Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks
The node of a wireless sensor network (WSN), which contains a sensor module with one or more physical sensors, may be exposed to widely varying environmental conditions, e.g., temperature, pressure, humidity, etc. Most of the sensor response characteristics are nonlinear, and in addition to that, ot...
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| Format: | Journal Article |
| Language: | English |
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2011
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| Online Access: | https://hdl.handle.net/10356/94366 http://hdl.handle.net/10220/7136 |
| _version_ | 1811695096818565120 |
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| author | Patra, Jagdish Chandra Meher, Pramod Kumar Chakraborty, Goutam |
| author2 | School of Computer Engineering |
| author_facet | School of Computer Engineering Patra, Jagdish Chandra Meher, Pramod Kumar Chakraborty, Goutam |
| author_sort | Patra, Jagdish Chandra |
| collection | NTU |
| description | The node of a wireless sensor network (WSN), which contains a sensor module with one or more physical sensors, may be exposed to widely varying environmental conditions, e.g., temperature, pressure, humidity, etc. Most of the sensor response characteristics are nonlinear, and in addition to that, other environmental parameters influence the sensor output nonlinearly. Therefore, to obtain accurate information from the sensors, it is important to linearize the sensor response and compensate for the undesirable environmental influences. In this paper, we present an intelligent technique using a novel computationally efficient Laguerre neural network (LaNN) to compensate for the inherent sensor nonlinearity and the environmental influences. Using the example of a capacitive pressure sensor, we have shown through extensive computer simulations that the proposed LaNN-based sensor can provide highly linearized output, such that the maximum full-scale error remains within ± 1.0% over a wide temperature range from -50 °C to 200 °C for three different types of nonlinear dependences. We have carried out its performance comparison with a multilayer-perceptron-based sensor model. We have also proposed a reduced-complexity run-time implementation scheme for the LaNN-based sensor model, which can save about 50% of the hardware and reduce the execution time by four times, thus making it suitable for the energy-constrained WSN applications. |
| first_indexed | 2024-10-01T07:18:02Z |
| format | Journal Article |
| id | ntu-10356/94366 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:18:02Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | ntu-10356/943662020-05-28T07:17:30Z Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks Patra, Jagdish Chandra Meher, Pramod Kumar Chakraborty, Goutam School of Computer Engineering DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation The node of a wireless sensor network (WSN), which contains a sensor module with one or more physical sensors, may be exposed to widely varying environmental conditions, e.g., temperature, pressure, humidity, etc. Most of the sensor response characteristics are nonlinear, and in addition to that, other environmental parameters influence the sensor output nonlinearly. Therefore, to obtain accurate information from the sensors, it is important to linearize the sensor response and compensate for the undesirable environmental influences. In this paper, we present an intelligent technique using a novel computationally efficient Laguerre neural network (LaNN) to compensate for the inherent sensor nonlinearity and the environmental influences. Using the example of a capacitive pressure sensor, we have shown through extensive computer simulations that the proposed LaNN-based sensor can provide highly linearized output, such that the maximum full-scale error remains within ± 1.0% over a wide temperature range from -50 °C to 200 °C for three different types of nonlinear dependences. We have carried out its performance comparison with a multilayer-perceptron-based sensor model. We have also proposed a reduced-complexity run-time implementation scheme for the LaNN-based sensor model, which can save about 50% of the hardware and reduce the execution time by four times, thus making it suitable for the energy-constrained WSN applications. Accepted version 2011-10-03T07:11:15Z 2019-12-06T18:54:58Z 2011-10-03T07:11:15Z 2019-12-06T18:54:58Z 2011 2011 Journal Article Patra, J. C., Meher, P. K., & Chakrabortty, G. (2011). Development of Laguerre Neural Network-based Intelligent Sensors for Wireless Sensor Networks. IEEE Transactions on Instrumentation and Measurement, 60(3), 725-734. 0018-9456 https://hdl.handle.net/10356/94366 http://hdl.handle.net/10220/7136 10.1109/TIM.2010.2082390 155055 en IEEE transactions on instrumentation and measurement © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: [DOI: http://dx.doi.org/10.1109/TIM.2010.2082390]. 10 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation Patra, Jagdish Chandra Meher, Pramod Kumar Chakraborty, Goutam Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks |
| title | Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks |
| title_full | Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks |
| title_fullStr | Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks |
| title_full_unstemmed | Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks |
| title_short | Development of Laguerre neural-network-based intelligent sensors for wireless sensor networks |
| title_sort | development of laguerre neural network based intelligent sensors for wireless sensor networks |
| topic | DRNTU::Engineering::Electrical and electronic engineering::Control and instrumentation |
| url | https://hdl.handle.net/10356/94366 http://hdl.handle.net/10220/7136 |
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