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Power and Size Optimized Multi-Sensor Context Recognition Platform
Osaka, Japan October 18-October 21
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/ISWC.2005.42Ninth IEEE International Symposium on ...
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Nagendra B. Bharatula, Mathias Stager, Paul Lukowicz, Gerhard Troster, "Power and Size Optimized Multi-Sensor Context Recognition Platform," Wearable Computers, IEEE International Symposium, pp. 194-195, Ninth IEEE International Symposium on Wearable Computers (ISWC'05), 2005.
 
 
BibTex
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@article{ 10.1109/ISWC.2005.42,
author = {Nagendra B. Bharatula and Mathias Stager and Paul Lukowicz and Gerhard Troster},
title = {Power and Size Optimized Multi-Sensor Context Recognition Platform},
journal ={Wearable Computers, IEEE International Symposium},
volume = {0},
year = {2005},
isbn = {0-7695-2419-2},
pages = {194-195},
doi = {http://doi.ieeecomputersociety.org/10.1109/ISWC.2005.42},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Wearable Computers, IEEE International Symposium
TI - Power and Size Optimized Multi-Sensor Context Recognition Platform
SN - 0-7695-2419-2
SP194
EP195
A1 - Nagendra B. Bharatula,
A1 - Mathias Stager,
A1 - Paul Lukowicz,
A1 - Gerhard Troster,
PY - 2005
KW - null
VL - 0
JA - Wearable Computers, IEEE International Symposium
ER -
 
Nagendra B. Bharatula, Wearable Computing Lab, ETH Z?urich, Switzerland
Mathias Stager, Wearable Computing Lab, ETH Z?urich, Switzerland
Paul Lukowicz, Institute for Computer Systems and Networks, UMIT Hall, Austria
Gerhard Troster, Wearable Computing Lab, ETH Z?urich, Switzerland

This paper presents a miniaturized low-power platform for real-time activity recognition. The wearable sensor system comprises of accelerometers, a microphone, a light sensor and signal processing units. The recognition is performed with low-power features and a decision tree classi- fier. Power measurements show that our 4.15?2.75 cm2, 9 gram platform consumes less than 3mW and can perform continuous classification and result transmission for 129 hours on a small lithium-polymer battery.

Citation:
Nagendra B. Bharatula, Mathias Stager, Paul Lukowicz, Gerhard Troster, "Power and Size Optimized Multi-Sensor Context Recognition Platform," iswc, pp.194-195, Ninth IEEE International Symposium on Wearable Computers (ISWC'05), 2005
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