Leveraging Proximity Sensing to Mine the Behavior of Museum Visitors

Claudio Martella, Armando Miraglia, Marco Cattani, Maarten van Steen

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

23 Citations (Scopus)

Abstract

Face-to-face proximity has been successfully leveraged to study the relationships between individuals in various contexts, from a working place, to a conference, a museum, a fair, and a date. We spend time facing the individuals with whom we chat, discuss, work, and play. However, face-to-face proximity is not the realm of solely person-to-person relationships, but it can be used as a proxy to study person-to-object relationships as well. We face the objects with which we interact on a daily basis, like a television, the kitchen appliances, a book, including more complex objects like a stage where a concert is taking place. In this paper, we focus on the relationship between the visitors of an art exhibition and its exhibits. We design, implement, and deploy a sensing infrastructure based on inexpensive mobile proximity sensors and a filtering pipeline that we use to measure face-to-face proximity between individuals and exhibits. Our pipeline produces an improvement in measurement accuracy of up to 64% relative to raw data. We use this data to mine the behavior of the visitors and show that group behavior can be recognized by means of data clustering and visualization.
Original languageEnglish
Title of host publication14th IEEE International Conference on Pervasive Computing and Communications (PerCom 2016)
Place of PublicationPiscataway
PublisherIEEE
Pages1-9
Number of pages9
ISBN (Electronic)978-1-4673-8779-8
DOIs
Publication statusPublished - 2016
Event14th IEEE International Conference on Pervasive Computing and Communications (PerCom 2016) - Sydney, Australia
Duration: 14 Mar 201619 Mar 2016

Conference

Conference14th IEEE International Conference on Pervasive Computing and Communications (PerCom 2016)
Country/TerritoryAustralia
CitySydney
Period14/03/1619/03/16

Bibliographical note

Accepted Author Manuscript

Keywords

  • Sensors
  • Mobile handsets
  • Pipelines
  • Art
  • Data mining
  • Bluetooth
  • Databases

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