P2 - gAR-age: A Feedback-Enabled Blended Ecosystem for Vehicle Health Monitoring

Standard vehicle maintenance activities can be challenging, time-consuming, error-prone, and expensive. While there is a lot of innovative work that has incorporated latest technologies to provide newer forms of interaction between users and vehicles, there has been less inclination towards utilizing these technologies to enhance activities like vehicle maintenance. The ability to draw parallels simultaneously from physical interaction with vehicles and analysis of recorded data is vital to support prompt and effective decision-making. To blur the disparity between these real and virtual worlds, we present "gAR-age"- an ecosystem that enables maintenance personnel to interact with both worlds in a common setting. By learning from historical changes in vehicular components, user behavior, and feedback, this blended ecosystem allows multi-channel communication among users, featuring personalized contextual insights, thereby enabling users to make data-driven decision on the fly.