Tagging strategies for extracting real-world events with networked sensors.

ABSTRACTIn this paper, we introduce our 's-room' project as well as the tagging strategies and environment developed for the project. In the s-room, many small sensor nodes are attached to various objects. Our project aims to construct a system for comprehending real-world events and the properties or status information of physical objects by utilizing sensor nodes distributed throughout the room as well as general knowledge obtained from web space. The events extracted in the s-room are then published as web contents. We defined a set of event descriptors as a middle language between the sensor data stream and natural language description. The descriptors are selected by a two-way method: 1) a top-down approach based on definitions in NL-dictionaries and laws in physics, 2) a bottom-up approach based on manually tagged sensor data streams. We also developed a tagging environment that enables us to arrange the relationship between NL phrase expressions of human activities and multiple sensor events automatically extracted from the sensor signal streams.