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Overview
This system is built on the Raspberry Pi 4B platform, utilizing YOLO object detection technology and the Blynk IoT platform to create a professional and efficient real-time parking lot monitoring solution. Through an external camera, the system captures real-time parking lot footage, accurately detects the occupancy status of parking spaces, and displays the results on an intuitive user interface for real-time monitoring.
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Requirements
The hardware and software we use in the process.
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System Architecture
Hardware Components
Raspberry Pi 4B
Serves as the core processing unit, running the object detection algorithm and managing data transmission.
External Camera
Captures real-time footage of the parking lot, providing input for detection.
YOLO
YOLO Object Detection Technology
YOLO (You Only Look Once) is a real-time object detection technology based on deep learning. Unlike traditional methods, YOLO divides an image into multiple grids and simultaneously predicts object classes and locations within each grid. This approach ensures high accuracy while maintaining exceptional computational efficiency, making it ideal for resource-constrained devices like the Raspberry Pi.
In this system, YOLO identifies whether parking spaces in the captured footage are occupied and relays the results to subsequent modules.
Blynk IoT Platform
Blynk is a development platform for IoT applications, offering user-friendly interface design tools and easy-to-use APIs, supporting multiple devices and communication protocols. Developers can use Blynk to quickly create applications for remote monitoring and control .In this system, Blynk is utilized to implement the user interface. The Raspberry Pi transmits the parking space status to the Blynk platform, where it is displayed in a graphical and textual format for the user.
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System Workflow
1. Image Capture:
The external camera captures real-time footage of the parking lot.
2. Object Detection:
The Raspberry Pi runs the YOLO model to analyze the status of each parking space in the footage.
3. Data Transmission:
Detection results are sent to the Blynk platform over the network.
4. Interface Update:
The Blynk interface dynamically refreshes to display the status of each parking space.