The PAVE-SCAN project aims to build EGNSS-based and AI-driven technologies for the high-accuracy, yet low-cost, assessment of roadway pavements, and to improve the safety of drivers and the operations and maintenance of roadway networks. The maintenance, performance, and safety of roadway infrastructure are critical concerns for modern societies. Growing traffic volumes, rapid urbanisation, and ageing infrastructure increase the need for efficient and scalable methods for monitoring pavement condition. Detecting surface degradation (such as cracks, roughness, potholes, or deformation) at early stages allows timely maintenance, reduces operational costs, and enhances safety. Conventional inspection approaches, including manual surveys or specialised survey vehicles, are costly, labour-intensive, and difficult to perform at high frequency or across large networks. PAVE-SCAN, and the derived PAVE-SENS technologies, address this challenge through a scalable, low-cost, AI-enabled solution for continuous pavement assessment. Funded under Horizon Europe and supported by the European Union Agency for the Space Programme (EUSPA), the project combines low-cost sensing technologies, GNSS-based positioning, and data-driven analytics to monitor road conditions at high resolution and frequency. By leveraging vehicles already circulating on …