DESIGN AND CONSTRUCTION OF A RAINFALL PREDICTION DEVICE USING MACHINE LEARNING AND TINYML

A rain detector using TinyML technology is designed and constructed to detect rainfall based on temperature, pressure, and humidity sensors.The sensor sends digital corresponding signals to the microcontroller to be analyzed according to the defined instructions. The TinyML was trained with a dataset of rain and non-rain events. It was tested under various weather conditions to assess its accuracy. The device achieved an accuracy of over 75%. It could be a useful tool for a weather monitoring system.