Smart Parking based on Car Detection using Deep Learning YOLOv8 - Waluyo Nugroho; Afianto Afianto; Mada Jimmy Fonda Arifianto (Universitas Khairun, 2024)
In the context of rapidly growing urbanization, the need for efficient parking management solutions is becoming increasingly urgent. This research develops and implements a car detection system based on YOLOv8 (You Only Look Once Version 8) for smart parking applications using Raspberry Pi and the Node-RED platform. This system is designed to optimize the use of parking spaces and increase parking management efficiency by utilizing YOLO's real-time object detection capabilities. Data processed by the Raspberry Pi is sent to the Node-RED platform for Internet of Things (IoT) via MQTT protocol. Node-RED functions as a management and visualization system, allowing users to monitor parking status in real-time through an intuitive graphical interface. With Node-RED, users can find out which parking lots are full and which areas are still available.