Museum Layout Evaluation based on Visitor Statistical History


  • La-or Kovavisaruch National Electronics and Computer Technology Center
  • Taweesak Sanpechuda National Electronics and Computer Technology Center
  • Krisada Chinda
  • Pobsit Kamolvej Department of Computer Science , Kasetsart University
  • Virach Sornlertlamvanich School of Information, Computer, and Communication Technology (ICT) , Sirindhorn International Institute of Technology


visitor behavior analysis, museum layout evaluation, museum mobile application


Museum layouts form a crucial component of the museum experience. However, it is not an easy task to evaluate and validate the performance of particular layouts. Currently, methods are used to track organic visitor paths in relation to layout design. With new technology, visitor tracking data can be collected through mobile applications or various sensors. While most researchers are interested in the density of visitor traffic gathered at each point of interest, our proposed methods focus on identifying the most visited path in the museum. Through the analysis of data collected from visitors, we can recreate the most visited path from probability calculations of any given visitor traveling from one point of interest to another. This method has been applied at the Chao Sam Phraya National Museum and our results reveal 4 broken paths in the path of heaviest traffic. In addition, we found that not all points of interest included on this path. These findings indicate that the museum curator may need to further investigate or redesign the display layouts to highlight any overlooked points of interest. One limitation of the proposed method is its reliance on statistical data collected from visitors. This means that viable results are predicated on large and clean datasets for processing.


S. Carliner, “Modeling Information for Three-dimensional Space: Lassons Learned from Museum Exhibit Design†Technical Communication Vol. 48 No. 1, pp. 66-81, Fubruary 2001

K. Tziortzi, “Museum Building Design and Exhibition Layout: pattern of interaction†Proceeding, 6th International Space Syntc Synposium, Instanbul, pp 1-15,2007.

L. Kovavisaruch • V. Sornlertlamvanich• T. Charoenporn • P. Kamolvej • N. Iamrahong “Evaluating and collecting museum visitor behavior via RFID†Portland Technology Management for Emerging Technologies (PICMET), 2012 Proceedings of PICMET '12, pp. 1099-1101, 2012

K. Sookhanaphibarn, R. Thawonmas, F. Rinaldo, and K. Chen, “Spatiotemporal Analysis of Circulation Behaviors Using Path And Residing Time displaY (PARTY)â€, 2011 Workshop on Digital Media and Digital Content Management. pp. 284 – 291, 2011.

R. Krueger, F. Heimerl, Q. Han, K. Kurzhals, S. Koch, and T. Ertl, “Visual Analysis of Visitor Behavior for Indoor Event Managementâ€, 48th Hawaii International Conference on System Sciences, pp 1148-1157, 2015.

Takayuki Kanda, Masahiro Shiomi, Laurent Perrin, Tatsuya Nomura, Hiroshi Ishiguro, and Norihiro Hagita, “Analysis of People Trajectories with Ubiquitous Sensors in a Science Museumâ€, IEEE International Conference on Robotics and Automation Roma, Italy, pp 4846 - 4853, 2007.

T. Wongsatho, L. Kovavisaruch, T. Sanpachuda, K. Chinda, S. Wisadsud, A. Chaiwongyen, “The Development of Museums Network Guide System by using QR code on Smart Phone†WMS Journal of Management, Vol. 4, No. 1 pp. 12-22, 2015.

N. Proctor “Mobile App for Museum,†, access January 15, 2015

U.Biader Ceipidor, C.M Medaglia., V. Volpi, A. Moroni, S. Sposato, M. Carboni, A. Caridi. 2013. NFC technology applied to touristic-cultural field: A case study on an Italian museum. International Workshop on Near Field Communication (NFC), pp. 1-6 , 2013.




How to Cite

Kovavisaruch, L.- or, Sanpechuda, T., Chinda, K., Kamolvej, P., & Sornlertlamvanich, V. (2017). Museum Layout Evaluation based on Visitor Statistical History. Asian Journal of Applied Sciences, 5(3). Retrieved from