研究生: |
鍾宜曄 Chung, Yi-Yeh |
---|---|
論文名稱: |
智慧手機結合G-sensor之打瞌睡偵測系統之研發 Research and DEvelopment of Drowsiness Detection System by Using Smartphone and G-sensor |
指導教授: |
何宏發
Ho, Hong-Fa |
學位類別: |
碩士 Master |
系所名稱: |
電機工程學系 Department of Electrical Engineering |
論文出版年: | 2015 |
畢業學年度: | 103 |
語文別: | 中文 |
論文頁數: | 116 |
中文關鍵詞: | 打瞌睡偵測器 、G-sensor 、Haar cascade演算法 、瞌睡的點頭 、瞌睡的閉眼 |
英文關鍵詞: | Doze (sleep) nod detector, G-sensor, Haar cascade algorithm, Doze (sleep) nod, Doze (sleep) eye closure |
論文種類: | 學術論文 |
相關次數: | 點閱:116 下載:23 |
分享至: |
查詢本校圖書館目錄 查詢臺灣博碩士論文知識加值系統 勘誤回報 |
由於紅外線車上型打瞌睡偵測器有照久了眼睛會有灼熱感的情形,故本論文的方向為開發不用紅外線且在光線不足時能做偵測打瞌睡的系統,我們用G-sensor偵測瞌睡點頭來補足光線不足時的情況。
為了解決問題,本研究開發出打瞌睡偵測器App和G-sensor帽子,App結合智慧手機內建的攝影機用來偵測瞌睡的閉眼,App結合G-sensor帽子則可偵測瞌睡的點頭,閉眼和點頭的偵測是同時進行,所以當光線不足,無法偵測閉眼時,還有點頭偵測判斷使用者是否在打瞌睡,App偵測閉眼部分的演算法用的是Haar cascade演算法,平均處理1張影片要0.48秒,App偵測點頭部分,G-sensor帽子上裝有G-sensor、Arduino板子、藍芽模組及行動電源,G-sensor的類比資料會先透過Arduino板子轉成字串數據,再透過藍芽傳送到App做分析。
由我們的實驗一得知,偵測閉眼的準確率為99.52%,偵測點頭的準確率為100%,由我們的實驗二得知,偵測閉眼的準確率為99.89%,偵測點頭的準確率為100%,由於兩實驗偵測點頭的準確率都為100%,故能解決光線不足時的問題。
關鍵字:打瞌睡偵測器、G-sensor、Haar cascade演算法、瞌睡的點頭、瞌睡的閉眼
This research has developed a system to detect doze (sleep) nod while driving, through G-sensor and without infrared. This newly invented system is not only able to detect slim eyes-brainwave-and head motion of the drivers at dim light, but capable to eliminate allergy to the eyes that are caused by infrared eye detectors, as the primary source of light for most detection equipment used by many of the eye tracking systems currently available in the market.
To solve the problem, the research develop doze detector by using App and G-sensor cap, App combine smart phone built-in camera to detect sleepy eyes closed, App can be combined with G-sensor cap detects sleepy nod, eyes closed and nodded detection are performed simultaneously, so when lighting is poor, can not detect when eyes closed, and determine whether the user is in a nod to detect doze. To detect doze (sleep) eye closure by APP, this research has adopted Haar Cascade algorithm for measurement, with average processing time of 0.48 seconds per one photo. To effectively assess doze (sleep) nod, a G-sensor hat has been developed to cooperate with APP detector. The G-sensor cap comes with G-sensor device, Arduino board, Bluetooth module, and portable battery. G-sensor analog data will be converted into a string of data through the Arduino board, then sent via Bluetooth to the App for analysis.
By our first experiment, detection accuracy rate of 99.52 percent with eyes closed, nodding detection accuracy was 100%. By our second experiment, detection accuracy rate of 99.89 percent with eyes closed, nodding to detect accuracy was 100%, due to the accuracy of the two experimental detection nod are 100%, it can solve the problem when lighting is poor.
Keyword: Doze (sleep) nod detector, G-sensor, Haar cascade algorithm, Doze (sleep) nod, Doze (sleep) eye closure
[1] I.-L. Tsai, C.-L. Ting, and R.-I. Chang, "Drowsiness Detection and Warning for Vehicle Active Safety," JITAS, pp. 1-20, 2013.
