Dealing with Uncertainty in Situation-aware Computing System

Abstract

Situation awareness is a more holistic and promising version of context awareness, which is a key to making Ambient Intelligence systems more adaptive and intelligent. A situation-aware computing system needs to represent context information, identify relevant situations based on the context, and then take appropriate actions according to situations. However, two main kinds of uncertainty need to be handled in these processes: the semantic of context or situation may be fuzzy; context is inherently imperfect. This paper proposes an innovative framework for carrying out situation-aware computing under uncertainty where fuzzy ontology based on fuzzy description logic is used to model context, several new algorithms are proposed to identify entities’ situations considering uncertainty, a fuzzy system based on fuzzy logic and fuzzy learning techniques is developed to make decisions proactively and automatically. In addition, we develop a prototype of smart home application, experimental results from it show that our new technologies are feasible and effective.