ClimeX: Next-gen Weather Prediction System

Accurate weather information at the local level plays a crucial role in fields like farming, emergency response, transport planning, and environmental studies. Most current weather prediction systems depend on satellite data and large numerical models, which often overlook rapid changes happening close to the ground. This limitation is especially noticeable in rural and semi-urban areas. In addition, traditional automatic weather stations are expensive and installed in limited locations, leaving many regions without proper coverage. This work introduces ClimeX, a compact and low-cost IoT-based weather monitoring system developed for real-time local observation and short-term weather prediction. The system collects environmental data directly from the surroundings using sensors that measure temperature, humidity, air pressure, wind speed, and rainfall. These sensors are connected to a Raspberry Pi, which sends the data securely to the AWS IoT Core platform using the MQTT communication protocol. Along with sensor readings, satellite images and cloud information are fetched through external APIs to improve prediction quality. A machine learning model trained on historical data from the Indian Meteorological Department (IMD) analyzes both live and past data to generate short-term forecasts and early warnings for extreme weather conditions. All outputs are displayed on an interactive web dashboard that allows users to monitor weather conditions easily in real time. Overall, the proposed system provides an affordable, scalable, and dependable approach to localized weather forecasting, making it well suited for smart agriculture, disaster readiness, and environmental analysis.