SmartBinder: An AM-based, AI-driven system for Sustainable Crack Repair in Infrastructure

Australia’s road authorities spend significant resources maintaining road networks, with pavement cracking a major and largely preventable cause of deterioration. Current detection and repair methods rely heavily on manual inspection and application, often missing early cracks and producing inconsistent results.

Civiltech Solutions, in collaboration with Charles Darwin University, is developing an AI-powered crack repair system that automates the detection, classification, and sealing of road defects. Built on Civiltech’s LiDAR and AI road defect platform by Cyvl, the system combines advanced road scanning with a robotic binder injector capable of applying sealing material layer-by-layer with high precision.

The project includes development of a custom binder, AI training for crack classification, additive manufacturing of lightweight dispenser components, and integration of a robotic prototype to be validated at Manufacturing Readiness Level (MRL) 6. The result is a scalable, data-driven solution that improves repair quality while reducing labour demands and material waste in road maintenance.