Landslide Early Warning System Based with Qubitro and Arduino Nano 33 IoT.
Landslide Introduction
Landslides or often called soil movements are a geological event that occurs due to the movement of masses of rocks or soil with various types and types such as falling rocks or large lumps of soil.
In general, landslides are caused by two factors, namely driving factors and triggering factors. Driving factors are factors that affect the condition of the material itself, while trigger factors are factors that cause the movement of the material.
We propose a landslide detector prototype that measures the vital parameters of landslides at the same time using an accelerometer and gyroscope sensor.
The sensor detection results will be received by the transmitter and transmitted wirelessly to the receiver unit which will then be displayed on a digital information board in the form of a warning system in landslide-prone areas. Thus, this information can be accessed easily by the public.
The prototype is expected to be a tool for early mitigation of landslides that are precise, accurate, and can reduce the risk of casualties. Besides, the expected outcome of this research is the publication of scientific articles as initial information in the development of landslide disaster mitigation studies.
List of Materials
- Arduino Nano 33 IoT
- PlatformIO
- Visual Studio Code
- LSM6DS3 IMU Sensor
- A Breadboard
- A USB Cable
Landslide Early Warning System Based on Internet of Things and Data Analytics
Using LSM6DS3 accelerometer and gyroscope module sensor embedded with The Nano 33 will be used to collect the raw data. Then, the data will be analyzed by Qubitro Analytics. Arduino Nano 33 IoT is an advanced Arduino dev kit designed for IoT implementation. It has a network module such as WiFi and BLE, allowing us to send the data to Qubitro over MQTT and HTTP by using internet connectivity.
This project is to aims at how we could integrate LSM6DS3 (accelerometer and gyroscope) module sensors embedded on Arduino nano 33 IoT, so this dev kit is very easy to do an experiment. The data was published to Qubitro Cloud, accelerometer, and gyroscope data visualized on the Qubitro dashboard.
