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IWR6843AOPEVM: People tracking

Gnanender V
Prodigy 20 points
Part Number: IWR6843AOPEVM

Tool/software:

We are exploring the implementation of People tracking, fall detection and vitals signs as one feature development. We would want to implement this functionality use the current TI based ALGOs on the Arm-R4F microcontrollers. Need support for the same

  • 0
    TI__Genius 16471 points

    Hello, 

    People Tracking and Vital Signs demos for 6843 are included in the Radar Toolbox. Please download the toolbox to access the example code. Regarding fall detection, we do not have any example code that runs on the device. There is an option to enable fall detection when running the people tracking demo in the Applications Visualizer but the fall detection logic is all implemented in the python visualizer code. 

    Best Regards,

    Josh

  • 0 in reply to Josh Dye
    TI__Genius 16471 points

    Hi, 

    I noticed you selected that your issue is not resolved. Please let me know your questions/doubts. 

    Best Regards,

    Josh

  • 0 in reply to Josh Dye
    Prodigy 20 points
    Am aware of the fall detection being implemented in the visualizer. I wanted to know if this can be implemented as part of the Radar tool box. If yes, we will need some initial support on how we can implement the ALGO. 
    I do have an understanding of how the ALGO works. Need support in terms of how we can implement in the tool box and only send the detection/alerts as per of the TLV to external processor/microcontroller??
  • 0 in reply to Josh Dye
    Prodigy 20 points

    I had replied directly to the email I received, on the same day I got your message. Looks like reply to e2e email dont work

  • 0 in reply to Gnanender V
    TI__Genius 16471 points

    Hi, 

    Yes, replying to the email notification will not work. Sorry about the confusion. 

    To answer your question, yes, you would be able to implement the fall detection logic in the code running on the device and output the fall detection result as part of the TLV outputs. This will require some code modifications from you. 

    To implement this you would want to import the 3D People Tracking example project to CCS (The process for this is explained in the Developers Guide section of the 3D People Tracking example user guide.) After importing you can add the fall detection processing. I believe the fall detection logic in the visualizer uses the reported height information of each track so you would probably need to add the fall detection code after the track height estimation is done. The code will not be able to be copied directly since it is written in python, you will need to adapt it to the C code running on the embedded device. I think this document would also be very helpful for your reference while modifying the people tracking demo (3D People Tracking Demo Implementation Guide). 

    Best Regards,

    Josh