Collaborative context recognition for handheld devices

Handheld communication devices equipped with sensing capabilities can recognize some aspects of their context to enable novel applications. We seek to improve the reliability of context recognition through an analogy to human behavior. Where multiple devices are around, they can jointly negotiate on a suitable context and behave accordingly. We have developed a method for this collaborative context recognition for handheld devices. The method determines the need to request and collaboratively recognize the current context of a group of handheld devices. It uses both local context time history information and spatial context information of handheld devices within a certain area. The method exploits dynamic weight parameters that describe content and reliability of context information. The performance of the method is analyzed using artificial and real context data. The results suggest that the method is capable of improving the reliability.