Abstract
Sleep is an essentially physiologic phenomenon that compels humans to spend one-third of their lives sleeping. This paper deals with the correlation between sleep and condition data acquired from the data concerning bedroom sleep environments. The first thing we did in order to measure sleep environments was to install and run TinyOS, a compact operating system. Then we collected environmental data using the humidity sensor (SHT11) and the ambient light sensor (GL5507) in the H-MOTE2420 sensor. In this paper, the microphone sensor (WM62A) is not dealt with. Next, the subjects were asked to enter the information about levels of fatigue, levels of drinking, and levels of stomach emptiness as the weighting information affecting sleep. Finally, the difference image, the color histogram, and the χ 2 histogram, all of which are scene change detection methods, were used to detect scene transitions. The scenes obtained through scene change detection mean the number of the subjects' tossing and turning under different situations for different weights. In this paper, we used tables and figures, in particular, to make it easier to understand how frequently different levels of drinking left the subjects tossing and turning during sleep.
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