[2] Y. Takei and Y. Furukawa, "Development of Vehicle Driver Drowsiness Detection System Using Electrooculogram (EOG)," IEEE International Conference on Systems, Man and Cybernetics, pp. 1765-1770, 2005.
[3] 仇多寜, "打盹報警器," CN2383165Y, 2000.06.14, 2000.
[4] J. Vicente, P. Laguna, A. Bartra, and R. Bailón, "Detection of Driver's Drowsiness by Means of HRV Analysis," Computing in Cardiology, pp. 89-92, 2011.
[5] G. Borghini, G. Vecchiato, J. Toppi, L. Astolfi, A. Maglione, R. Isabella, et al., "Assessment of mental fatigue during car driving by using high resolution EEG activity and neurophysiologic indices," 34th Annual International Conference of the IEEE EMBS, pp. 6442-6445, 2012.
[6] S. D. Baulk, L. A. Reyner, J. A. Horne, “Driver Sleepiness –
Evaluation of Reaction Time Measurement as a Secondary Task”,
Sleep, vol. 24, no. 6, pp. 695-698.
[7] K. M. Bach, M. G. Jæger, M. B. Skov, N. G. Thomassen, “Interacting
with In – Vehicle System: Understanding, Measuring, and Evaluating
Attention”, HCI 2009 – People and Computers XXIII – Celebrating
people and technology, pp. 453 – 462.
[8] M. Simon, E. A. Schmidt, W. E. Kincses, M. Fritzsche, A. Bruns, C.
Aufmuth, C. Bogdan, W. Rosenstiel, M. Schrauf, “EEG alpha spindle
measures as indicators of driver fatigue under real traffic conditions”,
Clinical Neurophysiology, vol. 122, no. 6, pp. 1168 – 1178, 2011.
[9] C. Papadelis, Z. Chen, C. Kourtidou-Papadeli, P. D. Bamidis, I.
Chouvarda, E. Bekiaris, N. Maglaveras, “Monitoring sleepiness with
on – board electrophysiological recordings for preventing sleep -
deprived traffic accidents”, Clinical Neurophysiology, vol. 118, pp.
1906 – 1922, 2007.
[10] W. Klimesch, “EEG alpha and theta oscillations reflect cognitive and
memory performance: a review and analysis”, Brain Research
Reviews, vol. 29, pp. 169-195, 1999
[11] R. R. Knipling & J. S. Wang, "Revised estimates of the US drowsy
driver crash problem size based on general estimates system case
reviews", 39th Annual Proceedings, Association for the Advancement of
Automotive Medicine, Chicago, pp. 451-456, 1995.
[12] D. F. Dinges & M. M. Mallis, "Managing fatigue by drowsiness
detection: Can technological promises be realised?" In Managing
Fatigue in Transportation. Proceedings of the Third International
Conference on Fatigue and Transportation, L. R. Hartley, Ed. Fremantle,
Western Australia, 1998, pp. 209-229.
[13] S. K. L. Lal, & A. Craig, "A critical review of the psychophysiology of
driver fatigue", Biological Psychology vol. 55, pp. 173-194,2001.
[14] B. V. Dasarathy, "Sensor Fusion Potential Exploitation - Innovative
Architectures and Illustrative Applications", Proceedings of the IEEE
85(1), pp. 24-38, 1997.
[15] A. B. Albu, B. Widsten, T. Wang, J. Lan, and J. Mah, "A Computer Vision-Based System for Real-Time Detection of Sleep Onset in Fatigued Drivers," 2008 IEEE Intelligent Vehicles Symposium, pp. 25-30, 2008.
[16] Z. Zhu and Q. Ji, “Real-Time and non-intrusive driver fatigue
monitoring”, in Proc. of IEEE Intelligent Transportation Systems
Conference, pp. 657-662, 2004.
[17] L. M. Bergasa, J. Nuevo, M. A. Sotelo, and Manuel Vazquez, “Realtime
system for monitoring driver vigilance”, IEEE. Int. Conf. on
Intelligent Vehicles, pp. 78-83, 2004.
[18] P. Smith, M. Shah, and N.da Vitoria Lobo, “Monitoring head/eye
motion for driver alertness with one camera”, in Proc. of IEEE Int.
Conf. on Pattern Recognition (ICPR), vol. 4, pp. 4636-4643, 2000.
[19] P. Smith, M. Shah, and N.da Vitoria Lobo, “Determining driver visual
attention with one camera”, IEEE Trans. on Intelligent Transportation
systems, vol. 4:4, pp. 205-218, 2003.
