Context-aware collective decision making based on fuzzy outranking

In sensor networks, depending on the user-defined goal and the number of objects-of-interest within the common sensor coverage area, multiple sensors generate multiple sources of information. Combining this information is essential and in this paper we propose a fuzzy outranking approach to combining information at the decision level, therefore leading to a collaborative decision making framework. Decision level information is represented through graphical models which helps in enhancing quantifiable system performance by processing information at a higher level and the second advantage is the ability to implement an adaptive framework for decision making. When used with dynamic belief update and an integrated database, a fuzzy outranking approach can be implemented with the ability to adapt to new sensor information and combined various local sensor decisions.