39% of US roads are graded under poor or mediocre quality. Continued deterioration escalates costs and increases GHG emissions associated with roadway maintenance. US infrastructure collectively represents one of the most carbon-intensive industries—small improvements, like proactively identifying and fixing
cracks before they become potholes, can mitigate several million tons of CO2 emissions. We want to conduct a feasibility study on using cameras in UIUC vehicles around campus to collect real-time data on road conditions. We would feed this data into computer vision models where road damage can be systematically mapped out, and ML algorithms can optimize for less carbon-intensive repairs.

This proposal directly funds:
1. Garmin Dash Cameras
2. Real-Time Dash Cameras
3. SD Cards
4. External Hard Drive & Cloud Storage