UniRide: Real-Time Vehicle Tracking and AI-Enhanced Driver Rating for Universities

Abstract

The primary objective of this project is to enhance the efficiency, reliability and convenience of university transportation system through a real-time vehicle tracking and AI-enhanced driver review system. This Android-based application, named UniRide, utilizes modern mobile technology to provide students and staffs with precise, up-to-date, real-time information on bus locations, routes, schedules etc. The system also enables students to submit driver reviews which are analyzed and summarized by AI to provide actionable feedback for continuous service improvement. The development of UniRide primarily involves the use of Kotlin programming language. Various other packers are also used such as Jetpack Compose for frontend, Firebase for backend services, Google Maps API for map and location related tasks, and Gemini API for AI-driven driver review analysis. This application aims to reduce the uncertainties associated with traditional transport system, improve user experience, and enhance safety through various features like emergency helpline, occupancy alerts and announcement notification system. This report documents the project's development, from initial prototype design and user feedback collection to the implementation of core functionalities and performance optimizations. It highlights the iterative process of refining the app based on user input, ensuring a user-friendly interface and reliable performance. By addressing the challenges of real-time data synchronization, efficient data storage, and user privacy, this project sets a new standard for campus transportation systems, paving the way for future enhancements and broader applications.