Tools
ToolsHossmann-Picu, A., Liu, Z., Zhao, Z., Braun, T., Angelopoulos, C.M., Evangelatos, O., Rolim, J., Papandrea, M., Garg, K., Giordano, S., Tossou, A.C.Y., Dimitrakakis, C. and Mitrokotsa, A., 2016. Synergistic user ↔ context analytics. In: ICT Innovations 2015: Emerging Technologies for Better Living, 1-4 October 2015, Ohrid, Macedonia, 163 - 172.
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DOI: 10.1007/978-3-319-25733-4_17
Abstract
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.
| Item Type: | Conference or Workshop Item (Paper) |
|---|---|
| ISSN: | 2194-5357 |
| Additional Information: | Volume 399 of the series Advances in Intelligent Systems and Computing pp 163-172 |
| Uncontrolled Keywords: | crowd-sensing; information fusion; crowd-sensing analytics |
| Group: | Faculty of Science & Technology |
| ID Code: | 24078 |
| Deposited By: | Symplectic RT2 |
| Deposited On: | 21 Jun 2016 09:35 |
| Last Modified: | 14 Mar 2022 13:56 |
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