[20] A. K. Jain, R. P. W. Duin, and J. Mao, “Statistical Pattern
Recognition: A review”, IEEE Trans. on Pattern Analysis and
Machine Intelligence, vol. 22:1, pp. 4-37, 2000.
[21] S. M. Lin, "A Real-Time Driver Drowsiness Detection and Alertness Monitor System," Master thesis, Department of Computer Science and Information Engineering, National Central University, Jun. 2007.
[22] L. Lang and H. Qi, "The Study of Driver Fatigue Monitor Algorithm Combined PERCLOS and AECS," International Conference on Computer Science and Software Engineering, (2008): pp. 349-352.
[23] R. Grace, "Drowsy driver monitor and warning system," International Symposium on Human Factors in Driver Assessment, Training and Vehicle Design, 2001: pp. 64-69.
[24] M. Soriano, B. Martinkauppi, S. Huovinen and M. Laaksonen, "Adaptive skin color modeling using the skin locus for selecting training pixels," Pattern Recognition,(36:3), 2003: pp. 681-690.
[25] M. Soriano, B. Martinkauppi, S. Huovinen, and M. Laaksonen, "Adaptive skin color modeling using the skin locus for selecting training pixels," Pattern Recognition 36, pp. 681-690, 2003.
[26] 陳克智, "License Plate Detection and Recognition of Smart-Phone," unpublished.
[27] Cao, J., M. Ahmadi, and M. Shridhar, "Recognition of handwritten numerals
with multiple feature and multistage classifier," Pattern Recognition, vol.2,
no.28, pp.153-160, Feb. 1995.
[28] Capar, A. and M. Gokmen, "Concurrent segmentation and recognition with
shape-driven fast marching methods," in Proc. 18th Int. Conf. on Pattern
Recognition, Hong Kong, Aug.20-24, 2006, vol.1, pp.155-158.
[29] Chang, S.-L., L.-S. Chen, Y.-C. Chung, and S.-W. Chen, "Automatic license
plate recognition," IEEE Trans. Intelligent Transportation Systems, vol.5, no.1,
pp.42-53, Mar. 2004.
[30] Comelli, P., P. Ferragina, M. N. Granieri, and F. Stabile, "Optical recognition of
motor vehicle license plates," IEEE Trans. Vehicular Technology. vol.44, no.4,
pp.790-799, Nov. 1995.
[31] Draghici, S., "A neural network based artificial vision system for license plate
recognition," Int. Journal of Neural Systems, vol.8, no.1, pp.113-126, Feb. 1997.
[32] L. Xu, S. Li, K. Bian, T. Zhao, and W. Yan, "Sober -Drive: A Smartphone-assisted Drowsy Driving Detection System," 2014 International Conference on Computing, Networking and Communications, Mobile Computing & Vehicle Communications Symposium, pp. 398-402, 2014.
[33] 趙修鼎, "Real-time Multi-vehicles Detection and Tracking Techniques for an Intelligent Driving Asssistant System Used in Complex Traffic Environments," unpublished.
[34] Bo Wu and Nevatia R, "Cluster Boosted Tree Classifier for Multi-View, Multi-Pose Object Detection," IEEE 11th International Conference, pp. 1-8, 2007.
[35] C. P. Papageorgiou, M. Oren and T. Poggio, "A general framework for object detection," Sixth International Conference on Computer Vision, pp. 555-562, Jan. 1998.
[36] Y. Freund and R. E. Schapire, "A decision-theoretic generalization of on-line learning and an application to boosting," Journal of Computer and System Sciences, vol. 55, no. 1, pp. 119-139, Aug. 1997.
[37] J. He, S. Roberson, B. Fields, J. Peng, S. Cielocha and J. Coltea, "Fatigue Detection using Smartphones," J Ergonomics, pp. 1-7, 2013.
[38] P. Viola and M. J. Jones, "Robust Real-Time Face Detection," International Journal of Computer Vision, pp. 137-154, 2004.
[39] Richard J. Estrada, " Vehicle operator sleep alarm," US5353013 A, 1994.10.04, 1994.
[40] Kakuichi Shiomi and Shozo Hirose, "Apparatus for detecting fatigue and doze by voice, and recording medium," US6876964 B1, 2005.04.05, 2005.
[41] Kiichi Yamada and Minakami Yumi, "Doze-off warning apparatus for vehicle," US7868771 B2, 2011.01.11, 2011.
