Embodiment Perception of a Smart Home Assistant

  • Conference paper
  • First Online:
Social Robotics (ICSR 2022)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 13818))

Included in the following conference series:

  • 1181 Accesses

Abstract

Demographic growth and rise in the average age of the population is increasing the demand for the elderly assistance. Health care oriented ambient intelligence technologies are fundamental to support elderly peoples’ autonomy. In this paper, we present a smart home system that is able to recognize human activities and is integrated with a proactive vocal assistant. We chose one of possible user scenarios to show the performance of this smart home system and to perform a preliminary comparison between users’ experience while watching videos of a volunteer interacting with an embodied versus a not-embodied assistant. The scenario is recorded from the user’s point of view, while the user interacts with a robot assistant or a simple vocal assistant. The results of the User Experience Questionnaire show that participants found the robot assistant considerably more attractive, innovative and stimulating in comparison to the vocal assistant.

M. Kilina and T. Elia—The authors contributed equally.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
EUR 29.95
Price includes VAT (Germany)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
EUR 85.59
Price includes VAT (Germany)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
EUR 106.99
Price includes VAT (Germany)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

Notes

  1. 1.

    https://estimote.com/.

  2. 2.

    https://github.com/TheEngineRoom-UniGe/OWLOOP.

  3. 3.

    https://youtu.be/85BQhc87pqA.

  4. 4.

    https://youtu.be/w9-w5tZRZDE.

References

  1. Baldissera, T.A., Camarinha-Matos, L.M.: Services evolution in elderly care ecosystems. In: Camarinha-Matos, L.M., Afsarmanesh, H., Rezgui, Y. (eds.) PRO-VE 2018. IAICT, vol. 534, pp. 417–429. Springer, Cham (2018). https://doi.org/10.1007/978-3-319-99127-6_36

    Chapter  Google Scholar 

  2. Bruno, B., Mastrogiovanni, F., Sgorbissa, A., Vernazza, T., Zaccaria, R.: Analysis of human behavior recognition algorithms based on acceleration data. In: 2013 IEEE International Conference on Robotics and Automation, pp. 1602–1607. IEEE (2013)

    Google Scholar 

  3. Chan, M., Estève, D., Escriba, C., Campo, E.: A review of smart homes-present state and future challenges. Comput. Methods Prog. Biomed. 91(1), 55–81 (2008)

    Article  Google Scholar 

  4. Costa, A., Julián, V., Novais, P.: Advances and trends for the development of ambient-assisted living platforms. Expert Syst. 34(2), e12163 (2017)

    Article  Google Scholar 

  5. Edgell, S.E., Noon, S.M.: Effect of violation of normality on the t test of the correlation coefficient. Psychol. Bull. 95(3), 576 (1984)

    Article  Google Scholar 

  6. Gama, E.V., Damian, J., Perez de Molino, J., López, M.R., Lopez Perez, M., Gavira Iglesias, F.: Association of individual activities of daily living with self-rated health in older people. Age Ageing 29(3), 267–270 (2000)

    Google Scholar 

  7. Jara, A.J., Zamora, M.A., Skarmeta, A.F.: An internet of things-based personal device for diabetes therapy management in ambient assisted living (aal). Pers. Ubiq. Comput. 15(4), 431–440 (2011)

    Article  Google Scholar 

  8. Kareem, S.Y., Buoncompagni, L., Mastrogiovanni, F.: Arianna\(^{+}\): scalable human activity recognition by reasoning with a network of ontologies. In: Ghidini, C., Magnini, B., Passerini, A., Traverso, P. (eds.) AI*IA 2018. LNCS (LNAI), vol. 11298, pp. 83–95. Springer, Cham (2018). https://doi.org/10.1007/978-3-030-03840-3_7

    Chapter  Google Scholar 

  9. Kim, K., Boelling, L., Haesler, S., Bailenson, J., Bruder, G., Welch, G.F.: Does a digital assistant need a body? the influence of visual embodiment and social behavior on the perception of intelligent virtual agents in ar. In: 2018 IEEE International Symposium on Mixed and Augmented Reality (ISMAR), pp. 105–114. IEEE (2018)

    Google Scholar 

  10. Kim, K., Norouzi, N., Losekamp, T., Bruder, G., Anderson, M., Welch, G.: Effects of patient care assistant embodiment and computer mediation on user experience. In: 2019 IEEE International Conference on Artificial Intelligence and Virtual Reality (AIVR), pp. 17–177. IEEE (2019)

    Google Scholar 

  11. Kontogiorgos, D., et al.: The effects of anthropomorphism and non-verbal social behaviour in virtual assistants. In: Proceedings of the 19th ACM International Conference on Intelligent Virtual Agents, pp. 133–140 (2019)

    Google Scholar 

  12. Lin, W.Y., Verma, V.K., Lee, M.Y., Lai, C.S.: Activity monitoring with a wrist-worn, accelerometer-based device. Micromachines 9(9), 450 (2018)

    Article  Google Scholar 

  13. Nakanishi, J., Baba, J., Kuramoto, I., Ogawa, K., Yoshikawa, Y., Ishiguro, H.: Smart speaker vs. social robot in a case of hotel room. In: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 11391–11396. IEEE (2020)

    Google Scholar 

  14. Ranasinghe, S., Al Machot, F., Mayr, H.C.: A review on applications of activity recognition systems with regard to performance and evaluation. Int. J. Distrib. Sensor Netw. 12(8), 1550147716665520 (2016)

    Article  Google Scholar 

  15. Ruzzon, M., Carfì, A., Ishikawa, T., Mastrogiovanni, F., Murakami, T.: A multi-sensory dataset for the activities of daily living. Data Brief 32, 106122 (2020)

    Article  Google Scholar 

  16. Sadri, F.: Ambient intelligence: a survey. ACM Comput. Surv. (CSUR) 43(4), 1–66 (2011)

    Article  Google Scholar 

  17. Schrepp, M., Hinderks, A., Thomaschewski, J.: Construction of a benchmark for the user experience questionnaire (ueq). IJIMAI 4(4), 40–44 (2017)

    Article  Google Scholar 

  18. Wagner, K., Nimmermann, F., Schramm-Klein, H.: Is it human? the role of anthropomorphism as a driver for the successful acceptance of digital voice assistants. In: Proceedings of the 52nd Hawaii International Conference on System Sciences (2019)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Mariya Kilina .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Kilina, M., Elia, T., Kareem, S.Y., Carfí, A., Mastrogiovanni, F. (2022). Embodiment Perception of a Smart Home Assistant. In: Cavallo, F., et al. Social Robotics. ICSR 2022. Lecture Notes in Computer Science(), vol 13818. Springer, Cham. https://doi.org/10.1007/978-3-031-24670-8_45

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-24670-8_45

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-24669-2

  • Online ISBN: 978-3-031-24670-8

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Navigation