Implementing an In-Home Sensor Agent in Conjunction with an Elderly Monitoring Network

Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 558)

Abstract

In this paper, we present the design and implementation of the in-home sensor agent MaMoRu-Kun as an Internet of Things (IoT) smart device, developed via the “Research and development of the regional/solitary elderly life support system using multi-fusion sensors” project. At Akita Prefectural University, the bed and pillow sensors and corresponding monitoring system have been developed to watch elderly individuals at bedtime, in particular those who live alone. As a sensor agent, MaMoRu-Kun is connected to the in-home wireless network of the target individuals accommodations and collects trigger information from various switches, motion detection sensors, and a remote controller. This smart device is also able to send its entire set of data along with the status of the sensor to a collection and monitoring server connected via a long-term evolution (LTE) router. We implemented this agent using an Arduino and a Bluetooth-connected Android terminal.

References

  1. 1.
    Mitas, A. W., Rudzki, M., Skotnicka, M., & Lubina, P. (2014). Activity monitoring of the elderly for telecare systems – review. In E. Pietka, J. Kawa, & W. Wieclawek (Eds.), Information technologies in biomedicine (Vol. 4, pp. 125–138). Cham: Springer.Google Scholar
  2. 2.
    Jian, Y., Kiong, T. K., & Heng, L. T. (2010). Development of an e-Guardian for the single elderly or the chronically-ill patients. In Proceedings of Communications and Mobile Computing Conference (CMC) (pp. 378–382).Google Scholar
  3. 3.
    Gaddam, A., Mukhopadhyay, S. C., & Gupta, G. S. (2011) Trial and experimentation of a smart home monitoring system for elderly. In Proceedings of Instrumentation and Measurement Technology Conference (I2MTC) (pp. 1–6).Google Scholar
  4. 4.
    Yan, H., Huo, H., Xu, Y., & Gidlund, M. (2010). Wireless sensor network based E-health system: Implementation and experimental results. In IEEE Transaction on Consumer Electronics (Vol. 56, no. 4, pp. 2288–2295).Google Scholar
  5. 5.
    Mayr, H., Franz, B., & Mayr, M. (2010). IHE-compliant mobile application for integrated home healthcare of elderly people. In Proceedings of Information Technology: New Generations Conference (ITNG) (pp. 798–803).Google Scholar
  6. 6.
    Schikhof, Y., & Mulder, I. (2008). Under watch and ward at night: Design and evaluation of a remote monitoring system for dementia care. In D. Hutchison, A. Holzinger, T. Kanade, J. Kittler, J. M. Kleinberg, F. Mattern, J. C. Mitchell, M. Naor, O. Nierstrasz, C. Pandu Rangan, B. Steffen, M. Sudan, D. Terzopoulos, D. Tygar, M. Y. Vardi, & G. Weikum (Eds.), HCI and usability for education and work (LNCS, Vol. 5298, pp. 475–486). Berlin/Heidelberg: Springer.Google Scholar
  7. 7.
    Chen, J., Kam, A., Zhang, J., Liu, N., & Shue, L. (2005). Bathroom activity monitoring based on sound. In H. W. Gellersen, R. Want, & A. Schmidt (Eds.), Pervasive computing (LNCS, Vol. 3468, pp. 65–76). Berlin/New York: Springer.Google Scholar
  8. 8.
    Wtorek, J., Bujnowski, A., Lewandowska, M., Ruminski, J., Polinski, A., & Kaczmarek, M. (2010). Evaluation of physiological and physical activity by means of a wireless multi-sensor. In Proceedings of Information Technology Conference (ICIT) (pp. 239–242).Google Scholar
  9. 9.
    Coronato, A., Pietro, G. D., & Sannino, G. (2010) Middleware services for pervasive monitoring elderly and ill people in smart environments. In Proceedings of Information Technology: New Generations Conference (ITNG) (pp. 810–815).Google Scholar
  10. 10.
    Arcelus, A., Jones, M. H., Goubran, R., & Knoefel, F. (2007). Integration of smart home technologies in a health monitoring system for the elderly. In Proceedings of Advanced Information Networking and Applications Workshops (AINAW) (Vol. 2, pp. 820–825).Google Scholar
  11. 11.
    Shimoi, N., & Madokoro, H. (2013). A study for the bed monitoring system using 3 dimensional accelerometer and piezoelectric weight sensor. Transactions of SICE (Japanese edition), 49(12), 1092–1100.CrossRefGoogle Scholar
  12. 12.
    Madokoro, H., Shimoi, N., & Sato, K. (2013). Development of non-restraining and QOL sensor systems for bed-leaving prediction. In IEICE Transactions on Information and Systems (Japanese edition), 96(12), 3055–3067.Google Scholar
  13. 13.
    MIFARE. ISO/IEC 14443 Type A 13.56 MHz contactless smart card standard [Online]. Available http://www.mifare.net/.
  14. 14.
    Arduino, An open-source prototyping platform for embedded systems [Online]. Available http://www.arduino.cc/.
  15. 15.
    1Sheeld, An Arduino multi-purpose shield with smart-phone [Online]. Available http://1sheeld.com/.
  16. 16.
    D3, Data-driven documents [Online]. Available http://d3js.org/.

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Katsumi Wasaki
    • 1
  • Masaaki Niimura
    • 1
  • Nobuhiro Shimoi
    • 2
  1. 1.Faculty of EngineeringShinshu UniversityNaganoJapan
  2. 2.Faculty of Systems Science and TechnologyAkita Prefectural UniversityAkitaJapan

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