This project aims to leverage machine learning techniques and capabilities to detect anomalies on air quality data and predict air quality trends. It aims to address the problem of forecasting air pollution levels and identifying unexpected pollution irregularities and spikes in environmental data. By utilizing datasets aggregated from multiple sources, the proposed system aims to provide an extensive real-time overview of air quality trends. The system would primarily utilize machine learning models to reach accurate predictions of key air quality indices (e.g. AQI) in different states across Nigeria.
- Make sure you have Python installed.
- A streamlit account
- A GitHub Page
- Clone the team's repository:
git clone https://github.com/AISaturdaysLagos/Cohort8-Mandela.git
- Sign up on Streamlit
- A python environment
pip install -r requirements.txt
To run the app, use the following command:
streamlit run Air_Quality.py
- Enter the state name and coordinates for prediction.
- Explore the air quality pollutants on the map.
- Feel free to customize and enhance the app according to your needs!
Big thanks to the AI Saturday Lagos team for providing a platform that not only teaches machine learning but plays a pivotal role in democratizing artificial intelligence in Nigeria🙌.
Special thanks to Joscha Cüppers for his invaluable support and exceptional hands-on mentorship🙌.
Team Mentor
Project maintainers/Team members