Project AI CARE for thermal and face mask detection , Plese refer the detail steps on Hands-ond Guide(./Proejct AI Care Hands-On Guide.pdf)
1. AI Care Edge Demo - https://youtu.be/Wh_21go4Thg
2. AI Care Device hands-on - https://youtu.be/d4HqonLCNmM
3. Mask Training by Custom Vision - https://youtu.be/eEb9vfvgW0g
4. Mask Inference Demo with Custom Vision on IoT Edge - https://youtu.be/dXDriffeE6Q
System Overview
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Mask Training –
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IoT Edge –
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IoT Central –
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BoT Service –
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Power BI + CosmosDB –
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Hands-On Guide Tutorial -
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Device Side
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6.1. M5StackCore or Any other Azure Certified Device or Rasiperry Pi –
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Development & Pinout Reference – https://docs.m5stack.com/#/en/quick_start/m5core/m5stack_core_get_started_Arduino_Windows
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Git clone from - https://github.com/tommywu052/project-AICARE.git
Reference from https://github.com/m600x/M5Stack-Thermal-Camera
- Go to project-AICARE/[device](https://github.com/tommywu052/project- AICARE/tree/master/device)/M5Stack_Thermal/, modify the code as below for your own wifi ssid / password and Azure IoT Central device connection string.
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6.2. ESP32 CAM or Any other CSI Camera component –
- Development & Pinout Reference – https://www.instructables.com/id/ESP-32-Camera-Streaming-Video-Over-WiFi-Getting-St/
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6.3. AMG 8833 or MLX90640 Thermal Camera –
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Backend Side –
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Mask Training with Azure Custom Vision –
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Download Kiosk App : http://aka.ms/kioskapp
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Setting your training & prediction key in kiosk app from https://www.customvision.ai/ website.
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Edge Computing with Azure IoT Edge -
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Refer the document https://github.com/Azure-Samples/Custom-vision-service-iot-edge-raspberry-pi/tree/master/ for IoT Edge setup, remember to choose amd64 for x64 platform.
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Install the node-red IoT Edge module as - https://github.com/iotblackbelt/noderededgemodule
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Import the code from https://github.com/tommywu052/project-AICARE/blob/master/backend/IoTEdge/AICare-nodered-flows.json into your node-red edge.
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Get the inference code from - https://github.com/tommywu052/project-AICARE/blob/master/backend/IoTEdge/yolocv-public.py
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Modify the code - line 22-24 as your device key on IoT Central :
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Modify the code – line 63 as your image inference host at 5.5.1 step
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Modify the code – line 261 as your ESP32 CAM streaming IP (ex:192.168.43.138, port 81 is default MJPEG streaming )
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Power BI Dashboard -
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Refer the document for Real-Time Streaming – https://docs.microsoft.com/zh-tw/power-bi/service-real-time-streaming
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Add Real-Time widget with Web Content and Streaming data set -
https://docs.microsoft.com/zh-tw/power-bi/service-dashboard-add-widget
- Note – Data on real-time dashboard is coming from IoT Central export as Azure Event Hubs-
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IoT Device Control and Monitoring on IoT Central -
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Refer the document to Create Your IoT Central Dashboard Application - https://docs.microsoft.com/zh-tw/azure/iot-central/core/quick-deploy-iot-central
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Device Configuration –
Configure your device telemetry/settings/command/triggers on the device template (mapping the code on the device side Arduino and python code)
- Enable Alert Notification –
https://docs.microsoft.com/zh-tw/azure/iot-central/core/quick-configure-rules
- If you just want to copy my existing application template quickly , Please create your application based my share template, click the below - https://apps.azureiotcentral.com/build/new/7490af0a-4e9c-4b54-b7a6-bd0c6092e522
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(To-Do) Azure BOT service integration –
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Check this for more detail notification - https://docs.microsoft.com/zh-tw/azure/bot-service/bot-builder-tutorial-basic-deploy?view=azure-bot-service-4.0&tabs=csharp
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LINE Integration - https://docs.microsoft.com/zh-tw/azure/bot-service/bot-service-channel-connect-line?view=azure-bot-service-4.0
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Feedback -
Welcome and Improve the code based on your advanced requirement .Please contact towu@microsoft.com or submit request on the github. Thanks !