Assessment of Road Conditions on the University of Illinois Campus: Integrating Mobile, Drone, and Satellite Imagery

Monitoring the condition of concrete and asphalt pavements is essential for ensuring their sustainability and structural integrity. Traditional road inspection methods are costly and dependent on the inspector's expertise. To overcome these limitations, we developed robust image-based techniques independent of operator skills. Our advanced algorithms for rapid image processing achieved a high correlation with traditional Pavement Condition Index (PCI) assessments (R² = 0.97). We integrated mobile, drone, and satellite imagery to assess road conditions on the University of Illinois campus, focusing on detecting and repairing distressed pavements. Data was collected from the B-1, E-14, and F-23 parking lots. Specifically, the F-23 lot showed significant degradation with ratios of 8.32% (iPhone), 7.91% (drone), and 7.64% (satellite). This project also focuses on repairing distressed concrete pavements on the University of Illinois campus, aiming to enhance their appearance. Thus, we propose practical methods for pavement repair, including preparation steps before applying our developed APTES-based penetrating sealant, which costs roughly 1/5th of a similar commercial product. This sealant with an application rate of 300 ft2/ gal significantly enhances concrete durability by creating a hydrophobic layer, providing long-lasting protection against moisture and chemical intrusion.