Inspiration: In our breadth class, we are working with the organization Physicians, Scientists, and Engineers for Healthy Energy (PSE), who is one of the first to deploy air quality monitoring in a localized manner. This means that there is an extra wealth of data that will come, and making sense of that data is what we hope to do.
Our project demonstrates a mapping of pollution levels over time. Given the concentrations of pollutants recorded by sensors placed strategically throughout an area, we use statistical analysis to identify the impact of different types of pollution on a region allowing for future environmental decisions to be more informed.
Tech: We used Esri ArcGIS to develop our visualization, and we used flask in order to set up a REST endpoint to transfer data.
Challenges: We initially tried to use polygons to show regions of pollution, but this proved too computationally intensive given the amount of time we currently have. Many other problems arose from learning ArcGIS, which was also very frustrating to use
Accomplishments that I'm proud of none
What I learned ArcGIS, a lot of python, flaskCORS, and more
future plansWe will soon gather real data from the sensors PSE is setting up within the next year. We are also hoping to make this animated, and hopefulyl make the information presentable as a form of educational material
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