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2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications
Feature Selection and Activity Recognition to Detect Water Waste from Water Tap Usage
Toyama, Japan
August 28-August 31
ISBN: 978-0-7695-4502-8
| ASCII Text | x | ||
| Trang Thuy Vu, Akifumi Sokan, Hironori Nakajo, Kaori Fujinami, Jaakko Suutala, Pekka Siirtola, Tuomo Alasalmi, Ari Pitkänen, Juha Röning, "Feature Selection and Activity Recognition to Detect Water Waste from Water Tap Usage," 2012 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications, vol. 2, pp. 138-141, 2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications, 2011. | |||
| BibTex | x | ||
| @article{ 10.1109/RTCSA.2011.47, author = {Trang Thuy Vu and Akifumi Sokan and Hironori Nakajo and Kaori Fujinami and Jaakko Suutala and Pekka Siirtola and Tuomo Alasalmi and Ari Pitkänen and Juha Röning}, title = {Feature Selection and Activity Recognition to Detect Water Waste from Water Tap Usage}, journal ={2012 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications}, volume = {2}, year = {2011}, issn = {1533-2306}, pages = {138-141}, doi = {http://doi.ieeecomputersociety.org/10.1109/RTCSA.2011.47}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - CONF JO - 2012 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications TI - Feature Selection and Activity Recognition to Detect Water Waste from Water Tap Usage SN - 1533-2306 SP138 EP141 A1 - Trang Thuy Vu, A1 - Akifumi Sokan, A1 - Hironori Nakajo, A1 - Kaori Fujinami, A1 - Jaakko Suutala, A1 - Pekka Siirtola, A1 - Tuomo Alasalmi, A1 - Ari Pitkänen, A1 - Juha Röning, PY - 2011 VL - 2 JA - 2012 IEEE International Conference on Embedded and Real-Time Computing Systems and Applications ER - | |||
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/RTCSA.2011.47
In this paper, water tap usage is examined based on water sound analysis. We focus on detecting gwater wasteh to make persuasion of water savings effective, where two types of water waste are defined: inter-activity water waste and intra-activity water waste. Based on a preliminary user survey, four types of basin-related activities are identified that occur with water waste. We apply a spectrum subtraction method for feature selection and propose cascaded classifiers for activity recognition. The result of an evaluation presents that the aggregate accuracies to identify inter-activity water waste and intra-activity one are 100.0 % and 81.1%, respectively.
Citation:
Trang Thuy Vu, Akifumi Sokan, Hironori Nakajo, Kaori Fujinami, Jaakko Suutala, Pekka Siirtola, Tuomo Alasalmi, Ari Pitkänen, Juha Röning, "Feature Selection and Activity Recognition to Detect Water Waste from Water Tap Usage," rtcsa, vol. 2, pp.138-141, 2011 IEEE 17th International Conference on Embedded and Real-Time Computing Systems and Applications, 2011
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