actuators.
Integrated into this hardware is a Grove D7S Vibration Sensor sporting a highly precise earthquake detection module developed by Omron Corporation. This sensor utilizes a three-axis accelerometer and a specialized Spectral Intensity (SI) value algorithm to determine the destructive force of an earthquake. The SI value is strongly correlated with seismic intensity scales used in Japan, making it a reliable measure for detecting and classifying earthquakes.
To show system status and alerts, the project uses a SparkFun 16×2 LCD display, which communicates with the microcontroller using the I2C protocol. The system also includes an M5Stack Watering Unit, which simulates an industrial water pump. This pump is powered separately using an M5Stack USB Type-C to Grove module due to its high current draw. A buzzer is also built into the system to give an audible alert.
When the system detects an earthquake, it immediately sends an alert via the Particle Console, a cloud-based IoT platform. This alert is transmitted to a mobile app that users can access in real time. The app can also be used to manually trigger emergency actions, such as shutting down water pumps to prevent infrastructure damage and secondary disasters like flooding.
Kumar’s earthquake detection and response system demonstrates the potential of cost-effective, reliable, and scalable solutions for disaster management. By leveraging powerful IoT hardware and cloud connectivity, the system not only provides timely alerts but also enables automated safety measures to minimize earthquake-related damage. With further development, systems like this could become a crucial part of emergency preparedness strategies worldwide.
This earthquake detection system is inexpensive and accessible (📷: Naveen Kumar)
The Particle M-SoM LTE-M/2G + Wi-Fi module (📷: Naveen Kumar)
A Grove D7S Vibration Sensor (📷: Naveen Kumar)
Source link
