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 language | English |
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Title of host publication | 14th IEEE International Conference on Pervasive Computing and Communications (PerCom 2016) |
Place of Publication | Piscataway |
Publisher | IEEE |
Pages | 1-9 |
Number of pages | 9 |
ISBN (Electronic) | 978-1-4673-8779-8 |
DOIs | |
Publication status | Published - 2016 |
Event | 14th IEEE International Conference on Pervasive Computing and Communications (PerCom 2016) - Sydney, Australia Duration: 14 Mar 2016 → 19 Mar 2016 |
Conference
Conference | 14th IEEE International Conference on Pervasive Computing and Communications (PerCom 2016) |
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Country/Territory | Australia |
City | Sydney |
Period | 14/03/16 → 19/03/16 |
Bibliographical note
Accepted Author ManuscriptKeywords
- Sensors
- Mobile handsets
- Pipelines
- Art
- Data mining
- Bluetooth
- Databases