| Summary: | 碩士 === 國立宜蘭大學 === 多媒體網路通訊數位學習碩士在職專班 === 101 === Mobile Devices (Smart Phones, Tablets) dig deeper and deeper into people's lives all these years. However, the prevention of eye strain while using mobile devices have been ignored. Close-distance reading and viewing devices in shaky environment may lead to myopia or Presbyopia. This research is aimed at reading distance and context-aware. The technology has been applied on Android APP, which reminds end users at a point that vision can be harmed if the condition continues. Detecting distance and optimizing battery usages are being analyzed simultaneously for this research. For distance detection, we utilize the device's front camera to capture the image of the user to analyze his eyes distance pixel by the Android's built-in face detection system. According to the research, 114.14 pixels are the safety reading distance, hence, it has applied as default value for the Mobile Devices Vision Protect APP. For context-aware, using the Tri-Axis accelerometer sensor each data delay level with Decision tree、k-Nearest Neighbor、Support Vector Machine algorithm as a context-aware experimental methods，through Weka software application, 93.82% recognition with 3mW of atomizing battery usages are the best combination to apply for the Mobile Device Vision Protect APP. The research using the device built-in system and sensor to perform the reading distance detection and context-aware which are the cost effective to save end user's vision.
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