Pervasive NFC-based solution for the analysis of tourism data in an environment of smart cities

Eliana Andrea Concha Agredo, Luis Carlos Martínez-Acosta, Angela Chantre, Gustavo Ramirez-Gonzalez

Abstract


Detailed recording and analysis of visitor paths and individual mouse movements in real time of tens-of-thousands of visitors is one of the most important areas of tourism research, and to observe tourist movements a variety of techniques are available. New tracking techniques are explored and due to the advance of technology we can have information at any time and from anywhere (pervasive computing). This has been used to record movement information of tourists with high resolution. In these environments (tags environments) where the user interacts with the environment, an emerging technology called NFC (Near Field Communication) is providing a natural means of interaction between the users and their environment. This paper shows the implementation of an NFC-based pervasive solution that allows tourist tracking data to be obtained in real time; it is simplified and analyzed with the Markov chains method by experimental and statistical testing. It is also demonstrated that the movement of a tourist is influenced by the state or tourist site where he or she is to move to another, corroborating the hypothesis "that if you can capture the information left by tourists through technological tools, thanks to the processing of such information you can obtain a trace that is a sample of the activity which, through its display, allows decisions that promote tourism as part of the regional and national economy".

Keywords


Context; pervasive computing, smart cities; NFC; tourism; location; Markov chains analysis; movements and tourists.

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References


Ahas, R., Aasa, A., Mark, Ü., Pae, T., & Kull, A. (2007). Seasonal tourism spaces in Estonia: Case study with mobile positioning data. Tourism Management, 28(3), 898-910.

Ailisto, H., Pohjanheimo, L., Välkkynen, P., Strömmer, E., Tuomisto, T., & Korhonen, I. (2006). Bridging the physical and virtual worlds by local connectivity-based physical selection. Personal and Ubiquitous Computing, 10(6), 333-344.

Akaike, H. (2014, May). Statistical Inference and Measurement of Entropy. In Scientific Inference, Data Analysis, and Robustness: Proceedings of a Conference Conducted by the Mathematics Research Center, the University of Wisconsin—Madison, November 4–6, 1981 (p. 165). Academic Press.

Arrowsmith, C. & Inbakaran, R. (2002). Estimating environmental resiliency for the Grampians National Park, Victoria, Australia: a quantitative approach. Tourism Management, 23(3), 295-309.

Arrowsmith, C., Chhetri, P., & Zanon, D. (2005). Monitoring visitor patterns of use in natural tourist destinations. In Taking Tourism to the Limits: Issues, Concepts and Managerial Perspectives, (pp. 33-52). Amsterdam, The Netherlands: Elsevier

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.

Bajaj, R., Ranaweera, S. L., & Agrawal, D. P. (2002). GPS: location-tracking technology. Computer, 35(4), 92-94.

Borrego-Jaraba, F., Ruíz, I. L., & Gómez-Nieto, M. Á. (2011). A NFC-based pervasive solution for city touristic surfing. Personal and Ubiquitous Computing, 15(7), 731-742.

Buhalis, D. & Amaranggana, A. (2013). Smart Tourism Destinations. In Information and Communication Technologies in Tourism 2014 (pp. 553-564). Springer International Publishing.

Cheverst, K., Davies, N., Mitchell, K., & Friday, A. (2000). Experiences of developing and deploying a context-aware tourist guide: the GUIDE project. In Proceedings of the 6th Annual International Conference on Mobile Computing and Networking, 20-31. New York, NY: ACM.

Chon, J., & Cha, H. (2011). Lifemap: A smartphone-based context provider for location-based services. IEEE Pervasive Computing, 10(2), 58-67.

Coskun, V., Ozdenizci, B., & Ok, K. (2013). A survey on near field communication (NFC) technology. Wireless Personal Communications, 71(3), 2259-2294.

Davies, N., Cheverst, K., Mitchell, K., & Efrat, A. (2001). Using and determining location in a context-sensitive tour guide. Computer, 34(8), 35-41.

Digital Tourism Think Tank [DTTT] (2014). 2014 year in digital travel [video]. Retrieved from http://youtu.be/rJZbtg_irZU

Ducatel, K., Bogdanowicz, M., Scapolo, F., Leijten, J., & Burgelman, J.-C. (2001). Scenarios for ambient intelligence in 2010 [online]. Seville, Spain: ISTAG. Retrieved from http://www.ist.hu/doctar/fp5/istagscenarios2010.pdf

Dumont, B., Roovers, P., & Gulinck, H. (2005). Estimation of off-track visits in a nature reserve: a case study in central Belgium. Landscape and Urban Planning, 71(2), 311-321.

Egger, R. (2013). The impact of near field communication on tourism. Journal of Hospitality and Tourism Technology, 4(2), 119-133.

Fennell, D. A. (1996). A tourist space-time budget in the Shetland Islands. Annals of Tourism Research, 23(4), 811-829.

Fundación Telefónica (2011). Smart Cities: un primer paso hacia la Internet de las Cosas. Madrid, Spain: Fundación Telefónica.

Girardin, F., Vaccari, A., Gerber, A., Biderman, A., & Ratti, C. (2009). Quantifying urban attractiveness from the distribution and density of digital footprints. International Journal of Spatial Infrastructures Research, 4, 175-200

Hadley, D., Grenfell, R., & Arrowsmith, C. (2003). Deploying location-based services for nature-based tourism in non-urban environments [conference paper in Spatial Sciences Coalition Conference, Canberra-2003].

Haritaoglu, I., Harwood, D., & Davis, L. (2000). W 4: Real-time surveillance of people and their activities. IEEE Transactions on Pattern Analysis and Machine Intelligence, 22(8), 809-830.

