Braun, Andreas ; Wichert, Reiner ; Kuijper, Arjan ; Fellner, Dieter W. (2014)
A Benchmarking Model for Sensors in Smart Environments.
Ambient Intelligence.
doi: 10.1007/978-3-319-14112-1_20
Konferenzveröffentlichung, Bibliographie
Kurzbeschreibung (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.
| Typ des Eintrags: | Konferenzveröffentlichung |
|---|---|
| Erschienen: | 2014 |
| Autor(en): | Braun, Andreas ; Wichert, Reiner ; Kuijper, Arjan ; Fellner, Dieter W. |
| Art des Eintrags: | Bibliographie |
| Titel: | A Benchmarking Model for Sensors in Smart Environments |
| Sprache: | Englisch |
| Publikationsjahr: | 2014 |
| Verlag: | Springer, Berlin, Heidelberg, New York |
| Reihe: | Lecture Notes in Computer Science (LNCS); 8850 |
| Veranstaltungstitel: | Ambient Intelligence |
| DOI: | 10.1007/978-3-319-14112-1_20 |
| Kurzbeschreibung (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. |
| Freie Schlagworte: | Business Field: Digital society, Research Area: Modeling (MOD), Forschungsgruppe Semantic Models, Immersive Systems (SMIS), Benchmarking, Smart environments, Modeling, Sensor technologies |
| Fachbereich(e)/-gebiet(e): | 20 Fachbereich Informatik 20 Fachbereich Informatik > Graphisch-Interaktive Systeme |
| Hinterlegungsdatum: | 12 Nov 2018 11:16 |
| Letzte Änderung: | 04 Feb 2022 12:39 |
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