HOME | CHECKOUT | ABOUT | FAQ | CONTACT US |
 
Welcome Guest [create an account] or log-in:
email
password

Chapter 8 Tracking via Bluetooth and Wi Fi

DOI: 10.23912/9781911635383-4560

ISBN: 9781911635383

Published: Nov 2020

Component type: chapter

Published in: Tracking Tourists

Parent DOI: 10.23912/9781911635383-4277

Abstract

The technique of tracking tourists’ mobility using Bluetooth and Wi-Fi technology has emerged as a reliable and viable option for tourism planners and researchers (Shoval and Ahas, 2016; Musa and Eriksson, 2012). Recent studies have employed Bluetooth to measure the time it takes for people to pass through security (Bullock et al., 2010); assess movement flows at festivals (Versichele et al., 2012); and explore movement through cities (Verischele, 2014). Bluetooth has also been used to track high speed movement, such as car and cyclists, whereas Wi-Fi scanning, which takes a longer time to capture a signal, has been used to assess the flows of slower moving objects, such as tourists on foot, or other pedestrians (Abedi et al., 2013). Tracking using Wi-Fi or Bluetooth offers researchers the ability to track vast amounts of data on movement in a relatively short period of time. Verischele et al., (2012) describes the scanning of Wi-Fi and Bluetooth signals as ‘non-participatory’ research because individuals are not required to sign up and participate to studies of this nature, nor are they aware they are being tracked. The advantage of this approach is that tourists do not change their behaviour because of the knowledge that they are being tracked. This chapter will now review these forms of tracking technology, along with their advantages, limitations and ethical implications.

Sample content

Click here to download PDF

Contributors

For the source title:

Cite as

Hardy, 2020

Hardy, A. (2020) "Chapter 8 Tracking via Bluetooth and Wi Fi" In: Hardy, A. (ed) . Oxford: Goodfellow Publishers http://dx.doi.org/10.23912/9781911635383-4560

References

Abedi, N., Bhaskar, A., and Chung, E. (2013) Bluetooth and Wi-Fi MAC address based crowd data collection and monitoring: benefits, challenges and enhancement, In Proceedings of 36th Australasian Transport Research Forum, Brisbane, Queensland, Australia.

Addinsight (2017) Addinsight: Travel intelligence system. Available from: https://addinsight.com.au/ [Accessed 11th August, 2020]

Agostaro, F., Collura, F., Genco, F. and Sorce, S. (2004) Problems and solutions in setting up a low cost Bluetooth positioning system, WSEAS Transactions on Computers, 3(4), 1102-1106.

Arreeras, T., Arimura, M., Asada, T. and Arreeras, S. (2019) Association rule mining tourist-attractive destinations for the sustainable development of a large tourism area in Hokkaido using Wi-Fi tracking data, Sustainability, 11(14), 3967. Brennan Jr, T. M., Ernst, J. M., Day, C. M., Bullock, D. M., Krogmeier, J. V. and Martchouk, M. (2010) Influence of vertical sensor placement on data collection efficiency from Bluetooth MAC address collection devices, Journal of Transportation Engineering, 136(12), 1104-1109.

https://doi.org/10.3390/su11143967

Bullock, D.M., Haseman, R., Wasson, J.S. and Spitler, R. (2010) Automated measurement of wait times at airport security: deployment at Indianapolis International Airport, Indiana, Transportation Research Record, 2177(1), 60-68. Fukuda, D., Kobayashi, H., Nakanishi, W., Suga, Y., Sriroongvikrai, K. and Choocharukul, K. (2017) Estimation of paratransit passenger boarding/ alighting locations using Wi-Fi based monitoring: Results of field testing in Krabi City, Thailand, Journal of the Eastern Asia Society for Transportation Studies, 12, 2151-2169.

https://doi.org/10.3141/2177-08

General Data Protection Regulation (GDPR) (2018) General Data Protection Regulation Available at: https://gdpr-info.eu/ [Accessed 9 May 2018]

