Insect Detection
Introduction
🌱 I. Global Agriculture's Critical Challenges & Digital Transformation Opportunity
Facing severe labor shortages, escalating production costs, and environmental sustainability pressures, modern agriculture requires intelligent solutions to revolutionize efficiency and quality control. Traditional manual pest inspection methods – plagued by inefficiency, high error rates, and delayed responses – have become obsolete in meeting contemporary agricultural demands.
🤖 II. Arducam's Embedded AI Revolution: SONY IMX500-Powered Ecosystem
Core Solution:
Arducam's embedded AI technology deploys SONY IMX500-equipped smart cameras, edge nodes, and development kit for real-time crop analysis. This solution supports autonomously identifying pest species and severity through leaf image processing.
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. Strategic Advantages & Transformational Impact
In addition, embedded AI systems have the characteristics of low power consumption, fast response, and easy deployment. They are suitable for remote, harsh or poorly covered agricultural scenarios, and promote the transformation and upgrading of agricultural production towards intelligence and refinement.
"Arducam's edge AI solutions enable precision agriculture 3.0 – transitioning from reactive pest management to predictive ecosystem stewardship while driving industry-wide standardization in smart farming infrastructure."
AI Model Dataset
Arducam Pre-trained insect 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
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/IP102.txt
