The City of Houston (COH), Texas is now actively identifying which roads to repair using a combination of ArcGIS, Machine Learning, and Image Recognition. Hear this preview of our talk at EnerGIS 19.
The COH area contains approx. 15,000 lane miles that are heavily used and need regular repairs. In the past, the city relied on a Street Surface Assessment Vehicle (SSAV) to inspect and provide data for recommended maintenance for this immense quantity of roadways. The data gathered by the SSAV resulted in a large amount of GIS data that required a system able to quantify and interpret that huge amount of data. Argis Solutions was selected as part of the team who implemented a machine learning and image recognition project utilizing this re-purposed RQMV. The application of machine learning combined with image analysis and recognition to a Public Works management system (SSAV/StreetSaver systems) will assist with creating valuable outcomes for the City. Learn more about how the project was envisioned and implemented and how the COH is benefiting from this new technology.
This will be a 40-minute online presentation with time for Q&A at the end.