Realization of self-diagnosis and self-calibration strategies using conventional signal processing and fuzzy approach for distributed intelligent sensor systems

Salam Maria Srie Rezeki; Wai Chan; Malcolm R. Haskard; Dennis E. Mulcahy; David E. Davey

doi:10.1117/12.354278

20 July 1999 Realization of self-diagnosis and self-calibration strategies using conventional signal processing and fuzzy approach for distributed intelligent sensor systems

Salam Maria Srie Rezeki, Wai Chan, Malcolm R. Haskard, Dennis E. Mulcahy, David E. Davey

Author Affiliations +

Proceedings Volume 3673, Smart Structures and Materials 1999: Smart Electronics and MEMS; (1999) https://doi.org/10.1117/12.354278
Event: 1999 Symposium on Smart Structures and Materials, 1999, Newport Beach, CA, United States

Abstract

This paper describes an implementation of self-diagnosis and self-calibration strategies in a microcontroller-based distributed intelligent sensor system for environment monitoring. Two different areas of interest have been considered, namely water and air quality, where ion selective electrodes and thermal conductivity gas detectors, respectively, are used as the sensing elements.

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Salam Maria Srie Rezeki, Wai Chan, Malcolm R. Haskard, Dennis E. Mulcahy, and David E. Davey "Realization of self-diagnosis and self-calibration strategies using conventional signal processing and fuzzy approach for distributed intelligent sensor systems", Proc. SPIE 3673, Smart Structures and Materials 1999: Smart Electronics and MEMS, (20 July 1999); https://doi.org/10.1117/12.354278

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