This is an IoT project for Air Quality Monitoring and analyze of collected data with Machine Learning models.
Dataset in different formats for data of: pm2.5, pm10, temperature, humidity, air pressure, alarm.
Python script for RasberryPi 3 and sensors configuration.
Runs on RaspberryPi 3 to measure and collect data through sensors - air_quality_sensor.py
Python and Jupyter scripts with ML models for data analyze for below use-cases.
ML Algorithms:
- Decission Tree
- Random Forest
Use cases:
- Predict alarm status for next n hours
- Predict future n values of alarm status
- Predict dust (or other parameters) based on historic samples in time-series
- Predict dust (or other parameters) future n values
- Decission Tree for alarm status based on all parameters historic values
Clone the repo and install the necessary libraries:
git clone https://github.com/albamerdani/iot_air_quality_ml.git
- Install python3 and pip or pip3 - https://realpython.com/installing-python/
- Install libraries under requirements.txt
pip3 install -r requirements.txt
- Run python/jupyter scripts of different use-cases