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SDS Application for ST B-U585I-IOT02A board with SDSIO using USB Interface

This application is an example of using Edge Impulse Continuous Motion Recognition ML algorithm on a physical board. It lets you record and play back real-world data streams on physical hardware, feeding them to your algorithm for testing. The data streams are stored in SDS data files.

Pre-Requisite

To run this example:

ST B-U585I-IOT02A board

The ST B-U585I-IOT02A board is based on a Cortex-M33 processor. For using the integrated ST-Link install the ST-Link USB driver or your computer and update the firmware.

Projects

The SDS.csolution.yml application is configured for the targets B-U585I-IOT02A or SSE-300-U55 FVP simulation models.

It contains two projects:

  • DataTest.cproject.yml: Verifies the SDSIO interface on hardware.
  • AlgorithmTest.cproject.yml: Verifies a Continuous Motion Recognition ML algorithm with recording and playback of SDS data files.

Layer Type: Board and Layer Type: SDSIO

The board layer implements the Hardware Abstraction Layer (HAL) layer. Depending on the selected target, a different board implementation with the appropriate I/O interfaces is used:

  • Board/B-U585I-IOT02A/Board.clayer.yml and sdsio_usb.clayer.yml use the development board's USB interface for SDSIO communication.
  • Board/Corstone-300/Board-U55.clayer.yml and sdsio_fvp.clayer.yml use the VSI Interface to the AVH FVP simulator for SDSIO communication.

Layer Type: Edge Impulse layer

This layer contains the ML model that is used in the AlgorithmTest.cproject.yml.

ML Model update procedure

  1. Clone the project
    Clone the Tutorial: Continuous motion recognition project from Edge Impulse.
  2. Build CMSIS pack
    • Under Time series data, Spectral Analysis, Classification, Anomaly Detection (K-means), select Deployment.
    • Under Search deployment options, type Open, then choose Open CMSIS pack (Generates a CMSIS Software Component pack).
    • Click Build to generate the CMSIS pack.
  3. Download and extract
    Once the build completes, download the generated ZIP file: tutorial_-continuous-motion-recognition-cmsis-package-v<version>.zip Extract its contents locally.
  4. Copy updated packs
    Copy the contents of the extracted .pack files into: ./algorithm/ML/Packs/EdgeImpulse. Maintain the same directory structure and organization as the existing packs.
  5. Update layer configuration
    Edit the edgeimpulse.clayer.yml file and update all version references to match the new pack versions.

Projects

  • DataTest.cproject.yml: Verifies SDSIO interface on hardware.
  • AlgorithmTest.cproject.yml: Verifies a Continuous Motion Recognition ML algorithm with recording (on hardware only) and playback of SDS data files.

Build Targets

  • Debug: Debug version of the application used for recording/playback of input data and algorithm output data.
  • Release: Release version of the application used for recording/playback of input data and algorithm output data.

Note: Only difference between Debug and Release targets is compiler optimization level and the amount of debug information printed to the STDIO.

For more details, refer to the SDS Template Application.

DataTest Project on the ST B-U585I-IOT02A board

The DataTest project allows you to verify the SDSIO communication and it is recommended to use this project first.

Build and run this project in VS Code by following these steps:

  1. Use Manage Solution Settings and select:
    • Target type B-U585I-IOT02A.
    • Project DataTest with Build Type Debug.
  2. Open in VS Code a Terminal window and start the SDSIO-Server with sdsio-server usb .
  3. Build Solution to create an executable image.
  4. Connect a USB cable between the host PC and the STLK (CN8) USB connector on the B-U585I-IOT02A board.
  5. Connect a second USB cable between host PC and the USB-C (CN1) connector on the B-U585I-IOT02A board.
  6. Open the VS Code Serial Monitor and start monitoring the application output (STDIO) on the STLink Virtual COM port.
  7. Load and Run to download the application to the board and start it.
  8. Observe the application output (STDIO) like below
SDSIO-Client USB interface initialized successfully
99% idle
99% idle

alternatively if SDSIO-Server is not reachable or not running you will see the output:

SDSIO-Client USB interface initialization failed!
Ensure that device is connected via USB to the host PC running SDSIO-Server, then restart the application!

Note:

  • If the SDSIO-Server is not found, verify your SDS Utilities Setup.
  • It is possible to configure the input data bandwidth by editing ALGO_TEST_BANDWIDTH define in the algorithm_config.h file. Default bandwidth is configured to 100000U which means approximately 100000 bytes per second.

