A Smart Parking System Using Surveillance Cameras and Fuzzy Logic: A Case Study at Pardubice University's Campus

Abstract

This paper introduces a novel methodology for optimizing parking recommendations on the campus of Pardubice University, aimed at enhancing the management of existing parking areas. The model takes into account factors such as distance, travel time, parking spot availability, and user preferences, leveraging data processed via the Google Maps API and Open-CV. Fuzzy logic is employed within the model to deal with imprecise concepts, providing adaptability. Performance evaluations yielded an impressive accuracy of 92%, attesting to its viability for real-world implementation. This research significantly advances smart parking solutions, showing promise for reductions in wasted time, alleviated traffic congestion, and improved parking efficiency.