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All Journal Simtek : Jurnal Sistem Informasi dan Teknik Komputer Jurnal Informasi dan Teknologi Jurnal Sains Teknologi dan Sistem Informasi Journal of Artificial Intelligence and Digital Business Jurnal Fokus Elektroda (Energi Listrik, Telekomunikasi, Komputer, Elektronika dan Kendali) COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi KETIK : Jurnal Informatika Indonesian Journal of Innovation Multidisipliner Research
Adha Mashur Sajiah
Universitas Halu Oleo
Chemical Engineering, Chemistry & Bioengineering Civil Engineering, Building, Construction & Architecture Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Electrical & Electronics Engineering Energy Engineering Industrial & Manufacturing Engineering Mechanical Engineering Transportation

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Recognition of Parking Space Availability Patterns Based on Visual Feature Extraction Using YOLOv8 for a Smart Parking System Juliyana Herman; Syalsa Ananda; Siti Samriah; Adha Mashur Sajiah
COREAI: Jurnal Kecerdasan Buatan, Komputasi dan Teknologi Informasi Vol 7, No 1 (2026): Sustainable Information Technology Innovation Supports a Digital-Based Smart Eco
Publisher : Universitas Nurul Jadid

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.33650/coreai.v7i1.15671

Abstract

The growing number of vehicles in urban areas is driving the need for smart parking systems capable of automatically detecting parking space availability in real time. This study developed a YOLOv8s-based detection model trained using the PKLot v2 dataset (Roboflow), which consists of a total of 12,416 images from various locations, camera angles, and weather conditions. Preprocessing included converting annotations from the COCO JSON format to YOLO TXT and removing duplicate bounding boxes using an IoU filter of >0.85. The model was trained for 50 epochs using the AdamW optimizer, with mosaic and copy-paste data augmentation, and an image size of 640×640 pixels. Evaluation on the validation subset yielded a mAP@0.5 of 0.9512, precision of 0.9241, recall of 0.9073, and an F1-Score of 0.9156, outperforming similar studies that used YOLOv5 or single-location datasets. A polygon-based Region of Interest (ROI) mechanism was applied to filter out detections outside the parking area, effectively reducing false positives. This study demonstrates that YOLOv8s, optimized on a multi-location dataset, can accurately recognize parking slot availability patterns as the foundation for a smart parking system that can be widely implemented.
Co-Authors Auliya Afifah Adnan Hakim Bambang Pramono Bambang Pramono Cindy Rahmayanti Elisa Wulan Sari Golok Jaya, La Ode Muhammad Ika P.N. Purnama Ilham Julian Efendi Juliyana Herman Jumadil Nangi L.M. Bahtiar Aksara La Ode Pali Aqsan La Surimi Muhammad Akbar Perdana Ramadhan Muhammad Ijlal Prayoga Muhammad Irwan Syahib Natalis Ransi Putri Angraini Aziz Ramlia Ramadani Sudin Reza Sanjaya Rizal Adi Saputra sandy suseno Siti Samriah Subardin Subardin Sumiarni Moka Sutardi Sutardi Syaban Barokah Nur Ilahi Syalsa Ananda