Abstract
In increasingly hyper-connected societies, where individuals rely on short and fast online communications to consume information, museums face a significant survival challenge. Collaborations between scientists and museums suggest that the use of the technological framework known as Internet of Things (IoT) will be a key player in tackling this challenge. IoT can be used to gather and analyse visitor generated data, leading to data-driven insights that can fuel novel, adaptive and engaging museum experiences. We used an IoT implementation—a sensor network installed in the physical space of a museum—to look at how single visitors chose to enter and spend time in the different rooms of a curated exhibition. We collected a sparse, non-overlapping dataset of individual visits. Using various statistical analyses, we found that visitor attention span was very short. People visited five out of twenty rooms on average, and spent a median of two minutes in each room. However, the patterns of choice and time spent in rooms were not random. Indeed, they could be described in terms of a set of linearly separable visit patterns we obtained using principal component analysis. These results are encouraging for future interdisciplinary research that seeks to leverage IoT to get numerical proxies for people attention inside the museum, and use this information to fuel the next generation of possible museum interactions. Such interactions will based on rich, non-intrusive and diverse IoT driven conversation, dynamically tailored to visitors.
Highlights
The digital revolution is changing the definition of the traditional museum, and opening the space for a wide range of novel visitor dynamics
Architectures and suitable algorithms to derive indicators concerning visitor attention with a significant degree of confidence. While such an indicator of attention is likely to depend on many different factors and variables, in this work, we focused on a baseline study considering: (1) the patterns of choices individuals make regarding what to see in the museum—specific rooms in the case of this study; and (2) completing patterns of choices with the total time spent in each of the visited rooms
We support the use of spacial sensor networks within an Internet of Things (IoT) framework to gather information about how people experience museums
Summary
The digital revolution is changing the definition of the traditional museum, and opening the space for a wide range of novel visitor dynamics. A current key challenge for museums is to understand the patterns of interaction between its visitors and curated exhibits or the architectural features of its physical spaces This is essential to determine the different mechanisms that can be used to attract attention and engagement effectively along the time-line of the visitor’s museum experience. Museum fatigue is a compound variable that determines phenomena such as cognitive overload Such fatigue can be caused by spacial features such as light and air quality, the amount and nature of stimuli presented, failure to create engaging first interactions, the nature and flow of information presented to the visitor, and many other features. Such interventions may be a key to start or re-ignite meaningful conversations between the museum and its visitors
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