Integration of YOLOv5Algorithm and OpenCV in InnovativeSmart Parking Management Approach

Integration of YOLOv5Algorithm and OpenCV in InnovativeSmart Parking Management Approach

smart parking;YOLOv5;OpenCV;vehicle detection;parking space identification

The problem of automatic parking lot identification and vehicle detection in open areas is becoming increasingly important due to the growth in the number of vehicles in Indonesia, particularlyin big cities, resulting in difficulties in finding parking spaces during peak hours. In thiscondition,themotorists often have to compete for parking spaces. This research aims to develop a smart parking system that integrates YOLOv5 and OpenCV algorithms. This approach combines both algorithms thoroughly to identify parking spaces and detect vehicles in real-time indiverse parking scenarios. It is conducted in an open area with reference to parking conditions at the BRIN Bandung office.This study collected data fromthree different parking lot conditions, namelyempty, partially occupied, and full. In each condition, the system successfully detected the parking lots and vehicles accurately. The novel contribution of this research is the development of a smart parking system that uses an integrated approach, providing an effective solution forthe challenges of parking lot availability and vehicle detection. By utilizing the advantages of both algorithms, we successfully created a system that can identify the parking spaces and detect the vehicles accurately and efficiently under various parking circumstances. Thus, this research makes a significant contribution to the development of smart and adaptive parking management technology.

Akmal Hidayah1,6*, Sitti Zuhriyah2, Billy Eden William Asrul3,Yuyun4,5, Esa Prakasa

https://jurnal.iaii.or.id/index.php/RESTI/article/view/5728/942

Dept. of Computer System, Faculty of Computer Science, Handayani University, Makassar, Indonesia

22-06-2024

FAJAR BAGUS W

PDF

ENGLISH

TEXT