TY  - CONF
ID  - 20494938
AU  - Fabbricatore, Christian
AU  - Boley, Harold
AU  - Karduck, Achim P.
T1  - Machine learning for resource management in smart environments
C8  - 2012 6th IEEE International Conference on Digital Ecosystem Technologies (DEST)
T3  - 6th IEEE International Conference on Digital Ecosystem Technologies, 18-20 June 2012, Campione d’Italia, Italy
PY  - 2012
KW  - machine learning
KW  - resource management
KW  - energy savings
KW  - ambient assisted living
KW  - smart environment
KW  - semantic web
N2  - Efficient resource and energy management is a key research and business area in todays IT markets. Cyber-physical ecosystems, like smart homes (SHs) and smart Environments (SEs) get interconnected, the efficient allocation of resources will become essential. Machine Learning and Semantic Web techniques for improving resource allocation and management are the focus of our research. They allow machines to process information on all levels, inferring expressive knowledge from raw data, in particular resource predictions from usage patterns. Our aim is to devise a novel approach for a machine learning (ML) and resource Management (RM) framework in SEs. It combines ML and SemanticWeb techniques and integrates user interaction. The main objective is to enable the creation of platforms that decrease the overall resource consumption by learning and predicting various usage patterns, and furthermore making decisions based on user-feedback. For this purpose, we evaluate recent research and applications, elicit framework requirements, and present a framework architecture. The approach and components are assessed and a prototype implementation is described.
DO  - http://dx.doi.org/10.1109/DEST.2012.6227910
U3  - Information and Communication Technologies
U3  - Technologies de l'information et des communications
U3  - National Research Council Canada
U3  - Conseil national de recherches Canada
U3  - Information and Communication Technologies
U3  - Technologies de l'information et des communications
ER  -