Project: Walkable Networks
Year: 2013
Professors: Thomas Kearns, Jordan Kanter with Keith Besserud, Thomas Hussey (SOM) 
Partner: Adam Weissert

Walkable Networks analyzes the city of Chicago for the most ideal routes to take by foot.

This project is an attempt to produce an autonomous process capable of producing accurate investigations of the metropolis using quantifiable data while maintaining the specificity of most urban analysis. In the studies for this project, the routes from CTA stops to restaurants and bars within a mile were analyzed, as it is a typical start and end location for occupants of the city and tourists. Due to the amount of data available in the city of Chicago the possibilities for start and end locations for these routes are limitless. 

Using the Dijkstra Algorithm, the Walkable Network Prototype found paths from one point to another, searching for the lowest cost to get there. "Cost" is typically attributed to distance to find the shortest paths, but Walkable Networks incorporates data from the city to influence the paths for the benefit of the traveller. This data included thickness of sidewalk, amount and type of crime, number of Facebook likes of businesses on blocks, vegetation on the street, 311 reports, etc.

This data could also be manipulated to suit the needs of an individual. This sets the foundation for development of this prototype. This development could range from  a smartphone app that finds the most ideal routes for tourists to a program that identifies need for commercial development in the city.