An Intelligent AI-Based Vehicle Breakdown Assistance System with Network-Aware Mobile Deployment

Abstract: When a vehicle breaks down in the wilderness, finding a reliable connection to get help or assistance is often difficult or sporadic. For this reason, this study proposes an AI-based intelligent assistant, IntelliFix, to help users with broken-down vehicles through a Progressive Web Application (PWA)-based mobile system. The classification and semantic matching functions of the app are based on a transformer-based NLP. This enables accurate interpretation of the user's breakdown by gathering both data and integrating the user's account within the context of the app, regardless of whether or not the user was connected to the network. An additional aspect of the proposed Progressive Web Application (PWA) is its use of GPS and OpenStreetMap to geocode the location of broken-down vehicles and rank them in proximity to nearby repair shops. The application will enable users to report repairs via WhatsApp as well as make sequential voice calls to various mechanics. The classification process produced an accuracy of 91.05%, and the semantic matching process had an accuracy of 99.47%. In summary, the breakdown assistance system presents an increase in mobilization and efficiency of providing intelligent roadside assistance.

Keywords: Vehicle Breakdown Assistance, Artificial Intelligence, Natural Language Processing, Progressive Web Application, Network-Aware Systems, Semantic Matching, OpenStreetMap, Intelligent Transportation Systems