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A benchmarking model for sensors in smart environments

 
: Braun, Andreas; Wichert, Reiner; Kuijper, Arjan; Fellner, Dieter W.

:

Aarts, Emile (Ed.); Ruyter, Boris de (Ed.); Markopoulos, Panos (Ed.); Loenen, Evert van (Ed.); Wichert, Reiner (Ed.); Schouten, Ben (Ed.); Terken, Jacques (Ed.); Kranenburg, Rob van (Ed.); Ouden, Elke Den (Ed.); O'Hare, Gregory (Ed.):
Ambient intelligence. European Conference, AmI 2014 : Eindhoven, The Netherlands, November 11 - 13, 2014; Revised selected papers
Cham: Springer International Publishing, 2014 (Lecture Notes in Computer Science 8850)
ISBN: 978-3-319-14111-4 (Print)
ISBN: 978-3-319-14112-1 (Online)
DOI: 10.1007/978-3-319-14112-1
S.242-257
European Conference on Ambient Intelligence (AmI) <11, 2014, Eindhoven>
Englisch
Konferenzbeitrag
Fraunhofer IGD ()
Benchmarking; smart environments; modeling; sensor technology; Business Field: Digital society; Research Area: Modeling (MOD); Forschungsgruppe Semantic Models, Immersive Systems (SMIS)

Abstract
In smart environments, developers can choose from a large variety of sensors supporting their use case that have specific advantages or disadvantages. In this work we present a benchmarking model that allows estimating the utility of a sensor technology for a use case by calculating a single score, based on a weighting factor for applications and a set of sensor features. This set takes into account the complexity of smart environment systems that are comprised of multiple subsystems and applied in non-static environments. We show how the model can be used to find a suitable sensor for a use case and the inverse option to find suitable use cases for a given set of sensors. Additionally, extensions are presented that normalize differently rated systems and compensate for central tendency bias. The model is verified by estimating technology popularity using a frequency analysis of associated search terms in two scientific databases.

: http://publica.fraunhofer.de/dokumente/N-369949.html