A Low-Power Sensing Management Method for Sustainable Context-Awareness in Exclusive Contexts

摘要

A context-aware service makes the assumption that two or more exclusive contexts are not inferred simultaneously such as driving and studying, indoor and outdoor. However, in practice they are sometimes inferred at the same time, and it causes inefficient power consumption because it does not make sense. To handle this problem and improve power efficiency, we propose a low-power sensing management method for sustainable context-awareness in exclusive contexts. In our method, we identify the exclusive contexts by using sensing models. Then, we determine next sensing time by utilizing supplementary sensor or increase the period of sensing in the exclusive contexts (i.e., back off). The results of our preliminary application show that the power efficiency is improved to 21 % in the exclusive contexts. The proposed method will be more effective when the exclusive contexts are inferred more frequently according to diffusion of context-aware services in the future.