Documentation of Weather Predictor
AI-Based Weather Monitoring and Analysing System
An advanced weather forecasting system that combines real-time API data, AI models, and IoT sensors to deliver accurate weather predictions. The project features:
Real-Time Data: Uses OpenWeatherMap API to display current weather conditions with a clean, responsive UI.
Machine Learning Forecasting: Utilizes Python with LSTM and regression models to predict temperature trends for the next 7 days.
IoT Integration: Employs sensors (DHT11, BMP180) with Arduino/Raspberry Pi to collect local environmental data and send it to the cloud (ThingSpeak).
Features
- Real-Time API Integration: Uses OpenWeatherMap API to display current weather conditions with a clean UI.
- Machine Learning Forecasting: Utilizes LSTM and regression models to predict temperature trends for the next 7 days.
- IoT Integration: Collects local environmental data and sends it to the cloud (ThingSpeak) using physical sensors.
Tech Stack
- Backend & ML: Python, LSTM, Streamlit, Pandas, scikit-learn, Regression models.
- Hardware & IoT: Arduino/Raspberry Pi, DHT11 & BMP180 sensors, ThingSpeak, Oled display.
- Frontend: Responsive web UI for displaying data.