Auto Wise: An AI/ML-Based Vehicle Valuation and Visual Damage Inspection System

DOI

No DOI

Published In

Volume 5, Issue 3 (2026)

Published Online

September-December 2026

Pages

626-632

Article Type

Original Article

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The used-vehicle market provides an important option for buyers who want affordable transportation and sellers who want to recover value from an existing vehicle. However, estimating a fair price can be difficult because the value of a vehicle depends on several factors, including make, model, manufacturing year, distance travelled, fuel type, transmission, ownership history, maintenance, visible condition, and local market demand. AutoWise is proposed as an integrated AI/ML-based vehicle valuation and inspection platform intended to support more informed used-car decisions. The system combines a machine-learning model for estimating a vehicle's market value with a computer-vision component for identifying visible damage, such as dents and scratches, from suitable images. The platform is also designed to present the results through a readable inspection and valuation report and to support marketplace functions such as user accounts, vehicle listings, seller information, and buyer interest. A Python-based backend can coordinate the prediction model, image-processing workflow, database operations, and web interface. Historical vehicle data is used to train and evaluate the price-estimation model, while image data with appropriate annotations is required for damage detection. The predicted price and damage findings are presented as estimates rather than guarantees; photographs cannot establish every hidden mechanical or structural fault. This paper describes the problem, proposed system, related technical concepts, modules, architecture, development methodology, testing strategy, limitations, and possible future improvements for AutoWise.