Sistem Pendeteksi Citra Mobil Untuk Menghitung Jumlah Tempat Parkir di Politeknik Caltex Riau Menggunakan YOLO

Authors

  • Fadel Abef

Keywords:

API, Deep Learning, IP camera, JSON, Parkir Mobil, YOLOv3

Abstract

Often happens that the car park's full in the car park of Polytechnic Caltex Riau (PCR) directorate because there's no system to calculate number of empty parking spaces. As result, staff/lecturer drivers when directorate parking space's full, they have to turn around and look for empty parking space so it takes a long time to park their car. The solution to this problem is create a car image detection system to find the number of parking spaces in PCR using YOLOv3. This system uses an IP Camera as media to capture image data from PCR parking space, then Raspberry Pi to forward image data to the Deep Learning server. The deep learning server will count the number of cars and number of empty car parks. With the help of You Only Look Once (YOLOv3), Application Programming Interface (API), JSON, and Cloud Computing, car object detection will be easier. Results of directorate parking image detection, results calculating of car parks and the number of empty parking spaces will be displayed in a website. The average result of detection of car objects using YOLOv3 is 91%, and the average result of detection accuracy for each car objects using YOLOv3 is 79%. Keywords: API, Car Parks, Deep Learning, IP Camera, JSON, YOLOv3.

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Published

2022-06-06

Issue

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Artikel