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The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

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Standard

The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics. / Li, Hai; Price, Mark C.; Stott, Jonathan et al.
2007. Paper presented at Proc. IWSOS 2007.

Research output: Contribution to conference - Without ISBN/ISSN › Conference paper › peer-review

Harvard

Li, H, Price, MC, Stott, J & Marshall, IW 2007, 'The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics.', Paper presented at Proc. IWSOS 2007, 1/01/00.

APA

Li, H., Price, M. C., Stott, J., & Marshall, I. W. (2007). The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics.. Paper presented at Proc. IWSOS 2007.

Vancouver

Li H, Price MC, Stott J, Marshall IW. The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics.. 2007. Paper presented at Proc. IWSOS 2007.

Author

Li, Hai ; Price, Mark C. ; Stott, Jonathan et al. / The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics. Paper presented at Proc. IWSOS 2007.

Bibtex

@conference{d8a14e0a3d954fe085181675f3ba3ae6,
title = "The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics.",
abstract = "In Wireless Sensor Network (WSN) applications, sensor nodes are often deployed in harsh environments. Routine maintenance, fault detection and correction is dicult, infrequent and expensive. Further-more, for long-term deployments in excess of a year, a node's limited power supply tightly constrains the amount of processing power and long-range communication available. In order to support the long-term autonomous behaviour of a WSN system, a self-diagnostic algorithm implemented on the sensor nodes is needed for sensor fault detection. This algorithm has to be robust, so that sensors are not misdiagnosed as faulty to ensure that data loss is kept to a minimum, and it has to be light-weight, so that it can run continuously on a low power microprocessor for the full deployment period. Addition-ally, it has to be self-adapative so that any long-term degradation ofsensors is monitored and the self-diagnostic algorithm can continuously revise its own rules to accomodate for this degradation. This paper de-scribes the development, testing and implementation of a heuristically determined, robust, self-diagnostic algorithm that achieves these goals.",
author = "Hai Li and Price, {Mark C.} and Jonathan Stott and Marshall, {Ian W.}",
year = "2007",
language = "English",
note = "Proc. IWSOS 2007 ; Conference date: 01-01-1900",

}

RIS

TY - CONF

T1 - The development of a Wireless Sensor Network sensing node utilising adaptive self-diagnostics.

AU - Li, Hai

AU - Price, Mark C.

AU - Stott, Jonathan

AU - Marshall, Ian W.

PY - 2007

Y1 - 2007

N2 - In Wireless Sensor Network (WSN) applications, sensor nodes are often deployed in harsh environments. Routine maintenance, fault detection and correction is dicult, infrequent and expensive. Further-more, for long-term deployments in excess of a year, a node's limited power supply tightly constrains the amount of processing power and long-range communication available. In order to support the long-term autonomous behaviour of a WSN system, a self-diagnostic algorithm implemented on the sensor nodes is needed for sensor fault detection. This algorithm has to be robust, so that sensors are not misdiagnosed as faulty to ensure that data loss is kept to a minimum, and it has to be light-weight, so that it can run continuously on a low power microprocessor for the full deployment period. Addition-ally, it has to be self-adapative so that any long-term degradation ofsensors is monitored and the self-diagnostic algorithm can continuously revise its own rules to accomodate for this degradation. This paper de-scribes the development, testing and implementation of a heuristically determined, robust, self-diagnostic algorithm that achieves these goals.

AB - In Wireless Sensor Network (WSN) applications, sensor nodes are often deployed in harsh environments. Routine maintenance, fault detection and correction is dicult, infrequent and expensive. Further-more, for long-term deployments in excess of a year, a node's limited power supply tightly constrains the amount of processing power and long-range communication available. In order to support the long-term autonomous behaviour of a WSN system, a self-diagnostic algorithm implemented on the sensor nodes is needed for sensor fault detection. This algorithm has to be robust, so that sensors are not misdiagnosed as faulty to ensure that data loss is kept to a minimum, and it has to be light-weight, so that it can run continuously on a low power microprocessor for the full deployment period. Addition-ally, it has to be self-adapative so that any long-term degradation ofsensors is monitored and the self-diagnostic algorithm can continuously revise its own rules to accomodate for this degradation. This paper de-scribes the development, testing and implementation of a heuristically determined, robust, self-diagnostic algorithm that achieves these goals.

M3 - Conference paper

T2 - Proc. IWSOS 2007

Y2 - 1 January 1900

ER -