Integrating YOLOv8 with Fuzzy Logic System: A Novel Hybrid Approach for Efficient Parking Slot Availability Management

Abstract

In urban areas, the challenge of finding parking spaces has become a significant concern, leading to congestion, wasted time, and increased pollution. Traditional parking management systems often lack the efficiency needed to address this issue adequately. In this paper, a novel approach was proposed to smart parking management that integrates the YOLOv8 model and fuzzy logic system. YOLOv8, a state-of-the-art object detection algorithm, enables real-time detection and tracking of vehicles within parking lots. By utilizing YOLOv8, the system can accurately identify vacant parking spaces in a timely manner. Furthermore, fuzzy logic was employed to enhance decision-making in selecting the optimal parking slot for users. Fuzzy logic enables the system to consider various factors such as proximity to the destination, parking space size, and distance from the entrance. By incorporating fuzzy logic into the decision-making process, the system can provide personalized recommendations tailored to individual user preferences and parking requirements. Based on the fuzzy inputs namely distance from entrance, proximity to exit and space, the system analyzes the best parking slot and assigns “rank” which is also fuzzy output. The decision can be made based on the rank provided to every slot of the parking lot. Slots with the highest rank should be preferred for parking because they are more suitable as they provide ease to parking the cars and can be suitable to customized needs of the users. The model can be deployed with LCD screens at various parking lots in order to save fuel and time of the commuters.

Keywords

• yolov8 model
• internet of things (iot)
• smart parking systems