Current trends in the AI’s evolution are going towards enriching environments with intelligence in order to support humans in their everyday life. AmI systems are plunged in the real world and humans expect to interact with them in a way that is similar to the one they have with other humans. In this kind of systems, where eliciting requirements involves several documents and stakeholders (mainly users that will be the first consumers of the system), the requirement analysis phase can be affected by incomplete, ambiguous and imprecise information. Hence, the need to find a fruitful way for knowledge management and its representation at design time. In this paper we propose a set of abstractions to be used during the early requirements analysis of AmI systems development. The result is a simple and at the same time powerful set of concepts and guidelines for providing environment knowledge representation for AmI systems.
Ribino, P., Cossentino, M., Lodato, C., Lopes, S., Seidita, V. (2014). Requirement analysis abstractions for ami system design. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 28, 55-70 [10.3233/IFS-141217].
Requirement analysis abstractions for ami system design
SEIDITA, Valeria
2014-01-01
Abstract
Current trends in the AI’s evolution are going towards enriching environments with intelligence in order to support humans in their everyday life. AmI systems are plunged in the real world and humans expect to interact with them in a way that is similar to the one they have with other humans. In this kind of systems, where eliciting requirements involves several documents and stakeholders (mainly users that will be the first consumers of the system), the requirement analysis phase can be affected by incomplete, ambiguous and imprecise information. Hence, the need to find a fruitful way for knowledge management and its representation at design time. In this paper we propose a set of abstractions to be used during the early requirements analysis of AmI systems development. The result is a simple and at the same time powerful set of concepts and guidelines for providing environment knowledge representation for AmI systems.
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