Hurtado, M. (2011). Aportes al proceso administrativo del proyecto de trazabilidad para el sistema de información turística del departamento del Cauca como iniciativa piloto [thesis]. Universidad del Cauca: Popayán, Colombia.

Kuo, R. J., Wang, H. S., Hu, T. L., & Chou, S. H. (2005). Application of ant K-means on clustering analysis. Computers & Mathematics with Applications, 50(10), 1709-1724.

Leiper, N. (2003). Tourism management. Australia: Pearson

Loiterton, D. & Bishop, I. (2005). Virtual environments and location-based questioning for understanding visitor movement in urban parks and gardens [conference paper in Real-time Visualisation and Participation, Dessau-Germany]. Available at http://www.kolleg.loel.hs-anhalt.de/studiengaenge/mla/mla_fl/conf/pdf/conf2005/30loiterton_c.pdf

Loke, S. (2005). Context-aware Pervasive systems: Architectures for a new breed of applications. Boca Raton, FL: Auerbach.

McLaren, D. (2003). Rethinking tourism and ecotravel. Bloomfield, CT: Kumarian.

Naphade, M., Banavar, G., Harrison, C., Paraszczak, J., & Morris, R. (2011). Smarter cities and their innovation challenges. Computer, 44(6), 32-39.

NFC Forum (2015). [online]. Retrieved from http://nfc-forum.org/

O'Connor, A., Zerger, A., & Itami, B. (2005). Geo-temporal tracking and analysis of tourist movement. Mathematics and Computers in Simulation, 69(1), 135-150.

Ogilvie, F. (1933). The tourist movement: An economic study. London, UK: PS King & Son.

O'Neill, E., Kostakos, V., Kindberg, T., Penn, A., Fraser, D. S., & Jones, T. (2006). Instrumenting the city: Developing methods for observing and understanding the digital cityscape. In UbiComp 2006: Ubiquitous Computing (pp. 315-332). Berlin-Heidelberg, Germany: Springer

Pearce, D. (1995). Tourism today: A geographical analysis [2nd ed.]. London, UK: Longman Scientific & Technical.

Pesonen, J. & Horster, E. (2012). Near field communication technology in tourism. Tourism Management Perspectives, 4, 11-18.

PrimeFaces (2014). [online]. Retrieved from http://www.primefaces.org/

Ramirez, G., Chantré, A., & Delgado, C. (2014). Proyecto piloto de trazabilidad turística [internal document]. Universidad del Cauca: Popayán, Colombia.

Remedios, D., Sousa, L., Barata, M., & Osorio, L. (2006). NFC technologies in mobile phones and emerging applications. In Information Technology for Balanced Manufacturing Systems (pp. 425-434). New York, NY: Springer.

Roland, M. & Langer, J. (2010). Digital signature records for the NFC data exchange format. In Near Field Communication (NFC), 2010 Second International Workshop on, (pp. 71-76). Piscataway, NJ: IEEE.

Ronay, E. & Egger, R. (2013). NFC smart city: Cities of the future—a scenario technique application. Information and Communication Technologies in Tourism 2014 [Proceedings of the International Conference in Dublin, Ireland, January 21-24, 2014], (pp. 565-577). Cham, Switzerland: Springer.

Russo, A. P., Clave, S. A., & Shoval, N. (2010). Advanced visitor tracking analysis in practice: explorations in the PortAventura theme park and insights for a future research agenda. Information and Communication Technologies in Tourism 2010, 159-170.

Spitzer, F. (1964). Principles of random walk. New York, NY: Springer.

Tchetchik, A., Fleischer, A., & Shoval, N. (2009). Segmentation of visitors to a heritage site using high-resolution time-space data. Journal of Travel Research, 48(2), 216-229.

Tiru, M., Kuusik, A., Lamp, M. L., & Ahas, R. (2010). LBS in marketing and tourism management: measuring destination loyalty with mobile positioning data. Journal of Location Based Services, 4(2), 120-140.

Tobler, W. (1997). Movement modelling on the sphere. Geographical and Environmental Modelling, 1(1), 97-103.

United Nations World Tourism Organization [UNWTO]. (2014, Jan. 20). International tourism exceeds expectations with arrivals up by 52 million in 2013 [press release]. Retrieved from http://media.unwto.org/press-release/2014-01-20/international-tourism-exceeds-expectations-arrivals-52-million-2013

Van Setten, M., Pokraev, S., & Koolwaaij, J. (2004). Context-aware recommendations in the mobile tourist application COMPASS. Lecture Notes in Computer Science [Adaptive hypermedia and adaptive web-based systems], 3137, 235-244

Wang, B. & Manning, R. (1999). Computer simulation modeling for recreation management: A study on carriage road use in Acadia National Park, Maine, USA. Environmental Management, 23(2), 193-203.

Wang, Y., Lim, E. P., & Hwang, S. Y. (2006). Efficient mining of group patterns from user movement data. Data & Knowledge Engineering, 57(3), 240-282.

Xia, J. & Arrowsmith, C. (2005). Managing scale issues in spatio-temporal movement of tourists modelling. In International Congress on Modelling and Simulation. Retrieved from http://ip-103-1-174-100.ip.secureserver.net/modsim05/papers/xia.pdf

Xia, J. (2007). Modelling the spatial-temporal movement of tourists [PhD thesis]. RMIT University: Melbourne, Australia

Xia, J., Zeephongsekul, P., & Arrowsmith, C. (2009). Modelling spatio-temporal movement of tourists using finite Markov chains. Mathematics and Computers in Simulation, 79(5), 1544-1553.

Zimmermann, K. F. & Constant, A. F. (2003). The dynamics of repeat migration: A Markov chain analysis [discussion paper online]. Retrieved from http://www.econstor.eu/handle/10419/18135




DOI: http://dx.doi.org/10.18046/syt.v13i32.2016

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