Aggregation methods of multi-layered information about an environmental perception sensor

Abstract

This paper focuses on the fusion algorithms of multi-layer information, in which the environment quantities of temperature, humidity and brightness are to be sequentially aggregated. The fusion result is to give an overall illustration about the environment as comfort, which has been defined as one kind of high-level information. Three multi-layer fusion methods are totally proposed in this paper; i) probability criterion, ii) rule based fuzzy strategy and iii) multi-layer creditability tactics. Different from the popular fusion strategies, the presented approach works in a step-by-step framework, and proves to be more practical and more effective especially when more variables are in calculation. The applications to a multi-functional sensor have proved that the proposed algorithms deserve the advantages of multi-layer sensing. In the light of applications, these methods are compared each other in terms of efficiency and limitations. The extension of the fusion mechanisms to multi-sensors is also briefly discussed.