Using consumer behavior data to reduce energy consumption in smart homes: Applying machine learning to save energy without lowering comfort of inhabitants

Proceedings - 2015 IEEE 14th International Conference on Machine Learning and Applications, ICMLA 2015

Volumn , Issue , 2016, Pages 1123-1129

  Schweizer, Daniel ^a   Zehnder, Michael ^a   Wache, Holger ^a   Witschel, Hans Friedrich ^a   Zanatta, Danilo ^b   Rodriguez, Miguel ^b  

^a UNIVERSITY OF APPLIED SCIENCES AND ARTS NORTHWESTERN SWITZERLAND   (Switzerland)

^b Research and Development DigitalSTROM AG   (Switzerland)

Author keywords

Association rules; Energy saving; Internet of things; Recommender systems; Smart cities; Smart homes; Unsupervised learning

Indexed keywords

ALGORITHMS; ARTIFICIAL INTELLIGENCE; ASSOCIATION RULES; AUTOMATION; CONSUMER BEHAVIOR; ENERGY CONSERVATION; ENERGY UTILIZATION; INTELLIGENT BUILDINGS; INTERNET OF THINGS; LEARNING SYSTEMS; UNSUPERVISED LEARNING;

FREQUENT SEQUENTIAL PATTERNS; HISTORICAL DATASET; MEMORY CONSUMPTION; REDUCE ENERGY CONSUMPTION; SECOND PHASE; SMART CITIES; SMART HOMES; USAGE PATTERNS;

RECOMMENDER SYSTEMS;

EID: 84969674448     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICMLA.2015.62     Document Type: Conference Paper

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