Situation Aware Cognitive Assistance in Smart Homes

Smart Homes (SH) have emerged as a realistically viable solution capable of providing technology-driven assistive living for the elderly and disabled. Nevertheless, it still remains a challenge to provide situation-aware cognitive assistance for those in need in their Activity of Daily Living (ADL). This paper introduces a systematic approach to providing situation-aware ADL assistances in a smart home environment. The approach makes use of semantic technologies for sensor data modeling, fusion and management, thus creating machine understandable and processable situational data. It exploits intelligent agents for interpreting and reasoning semantic situational (meta)data to enhance situation-aware decision support for cognitive assistance. We analyze the nature and issues of SH-based healthcare for cognitively defficient inhabitants. We discuss the ways in which semantic technologies enhance situation comprehension. We describe a cognitive agent for realizing high-level cognitive capabilities such as prediction and explanation. We outline the implementation of a prototype assistive system and illustrate the proposed approach through simulated and real-time ADL assistance scenarios in the context of situation aware assistive living.

[1]  Mica R. Endsley,et al.  Toward a Theory of Situation Awareness in Dynamic Systems , 1995, Hum. Factors.

[2]  Paul R. Smart,et al.  Semantic Technologies and Enhanced Situation Awareness , 2007 .

[3]  Bernard Lefebvre,et al.  Ontology-Based Management of the Telehealth Smart Home, Dedicated to Elderly in Loss of Cognitive Autonomy , 2007, OWLED.

[4]  Jesse Hoey,et al.  A Decision-Theoretic Approach to Task Assistance for Persons with Dementia , 2005, IJCAI.

[5]  A.-C. Boury-Brisset,et al.  Ontology-based approach for information fusion , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[6]  Nicholas Gibbins,et al.  3store: Efficient Bulk RDF Storage , 2003, PSSS.

[7]  Tao Gu,et al.  A service-oriented middleware for building context-aware services , 2005, J. Netw. Comput. Appl..

[8]  Carlo Curino,et al.  A data-oriented survey of context models , 2007, SGMD.

[9]  Anind K. Dey,et al.  Understanding and Using Context , 2001, Personal and Ubiquitous Computing.

[10]  Ian Horrocks,et al.  FaCT++ Description Logic Reasoner: System Description , 2006, IJCAR.

[11]  Diego Calvanese,et al.  The Description Logic Handbook: Theory, Implementation, and Applications , 2003, Description Logic Handbook.

[12]  Dianne C. Berry,et al.  The role of awareness in situation awareness , 2004 .

[13]  Michael Wooldridge,et al.  Agent technology: foundations, applications, and markets , 1998 .

[14]  Ian Horrocks,et al.  Practical Reasoning for Expressive Description Logics , 1999, LPAR.

[15]  I. Horrocks,et al.  The Instance Store: DL Reasoning with Large Numbers of Individuals , 2004, Description Logics.

[16]  Koen De Bosschere,et al.  Towards an Extensible Context Ontology for Ambient Intelligence , 2004, EUSAI.

[17]  Abdenour Bouzouane,et al.  A Smart Home Agent for Plan Recognition of Cognitively-impaired Patients , 2006, J. Comput..

[18]  M. Weiser.  The Computer for the Twenty-First Century , 1991 .

[19]  Harry Chen,et al.  An ontology for context-aware pervasive computing environments , 2003, The Knowledge Engineering Review.

[20]  Katia Sycara,et al.  Information discovery and fusion: semantics on the battlefield , 2003, Sixth International Conference of Information Fusion, 2003. Proceedings of the.

[21]  A. Schmidt,et al.  Ontology-Centred Design of an Ambient Middleware for Assisted Living : The Case of SOPRANO * , 2007 .