Case Study: AI-Powered Damage Detection for Vehicle Inspections

IQTransit partnered with a rental vehicle inspection company to build a highly accurate, AI-driven
damage detection application. This enterprise-grade platform automates photo capture and
visual damage recognition for fleets, ensuring accountability and reducing human error in the inspection process.

Technologies Used

• Backend: Java, Grails Framework, MySQL, AWS Cloud, Microservices
• Frontend: HTML5, CSS3, Bootstrap 4, JavaScript (Vanilla)
• AI & Computer Vision: Python, PyTorch, TensorFlow, YOLOv5
• Infrastructure: Hosted entirely on AWS (EC2, S3, RDS, Lambda)

Solution Overview

The platform supports automated damage detection using computer vision models, built and trained using
real-world vehicle imagery. Integrated into a microservice architecture, it seamlessly delivers instant analysis
to end-users with an intuitive web dashboard.

– Impact

• Reduced manual inspection effort by over 60%
• Enhanced accuracy in identifying dents, scratches, and structural damage
• Improved accountability with image-based reports
• Real-time inspection scoring and AI confidence ratings

This solution is actively used by rental agencies, logistics fleets, and vehicle marketplaces to standardize
inspections and cut operational costs with AI automation.