In urban environments, the demand for convenient and reliable automotive services is ever-growing, yet locating a nearby garage or service center remains a significant challenge for drivers. GarageLocator is a real-time platform designed to bridge this gap by leveraging geolocation technologies and comprehensive service databases to connect users with nearby automotive service providers. This paper explores the development and implementation of GarageLocator, detailing its architecture, data integration methods, and user interface design. The platform incorporates real-time location tracking, an extensive directory of garages categorized by services offered, and user-generated reviews to enhance decision-making. Additionally, GarageLocator employs a recommendation algorithm that adapts to user preferences and history, providing personalized suggestions. We conducted a mixed-methods evaluation, combining usability testing with a field study across three metropolitan areas, to assess the effectiveness of the platform. Results indicated a 35% reduction in time spent searching for services and a 20% increase in customer satisfaction regarding service choices. The implications of this study suggest that platforms like GarageLocator can significantly improve urban mobility by streamlining access to automotive services, ultimately contributing to more efficient transportation networks and enhanced user experiences. Future work will focus on integrating predictive maintenance alerts and expanding the service network to suburban and rural areas.
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