- This application automates exterior and undercarriage vehicle inspection using deep-learning and AI technology
- A vehicle is driven through a scanning platform, and the system detects material degradation, dents, abnormal objects, structural deformation, leaks, brake and exhaust system issues, and tire/wheel condition by comparing the new scan against existing data and previous images
Case Studies
AI Undercarriage Inspection Tunnel
26 Jun 2026Edge AI GPU platform for multi-angle vehicle exterior and undercarriage inspection using cameras and deep-learning inference.
Overview
ChallengesThe main challenges were
- Manual inspection is slow, labor-intensive, and can miss hidden defects or threats simply because a human inspector's viewing angles and coverage are limited compared to a multi-camera scanning rig
- The system has to sustain inspection quality while increasing throughput and processing multi-angle camera data reliably, vehicle after vehicle, without slowing the line down
ObjectivesThe system needed to
- Automate vehicle exterior and undercarriage inspection
- remove the coverage limitations of manual inspection
- process multi-angle camera images
- run AI inference at the edge
- detect anomalies quickly and consistently
Solution DeliveredThe solution included
- A rugged edge AI GPU platform was installed to process camera data locally for deep-learning-based inspection as each vehicle passes through the scanning tunnel
- The platform supports PoE+ connectivity for GigE cameras and USB connectivity for USB cameras, which let the installation capture synchronized multi-angle imagery around the entire vehicle — including the undercarriage — as it moved through, and run inference on that imagery in real time rather than queuing it for later review
- Because inference happens locally on GPU-accelerated hardware rather than being sent off-site, results are available essentially as soon as the vehicle clears the tunnel
Products referenced in the source material include
Conclusion
This story is useful for Manufacturing because it demonstrates high-value visual inspection with AI at the edge. It can be positioned for automotive manufacturing, service inspection, and security inspection where consistency and speed matter.
