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Art museum professionals traditionally rely on observations and surveys to enhance their knowledge of visitor behavior and experience. However, these approaches often produce spatially and temporally limited empirical evidence and measurements. Only recently has the ubiquity of digital technologies revolutionized the ability to collect data about human behavior. Consequently, the greater availability of large-scale datasets based on quantifying visitors' behavior provides new opportunities to apply computational and comparative analytical techniques. In this article, the authors analyze visitor behavior in the Louvre Museum from anonymized longitudinal datasets collected from noninvasive Bluetooth sensors. They examine visitors' length of stay in the museum and consider this relationship with occupation density around artwork. This data analysis increases museum professionals' knowledge and understanding of the visitor experience. This article is part of a special issue on smart cities.
Sensors, Bluetooth, Tracking, Mobile handsets, Data collection, Pervasive computing, Museums, Behavioral sciences, Internet of Things, Data analysis,Bluetooth tracking, museum studies, visitor behavior, human mobility, pervasive computing, mobile, Internet of Things, data analysis
"Noninvasive Bluetooth Monitoring of Visitors' Length of Stay at the Louvre", IEEE Pervasive Computing, vol. 16, no. , pp. 26-34, Apr.-June 2017, doi:10.1109/MPRV.2017.33
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