Integration of Cameras and IoT for Parking Capacity Management Using the YOLOv8 Algorithm - HAYADI HAMUDA; ANJAR SETIAWAN (Institut Teknologi Nasional, Bandung, 2026)
Parking management in the mosque environment still faces challenges because vehicles are not being monitored properly. This research develops a parking capacity monitoring system based on cameras and the Internet of Things (IoT) using the YOLOv8 algorithm to automatically detect vehicles. The system is built with Python and digital image processing to detect vehicles entering and exiting. Parking capacity information is displayed in real-time thru a 20x4 I2C LCD and a web interface, and is stored in the Firebase Realtime Database. Testing using the black-box method shows that the system runs well, while the System Usability Scale (SUS) evaluation received a score of 90, categorized as very good. The vehicle detection results achieved an accuracy of 66.67% under optimal lighting conditions. This system is expected to help make mosque parking management more effective and efficient.