Weather Prediction from Satellite Image Using Machine Learning

Abstract

Weather plays an important role in farming and planning. This project, titled “Weather Prediction from Satellite Images using Machine Learning,” aims to create a smart system that analyzes weather conditions from satellite images. It helps farmers make informed decisions about irrigation and crop management. The project has three main features: Image-Based Weather Prediction, GPS-Based Weather Prediction, and an Agricultural Chatbot.The first feature uses a Convolutional Neural Network (CNN) model trained on labeled satellite weather data. It classifies weather conditions like cloudy, sunny, foggy, and rainy based on images uploaded by users. After predicting the weather and considering the crop details provided by users through speech-to-text, the system recommends how much irrigation water to use.The second feature predicts the weather based on the user's current location obtained through GPS. It also offers specific guidance on water usage. The third feature is an agricultural chatbot that answers questions related to farming. This includes advice on suitable pesticides, crop recommendations for different seasons, and crop management practices.By combining machine learning, natural language processing, and location-based prediction, this system provides an interactive and user-friendly solution to help farmers make better decisions.