Acoustic and device feature fusion for load recognition

IS'2012 - 2012 6th IEEE International Conference Intelligent Systems, Proceedings

Volumn , Issue , 2012, Pages 386-392

  Zoha, Ahmed ^a   Gluhak, Alexander ^a   Nati, Michele ^a   Imran, Muhammad Ali ^a   Rajasegarar, Sutharshan ^b  

^a UNIVERSITY OF SURREY   (United Kingdom)

^b UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

audio features; energy monitoring; energy reduction; Non intrusive Load Monitoring (NILM); Support Vector Machines (SVM)

Indexed keywords

AUDIO FEATURES; AUDIO-RECOGNITION; ENERGY DEMANDS; ENERGY METERS; ENERGY MONITORING; ENERGY REDUCTION; FEATURE FUSION; FEATURE SETS; LOAD MONITORING; LOAD RECOGNITION; LOW-POWER DEVICES; NON-INTRUSIVE; NONINTRUSIVE LOAD MONITORING; RECOGNITION ACCURACY; RECOGNITION PERFORMANCE; RESOURCE UTILIZATIONS; STATE OF THE ART; TIME DOMAIN;

ELECTRIC APPLIANCES; LEARNING ALGORITHMS; SUPPORT VECTOR MACHINES;

INTELLIGENT SYSTEMS;

EID: 84869858799     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/IS.2012.6335166     Document Type: Conference Paper

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