AR-Bicycle: Smart AR Component Recognition to Support Bicycle’s Second Life

This paper presents an augmented reality–based system for object and component recognition aimed at supporting product maintenance, repair, and lifecycle extension within a circular economy framework. The research focuses on bicycles as a case study, proposing a mobile application that combines 3D modeling, computer vision, and AR visualization to identify components and link them to contextualized repair information. The methodology integrates geometric analysis, average-shape modeling, and deep learning–based object recognition to enable scalable detection across different bicycle types. The workflow includes the definition of points of interest (PoIs), the creation of a generalized 3D model, and its implementation within Unity and Vuforia environments for AR interaction. As illustrated in the methodological diagram (Fig. 4, p. 613), the system connects recognition, information retrieval, and user interaction through a structured pipeline. The application allows users to visualize repair instructions, access multimedia content, and locate nearby service points, bridging digital knowledge and physical intervention. Results demonstrate the effectiveness of AR in improving component awareness, facilitating repair practices, and promoting sustainable product use, while highlighting limitations related to geometric variability and recognition accuracy across different product typologies.