Weather Monitoring and Prediction System for Rice Cultivation in Mandalay Using IoT and Machine Learning

The purpose of this research is to monitor and predict temperature, humidity and carbon-dioxide with the objective of increasing rice yields in the rice fields located east of Mandalay. This research focuses on monitoring the temperature and humidity of rice fields near MTU. The data are displayed on a LCD and uploaded to a server to ensure timely access for farmers. Monthly weather forecasts are provided to assist farmers in making advance preparations. The energy generated by the solar system is sufficient to meet the system’s low power consumption requirements. An ESP32 collects weather data from DHT11 sensor. CO2 data from the DM118 sensor is sent to the ESP32 via Arduino UNO using the UART protocol. These data are uploaded to the AWS Lightsail server. LSTM well-suited for time-series and sequence prediction tasks. Additionally, the data is presented in the farmers’ native language to ensure readability for non-English speakers.