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.
