Citation :

Anirudh Dev, Prof. Er. Rahul Sharma 2026. "Smart Parking Using Computer Vision Techniques" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 4, Issue 4: 09-15.

Abstract :

Finding a free parking space in busy cities, shopping malls, offices, and campuses wastes time and fuel, adds to traffic inside parking areas, and frustrates drivers. Traditional parking management relies on human attendants, tickets, or a sensor fitted at every slot, which is slow, costly, and hard to maintain. Computer vision offers a practical alternative: the CCTV cameras that already watch a parking area can be combined with artificial intelligence to find vehicles and decide, in real time, which slots are occupied and which are vacant. This paper presents a smart parking system based on computer vision. It reviews classical feature-based methods and deep learning detectors such as Faster R-CNN, SSD, YOLO, and RetinaNet, together with earlier smart parking studies [1]–[5]. It then describes a five-stage pipeline consisting of image capture, image processing, vehicle detection, data analysis, and information display, supported by authentication, cloud and edge deployment, and performance optimisation techniques such as lightweight models and temporal smoothing. The system counts the available spaces and shows live availability on LED boards, mobile applications, and websites. The paper also discusses evaluation measures, real-time applications, advantages, and challenges such as installation cost, poor light and bad weather, privacy, and maintenance, followed by future directions including integration with autonomous vehicles, online reservations, smart city infrastructure, and AI-driven fee collection. The study shows that single-stage detectors make real-time parking monitoring possible on practical hardware, and that an existing camera view can replace many individual slot sensors.

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Keywords :

Smart Parking, Computer Vision, Vehicle Detection, YOLO, Deep Learning, Real-Time Occupancy Detection, Smart City