Add /home/jiahao/Tutorial-of-AI-Kit-with-Raspberry-Pi-From-Zero-to-Hero/articles/Chapter_6-RaspberryPi_and_AIoT/Smart_Retail_with_reComputerR11_and_AIkit.md

Author: LJ-Hao

articles/Chapter_6-RaspberryPi_and_AIoT/Smart_Retail_with_reComputerR11_and_AIkit.md

@@ -13,4 +13,108 @@ Beyond inventory and security, we integrated environmental monitoring using temp
 
 All data and controls are consolidated into a Node-RED dashboard, providing an intuitive interface for monitoring and managing store operations effectively.
 
-## First : Set your environment
+## First: set up your environment
+
+### Download the project
+
+```
+git clone https://github.com/Seeed-Projects/Smart-Retail-with-reComputerR11-and-AI-kit.git
+cd Smart-Retail-with-reComputerR11-and-AI-kit
+```
+
+### Clone office example
+```
+git clone https://github.com/hailo-ai/hailo-rpi5-examples.git
+```
+### Setup environment
+
+```
+cd hailo-rpi5-examples && source setup.sh
+```
+### Install requirements
+
+```
+cd .. && pip install -r requirements.txt
+```
+### Post process compilation
+
+```
+cd hailo-rpi5-examples && ./compile_postprocess.sh
+```
+
+## Second: run Product_Detection
+
+> **Note:**  
+> /dev/video* will be your first usb camera 
+
+```
+cd ../Product_Detection && python detection_pipelin.py --hef-path ./yolov8n.hef -i /dev/video0 --labels-json ./config.json
+```
+## Third: run Warehouse_Monitoring
+
+> **Note:**  
+> '1' will be your second usb camera
+
+you should open another terminal and run command below:
+```
+cd ../Warehouse_Monitoring/ && python app.py --device 1
+```
+## Fourth: run Node-RED
+
+### Install mosquitto because the picture and message is sending by MQTT service:
+```
+sudo apt install -y mosquitto mosquitto-clients
+```
+
+### Install node-red:
+```
+bash <(curl -sL https://raw.githubusercontent.com/node-red/linux-installers/master/deb/update-nodejs-and-nodered)
+```
+
+### Enable node-red and start node-red:
+```
+sudo systemctl enable nodered.service
+sudo systemctl start nodered.service
+```
+
+### Open node-red:
+```
+localhost:1880
+```
+The interface is like below:
+![](../../pictures/Chapter6/nodered_start.png)
+
+### Install Dashboard and Modbus node:
+
+![](../../pictures/Chapter6/dashboard_node.png)
+
+![](../../pictures/Chapter6/modbus_node.png)
+
+### Import the workflow
+
+```
+cp nodered-workflow/flows.json ~/.node-red/lib/flows
+```
+And then, import flows like below:
+![](../../pictures/Chapter6/import_1.png)
+
+### Deploy the flow, and the result is shown as below:
+
+![](../../pictures/Chapter6/deploy_flow.png)
+
+### Open Dashboard:
+1. Click the Dashboard button.
+![](../../pictures/Chapter6/dashboard_1.png)
+
+2. Click the Dashboard button in the top right corner to open dashboard.
+![](../../pictures/Chapter6/dashboard_2.png)
+
+3. The result is shown like below:
+![](../../pictures/Chapter6/dashboard_show.png)
+
+
+## The result
+
+We use the Raspberry Pi to accelerate EfficientNet for intrusion detection in storage rooms through object recognition. Meanwhile, the AI Kit is used to accelerate the YOLOv8 model for object detection to determine the quantity of goods on the shelves.
+
+<iframe width="1273" height="716" src="https://www.youtube.com/embed/Sd5J5k863Vs" title="Making Next Gadget: Master AI with Raspberry Pi, Power Smart Retail Solutions" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share" referrerpolicy="strict-origin-when-cross-origin" allowfullscreen></iframe>