A simple weather station that uses a Raspberry Pi Pico W and sensors to collect temperature, humidity, pressure and light data. The data is then sent to a cloud service (Azure IoT Hub) for storage and visualization.

A ML model is used to predict the weather based on the collected data. The model is trained using a dataset of weather data from Kaggle.

1. Clone the repository
2. Create a virtual environment for the server and install the required packages

python3 -m venv venv
source venv/bin/activate
pip install -r requirements.txt

3. Create a config.json file inside the server directory with the following content:

{
    "CONNECTION_STRING": "<your-iot-hub-connection-string>",
}

4. Create a config.json file in the root directory and upload it to the Raspberry Pi Pico W:

{
    "WIFI_SSID": "<your-wifi-ssid>",
    "WIFI_PASSWORD": "<your-wifi-password>",
    "SERVER_URL": "<your-server-url>",
}

5. Upload the BME280 and lcd libraries to the Raspberry Pi Pico W
6. Run the server

flask run --host=0.0.0.0

7. Run the main.py script on the Raspberry Pi Pico W

• Raspberry Pi Pico W
• BME280 sensor
• LDR sensor
• LCD display 16x2

• MicroPython
• Azure services (IoT Hub, Stream Analytics, Power BI)