Recording/playback testing

For executing the recording or playback test, follow the steps below:

Recording

To perform a recording, follow these steps:

  • To start recording, press the R key in the SDSIO-Server window, or press the User button on the board.
  • To stop recording, press the S key in the SDSIO-Server window, or press the User button on the board again.

Output of SDSIO-Server during recording

>sdsio-server usb 
SDSIO-Server v3.1.0
Press 'Ctrl+C' or 'X' to exit.
Working directory: ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition
SDSIO command input: R=Record, P=playback, S/s=stop, T/t=reset, X/x=exit, A-H=set flags 0-7, a-h=clear flags 0-7.
SDSIO-Server waiting for USB SDSIO-Client...
SDSIO-Client USB device connected.
sdsFlags = 0x10000000.
99% idle.
SDSIO command: start recording ('R').
sdsFlags = 0x90000000.
Record:   Test_In (Test_In.0.sds)
Record:   Test_Out (Test_Out.0.sds)
98% idle.
SDSIO command: stop ('s').
sdsFlags = 0x10000000.
Closed:   Test_In (Test_In.0.sds)
Closed:   Test_Out (Test_Out.0.sds)
99% idle.

Application output in the Serial Monitor

99% idle
==== SDS recording started
98% idle
98% idle
==== SDS recording stopped
99% idle

Each run records two files: Test_In.<n>.sds and Test_Out.<n>.sds in the folder where SDSIO-Server was started. <n> is a sequential number.

Check SDS Files

The SDS-Check utility verifies SDS files for consistency. For example:

>sds-check -i Test_In.0.sds
File Name         : Test_In.0.sds
File Size         : 271.080 bytes
Number of Records : 270
Recording Time    : 2.690 ms
Recording Interval: 10 ms
Data Size         : 268.920 bytes
Block Size        : 996 bytes
Data Rate         : 99.600 byte/s
Jitter            : Not detected
Validation passed

Playback

To perform a playback, follow these steps:

  • To start the playback, press the P key in the SDSIO-Server window.
  • The playback will stop automatically when it plays all the data from the SDS file.

The stream Test_In.<n>.sds is read back and the algorithm processes this data. The stream Test_Out.<n>.p.sds is written containing results of the test algorithm. The SDS file Test_Out.<n>.p.sds created during playback should be identical to the Test_Out.<n>.sds file created during the recording.

Output of SDSIO-Server during playback

>sdsio-server usb
SDSIO-Server v3.1.0
Press 'Ctrl+C' or 'X' to exit.
Working directory: ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition
SDSIO command input: R=Record, P=playback, S/s=stop, T/t=reset, X/x=exit, A-H=set flags 0-7, a-h=clear flags 0-7.
SDSIO-Client USB device connected.
sdsFlags = 0x10000000.
99% idle.
SDSIO command: start playback ('P').
sdsFlags = 0xB0000000.
Playback: Test_In (Test_In.0.sds)
Record:   Test_Out (Test_Out.0.p.sds)
Closed:   Test_In (Test_In.0.sds)
Closed:   Test_Out (Test_Out.0.p.sds)
sdsFlags = 0x30000000.

Application output in the Serial Monitor

99% idle
==== SDS playback started
99% idle
==== SDS playback stopped
99% idle

DataTest Project on the AVH-FVP Simulator

The DataTest can be also executed on AVH-FVP simulation models using the steps below:

  1. Use Manage Solution Settings and select:
    • Target type SSE-300-U55.
    • Project DataTest with Build Type Debug.
  2. Build Solution to create an executable image.
  3. Load and Run starts the application on the AVH-FVP simulation. The output is shown in the Terminal console.

Notes:

  • The simulator target only supports playback mode.
  • This example includes an algorithm.sdsio.yml configuration file that sets algorithm/SDS Recordings as the working directory for SDS playback.
    To test the previous example, either: copy recorded files Test_In.0.sds and Test_Out.0.sds into that directory, or update the workdir in the algorithm.sdsio.yml and change stream names ML_In to Test_In and ML_Out to Test_Out.
    For details on the sdsio.yml configuration format and available options, refer to the documentation.
  • The VSI script used by the simulator also generates the sdsio.log output file.

