Knowledge-Oriented Approach to Requirements Engineering in Ambient-Assisted Living Domain Volodymyr Bolshutkin 1 , Claudia Steinberger 2 , and Mykola Tkachuk 1 1 National Technical University “Kharkiv Polytechnical Institute”, Kharkiv, Ukraine vladimir.bolshutkin@gmail.com, tka@kpi.kharkov.ua 2 Alpen-Adria-Universit¨at, Klagenfurt, Austria claudia.steinberger@aau.at Abstract. This paper sketches HBMS(Human Behavior Monitoring and Support), an Ambient Assisted Living (AAL) approach deriving cogni- tive behavioral models from individual behavioral processes and using this knowledge “learned” to compensate individual memory gaps. In the context of HBMS individual behavioral processes represent the require- ments to customize an individual assistive system. Keywords: ambient-assisted living, requirements engineering, knowl- edge, behavior modeling. In the context of demographic aging in the western world improving the quality of life for disabled and elderly people is an essential task for our society. Facing these challenges technological innovations can enhance the quality of life of older and impaired people and contribute to independent living and quality of life. Ambient Assisted Living (AAL) solutions are developed to help elderly to live longer at the place they like most enhancing their safety and security, giving them assistance to carry out daily activities, monitoring their activities and health, getting access to emergency systems and facilitating social contacts [1,2]. So far little attention has been paid in AAL research to give persons aid to memory to carry out their daily activities although memory gaps are very typical to evolve in an advanced age. Especially elderly people often need sup- port carrying out activities such as using technical devices(e.g. washing machine, TV-set), dealing with administrative duties, using electronic banking tools, us- ing online-shops or simply to remember all steps of their daily life activities. Existing assistive technology systems for cognition are forcing compliance with standardized processes defined by third parties [3] and neglect established user habits. Thus the user acceptance level of such systems is often rather low. The possibility to use established cognitive behavioral processes as requirements to assist the individual later on would improve user acceptance. Human Behavior Monitoring and Support (HBMS) [4,5] is an approach to derive cognitive behavioral models from individual behavioral processes. Knowl- edge “learned” in this way is stored in an “artificial memory” and can be recalled later in time to compensate gaps in the episodic memory of the respective person and to technically assist his or her activities. H.C. Mayr et al. (Eds.): UNISCON 2012, LNBIP 137, pp. 205–207, 2013. c  Springer-Verlag Berlin Heidelberg 2013