A couple of partners and I, developed predictive models using binomial logistic regression and random forest to analyze pollutants like PM10, PM2.5, CO, O₃, NO₂, and SO₂ for air quality monitoring stations in the northern zone of Monterrey's metropolitan area, based on data from Nuevo León's atmospheric monitoring system.
The project posed a significant challenge, as I aimed to create more than just a simple forecast model, which many may not fully understand or be familiar with. Inspired by the potential impact, I developed a new website for the Sistema Integral de Monitoreo Ambiental (SIMA), offering a more user-friendly portal. This platform provides valuable information for Monterrey residents who are curious about air quality and wish to stay informed about the government's latest air pollution policies.
During the development of the new SIMA website, I also took on the task of creating a REST API from scratch to fetch the real-time data published by SIMA. This was a necessary step due to the specific way their Apache servers handle and capture information. By designing this API, I ensured seamless integration of the latest data into the website, allowing users to access up-to-date information on air quality and government actions. The API improved the efficiency and accuracy of data retrieval, aligning with the goal of making the portal a more reliable and user-friendly resource for the public.
Update: ExpoIngeniría 2024
The SIMA project was selected by our professors to be presented at ExpoIngeniería 2024, an semestrally event where students showcase their projects to the public. The project was well received by the audience, and we were able to demonstrate the website and the predictive models to the public. The project was also presented to the SIMA team, who were impressed by the work done and to multiple organizations in the area, who were interested in the project not only to monitor Monterrey's air quality but also to implement it in other cities in Mexico. In my opinion, the project was a success, and I am proud of the work done by my partners and me.
- Websitehttps://sima-nuevoleon-ai.vercel.app
- Platform Windows 11
- Front end Next.js, Streamlit
- Back end Scikit-learn, R, Python, Streamlit