Synergistic user ↔ context analytics
Kapitel i bok, 2016
© Springer International Publishing Switzerland 2016. Various flavours of a new research field on (socio-)physical or personal analytics have emerged, with the goal of deriving semanticallyrich insights from people’s low-level physical sensing combined with their (online) social interactions. In this paper, we argue for more comprehensive data sources, including environmental and application-specific data, to better capture the interactions between users and their context, in addition to those among users. We provide some example use cases and present our ongoing work towards a synergistic analytics platform: a testbed based on mobile crowdsensing and IoT, a data model for representing the different sources of data and their connections, and a prediction engine for analyzing the data and producing insights.
Crowd-sensing
Crowd-sensing analytics
Information fusion
Författare
A. Hossmann-Picu
Universität Bern
Z. Li
Universität Bern
Z. Zhao
Universität Bern
T. Braun
Universität Bern
C.M. Angelopoulos
Universite de Geneve
O. Evangelatos
Universite de Geneve
J. Rolim
Universite de Geneve
M. Papandrea
K. Garg
S. Giordano
Aristide Tossou
Chalmers, Data- och informationsteknik, Datavetenskap
Christos Dimitrakakis
Chalmers, Data- och informationsteknik, Datavetenskap
Aikaterini Mitrokotsa
Chalmers, Data- och informationsteknik, Nätverk och system
Advances in Intelligent Systems and Computing
2194-5357 (ISSN)
163-172Ämneskategorier
Data- och informationsvetenskap
DOI
10.1007/978-3-319-25733-4_17
ISBN
9783319257310