Parking Space Detection¶
Introduction¶
🚗 Revolutionizing Urban Parking: Arducam's AI-Powered Space Detection Solution¶
As cities densify, parking scarcity escalates. Traditional systems—reliant on manual counts or basic sensors—fail to address soaring demand, causing plenty of vacancy misreporting and chronic congestion.
🤖 II. Arducam's Breakthrough: Real-Time Vision Intelligence¶
Core Solution:
Arducam's Parking Space Detection solution uses the yolov8n pklot model to identify the occupancy of parking spaces in the parking lot in real time, realize intelligent management of the parking lot, improve parking space utilization, alleviate parking pressure, and provide car owners with a convenient and efficient parking experience.
SONY IMX500 Ecosystem Advantage:
First intelligent vision sensor with integrated AI processing On-sensor machine learning eliminates cloud dependency 12.3MP resolution with ultra-low 100mW power consumption
⚡ III. Advantages of Arducam AI Camera Solution¶
Arducam’s AI camera solutions are dedicated to solving key parking challenges in urbanization – to maximize asset utilization while providing a driver-centric experience.
AI Model Dataset¶
Arducam Pre-trained Barcode Code detection dataset
AI Model Example¶
Hardware Preparation¶
The following demo is based on Arducam IMX500 Raspberry Pi 5 All-in-one AI Camera Kit:
| Product Image | SKU | Resolution | Sensor | Lens Mount | Focus Type | Field of View(DxHxV) | IR Sensitivity | Power Requirements | Operating Temp. |
|---|---|---|---|---|---|---|---|---|---|
 |
B0540 | 12.3MP | SONY IMX500 | Stock Lens | Fixed Focs | 78±3°(D)×66±3°(H)×52.3±3°(V) | Integral 650nm IR Filter | Max 7.5W | 0°C to 50°C |
Software Preparation¶
Export IMX500 AI model compressed package
IMX500 AI Model Package-Parking Space Detection
Deployment¶
Start the IMX500 Raspberry Pi All-in-One and run the following code to install the environment
sudo apt update && sudo apt full-upgrade
sudo apt install imx500-all imx500-tools
sudo apt install python3-opencv python3-munkres
Use the following command to package the IMX500 model into rpk (note to replace the path example below with the actual path)
imx500-package -i <path to packerOut.zip> -o <output folder>
Download and install picamera2, and run the startup script (note to replace the actual rpk model path)
git clone https://github.com/raspberrypi/picamera2
cd picamera2
pip install -e . --break-system-packages
cd examples/imx500
python imx500_object_detection_demo.py --model ~/dev_workspace/output/network.rpk --fps 17 --bbox-normalization --ignore-dash-labels --bbox-order xy --labels ~/dev_workspace/parking.txt
