Skip to main content

Research and Development of Normally-Off Computing—NEDO Project

  • Chapter
  • First Online:
Normally-Off Computing

Abstract

Based on normally-off computing design methodology, we developed three practical systems that introduced normally-off computing. These systems are healthcare, mobile information device and sensor node for social infrastructure. These systems are selected from different types of application areas. Through implementing a variety of systems, universalness of normally-off computing is confirmed. Also we introduce our “Normally-Off Computing Project”, which supports these practical developments.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Normally-off computing project (in Japanese). http://www.nedo.go.jp/activities/ZZJP_100016.html

  2. Nakajima, H., Shiga, T., Hara, Y.: Systems health care. In: Proceedings of IEEE SMC, pp. 1167–1172, Oct. 2011

    Google Scholar 

  3. Oshima, Y., Kawaguchi, K., Tanaka, S., Ohkawara, K., Hikihara, Y., Ishikawa-Tanaka, K., Tabata, I.: Classifying household and locomotive activities using a triaxial accelerometer. Gait Posture 31, 370–374 (2010)

    Article  Google Scholar 

  4. Roel, W., John, M.: Comparing spectra of a series of point events particularly for heart rate variability data. IEEE T-BME, BME-31 4, 384–387 (1984)

    Google Scholar 

  5. Yazaki, S., Matsunaga, T.: Evaluation of activity level of daily life based on heart rate and acceleration. In: Proceedings of SICE, pp. 1002–1005, Aug. 2010

    Google Scholar 

  6. Itao, K., Umeda, T., Lopez, G., Kinjo, M.: Human recorder system development for sensing the autonomic nervous system. In: Proceedings of IEEE Sensors, pp. 423–426, Oct. 2008

    Google Scholar 

  7. Itao, K., Ito, T.: Integrated sensing systems for health and safety. In: Proceedings of DTIP Symposium, pp. 212–216, May 2011

    Google Scholar 

  8. Zhang, F., Zhang, Y., Silver, J., et al.: A Battery-less 19 uW MICS/ISM-band energy harvesting body area sensor node SoC. In: ISSCC, pp. 298–299, Feb. 2012

    Google Scholar 

  9. Kim, H., Yazicioglu, R.F., Kim, S., et al.: A configurable and low-power mixed signal SoC for portable ECG monitoring applications. In: VLSI Symposium, pp. 142–143, Jun. 2011

    Google Scholar 

  10. Hsu, S.Y., Chen, Y.L., Chang, P.Y., et al.: A Micropower biomedical signal processor for mobile healthcare applications. In: Proceedings of IEEE ASSCC, pp. 301–304, Nov. 2011

    Google Scholar 

  11. Kimura, H., Fuchikami, T., Marumoto, K., Fujimori, Y., Izumi, S., Kawaguchi, H., Yoshimoto, M.: A 2.4 pJ ferroelectric-based non-volatile flip-flop with 10-year data retention capability. In: Proceedings of IEEE A-SSCC, Nov. 2014

    Google Scholar 

  12. Masui, S., Yokozeki, W., Oura, M., Ninomiya, T., Mukaida, K., Takayama, Y., Teramoto, T.: Design and applications of ferroelectric nonvolatile SRAM and Flip-FF with unlimited read, program cycles and stable recall. In: Proceedings of IEEE CICC, pp. 403–406 (2003)

    Google Scholar 

  13. Hsu, S.Y., Chen, Y.L., Chang, P.Y., Yu, J.Y., Yang, T.F., Chen, R.J., Lee, C.Y.: A micropower biomedical signal processor for mobile healthcare applications. In: Proceedings of IEEE A-SSCC, pp. 301–304, Nov. 2011

    Google Scholar 

  14. Fujii, T., Nakano, M., Yamashita, K., Konishi, T., Izumi, S., Kawaguchi, H., Yoshimoto, M.: Noise tolerant instantaneous heart rate and R-peak detection using short-term autocorrelation for wearable healthcare systems. In: Proceedings of IEEE EMBC, pp.7330–7333, July 2013

