Leveraging Proximity Sensing to Mine the Behavior of Museum Visitors

Claudio Martella, Armando Miraglia, Marco Cattani, Martinus Richardus van Steen

    Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

    23 Citations (Scopus)


    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 we interact with 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. We use this data to mine the behavior of the visitors and show that group behavior can be recognized by means of data clustering
    Original languageUndefined
    Title of host publicationProceedings of the IEEE International Conference on Pervasive Computing and Communication (PerCom 2016)
    Place of PublicationUSA
    Number of pages9
    ISBN (Print)978-1-4673-8779-8
    Publication statusPublished - Mar 2016
    EventIEEE International Conference on Pervasive Computing and Communication, PerCom 2016 - Sydney, Australia
    Duration: 14 Mar 201618 Mar 2016

    Publication series

    PublisherIEEE Computer Society


    ConferenceIEEE International Conference on Pervasive Computing and Communication, PerCom 2016
    Abbreviated titlePerCom
    Internet address


    • EWI-26883
    • METIS-316855
    • IR-100083

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