What is wind_energy_monitor?

Wind Energy Monitor is a Python web application that estimates how much electricity a wind turbine would generate based on live weather conditions at your location. You open it in a browser, it detects your location automatically (or you enter a pin code), fetches current wind speed and temperature data from a weather API, and runs that data through a trained machine learning model to produce an energy output prediction. The prediction models are built with Random Forest and XGBoost, two common machine learning approaches for regression tasks. They are trained on atmospheric measurements and turbine physics to translate conditions like wind speed into estimated power output in kilowatts. You can adjust turbine settings such as rated capacity and threshold values to match different turbine types. The interface is built with Streamlit, a Python library that turns scripts into interactive web dashboards without requiring a separate frontend codebase. Charts are rendered with Matplotlib. The README describes the feature set and technology choices but does not include installation instructions, setup steps, or sample outputs. The project appears to be a demonstration or prototype rather than a production-ready tool.