Example communication between two services with machine learning inside.
To run the data collection, you need:
- Android device with "ROS All Sensors" app installed, see https://play.google.com/store/apps/details?id=org.ros.android.android_all_sensors_driver&hl=en .
- Run the data collection service using
sudo docker run --net="host" issuds/tukana_demo /bin/bash /root/source/edge.sh
- On the machine that collects the data, navigate to http://localhost:5006/edge , you should be able to see a user interface after the page loads (cat take up to 20 sec).
- Run the ROS app on the smartphone with the IP address of the ROS master taken to be the IP of the device that runs the data collection (use
ifconfigcommand for Linux,
- When you hit the "Record" button, you should see the data coming from a smartphone.
- When you collect sufficient amount of data, click on
Recordagain. You should see a prediction of the service whether the mode of operation is normal or not.
- Run the datacenter service by running
sudo docker run --net="host" issuds/tukana_demo /bin/bash /root/source/datacenter.sh
- In the data collection web app, click on "Share data". You should see the predictions with more dedicated annotation of the sequence.
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