Optimising sensor layouts for direct measurement of discrete variables

X. Rosalind Wang, George Mathews, Don Price, Mikhail Prokopenko

Research output: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

5 Citations (Scopus)

Abstract

An optimal sensor layout is attained when a limited number of sensors are placed in an area such that the cost of the placement is minimised while the value of the obtained information is maximised.In this paper, we discuss the optimal sensor layout design problem from first principles, show how an existing optimisation criterion (maximum entropy of the measured variables) can be derived, and compare the performance of this criterion with three others that have been reported in the literature for a specific situation for which we have detailed experimental data available. This is achieved by firstly learning a spatial model of the environment using a Bayesian Network, then predicting the expected sensor data in the rest of the space, and finally verifying the predicted results with the experimental measurements. The development of rigorous techniques for optimising sensor layouts is argued to be an essential requirement for reconfigurable and self-adaptive networks.

Original languageEnglish
Title of host publicationSASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems
Place of PublicationLos Alamitos, Calif.
Pages92-102
Number of pages11
DOIs
Publication statusPublished - 2009
Externally publishedYes
EventSASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems - San Francisco, CA, United States
Duration: 14 Sep 200918 Sep 2009

Other

OtherSASO 2009 - 3rd IEEE International Conference on Self-Adaptive and Self-Organizing Systems
CountryUnited States
CitySan Francisco, CA
Period14/09/0918/09/09

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