    Google Scholar 

  15. Hsu, S.Y., Ho, Y., Chang, P.Y., Hsu, P.Y., Yu, C.Y., Tseng, Y., et al.: A 48.6-to-105.2\({\upmu }\text{W}\) machine-learning assisted cardiac sensor SoC for mobile healthcare monitoring. In: Dig. IEEE Symposium VLSI Circuits, pp. 252–253, Jun. 2013

    Google Scholar 

  16. Kim, H., Yazicioglu, R.F., Kim, S., et al.: A configurable and low-power mixed signal SoC for portable ECG monitoring applications. In: Dig. IEEE Symposium VLSI Circuits, pp. 142–143, Jun. 2011

    Google Scholar 

  17. Deepu, C.J., Zhang, X., Liew, W.S., Wong, D.L.T., Lian, Y.: An ECG-SoC with 535nW/channel lossless data compression for wearable sensors. In: Proceedings of IEEE A-SSCC, pp. 145–148. Nov. 2013

    Google Scholar 

  18. Izumi, S., Yamashita, K., Nakano, M., Konishi, T., Kawaguchi, H., Kimura, H., et al.: A 14 uA ECG processor with robust heart rate monitor for a wearable healthcare system. In: Proceedings of IEEE ESSCIRC, pp. 145–148, Sep. 2013

    Google Scholar 

  19. Kim, S., Yan, L., Mitra, S., Osawa, M., Harada, Y., Tamiya, K., et al.: A 20uW intra-cardiac signal-processing IC with 82dB bio-impedance measurement dynamic range and analog feature extraction for ventricular fibrillation detection. In: ISSCC Dig. Technical Papers, pp. 302–303, Feb. 2013

    Google Scholar 

  20. Zhang, F., Zhang, Y., Silver, J., Shakhsheer, Y., Nagaraju, M., Klinefelter, A., et al.: A battery-less 19uW MICS/ISM-band energy harvesting body area sensor node SoC. In: ISSCC Dig. Technical Papers, pp. 298–299, Feb. 2012

    Google Scholar 

  21. Abe, K., Nomura, K., Ikegawa, S., Kishi, T., Yoda, H., Fujita, S.: Hierarchical nonvolatile memory with perpendicular magnetic tunnel junctions for normally-off computing. In: The 2010 International Conference on Solid State Devices and Materials (SSDM), Tokyo, pp. 1144–1145, Sep. 2010

    Google Scholar 

  22. Ando, K.: A Normally-off Computer. FED Journal 12, 89 (2001). (in Japanese)

    Google Scholar 

  23. Ando, K., Ikegawa, S., Abe, K., Fujita, S., Yoda, H.: Normally-Off Computer: new roles of nonvolatile devices in future computer systems. In: Sustainable Green Computing, IGI press, ISBN 978-1-4666-1842-8, June, 2012

    Google Scholar 

  24. Takeda, S., et al.: Low-power cache memory with state-of-the-art STT-MRAM for high performance processors. In: ISOCC (2015)

    Google Scholar 

  25. Fujita, S., et al.: Novel nonvolatile memory hierarchies to realize normally-off mobile processors. In: 19th Asia and South Pacific Design Automation Conference (ASP-DAC) (2014)

    Google Scholar 

  26. Samsung Exynos\(^\text{ TM }\) (Exynos 4412) for Galaxy mobiles. http://www.samsung.com/exynos/

  27. Fujita, S., et al.: Technology trends and applications of MRAM from big data to wearable devices. In: ISSCC (2015)

    Google Scholar 

  28. Fujita, S., et al.: Technology trends and near-future applications of embedded STT-MRAM. In: IMW (2015)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Takashi Nakada .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer Japan KK

About this chapter

Cite this chapter

Nakada, T., Fujita, S., Hayashikoshi, M., Izumi, S., Fujimori, Y., Nakamura, H. (2017). Research and Development of Normally-Off Computing—NEDO Project. In: Nakada, T., Nakamura, H. (eds) Normally-Off Computing. Springer, Tokyo. https://doi.org/10.1007/978-4-431-56505-5_6

Download citation

  • DOI: https://doi.org/10.1007/978-4-431-56505-5_6

  • Published:

  • Publisher Name: Springer, Tokyo

  • Print ISBN: 978-4-431-56503-1

  • Online ISBN: 978-4-431-56505-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics