Case Study: a technology company achieves 95% accurate pavement defect detection in 1 hour with Crayon computer vision

Crayon reduces detection process from seven days to one hour

The customer, a large technology company, faced a significant challenge in manually detecting and measuring pavement defects using drone images. This labor-intensive process was extremely time-consuming, taking up to a week for each operational site. They engaged with Crayon to find an innovative way to leverage drone technology and drastically reduce their defect detection time.

Crayon implemented its Computer Vision solution, which involved designing a user workflow, building a solution architecture, and developing a highly accurate neural network model deployed on the cloud. As a result, Crayon delivered a model with 95% accuracy that slashed the image processing time from days down to just one to two hours per site. This solution also promises to increase measurement consistency across all sites by up to 30%.