A Context-Aware System that Changes Sensor Combinations Considering Energy Consumption

Authors:
Kazuya Murao;Tsutomu Terada;Yoshinari Takegawa;Shojiro Nishio
Affiliations:
Graduate School of Information Science and Technology, Osaka University, Suita-shi, Japan 565-0871;Graduate School of Engineering, Kobe University, Nada, Kobe, Japan 657-8501;Organization of Advanced Science and Technology, Kobe University, Nada, Kobe, Japan 657-8501;Graduate School of Information Science and Technology, Osaka University, Suita-shi, Japan 565-0871
Venue:
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
Year:
2009

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Abstract

In wearable computing environments, a wearable computer runs various applications using various sensors (wearable sensors). In the area of context awareness, though various systems using accelerometers have been proposed to recognize very minute motions and states, energy consumption was not taken into consideration. We propose a context-aware system that reduces energy consumption. In life, the granularity of required contexts differs according to the situation. Therefore, the proposed system changes the granularity of cognitive contexts of a user's situation and supplies power on the basis of the optimal sensor combination. Higher accuracy is achieved with fewer sensors. In addition, in proportion to the remainder of power resources, the proposed system reduces the number of sensors within the tolerance of accuracy. Moreover, the accuracy is improved by considering context transition. Even if the number of sensors changes, no extra classifiers or training data are required because the data for shutting off sensors is complemented by our proposed algorithm. By using our system, power consumption can be reduced without large losses in accuracy.