Projects that "Kill" Microcontrollers (Nov2020)

Post date: Nov 11, 2020 3:2:2 PM

Some embedded/IoT projects that require extensive processing and low power at the same time.

Like those that would take advantage of STM32F4/F7 DSP, FPU and SIMD, plus CMSIS-NN and CMSIS-DSP libraries.

The selected are those that can be downloaded directly. I skip those that require authentication.

• 1. Amoh,  J.  and  Odame,  K.  (2016).   Deep  neural networks for identifying cough sounds. IEEE transactions on biomedical circuits and systems,  10(5):1003–1011. 

  2. Available  https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7570164.

  3. Amoh,  J.  and  Odame,  K.  M.  (2019).   An  optimized  recurrent  unit  for  ultra-low-power  keyword  spotting. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies,3(2):1–17. 

  4. Available https://dl.acm.org/doi/pdf/10.1145/3328907.

  5. Lai,  L.,  Suda,  N.,  and  Chandra,  V.  (2018). CMSIS-NN:Efficient  neural  network  kernels  for  ARM  Cortex-M  CPUs. arXiv preprint arXiv:1801.06601. 

  6. Available https://arxiv.org/pdf/1801.06601.pdf.

  7. Liu, P.-X., Chen, Y.-j., Jiang, B.-H., and Zhang, X. (2016). Design  of  the  data  acquisition  system  based  on  STM32.   In 2016 Inter-national Conference on Computational Science and Engineering (ICCSE2016). Atlantis Press.

  8. Available https://download.atlantis-press.com/article/25862099.pdf.

  9. Xie, Y., Su, X., He, Y., Chen, X., Cai, G., Xu, B., and Ye,W.  (2017).   STM32-based  vehicle  data  acquisition  system  for  internet-of-vehicles.  In 2017 IEEE/ACIS 16th International Conference on Computerand Information Science (ICIS),  pages  895–898.  IEEE.   

  10. Available  https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=7960119.

  11. Zhang, Y. and Li, L. (2014). Smart home system basedon Zigbee network and STM32f407 microprocessor. The Open Cybernetics& Systemics Journal,  8(1).

  12. Available  https://benthamopen.com/contents/pdf/TOCSJ/TOCSJ-8-651.pdf.

  13. Zhang,  Y.,  Suda,  N.,  Lai,  L.,  and  Chandra,  V.  (2017). Hello  Edge:   Keyword   spotting   on   microcontrollers. arXiv preprintarXiv:1711.07128. 

  14. Available https://arxiv.org/pdf/1711.07128.pdf.

  15. Fezari, Mohamed, Mounir Bousbia-Salah, and Mouldi Bedda. Microcontroller Based Heart Rate Monitor. International Arab Journal of Information Technology (IAJIT) 5.4 (2008).

  16. Available http://www.academia.edu/download/49169562/11-198.pdf.