Smart Campus Mobility System (SCMS): Personalized and Sustainable Transit Solutions

Abstract

Efficient, sustainable, and personalized campus transportation enhances the student experience by ensuring seamless mobility and supporting academic and social engagement. This paper introduces a Smart Campus Mobility System (SCMS) that integrates Management Information Systems (MIS), predictive analytics, and multimodal transit solutions to create a dynamic and responsive transportation network tailored to university needs. The SCMS seeks to close the gap between the changing needs of contemporary campus communities and conventional, static transportation services. By leveraging the power of MIS and data-driven insights, the system can provide real-time notifications and route optimization, making commuting on campus more efficient and personalized for each user.

The SCMS's capacity to provide customized scheduling depending on each student's schedule and campus traffic patterns is one of its main advantages. Using predictive analytics, the system anticipates transit demand and adjusts service availability, accordingly, ensuring that shuttles and other modes of transportation are deployed when and where they are needed most. This personalized approach not only enhances the user experience by minimizing waiting times but also contributes to operational efficiency by optimizing the use of resources. The system supports multimodal options, including shuttle services, electric scooters, and bike rentals, providing flexible and eco-friendly travel alternatives that align with sustainability goals and reduce the campus’s carbon footprint.

Although GIS is not the primary focus, its integration plays a crucial role in SCMS by facilitating real-time data visualization and basic route mapping. GIS enhances the system's overall functionality by offering spatial insights that allow for adaptive routing and quick response to changes in traffic flow. This strategic use of GIS ensures that transit routes are continuously optimized and visually represented, aiding decision-making and improving user navigation. The combination of MIS, predictive analytics, and GIS in a limited but impactful manner results in a cohesive system that enhances campus transportation, supports sustainability initiatives, and streamline resource management, providing a robust and scalable model for universities seeking to modernize their transit infrastructure.