FVP simulation output in the terminal

Executing task: FVP_Corstone_SSE-300_Ethos-U55 -f Board/Corstone-300/fvp_config.txt -a out/DataTest/SSE-300-U55/Debug/DataTest.hex  

Ethos-U version info:
        Arch:       v1.1.0
        MACs/cc:    256
        Cmd stream: v0
SDSIO VSI interface initialized successfully
==== SDS playback started
==== SDS playback stopped

AlgorithmTest Project on the ST B-U585I-IOT02A board

The AlgorithmTest project includes an Edge Impulse Motion Recognition ML model that you can verify using the SDS-Framework.

Key Components

Accelerometer Data (data_in_user.c):

  • Initializes the on-board accelerometer sensor using the CMSIS vStream driver
  • Captures accelerometer samples and scales them to the range expected by the ML model
  • Provides the processed sensor data for SDS recording

Algorithm Processing (algorithm_user.cpp):

  • Initializes the ML model
  • Performs the ML inference pipeline, including pre-processing, inference, and post-processing
  • Copies detection results to the output buffer for SDS recording
  • Outputs motion recognition results to the STDIO

Hardware setup and running the example

Build and run this project in VS Code using the following steps:

  1. Use Manage Solution Settings and select:
    • Target type B-U585I-IOT02A.
    • Project AlgorithmTest with Build Type Debug.
  2. Open in VS Code a Terminal window and start the SDSIO-Server with sdsio-server usb .
  3. Build Solution to create an executable image.
  4. Connect a USB cable between the host PC and the STLK (CN8) USB connector on the B-U585I-IOT02A board.
  5. Connect a second USB cable between host PC and the USB-C (CN1) connector on the B-U585I-IOT02A board.
  6. Open the VS Code Serial Monitor and start monitoring the application output (STDIO) on the STLink Virtual COM port.
  7. Load and Run to download the application to the board and start it.

Recording

To perform a recording, follow these steps:

  • To start recording, press the R key in the SDSIO-Server window, or press the User button on the board.
  • To stop recording, press the S key in the SDSIO-Server window, or press the User button on the board again.

Output of SDSIO-Server during recording

>sdsio-server usb 
SDSIO-Server v3.1.0
Press 'Ctrl+C' or 'X' to exit.
Working directory: ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition
SDSIO command input: R=Record, P=playback, S/s=stop, T/t=reset, X/x=exit, A-H=set flags 0-7, a-h=clear flags 0-7.
SDSIO-Server waiting for USB SDSIO-Client...
SDSIO-Client USB device connected.
sdsFlags = 0x10000000.
96% idle.
93% idle.
SDSIO command: start recording ('R').
sdsFlags = 0x90000000.
Record:   ML_In (ML_In.0.sds)
Record:   ML_Out (ML_Out.0.sds)
94% idle.
SDSIO command: stop ('s').
sdsFlags = 0x10000000.
Closed:   ML_In (ML_In.0.sds)
Closed:   ML_Out (ML_Out.0.sds)
92% idle.

Application output in the Serial Monitor

==== SDS recording started
94% idle
96% idle
Predictions (DSP: 18.000000 ms., Classification: 0 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.000000
    snake: 0.000000
    updown: 0.996094
    wave: 0.000000
Anomaly prediction: 0.041957
93% idle
96% idle
Predictions (DSP: 18.000000 ms., Classification: 0 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.101562
    snake: 0.898438
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: 0.241648
==== SDS recording stopped
92% idle

Each run records two files: ML_In.<n>.sds and ML_Out.<n>.sds in the folder where SDSIO-Server was started. <n> is a sequential number.

Playback

To perform a playback, follow these steps:

  • To start the playback, press the P key in the SDSIO-Server window.
  • The playback will stop automatically when it plays all the data from the SDS file.

The stream ML_In.<n>.sds is read back and the algorithm processes this data. The stream ML_Out.<n>.p.sds is written containing results of the test algorithm. The SDS file ML_Out.<n>.p.sds created during playback should be identical to the ML_Out.<n>.sds file created during the recording.

