Situation Recognition and Medical Data Analysis in Pervasive Health Environments

Research Article

Automated Assistance Services: Experience from the SmartSenior Project

Download727 downloads
  • @INPROCEEDINGS{10.4108/icst.pervasivehealth.2012.248687,
        author={Mikhail Roshchin and Asa MacWilliams and Roland Pohle and Fabienne Waidelich and Ines Steinke},
        title={Automated Assistance Services: Experience from the SmartSenior Project},
        proceedings={Situation Recognition and Medical Data Analysis in Pervasive Health Environments},
        publisher={IEEE},
        proceedings_a={PERVASENSE},
        year={2012},
        month={7},
        keywords={aal situation understanding gas sensor intelligent watch complex event processing abductive and temporal reasoning smartsenior project},
        doi={10.4108/icst.pervasivehealth.2012.248687}
    }
    
  • Mikhail Roshchin
    Asa MacWilliams
    Roland Pohle
    Fabienne Waidelich
    Ines Steinke
    Year: 2012
    Automated Assistance Services: Experience from the SmartSenior Project
    PERVASENSE
    IEEE
    DOI: 10.4108/icst.pervasivehealth.2012.248687
Mikhail Roshchin1,*, Asa MacWilliams1, Roland Pohle1, Fabienne Waidelich1, Ines Steinke1
  • 1: Siemens AG
*Contact email: mikhail.roshchin@siemens.com

Abstract

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.