DN0034 Design note G-Module An Inertial and Environmental Sensor Module for IoT Designs from our labs describe tested circuit designs from ST labs which provide optimized solutions for specific applications. For more information or support, visit www.st.com By Michael Galizzi Main components BlueNRG-MS CSP Bluetooth Low Energy Network Processor BALF-NRG-01D3 50 Ω nominal input / conjugate match balun to BlueNRG STM32F411CEY High-performance, ARM Cortex-M4 core with DSP and FPU LSM6DS3 iNEMO inertial module: 3D accelerometer and 3D gyroscope LIS3MDLTR Ultra low-power, high performance 3-axis magnetometer UVIS25 Digital UV Index sensor: 0 - 15 UV Index output range LPS25HBTR MEMS pressure sensor: 260-1260 hPa absolute digital output LD39115J25R 150 mA low quiescent current low noise voltage regulator STC4054GR Li-Ion Battery charger with therminal regulation BAT60J Small Signal Schottky Diode Specification Bluetooth Low Energy Master-Slave V4.1 USB or battery powered MEMS module Low power consumption (down to 3 mA in continuous raw data streaming, up to 10 mA with MotionFX sensor fusion algorithm running at 100 Hz), 13.5 mm x 13.5 mm size Embedded sensor fusion for orientation estimation (IMU, AHRS) Embedded Activity recognition algorithm Circuit description Inertial Measurements Units (IMUs) provide core functions for essentially any wearable or embedded device and exhibit the most promising technology for applications where an accurate and reliable estimation of limb position and orientation is required. These systems, typically based on the combination of a triaxial geomagnetic sensor (MARG: Magnetic, Angular Rate, Gravity) and a microcontroller, can be enhanced by means of a Bluetooth LE radio interface. The orientation estimation processing can be performed on board, leading to an Attitude and Heading Reference System (AHRS). January 2016 DN0034 Rev 1 1/10 www.st.com Figure 1. Block Diagram January 2016 DN0034 Rev 1 2/10 www.st.com Figure 2. G-Module on cradle Figure 3. G-Module pin out and size comparison January 2016 DN0034 Rev 1 3/10 www.st.com Figure 4. Circuit diagram, BlueNRG January 2016 DN0034 Rev 1 4/10 www.st.com Figure 5. Circuit diagram, Sensors January 2016 DN0034 Rev 1 5/10 www.st.com Figure 6. Circuit diagram, STM32 microcontroller January 2016 DN0034 Rev 1 6/10 www.st.com Figure 7. Circuit diagram, other January 2016 DN0034 Rev 1 7/10 www.st.com Bill of material January 2016 Name Manufacturer Device Package U5 STMicroelectronics STM32F411CEY WLCSP49 U2 STMicroelectronics LD39115J25R FLIP-CHIP4 U11 STMicroelectronics LIS3MDLTR LGA-12 U10 STMicroelectronics LSM6DS3 LGA-14L U6 STMicroelectronics BlueNRG-MSCSP WLCSP36 U13 STMicroelectronics LPS25HBTR HCLGA-10L U4 STMicroelectronics BALF-NRG-01D3 CSP4 U12 STMicroelectronics UVIS25 HCLGA-10L D1 STMicroelectronics BAT60J SOD323 U7 STMicroelectronics STC4054GR SOT23-5L U8 Alps Electric Co. SSAJ120100 X2 AVX CX2016DB32000D0FLJCC C11 C1, C3, C6, C7, C8, C16, C19, C44, C32, C34 AVX 02016D225MAT2A C0201 AVX 02016D225MAT2A C0201 C29 Samsung CL03A474KQ3NNNC C0201 C30 C2, C4, C5, C9, C10, C13, C15, C33, C43 TDK C0603X5R1A154K030BB C0201 Murata GRM033R60J104KE19D C0201 C12, C17 AVX 02013A150JAT2A C0201 C14, C31 AVX 02013A101JAT2A C0201 L11 Pulse Electronics W3008C R3 Any R0201 R2 Any R0201 C18, C20 Any C0201 L13 TDK R1 Any MLF1608E100K L0603 R0402 DN0034 Rev 1 8/10 www.st.com Measurement results An activity recognition algorithm (osxMotionAR available on st.com) has been designed and validated on G-Module and can detect and recognize stationary activity, walking, fast walking, jogging, biking and driving activity with a mean power consumption as low as 700uA @ 5 V. Figure 8. G-Module test display on Android phone A 6DOF (degrees of freedom), iNEMO Engine Lite sensor fusion and a high performance sensor fusion (osxMotionFX available on st.com) has been ported, tested and validated on the module. An embedded 6DOF magnetometer calibration procedure is available in order to compensate magnetic distortion. The quaternion based output of orientation estimation algorithm and raw sensor data can be remotely logged using a dedicated Android/iOS app. Figure 9. G-Module displays on phone or tablet app January 2016 DN0034 Rev 1 9/10 www.st.com Support material Related design support material Product/ system Evaluation board (G-Module, Programming Cradle and SWD to JTAG adapter) Software Development Kit (containing examples and source code for Atollic TrueSTUDIO, IAR Embedded Workbench and SystemWorkbench for STM32) Android and iOS app interfacing G-Module Gerber files (on request Eagle file can be provided) PCB layout, bill of materials and schematics files Revision history Date 19-Jan-2016 Version 1 Changes Initial Release IMPORTANT NOTICE – PLEASE READ CAREFULLY STMicroelectronics NV and its subsidiaries (“ST”) reserve the right to make changes, corrections, enhancements, modifications, and improvements to ST products and/or to this document at any time without notice. Purchasers should obtain the latest relevant information on ST products before placing orders. ST products are sold pursuant to ST’s terms and conditions of sale in place at the time of order acknowledgement. Purchasers are solely responsible for the choice, selection, and use of ST products and ST assumes no liability for application assistance or the design of Purchasers’ products. No license, express or implied, to any intellectual property right is granted by ST herein. Resale of ST products with provisions different from the information set forth herein shall void any warranty granted by ST f or such product. ST and the ST logo are trademarks of ST. All other product or service names are the property of their respective owners. Information in this document supersedes and replaces information previously supplied in any prior versions of this document. © 2015 STMicroelectronics – All rights reserved January 2016 DN0034 Rev 1 10/10 www.st.com