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EnglishSocial interactions play an important role in the overall well-being. Current practice of monitoring social interactions through questionnaires and surveys is inadequate due to recall bias, memory dependence and high end-user effort. However, sensing capabilities of smart-phones can play a significant role in automatic detection of social interactions. In this paper, we describe our method of detecting interactions between people, specifically focusing on interactions that occur in synchrony, such as walking. Walking together between subjects is an important aspect of social activity and thus can be used to provide a better insight into social interaction patterns. For this work, we rely on sampling smartphone accelerometer and Wi-Fi sensors only. We analyse Wi-Fi and accelerometer data separately and combine them to detect walking in synchrony. The results show that from seven days of monitoring using seven subjects in real-life setting, we achieve 99% accuracy, 77.2% precision and 90.2% recall detection rates when combining both modalities.
Detecting walking in synchrony through smartphone accelerometer and Wi-Fi traces / Garcia Ceja, Enrique; Osmani, Venet; Maxhuni, Alban; Mayora, Oscar. - 8850(2014), pp. 33-46. ((Intervento presentato al convegno Ambient intelligence tenutosi a Eindhoven nel 11th - 13th November 2014.
| Titolo: | Detecting walking in synchrony through smartphone accelerometer and Wi-Fi traces |
| Autori: | Garcia Ceja, Enrique; Osmani, Venet; Maxhuni, Alban; Mayora, Oscar |
| Autori Unitn: | |
| Titolo del volume contenente il saggio: | Lecture notes in computer science |
| Luogo di edizione: | Berlin ; Heidelberg. |
| Casa editrice: | Springer |
| Anno di pubblicazione: | 2014 |
| Codice identificativo Scopus: | 2-s2.0-84996508215 |
| Codice identificativo ISI: | WOS:000354691100003 |
| ISBN: | 978-3-319-14111-4 978-3-319-14112-1 |
| Handle: | http://hdl.handle.net/11572/170526 |
| Citazione: | Detecting walking in synchrony through smartphone accelerometer and Wi-Fi traces / Garcia Ceja, Enrique; Osmani, Venet; Maxhuni, Alban; Mayora, Oscar. - 8850(2014), pp. 33-46. ((Intervento presentato al convegno Ambient intelligence tenutosi a Eindhoven nel 11th - 13th November 2014. |
| Appare nelle tipologie: | 04.1 Saggio in atti di convegno (Paper in proceedings) |
File in questo prodotto:
| File | Descrizione | Tipologia | Licenza | |
|---|---|---|---|---|
| Detecting Walking in Synchrony through Smartphone Accelerometer and Wi-Fi traces.pdf | Post-print referato (Refereed author’s manuscript) | Tutti i diritti riservati (All rights reserved) | Open Access Visualizza/Apri |
http://hdl.handle.net/11572/170526
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