International Association of Privacy Professionals (2020) What the GDPR will mean for companies tracking location. Available from: https://iapp. org/news/a/what-the-gdpr-will-mean-for-companies-tracking-location/, [Accessed 4th April, 2020]

Kurkcu, A. and Ozbay, K. (2017) Estimating pedestrian densities, wait times, and flows with Wi-Fi and Bluetooth sensors, Journal of the Transportation Research Board, 2644(1), 72-82.

https://doi.org/10.3141/2644-09

Leccese, F., Cagnetti, M. and Trinca, D. (2014) A smart city application: a fully controlled street lighting isle based on Raspberry-Pi Card, a ZigBee sensor network and WiMAX, Sensors, 14(12), 24408-24424.

https://doi.org/10.3390/s141224408

Lesani, A. and Miranda-Moreno, L.F. (2016) Development and Testing of a real-time Wi-Fi-Bluetooth system for pedestrian network monitoring and data extrapolation, Presented at 95th Annual Meeting of the Transportation Research Board, Washington, D.C.

Musa, A.B.M. and Eriksson, J. (2012) Tracking unmodified smartphones using Wi-Fi monitors, In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems-SenSys, 12, Toronto, ON, Canada, 281-294 National Health and Medical Research Council, the Australian Research Council

https://doi.org/10.1145/2426656.2426685

and Universities Australia (2018). National Statement on Ethical Conduct in Human Research 2007 (Updated 2018). Commonwealth of Australia, Canberra

Oosterlincka, D., Benoita , D.F., Baeckeb , P. and Van de Weghec, N. (2017) Bluetooth tracking of humans in an indoor environment: an application to shopping mall visits, Applied Geography, 78, 55-65.

https://doi.org/10.1016/j.apgeog.2016.11.005

Privacy Company (2019) What does the GDPR say about WiFi Tracking?, Available from: https://www.privacycompany.eu/en/what-does-the-gdpr-say-about-wifi-tracking/ [Accessed 6 April, 2020].

Shoval, N. and Ahas, R. (2016) The use of tracking technologies in tourism research: the first decade, Tourism Geographies, 18(5), 587-606.

https://doi.org/10.1080/14616688.2016.1214977

Song, J., Lee, N.N., Chen, J.L., Dong, Y.F. and Zhao, Z. (2008) Design and implementation of intelligent transportation system based on GPRS and Bluetooth hybrid model, In Proceedings of International Conference on Automation and Logistics, 1381-1385.

https://doi.org/10.1109/ICAL.2008.4636369

Versichele, M., Neutens, T., Delafontaine, M. and Van de Weghe, N. (2012) The use of Bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent festivities, Applied Geography, 32(2), 208-220. Versichele, M., De Groote, L., Bouuaert, M. C., Neutens, T., Moerman, I. and van de Weghe, N. (2014) Pattern mining in tourist attraction visits through association rule learning on Bluetooth tracking data: A case study of Ghent, Belgium, Tourism Management, 44, 67-81. Yoshimura, Y., Sobolevsky, S., Ratti, C., Giradin, F., Carrascal, J., Blat, J. and Sinatra, R. (2014) An analysis of visitors' behavior in The Louvre Museum: a study using Bluetooth data, Environment and Planning B: Planning and Design, 41(6), 1113-1131.

https://doi.org/10.1016/j.tourman.2014.02.009

Yoshimura, Y. Amini, A., Sobolevsky, S., Blat, J. and Ratti, C. (2017) Analysis of pedestrian behaviors through non-invasive Bluetooth monitoring, Applied Geography, 81, 43-51.

https://doi.org/10.1016/j.apgeog.2017.02.002

Available

Chapter 8 Tracking via Bluetooth and Wi Fi [Details]Price: £5.99
(£5.99 including VAT)
*
Licences / Downloadable file

Published in Tracking Tourists

Chapter 8 Tracking via Bluetooth and Wi Fi [Details]Price: £5.99
(£5.99 including VAT)
*
Licences / Downloadable file
Paperback format [Details]Price: £34.99Copies / Delivery by post
Terms and conditions of purchase | Privacy policy