Technical Information

How are we addressing this problem? The purpose of this simulation is to demonstrate a proof of concept as to how different vehicle fleets could be utilized to measure various health aspects of a city, and which would be most economic and efficient. 

We have chosen to create our simulation in Python, as it is a high level programming language with many libraries out there ready to adapt to our needs. Specifically, we are using the OSMNX library, which stands for OpenStreetMapsNetworkX, which is built on top of GeoPandas, NetworkX, and the Matplot library. 

To gather our electrical pole data, we have turned to OpenData government portal links, which house various datasets collected by governments and third party companies for developers and academic research. OpenData portals contain all sorts of things, from electrical pole and streetlight data, to police beats and housing price heatmaps. 

For our simulation, we are focusing on electrical pole data, but these are some examples of the other ways in which our simulation could be applied. For example instead of sensing electrical poles we could do fire hydrants, or monitor air quality at many points in the city throughout the day.