Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors
We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In o...
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doaj-ec961069ebea4e9cbc41f32b77a01ee72020-11-24T22:01:01ZengMDPI AGSensors1424-82202016-05-0116571310.3390/s16050713s16050713Field-Based Optimal Placement of Antennas for Body-Worn Wireless SensorsŁukasz Januszkiewicz0Paolo Di Barba1Sławomir Hausman2Institute of Electronics, Lodz University of Technology, ul. Wólczańska 211/215, 90-924 Łódź, PolandDepartment of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, ItalyInstitute of Electronics, Lodz University of Technology, ul. Wólczańska 211/215, 90-924 Łódź, PolandWe investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer’s chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes.http://www.mdpi.com/1424-8220/16/5/713body area networkswireless sensor networkcomputer optimization algorithmscomputational electromagnetics |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Łukasz Januszkiewicz Paolo Di Barba Sławomir Hausman |
spellingShingle |
Łukasz Januszkiewicz Paolo Di Barba Sławomir Hausman Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors Sensors body area networks wireless sensor network computer optimization algorithms computational electromagnetics |
author_facet |
Łukasz Januszkiewicz Paolo Di Barba Sławomir Hausman |
author_sort |
Łukasz Januszkiewicz |
title |
Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors |
title_short |
Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors |
title_full |
Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors |
title_fullStr |
Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors |
title_full_unstemmed |
Field-Based Optimal Placement of Antennas for Body-Worn Wireless Sensors |
title_sort |
field-based optimal placement of antennas for body-worn wireless sensors |
publisher |
MDPI AG |
series |
Sensors |
issn |
1424-8220 |
publishDate |
2016-05-01 |
description |
We investigate a case of automated energy-budget-aware optimization of the physical position of nodes (sensors) in a Wireless Body Area Network (WBAN). This problem has not been presented in the literature yet, as opposed to antenna and routing optimization, which are relatively well-addressed. In our research, which was inspired by a safety-critical application for firefighters, the sensor network consists of three nodes located on the human body. The nodes communicate over a radio link operating in the 2.4 GHz or 5.8 GHz ISM frequency band. Two sensors have a fixed location: one on the head (earlobe pulse oximetry) and one on the arm (with accelerometers, temperature and humidity sensors, and a GPS receiver), while the position of the third sensor can be adjusted within a predefined region on the wearer’s chest. The path loss between each node pair strongly depends on the location of the nodes and is difficult to predict without performing a full-wave electromagnetic simulation. Our optimization scheme employs evolutionary computing. The novelty of our approach lies not only in the formulation of the problem but also in linking a fully automated optimization procedure with an electromagnetic simulator and a simplified human body model. This combination turns out to be a computationally effective solution, which, depending on the initial placement, has a potential to improve performance of our example sensor network setup by up to about 20 dB with respect to the path loss between selected nodes. |
topic |
body area networks wireless sensor network computer optimization algorithms computational electromagnetics |
url |
http://www.mdpi.com/1424-8220/16/5/713 |
work_keys_str_mv |
AT łukaszjanuszkiewicz fieldbasedoptimalplacementofantennasforbodywornwirelesssensors AT paolodibarba fieldbasedoptimalplacementofantennasforbodywornwirelesssensors AT sławomirhausman fieldbasedoptimalplacementofantennasforbodywornwirelesssensors |
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