An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm
Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it wi...
Ausführliche Beschreibung
Autor*in: |
Lu, Tianqi [verfasserIn] |
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Englisch |
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2017 |
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Enthalten in: IEEE pervasive computing - New York, NY : IEEE, 2002, 16(2017), 4, Seite 54-61 |
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Übergeordnetes Werk: |
volume:16 ; year:2017 ; number:4 ; pages:54-61 |
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DOI / URN: |
10.1109/MPRV.2017.3971125 |
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OLC1999761685 |
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520 | |a Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. | ||
650 | 4 | |a Event detection | |
650 | 4 | |a hidden Markov model | |
650 | 4 | |a Viterbi algorithm | |
650 | 4 | |a maximum and minimum points | |
650 | 4 | |a Computational modeling | |
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650 | 4 | |a Internet of Things | |
650 | 4 | |a Monitoring | |
650 | 4 | |a Software engineering | |
650 | 4 | |a pervasive computing | |
650 | 4 | |a nonintrusive load monitoring | |
700 | 1 | |a Xu, Zhengguang |4 oth | |
700 | 1 | |a Huang, Benxiong |4 oth | |
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10.1109/MPRV.2017.3971125 doi PQ20171228 (DE-627)OLC1999761685 (DE-599)GBVOLC1999761685 (PRQ)i651-cce6362bb2d8a6ab42bde3e7d46c9c66fff0d7ef3d44139c2c4319082725c4ba0 (KEY)0492180120170000016000400054eventbasednonintrusiveloadmonitoringapproachusingt DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Lu, Tianqi verfasserin aut An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. Event detection hidden Markov model Viterbi algorithm maximum and minimum points Computational modeling Hidden Markov models data analysis Green computing Sparse matrices Internet of Things Monitoring Software engineering pervasive computing nonintrusive load monitoring Xu, Zhengguang oth Huang, Benxiong oth Enthalten in IEEE pervasive computing New York, NY : IEEE, 2002 16(2017), 4, Seite 54-61 (DE-627)347040918 (DE-600)2078362-0 (DE-576)098783882 1536-1268 nnns volume:16 year:2017 number:4 pages:54-61 http://dx.doi.org/10.1109/MPRV.2017.3971125 Volltext http://ieeexplore.ieee.org/document/8090442 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.00 AVZ AR 16 2017 4 54-61 |
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10.1109/MPRV.2017.3971125 doi PQ20171228 (DE-627)OLC1999761685 (DE-599)GBVOLC1999761685 (PRQ)i651-cce6362bb2d8a6ab42bde3e7d46c9c66fff0d7ef3d44139c2c4319082725c4ba0 (KEY)0492180120170000016000400054eventbasednonintrusiveloadmonitoringapproachusingt DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Lu, Tianqi verfasserin aut An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. Event detection hidden Markov model Viterbi algorithm maximum and minimum points Computational modeling Hidden Markov models data analysis Green computing Sparse matrices Internet of Things Monitoring Software engineering pervasive computing nonintrusive load monitoring Xu, Zhengguang oth Huang, Benxiong oth Enthalten in IEEE pervasive computing New York, NY : IEEE, 2002 16(2017), 4, Seite 54-61 (DE-627)347040918 (DE-600)2078362-0 (DE-576)098783882 1536-1268 nnns volume:16 year:2017 number:4 pages:54-61 http://dx.doi.org/10.1109/MPRV.2017.3971125 Volltext http://ieeexplore.ieee.org/document/8090442 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.00 AVZ AR 16 2017 4 54-61 |
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10.1109/MPRV.2017.3971125 doi PQ20171228 (DE-627)OLC1999761685 (DE-599)GBVOLC1999761685 (PRQ)i651-cce6362bb2d8a6ab42bde3e7d46c9c66fff0d7ef3d44139c2c4319082725c4ba0 (KEY)0492180120170000016000400054eventbasednonintrusiveloadmonitoringapproachusingt DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Lu, Tianqi verfasserin aut An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. Event detection hidden Markov model Viterbi algorithm maximum and minimum points Computational modeling Hidden Markov models data analysis Green computing Sparse matrices Internet of Things Monitoring Software engineering pervasive computing nonintrusive load monitoring Xu, Zhengguang oth Huang, Benxiong oth Enthalten in IEEE pervasive computing New York, NY : IEEE, 2002 16(2017), 4, Seite 54-61 (DE-627)347040918 (DE-600)2078362-0 (DE-576)098783882 1536-1268 nnns volume:16 year:2017 number:4 pages:54-61 http://dx.doi.org/10.1109/MPRV.2017.3971125 Volltext http://ieeexplore.ieee.org/document/8090442 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.00 AVZ AR 16 2017 4 54-61 |
