Parking Slot Scanning for Maximum Efficiency Using Python

Algyon Faras; Gany Andisa; Nakula Bintang Nashwandra; Jauza Nadhifah; David Reza Widhiwipati; Endang Purnama Giri; Gema Parasti Mindara

doi:10.62951/ijies.v1i4.122

Authors

Algyon Faras IPB University
Gany Andisa IPB University
Nakula Bintang Nashwandra IPB University
Jauza Nadhifah IPB University
David Reza Widhiwipati IPB University
Endang Purnama Giri IPB University
Gema Parasti Mindara IPB University

DOI:

https://doi.org/10.62951/ijies.v1i4.122

Keywords:

Smart Parking System, Python, OpenCV, Image Processing, Parking Slot Detection

Abstract

The growing number of vehicles in major cities has posed significant challenges in parking lot management. Motorists often have difficulty finding empty parking slots quickly, which not only wastes time but also aggravates traffic congestion and increases air pollution. This research develops a Python-based smart parking system by utilizing the OpenCV library to detect the status of parking slots in real-time. The system uses a camera as the main sensor and processes the image using techniques such as grayscale, Gaussian blur, and adaptive threshold to identify the parking slot status, whether empty or occupied, with good accuracy. The parking slot coordinate data is stored in CSV format to ensure efficient data management. Experimental results with video recordings show that the system is able to operate well in various parking conditions. The system proved to be cost-effective and easy to implement, making it an ideal solution for parking managers who want to improve management efficiency without being burdened with high costs. This research offers a practical solution to help motorists and parking managers optimize parking space usage, reduce search time, and minimize negative impacts such as congestion and carbon emissions.

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