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    Please use this identifier to cite or link to this item: http://ccur.lib.ccu.edu.tw/handle/A095B0000Q/518

    Title: 智慧型駕駛狀態監測系統;Intelligent Driving Condition Monitoring System
    Authors: 賴建宏;LAI, CHIEN-HUNG
    Contributors: 資訊工程學系碩士在職專班
    Keywords: 眨眼頻率;脈搏頻率;二維模組;離群值;監測;密度;two-dimensional module;Outlier;Blink frequency;Pulse frequency;Density;monitoring
    Date: 2017
    Issue Date: 2019-07-17
    Publisher: 資訊工程學系碩士在職專班
    Abstract: 本研究針對駕駛人狀態特徵建置一套主動式安全輔助系統-「智慧型駕駛狀態監測系統」,擷取兩項生理資訊建置專屬的生理模組,分別是脈搏頻率和眨眼頻率。取得這兩項生理資訊建立二維向量模組,去除離群值以後,就可以在行車的時候使用偵測模式做駕駛狀態監測。 眨眼頻率是使用Webcam擷取影像,使用P.Viola提出的臉部偵測方法[20]定位出臉部,然後用霍夫轉換的原理找尋虹膜位置,便可以偵測出眨眼的動作,從而算出眨眼頻率。脈搏頻率使用Arduino Uno[1]和搭配的光反射感測器,感測器打出光線到手指上,光反射回感測器上的接收器,血管中的血液會吸收光,影響反射光的強度,偵測出接收器接收的光線強弱變化的規律,就可以判斷脈搏的發生,依照此原理偵測可以抓到脈搏的間隔時間,從而計算出脈搏頻率。 使用上述原理取得生理資訊以後建立二維模組,使用密度方法(Outlier detect based on Density),濾除離群值以後便完成個人專屬的偵測模組。在行車的時候載入針對該駕駛狀態訓練完成的專屬模組,同時做即時的生理資訊偵測,就可以即時偵測目前駕駛人的生理狀態是否正常。 本研究可以應用在計程車總部監控部門,或是客運公司的監測單位,可以即時監測旗下的駕駛人狀態,評估駕駛狀態做及時調度,避免憾事發生,提高行車品質。關鍵詞:眨眼頻率,脈搏頻率,二維模組,離群值,監測,密度
    In this study, by investigating the pulse frequency and the blink frequency, two physiological information models were used to establish an active safety aided system - the "intelligent driving condition monitoring system", and the two physiological information were established as two vectors Module, after the removal of the outliers, you can use the detection mode in the driving time to do driving state monitoring . Blink frequency is to use Webcam to capture images, through P.Viola proposed face detection method[20] to locate the face, and then use the Hough conversion principle to find the pupil position, you can detect the blink of an action to calculate the blink frequency. Pulse frequency detection is the use of Arduino Uno[1] and with the light reflection sensor, the sensor sends light to the finger, the light reflected back to the receiver on the sensor, blood vessels will absorb light, resulting in reflected light Strength changes, in accordance with this principle can be detected to grasp the pulse of the interval time to calculate the pulse frequency. After using the above principle to obtain physiological information, use it to establish a two-dimensional module, by using the density method (Outlier detect based on Density) filter out the outliers, you can complete the individual exclusive detection module. In the driving time to load a dedicated module to do real-time physiological information detection, you can immediately detect the current state of the driver's normal or not. This study can be applied to the monitoring department of the taxi headquarters, or the monitoring unit of the passenger company. It can monitor the driver's status in real time, evaluate the driving state and timely dispatch, avoid the occurrence of the trouble and improve the running quality.Keywords:two-dimensional module, Outlier, Blink frequency, Pulse frequency, Density, monitoring
    Appears in Collections:[資訊工程學系] 學位論文

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