The project aims to advance EGNSS-based, low-cost sensor technologies and AI-driven software (utilizing machine learning and machine vision) to market readiness (TRL8-9). These solutions will detect, classify, and geo-reference road surface anomalies for cost-effective pavement assessment via participatory detection.

The system provides continuous road condition data, enhancing traffic infrastructure monitoring and public safety. It envisions using smartphone-like technology for data collection and analysis in GIS-based pavement management systems, positioning the developed tools as transformative for the transport and infrastructure industry.