An annotation method for sensor data streams based on statistical patterns
Atsuhiro Takasu, Kenro Aihara · 2006
Due to recent advances in sensor technology greater quantities of sensor data are being generated and circulated. In these circumstances, sensor data stream processing and management technologies have become important research areas. In the development of mechanical and electrical systems, sensor stream data are a potential medium for sharing information among the engineers who are engaged in the various phases in the system development and operation. This paper proposes an annotation method for a sensor data stream that links the information generated in the development and operational phases of a system. The key techniques of the proposed method are sensor pattern construction using hidden Markov models (HMMs) and an annotation method based on the HMMs constructed. We applied the proposed method to the sensor data stream of a supersmall artificial satellite and showed that the proposed method achieved approximately 95% annotation accuracy for long fragments of the sensor data stream.