Real-Time Environmental Parameter Monitoring and Temperature Forecasting Using a Custom IoT Weather Station and Linear Regression

based weather station for environmental parameter monitoring and temperature forecasting. The system includes multiple sensors connected to a microcontroller that sends data to a local server, where it is stored in an SQLite database and visualized through a custom Flask-based web platform. The platform provides real-time measurements in both numeric and graphical formats, supports temperature forecasting, enables data export, and issues alerts in case of extreme environmental conditions. The forecasting is achieved using a linear regression model trained on both historical and locally collected data. The model yielded a Mean Absolute Error (MAE) of 0.31°C and an R² score of 0.8516, indicating robust predictive performance for a lightweight model.