Output of SDSIO-Server during playback

>sdsio-server usb
SDSIO-Server v3.1.0
Press 'Ctrl+C' or 'X' to exit.
Working directory: ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition
SDSIO command input: R=Record, P=playback, S/s=stop, T/t=reset, X/x=exit, A-H=set flags 0-7, a-h=clear flags 0-7.
SDSIO-Server waiting for USB SDSIO-Client...
SDSIO-Client USB device connected.
sdsFlags = 0x10000000.
88% idle.
SDSIO command: start playback ('P').
sdsFlags = 0xB0000000.
Playback: ML_In (ML_In.0.sds)
Record:   ML_Out (ML_Out.0.p.sds)
Closed:   ML_In (ML_In.0.sds)
Closed:   ML_Out (ML_Out.0.p.sds)
sdsFlags = 0x30000000.
83% idle.

Application output in the Serial Monitor

==== SDS playback started
Predictions (DSP: 18.000000 ms., Classification: 0 ms., Anomaly: 1.000000ms.): 
#Classification results:
    idle: 0.101562
    snake: 0.898438
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: 0.241648
==== SDS playback stopped
83% idle

Notes:

  • The playback implementation replays recordings as quickly as possible and does not account for timeslot data. During playback, the ML system receives the same recorded input data, so timing information is not relevant in this context.
  • This example includes an algorithm.sdsio.yml configuration file that sets algorithm/SDS Recordings as the working directory for SDS playback.
    To test the previous example, either: copy recorded files ML_In.0.sds and ML_Out.0.sds into that directory, or update the workdir in the algorithm.sdsio.yml.
    For details on the sdsio.yml configuration format and available options, refer to the documentation.

AlgorithmTest playback on the AVH-FVP Simulator

The AlgorithmTest can be also executed on AVH-FVP simulation models using the steps below:

  1. Use Manage Solution Settings and select:
    • Target type SSE-300-U55.
    • Project AlgorithmTest with Build Type Debug.
  2. Build Solution to create an executable image.
  3. Load and Run starts the application on the AVH-FVP simulation. The output is shown in the Terminal console.

FVP simulation output in the terminal

Executing task: FVP_Corstone_SSE-300_Ethos-U55 -f Board/Corstone-300/fvp_config.txt -a out/AlgorithmTest/SSE-300-U55/Debug/AlgorithmTest.hex  

Ethos-U version info:
        Arch:       v1.1.0
        MACs/cc:    256
        Cmd stream: v0
SDSIO VSI interface initialized successfully
==== SDS playback started
Predictions (DSP: 9.000000 ms., Classification: 0 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.996094
    snake: 0.000000
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: -0.432440
Predictions (DSP: 10.000000 ms., Classification: 0 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.996094
    snake: 0.000000
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: -0.274266
Predictions (DSP: 10.000000 ms., Classification: 0 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.996094
    snake: 0.000000
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: -0.183553
Predictions (DSP: 9.000000 ms., Classification: 0 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.996094
    snake: 0.000000
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: -0.168577
Predictions (DSP: 10.000000 ms., Classification: 1.000000 ms., Anomaly: 0ms.): 
#Classification results:
    idle: 0.996094
    snake: 0.000000
    updown: 0.000000
    wave: 0.000000
Anomaly prediction: -0.180526
==== SDS playback stopped

Content of the sdsio.log file recorded during the run

Created by ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition\Board\Corstone-300\vsi\python\arm_vsi3.py

SDSIO VSI version 3.1.0
SDSIO_FVP environment variable not set.
Working directory: ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition\algorithm\SDS Recordings.
SDSIO configuration YAML: ...\Arm-Examples\SDS-Examples\ST\B-U585I-IOT02A\MotionRecognition\algorithm.sdsio.yml.
sdsFlags = 0xB0000000.
Playback step 1/1: Play ML_In.0.sds.
Playback: ML_In (ML_In.0.sds)
Record:   ML_Out (ML_Out.0.p.sds)
Closed:   ML_In (ML_In.0.sds)
Closed:   ML_Out (ML_Out.0.p.sds)
Playback complete - no more steps remaining.
sdsFlags = 0x30000000.
sdsFlags = 0x70000000.
sdsFlags = 0x30000000.

Notes:

  • The simulator target only supports playback mode.
  • This example includes an algorithm.sdsio.yml configuration file that sets algorithm/SDS Recordings as the working directory for SDS playback.
    To test the previous example, either: copy recorded files ML_In.0.sds and ML_Out.0.sds into that directory, or update the workdir in the algorithm.sdsio.yml.
    For details on the sdsio.yml configuration format and available options, refer to the documentation.
  • The VSI script used by the simulator also generates the sdsio.log output file.