TIDUFE7 March   2026

 

  1.   1
  2.   Description
  3.   Resources
  4.   Features
  5.   Applications
  6.   6
  7. 1System Description
  8. 2System Overview
    1. 2.1 Block Diagram
    2. 2.2 Design Considerations
    3. 2.3 Highlighted Products
      1. 2.3.1 MSPM0G5187 Mixed-Signal Microcontrollers With Edge AI NPU
      2. 2.3.2 CC2755R10 SimpleLink™ Bluetooth® LE wireless MCU
  9. 3Hardware, Software, Testing Requirements, and Test Results
    1. 3.1 Hardware Requirements
      1. 3.1.1 PIR Analog Signal Chain
    2. 3.2 Software Requirements
    3. 3.3 Test Setup
      1. 3.3.1 Data Collection
    4. 3.4 Test Results
      1. 3.4.1 Passive Infrared Sensor (PIR)
      2. 3.4.2 HDC3020 – Temperature and Humidity Sensor (I2C)
      3. 3.4.3 BMP384 – Barometric Pressure Sensor (I2C)
      4. 3.4.4 OPT4001 – Ambient Light Sensor (I2C)
      5. 3.4.5 BMI270 – 6-Axis IMU (SPI)
      6. 3.4.6 MAG5170 – 3D Hall-Effect Sensor (SPI)
      7. 3.4.7 ICS43434 – Digital Microphone (I2S)
  10. 4Design and Documentation Support
    1. 4.1 Design Files
      1. 4.1.1 Schematics
      2. 4.1.2 BOM
    2. 4.2 Tools and Software
    3. 4.3 Documentation Support
    4. 4.4 Support Resources
    5. 4.5 Trademarks
  11. 5About the Author

3.3.1 Data Collection

The following steps describe how to collect sensor data using the BoosterPack together with Edge AI Studio. These instructions are demonstrated using the MSPM0G5187 EVM as the reference platform. However, other TI EVMs can also support sensors from the BoosterPack, and compatibility is continuously being expanded.

Detailed documentation for data collection with MSP devices is available from the tida_010997_data_capture ReadMe file.

  1. Hardware Setup:
    1. Connect the BoosterPack to the LP-MSPM0G5187 LaunchPad™ Development Kit
    2. Make sure jumper J7 on the BoosterPack is set to 1:2
    3. Build and flash the tida_010997_data_capture example from the MSPM0 SDK to the MSPM0G5187
  2. Data Collection:
    1. Launch the CCStudio™ Edge AI Studio on your host PC
    2. Create a Time-series Classification project and navigate to the Capture tab
    3. Make sure the correct COM port is selected and baud rate is configured to 115200bps
    4. Verify the status bar displays Hardware connected
    5. Select the appropriate sensor, set the sample count and sample label, and select Start Capture
    6. Data is saved in CSV format