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.
Augmented Street Art: a Critical Contents and Application Overview
Street art is a growing phenomenon. The frequent appearance of works, projects, and events in this area reveals its increasing social and cultural role worldwide. The chance of digitizing art represents a benefit to defining cultural paths on the territory, providing an additional tool to understand and interpret it. Street art is characterized by peculiar aspects that make it unique in the artistic panorama. The democratization of contents and the physical decay of the work are two pillars. Any digitalization and communication project should consider them carefully, proposing a knowledge model respectful of the art. Augmented Reality (AR) is a representation tool that leads to achieving that delicate bal-ance between the real and the digital, enhancing the specificities of both. The authors start from the experimentation about artwork digitalization, connecting image deterioration with image recognition. Besides, they show some possible applications in Rome through a critical analysis of the domain, open-ing some future multidisciplinarity scenarios.