Museum Layout Evaluation based on Visitor Statistical History

Abstract

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.