Cost-Effective Pavement Monitoring System and Management at the Local and State Level Public Agencies

Status: Ongoing

Funding Agency: New Jersey Department of Transportation (NJDOT)

Abstract: 

This project will enhance and validate Rowan CREATES’ smartphone-based AI pavement distress detection approach to provide a low-cost, scalable alternative to manual inspections and expensive automated survey vehicles for local agencies. The team will develop a standardized smartphone data collection protocol, collect and annotate pavement imagery across controlled test sections representing a full range of NJDOT 2025 SDI conditions, and upgrade the AI models to quantify distress measurements, classify severity, and compute SDI-compatible outputs. The resulting dataset and validated models will enable local agencies to submit consistent, data-driven pavement needs and help NJDOT prioritize local aid and preservation actions more transparently while supporting statewide asset management, safety, and resiliency goals.

Principal Investigators: Dr. Yusuf Mehta, PhD., Dr. Ayman Ali, PhD., Dr. Surya Teja Swarna, PhD.

Links to Publications: