Automated assistance services: Experience from the SmartSenior project

Ambient Assisted Living (AAL) addresses the drastic demographic change of today's modern world and motivates further research on the necessary technological steps for offering sufficiently sensitive and appropriately responsive smart environments in the near future. Thus, enhancements and permanent improvements of technology in the AAL domain result in the sustainable development of new software and hardware platforms for suitable automated assistance services, bound to relevant business models. In this paper, an innovative, practicable technological approach for a future automated assistance service is presented, covering several currently open issues: (1) incomplete sensing, (2) insufficient communication techniques among human beings and smart environments, and (3) lack of situation-awareness of assistance services. To solve these problems, we propose the following: usage of gas sensors in smart environments, an intelligent wristwatch for people in smart environments, and the implementation of new software algorithms for improved automated situation understanding and further assistance support. These components will be offered together with currently existing products for a qualitatively new technical automated assistance system.

[1]  Steffen Lamparter,et al.  Relaxed Abduction: Robust Information Interpretation for Incomplete Models , 2011, Description Logics.

[2]  Pramod K. Varshney,et al.  Accurate estimation of indoor occupancy using gas sensors , 2009, 2009 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP).

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

[4]  Sotirios Terzis,et al.  Situation determination with distributed context histories , 2005 .

[5]  M. Lawton,et al.  Assessment of older people: self-maintaining and instrumental activities of daily living. , 1969, The Gerontologist.

[6]  H.-P. Frerichs,et al.  Fire detection with low power fet gas sensors , 2007 .

[7]  Takahiro Hayashi,et al.  Recognition of human activities by gas sensor response using genetic algorithm , 2002 .

[8]  Munindar P. Singh,et al.  Service-Oriented Computing: Semantics, Processes, Agents , 2010 .

[9]  M. Lawton,et al.  Assessment of Older People: Self-Maintaining and Instrumental Activities of Daily Living , 1969 .

[10]  Peter Graubmann,et al.  Semantic Modelling in Agent-Based Software Development , 2007, AIS-ADM.

[11]  Kent Larson,et al.  Activity Recognition in the Home Using Simple and Ubiquitous Sensors , 2004, Pervasive.

[12]  M. Shelkey,et al.  Katz Index of Independence in Activities of Daily Living (ADL). , 2007, Urologic nursing.

[13]  H. Ulmer,et al.  Detection of human effluents by a MOS gas sensor in correlation to VOC quantification by GC/MS , 2010 .

[14]  Joachim Hänsel,et al.  SmartSenior - Intelligent Services for Senior Citizens , 2012, Handbook of Ambient Assisted Living.

[15]  M. Shelkey,et al.  Katz Index of Independence in Activities of Daily Living. , 1999, Journal of gerontological nursing.

[16]  Matthai Philipose,et al.  Building Reliable Activity Models Using Hierarchical Shrinkage and Mined Ontology , 2006, Pervasive.

[17]  A. Rector.  The Description Logic Handbook: Medical Informatics , 2007 .

[18]  Steffen Lamparter,et al.  Automata-Based Abduction for Tractable Diagnosis , 2010, Description Logics.

[19]  Alice M. Obenchain-Leeson,et al.  Volume 6 , 1998 .