Intruder Detection with RaspberryPi and Node Red

by Steve JeffersonSept 8th, 2016

Object detection model with Tensorflow.js, Deployed on RaspberryPi.

Flow

  1. The user owns or downloads a machine learning model in TensorFlow.js format.
  2. The user creates a Node-RED node for the TensorFlow.js model and wires the TensorFlow.js node in a Node-RED application.
  3. The user can deploy the Node-RED application locally.
  4. The user can access the Node-RED application from a browser and can trigger inferencing on images captured from a webcam.
  5. Alternatively, the user can deploy the Node-RED application to a Raspberry Pi.
  6. The device runs the Node-RED application and performs inferencing on images from a camera.
  7. The device can output to a connected speaker or take some other action depending on the inference results.

Configuration

  • GIT

    sudo apt update sudo apt install git

  • NodeJS and NVM

    curl -o- https://raw.githubusercontent.com/nvm-sh/nvm/v0.35.3/install.sh | bash nvm install node

  • Node packages

    
npm install /home/pi/app/node-red-tensorflowjs/node-red-contrib-tfjs-object-detection
npm install node-red-contrib-browser-utils node-red-contrib-play-audio node-red-contrib-image-output
npm install node-red-node-pi-gpio

  • RaspberryPi Camera

    npm install node-red-contrib-camerapi

  • USB Webcam

    
npm install node-red-contrib-usbcamera
sudo apt install fswebcam

  • Code

    
git clone https://github.com/IBM/node-red-tensorflowjs
cd node-red-tensorflowjs
npm start

Hardware Setup

  • Camera Configuration
    1. Open the Camera Port on the Raspberry Pi
    2. Insert the Camera Cable
    3. Test the connection with the command: raspistill -o Desktop/image.jpg
  • Motion Sensor
    1. Connect the sensor to pin 8 (or any other GPIO pin)
    2. Power the sensor with the RaspberryPi 5v pin

    • Import required Flows

    1. Make sure Node-RED is running
    2. Open a browser and go to your Node-RED Editor
    3. Click on the Node-RED Menu
    4. Click on Import
    5. Select the Clipboard tab
    6. Click on select a file to import
    7. Browse to and select one of the flow files in the cloned repo
      • If trying things out locally on your browser, then use the browser-flow.json.
      • If using a Raspberry Pi with peripherals, then use the raspberrypi-flows.json.
    8. Select Import to new flow
    9. Click Import

    Deploy and run on a Raspberry Pi

    1. Double click on Play Audio File exec node and change the path in the append section to the path of a .wav file of your choosing. Click Done when finished.
    2. Click the Deploy button.
    3. Trigger the camera.
      1. Can manually trigger the snapshot by clicking the Take Photo inject node.
      2. If using the motion sensor flow, motion near the sensor will trigger the camera.

    License

    Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so according to the MIT License