Skip to main content

Predicting from GPS and Accelerometer Data When and Where Tourists Have Viewed Exhibitions

  • Conference paper
  • First Online:
Information and Communication Technologies in Tourism 2014

Abstract

Research has been conducted to understand tourists’ spatio-temporal behaviours. However, it is very costly to investigate what the tourist was actually doing at each location and moment and what he/she was interested in Kawase et al. (When and where tourists are viewing exhibitions: Toward sophistication of GPS-assisted tourist activity surveys. Springer, Vienna, pp. 415–425, 2012) demonstrated the possibility that we can predict only from a tourist’s GPS log whether he/she is viewing an exhibition or not, which is one of the most basic activities in tourism. Following their work, we conduct an additional experiment two types of subjects, students and kindergarteners with parents, and refine the prediction model with additional explaining parameters. We found that the model for students could be successfully improved, while that for kindergarteners has a problem due to the inconsistency of their behaviour. In addition, we experimentally investigated the combined use of a GPS sensor and an accelerometer, both usually equipped in smartphones, for predicting tourists’ viewing state. The result shows that the combined use of these sensors seems promising to infer tourists’ activities.

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 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight 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

Similar content being viewed by others

References

  • Akahori, A., Kishimoto, Y., & Oguri, K. (2005). A Study of estimation of actions using a three-axis acceleration sensor. IEIC Technical Report, 105(456), 49–52.

    Google Scholar 

  • Asakura, Y., & Hato, E. (2004). Tracking survey for individual travel behaviour using mobile communication instruments. Transportation Research Part C: Emerging Technologies, 12(3–4), 273–291.

    Article  Google Scholar 

  • Asakura, Y., & Iryo, T. (2007). Analysis of tourist behaviour based on the tracking data collected using a mobile communication instrument. Transportation Research Part A: Policy and Practice, 41(7), 684–690.

    Google Scholar 

  • Birenboim, A., Anton-Clavé, S., Russo, A. P., & Shoval, N. (2013). Temporal activity patterns of theme park visitors. Tourism Geographies, published online.

    Google Scholar 

  • Intille, S. S., Bao, L., Tapia, E. M., & Rondoni, J. (2004). Acquiring in situ training data for context-aware ubiquitous computing applications. In SIGCHI Conference on Human factors in Computing Systems (pp. 1–8). ACM.

    Google Scholar 

  • Kanda, T., Shiomi, M., Perrin, L., Nomura, T., Ishiguro, H., & Hagita, N. (2007). Analysis of people trajectories with ubiquitous sensors in a science museum. In Robotics and Automation, 2007 IEEE International Conference (pp. 4846–4853). IEEE.

    Google Scholar 

  • Kawase, J., Kurata, Y., & Yabe, N. (2012). When and where tourists are viewing exhibitions: Toward sophistication of GPS-assisted tourist activity surveys. In ENTER 2012 (pp. 415–425). Springer Vienna.

    Google Scholar 

  • Kern, N., Antifakos, S., Schiele, B., & Schwaninger, A. (2004). A model for human interruptability: Experimental evaluation and automatic estimation from wearable sensors. In International Symposium on Wearable Computers, 2004 (Vol. 1, pp. 158–165). IEEE.

    Google Scholar 

  • Matsunami, H. (2007). Service science: Applications of observation to real world business. In 4th International Conference on Universal Access in Human-Computer Interaction (pp. 951–960). Berlin Heidelberg: Springer.

    Google Scholar 

  • Miluzzo, E., Papandrea, M., Lane, N. D., Lu, H., & Campbell, A. T. (2010). Pocket, bag, hand, etc.-automatically detecting phone context through discovery. In PhoneSense 2010 (pp. 21–25).

    Google Scholar 

  • Miyazaki, Y., Konishi, Y., Nakao, T., Koshiba, H., Aihara, K., and Takeda, H. (2010). M-066 in-store context estimation using sensors: Application of human and environmental sensing for development of e-Space. In Forum on Information Technology (Vol. 9(4), pp. 431–434). (In Japanese).

    Google Scholar 

  • Nagao, M., Kawamura, H., Yamamoto, M., & Ohuchi, A. (2004). Acquisition of personal tourism activity information based on GPS log mining method. In Fifth Asia-Pacific Industrial Engineering and Management Systems Conference (CD-ROM).

    Google Scholar 

  • Randell, C., & Muller, H. (2000). Context awareness by analysing accelerometer data. In Fourth International Symposium on Wearable Computers (pp. 175–176). IEEE.

    Google Scholar 

  • Shoval, N. (2008). Tracking technologies and urban analysis. Cities, 25(1), 21–28.

    Article  Google Scholar 

  • Shoval, N., & Isaacson, M. (2007a). Tracking tourist in the digital age. Annals of Tourism Research, 34(2), 141–159.

    Article  Google Scholar 

  • Shoval, N., & Isaacson, M. (2007b). Sequence alignment as a method for human activity analysis. Annals of the Association of American Geographers, 97(2), 282–297.

    Article  Google Scholar 

  • Thornton, P. R., Williams, A. M., & Shaw, G. (1997). Revisiting time-space diaries: An exploratory case study of tourist behaviour in Cornwall. England. Environment and Planning A, 29(10), 1847–1867.

    Article  Google Scholar 

  • Yabe, N., Arima, T., Okamura, Y., & Kadono, A. (2010). An agenda on tourist activity survey using GPS and investigation of analysis methods. International Journal of Tourism Science, 3, 17–30. (In Japanese).

    Google Scholar 

  • Yoshimura, Y., Girardin, F., Carrascal, J. P., Ratti, C., & Blat, J. (2012). New tools for studying visitor behaviours in museums: a case study at the Louvre. In ENTER 2012 (pp. 391–402). Springer Vienna.

    Google Scholar 

Download references

Acknowledgments

We appreciate the visitors to Tama Zoological Park who participated in our surveys, as well as its staff who kindly helped our surveys and gave valuable comments to us.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Junya Kawase .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer International Publishing Switzerland

About this paper

Cite this paper

Kawase, J., Kurata, Y., Yabe, N. (2013). Predicting from GPS and Accelerometer Data When and Where Tourists Have Viewed Exhibitions. In: Xiang, Z., Tussyadiah, I. (eds) Information and Communication Technologies in Tourism 2014. Springer, Cham. https://doi.org/10.1007/978-3-319-03973-2_9

Download citation

Publish with us

Policies and ethics