Artificial Intelligence methods for large microsensor arrays: feasibility and design

Elena Gaura, R. M. Newman, N Steele

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


Recently several authors have turned their attention to the design problems of very large arrays of intelligent sensors, such as would be suitable for inclusion as an integral part of a,smart structure'. Such systems have architectural and data throughput advantages, but to be used effectively need to be designed so as to be 'controllerless' and 'decentralised'. This paper explores some of these design issues, and illustrates how artificial intelligence (in particular Neural Networks techniques) could be effectively incorporated within the design of large intelligent microsystems with the scope of enhancing their functionality. Micromachined acceleration sensors are considered as a case study.

The paper opens with a discussion on the ever-increasing appropriateness of local sensor health monitoring, fault diagnosis and measurement confidence indices. The use of Artificial Intelligence techniques is suggested for implementing on-chip sensor diagnosis. Design issues for large, intelligent arrays of microsensors are brought forward.

Original languageEnglish
Title of host publicationArtificial Neural Nets and Genetic Algorithms
Subtitle of host publicationProceedings of the International Conference in Roanne, France, 2003
EditorsDavid W. Pearson, Nigel C. Steele, Rudolf F. Albrecht
Place of PublicationBerlin; New York
PublisherSpringer, Springer Nature
Number of pages7
ISBN (Electronic)9783709106464
ISBN (Print)3211007431, 9783211007433
Publication statusPublished - 2003
Externally publishedYes
EventInternational Conference on Artificial Neural Nets and Genetic Algorithms - Roanne, France
Duration: 23 Apr 200325 Apr 2003

Publication series

NameSpringer Computer Science
PublisherSpringer-Verlag Wien


ConferenceInternational Conference on Artificial Neural Nets and Genetic Algorithms


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