The University of Southampton
University of Southampton Institutional Repository

Intelligent sensors—a generic software approach

Intelligent sensors—a generic software approach
Intelligent sensors—a generic software approach
Designating a sensor as intelligent is a long-standing term implying that it provides more functionality than merely providing an output measurement. Since there is some discrepancy governing what makes a given sensor intelligent, this paper defines the features required for improving confidence in sensor measurements, from the sensor management perspective. We describe a software framework used to implement tasks such as condition monitoring onboard the sensor itself, rather than at the traditional supervisory level. The algorithms include data-based models, which allows for modelling of non-linear effects and estimation uncertainty, which is a prerequisite for data fusion. Density estimation for novelty detection is demonstrated for an accelerometer that is purposely damaged in an environmental chamber.
intelligent sensor, novelty detection, data-based model
1742-6588
155 -160
Boltryk, P.J.
82ca101e-7a14-49b5-8ac9-177a5a739c29
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
White, N.M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Prosser, S. J.
5890f226-9bb0-48b8-a70f-9f7862d4c402
Yan, Y.
3864bfec-4680-4297-95a8-7fedf0f5498d
Lewis, E.
6ca3b248-f4b6-4787-b93a-dddbc0b0d871
Boltryk, P.J.
82ca101e-7a14-49b5-8ac9-177a5a739c29
Harris, C.J.
c4fd3763-7b3f-4db1-9ca3-5501080f797a
White, N.M.
c7be4c26-e419-4e5c-9420-09fc02e2ac9c
Prosser, S. J.
5890f226-9bb0-48b8-a70f-9f7862d4c402
Yan, Y.
3864bfec-4680-4297-95a8-7fedf0f5498d
Lewis, E.
6ca3b248-f4b6-4787-b93a-dddbc0b0d871

Boltryk, P.J., Harris, C.J. and White, N.M., Prosser, S. J., Yan, Y. and Lewis, E.(eds.) (2005) Intelligent sensors—a generic software approach Journal of Physics: Conference Series, 15, (1), 155 -160.

Record type: Article

Abstract

Designating a sensor as intelligent is a long-standing term implying that it provides more functionality than merely providing an output measurement. Since there is some discrepancy governing what makes a given sensor intelligent, this paper defines the features required for improving confidence in sensor measurements, from the sensor management perspective. We describe a software framework used to implement tasks such as condition monitoring onboard the sensor itself, rather than at the traditional supervisory level. The algorithms include data-based models, which allows for modelling of non-linear effects and estimation uncertainty, which is a prerequisite for data fusion. Density estimation for novelty detection is demonstrated for an accelerometer that is purposely damaged in an environmental chamber.

Full text not available from this repository.

More information

Published date: 2005
Keywords: intelligent sensor, novelty detection, data-based model

Identifiers

Local EPrints ID: 30243
URI: http://eprints.soton.ac.uk/id/eprint/30243
ISSN: 1742-6588
PURE UUID: 6c386589-1ca3-4758-93b9-a36a938129f6
ORCID for N.M. White: ORCID iD orcid.org/0000-0003-1532-6452

Catalogue record

Date deposited: 11 May 2006
Last modified: 25 Oct 2017 04:16

Export record

Contributors

Author: P.J. Boltryk
Author: C.J. Harris
Author: N.M. White ORCID iD
Editor: S. J. Prosser
Editor: Y. Yan
Editor: E. Lewis

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of http://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×