This project is a data ingestion system that aggregates weather and soil moisture data, analyzes and visualizes the data, and give crop yield predictions.
The system collects weather data from various sources, such as weather stations and meteorological APIs. It also gathers soil moisture data from sensors placed in agricultural fields.
The system incorporates machine learning algorithms to train a crop prediction model. It uses historical weather data, soil moisture levels, and other factors to predict crop yields and identify potential risks.