Knowledge engineering: principles and methods
Data & Knowledge Engineering - Special jubilee issue: DKE 25
Using JessTab to Integrate Protégé and Jess
IEEE Intelligent Systems
FGCN '07 Proceedings of the Future Generation Communication and Networking - Volume 02
Ontology-Based Smart Home Solution and Service Composition
ICESS '09 Proceedings of the 2009 International Conference on Embedded Software and Systems
Attribute selection with fuzzy decision reducts
Information Sciences: an International Journal
Ontology-based expert system for home automation controlling
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part I
Discovering Activities to Recognize and Track in a Smart Environment
IEEE Transactions on Knowledge and Data Engineering
Ambient intelligence: A survey
ACM Computing Surveys (CSUR)
A Frequent Pattern Mining Approach for ADLs Recognition in Smart Environments
AINA '11 Proceedings of the 2011 IEEE International Conference on Advanced Information Networking and Applications
OWL 2 modeling and reasoning with complex human activities
Pervasive and Mobile Computing
Situation aware cognitive assistance in smart homes
Journal of Mobile Multimedia
Future Generation Computer Systems
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This paper presents a method for recognition of Activities of Daily Living (ADL) in smart homes. Recognition of activities of daily living and tracking them can provide unprecedented opportunities for health monitoring and assisted living applications, especially for elderly people and people with memory deficits. This paper presents Recognizing Activities of Daily Living (RADL) by discovering and monitoring patterns of ADLs in sensor equipped smart homes. The RADL is composed of two components: smart home management monitoring and ADL pattern monitoring. This paper studies the ontology base and the reasoning that are the main parts of ADL pattern monitoring. The ontology for RADL is designed and the prototype system of RADL is implemented using Protege and Jess tools. Also, the ontology for RADL is verified by OntoCheck in automatic mode and evaluated by a metric-based approach in manual mode.