Development of a smart GIS-based campus navigation and shortest path routing system for OAUSTECH, Ondo State, Nigeria

Abstract

Efficient navigation remains a persistent challenge on large campuses such as Olusegun Agagu University of Science and Technology (OAUSTECH), Nigeria, due to expansive layouts and complex pathways. Static maps are insufficient to meet users' dynamic needs, creating a demand for intelligent geospatial solutions. This study developed a GIS-based smart campus map integrated with Dijkstra’s algorithm to optimize route planning, enhance accessibility, and support campus management. Spatial data on campus infrastructure were collected through field surveys and Google Earth Pro imagery, then digitized and geo-referenced in ArcGIS. The campus network was modeled as a weighted graph, and Dijkstra’s algorithm was implemented in Python to compute the shortest paths, considering factors such as distance, pedestrian access, and restricted zones. The system was deployed as an interactive web and mobile application using HTML, CSS, JavaScript, Bootstrap, and Android Studio, enabling real-time navigation and flexible querying. The system successfully generated optimal routes across 12 major nodes, including distances of 1,129.10 meters from the main gate to the ICT Building and 1,696.93 meters to Principal Staff Housing. Usability testing with 30 participants showed 87% user satisfaction, with average route generation times under two seconds, and notable reductions in navigation time compared to paper maps. Overall, integrating GIS with Dijkstra’s algorithm improved route safety, efficiency, and user experience. While the system relies on static data, future work could incorporate AI-driven real-time updates. The approach provides a scalable model for smart campus development in resource-limited settings.