Synergistic user ↔ context analytics
Paper i proceeding, 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.

Information fusion

Crowd-sensing analytics

Crowd-sensing

Författare

A. Hossmann-Picu

Universität Bern

Z. Li

Universität Bern

Z. Zhao

Universität Bern

T. Braun

Universität Bern

C.M. Angelopoulos

Université de Genève

O. Evangelatos

Université de Genève

J. Rolim

Université de Genève

M. Papandrea

Scuola Universitaria Professionale della Svizzera Italiana (SUPSI)

K. Garg

Scuola Universitaria Professionale della Svizzera Italiana (SUPSI)

S. Giordano

Scuola Universitaria Professionale della Svizzera Italiana (SUPSI)

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)

Vol. 399 163-172

7th International Conference on Information and Communication Technologies, ICT 2015
Singapore, Singapore,

Ämneskategorier

Data- och informationsvetenskap

DOI

10.1007/978-3-319-25733-4_17

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Senast uppdaterat

2021-06-03