Automating Device Diagnostics with AI-Based Mobile Screen Damage Detection
Manual inspection of mobile devices for screen damage is subjective, time-consuming, and prone to inconsistency—especially in high-volume environments like service centers, insurance assessments, or quality control units.
To automate and standardize this process, an AI-powered object detection system was developed to identify and classify mobile screens as broken or intact from images. The model first detects the mobile device as an object within the image and then analyzes the screen to determine its condition.
This intelligent diagnostic tool enables rapid, accurate assessments without human intervention, improving operational efficiency and consistency. It is ideal for use in automated device check-in systems, repair service triage, and remote diagnostics through app-based submissions.
Technology Used
AI-Based Mobile Screen Detection
Developed an AI model to detect and classify mobile screens as broken or intact—enabling fast and accurate assessment from images.
Object Detection from Images
Automatically identified mobile devices within uploaded images, isolating the relevant object for analysis.
Damage Classification with High Precision
Classified the detected mobile screen as broken or unbroken—supporting use cases in diagnostics, returns, and insurance claims.
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