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10.1109/MPRV.2017.3971125 doi PQ20171228 (DE-627)OLC1999761685 (DE-599)GBVOLC1999761685 (PRQ)i651-cce6362bb2d8a6ab42bde3e7d46c9c66fff0d7ef3d44139c2c4319082725c4ba0 (KEY)0492180120170000016000400054eventbasednonintrusiveloadmonitoringapproachusingt DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Lu, Tianqi verfasserin aut An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. Event detection hidden Markov model Viterbi algorithm maximum and minimum points Computational modeling Hidden Markov models data analysis Green computing Sparse matrices Internet of Things Monitoring Software engineering pervasive computing nonintrusive load monitoring Xu, Zhengguang oth Huang, Benxiong oth Enthalten in IEEE pervasive computing New York, NY : IEEE, 2002 16(2017), 4, Seite 54-61 (DE-627)347040918 (DE-600)2078362-0 (DE-576)098783882 1536-1268 nnns volume:16 year:2017 number:4 pages:54-61 http://dx.doi.org/10.1109/MPRV.2017.3971125 Volltext http://ieeexplore.ieee.org/document/8090442 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.00 AVZ AR 16 2017 4 54-61 |
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10.1109/MPRV.2017.3971125 doi PQ20171228 (DE-627)OLC1999761685 (DE-599)GBVOLC1999761685 (PRQ)i651-cce6362bb2d8a6ab42bde3e7d46c9c66fff0d7ef3d44139c2c4319082725c4ba0 (KEY)0492180120170000016000400054eventbasednonintrusiveloadmonitoringapproachusingt DE-627 ger DE-627 rakwb eng 004 DNB 54.00 bkl Lu, Tianqi verfasserin aut An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm 2017 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. Event detection hidden Markov model Viterbi algorithm maximum and minimum points Computational modeling Hidden Markov models data analysis Green computing Sparse matrices Internet of Things Monitoring Software engineering pervasive computing nonintrusive load monitoring Xu, Zhengguang oth Huang, Benxiong oth Enthalten in IEEE pervasive computing New York, NY : IEEE, 2002 16(2017), 4, Seite 54-61 (DE-627)347040918 (DE-600)2078362-0 (DE-576)098783882 1536-1268 nnns volume:16 year:2017 number:4 pages:54-61 http://dx.doi.org/10.1109/MPRV.2017.3971125 Volltext http://ieeexplore.ieee.org/document/8090442 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT GBV_ILN_70 54.00 AVZ AR 16 2017 4 54-61 |
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An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm |
abstract |
Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. |
abstractGer |
Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. |
abstract_unstemmed |
Nonintrusive load monitoring technologies are gaining popularity for their low energy monitoring costs. In the article, the authors present a simple event-detection algorithm based on maximum and minimum points. Then, they use a variant of hidden Markov model as the appliance model and combine it with event detection to reduce the input. Specifically, they propose a simplified Viterbi algorithm, which considers fewer state transitions each time than the traditional Viterbi. The experiment results show that their work can achieve higher than 90 percent accuracy for most high-power devices and 60-80 percent accuracy for most low-power devices. Meanwhile, the computational complexity could be much lower than with the traditional Viterbi algorithm. |
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title_short |
An Event-Based Nonintrusive Load Monitoring Approach: Using the Simplified Viterbi Algorithm |
url |
http://dx.doi.org/10.1109/MPRV.2017.3971125 http://ieeexplore.ieee.org/document/8090442 |
remote_bool |
false |
author2 |
Xu, Zhengguang Huang, Benxiong |
author2Str |
Xu, Zhengguang Huang, Benxiong |
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author2_role |
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doi_str |
10.1109/MPRV.2017.3971125 |
up_date |
2024-07-03T15:21:56.934Z |
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1803571814129991680 |
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