TYRZ AI – AI-Powered Tyre Health Scanner Using Computer Vision
Author
Aadhil Yunis U, Dhanushkumar R, Aasif Khan S, Ajayrathnam R,M. Mithun
Abstract
Tyre tread depth is a safety-critical quantity that most drivers check only by eye, and measuring it normally needs a depth gauge. This paper describes TYRZ AI Tyre Health Scanner, a web prototype that asks a user to photograph a tyre tread with a reference object of known size in the frame, and then presents a tread-depth value, a condition label and an estimate of remaining tyre life in a health report. The prototype is hosted as a login-protected web portal, branded “TYRZ // AI Telemetry”, with pages for scanning, a health report, a vehicle record and a description of the AI. The paper documents what could be observed from the deployed interface and two screenshots, namely the account workflow, the guided photo-capture page and the calibration instructions, and states what could not be observed: the image-analysis method, the model, the accuracy of the reported depth and the basis of the remaining-life figure. No measurement accuracy, latency or user-study results are reported. TYRZ AI supports inspection decisions only and does not replace a physical tread-depth measurement or a professional tyre inspection.
Keywords
tyre health; tread depth; computer vision; reference-object calibration; vehicle safety; web application; decision support
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References
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