A professor from the University of South Florida is pioneering an innovative AI-driven dashcam designed to enhance the efficiency of post-storm road evaluations in Sarasota County. This advanced technology aims to expedite the recovery process after natural disasters by automating the inspection of road conditions.
The prototype dashcam is programmed to detect road safety issues such as potholes, flooding, downed trees, and damaged signage. Developed by Hao Zhou, the system emerged from the observation that the Florida Department of Transportation and Sarasota County faced staffing shortages in the aftermath of Hurricanes Helene and Milton. The AI solution is compatible with vehicles manufactured from 2015 onward, significantly reducing the time required for damage assessments from potentially three days to a swift six to eight hours.
While the benefits of this technology are clear, it remains uncertain when local and state transportation departments will officially implement this software on a permanent basis. Additionally, the potential adoption of this open-source technology by other counties across Florida remains to be seen, with public testing slated for completion this fall.
The increased speed of damage evaluations is crucial for enabling local teams to mobilize repair resources more effectively in the wake of major hurricanes. This automated system serves as an additional set of eyes for drivers, enhancing worker safety by minimizing fatigue and helping protect crews from hidden dangers, such as sudden flooding.
Looking ahead, Zhou's team is poised to conduct further road tests, particularly during heavy rain events. They aim to conclude their testing this fall and subsequently present the technology to the Florida Department of Transportation and Sarasota County, with plans to make it available as open-source software for other jurisdictions to utilize.