[42] Hideaki Yoshioka, "Doze prevention system," US4725824 A, 1988.02.16, 1988.
[43] Ataul Haq, "Doze-off early warning system for automotives and other applications," US20040032334 A1, 2004.02.19, 2004.
[44] Norihito Yamamoto and Takahide Tanaka, "Doze detector," EP0280124 A1, 1988.08.31, 1988.
[45] 金瀋陽 and 胡鐵剛, "Anti-doze device and anti-doze glasses," CN204010242 U, 2014.12.10, 2014.
[46] 鄭巨帥 and 溫從眾, "Doze preventing desk," CN202980878 U, 2013.06.12, 2013.
[47] James Russell Clarke, Sr. and Phyllis Maurer Clarke, "Sleep detection and driver alert apparatus," US5689241 A, 1997.11.18, 1997.
[48] 洪勝文 and 林錦蔚, "人臉辨識駕車提醒裝置," M479874, 2014.06.11, 2014.
[49] 許守港, "防止駕駛者打瞌睡之震動結構," M501617, 2015.05.21, 2015.
[50] 涂昆源, "疲勞駕駛監測裝置," M489800, 2014.11.11, 2014.
[51] 李佳憲, 張耀宗,and 林百洋, "防瞌睡預警系統及方法," I438727, 2014.05.21, 2014.
[52] 廖家儀, "防瞌睡噴水警示裝置," M474987, 2014.03.21, 2014.
[53] 陳泰良, "車輛防瞌睡系統及其方法," I424379, 2014.01.21, 2014.
[54] 方志恒, 陸家樑,and 林伯聰, "防瞌睡裝置," D148018, 2012.07.01, 2012.
[55] 程達隆, 葉歡賢, 高國陞,and 鄧瑞娟, "瞌睡喚醒系統," M431385, 2012.06.11, 2012.
[56] 葉嘉成, "打瞌睡警告裝置," M428445, 2012.05.01, 2012.
[57] 任恩, 陳年伸, 黃長漢, 李曜宸, 許齡芸, 宋方妤,and 林威佐, "駕駛狀態紀錄裝置," M498359, 2015.04.01, 2015.
[58] 任恩, 陳年伸, 黃長漢, 李曜宸, 許齡芸, 宋方妤,and 林威佐, "應用於偵測駕駛疲勞狀態之檢測耳機," M498360, 2015.04.01, 2015.
[59] 張家榮, ”智慧行車安全模組," M493490, 2015.01.11, 2015.
[60] 何昌年, 喻肇川,and 何怡慧, ”駕駛(操作)員身心監測器," M489799, 2014.11.11, 2014.
[61] 鄭丞謨, ”混合動力車之安全控制系統," M487238, 2014.10.01, 2014.
[62] 顏瑞成 and 陳漢臣, ”車輛駕駛頭部移動偵測方法與系統," I450205, 2014.08.21, 2014.
[63] 顏瑞成 and 阮瑞祥, ”駕駛頭部偏移偵測裝置," M478813, 2014.05.21, 2014.
[64] 林意師, ”行車中專注問題警示裝置," M469227, 2014.01.01, 2014.
[65] 張丕白, 賴文正,and 張錫琦, ”傾斜感測系統及以其為構件之安全警示與照明裝置," M469244, 2014.01.01, 2014.
[66] 黃正一 and 莊朝琪, ”客製化眼球感應行車安全偵測器," M466822, 2013.12.01, 2013.
[67] 劉冠佑, 吳錫修, 柯嘉南,and 吳信義, ”車用疲勞偵測暨提神裝置及其方法," I397030, 2013.05.21, 2013.
[68] 袁崐益, ”車載安全裝置," I379785, 2012.12.21, 2012.
[69] 黃琮暉, 許東岳, 伍柏霖, 楊智評, 楊燿瑝, 穆承佑,and 施柏衍, ”車用之脈搏監控裝置," M441896, 2012.11.21, 2012.
[70] 張獻中, 林允晟, 劉俊成, 蔡淳翔, 盧勁廷, 楊士賢, 高莉婷, 謝孟廷, 郭子嶢,林宗佑,and 許景淵, ”防止打瞌睡裝置," M436895, 2012.09.01, 2012.
[71] 陳運雄, ”具防瞌睡功能之行車記錄裝置," M418053, 2011.12.11, 2011.
[72] 鄒佳融, ”可提醒駕駛員注意駕駛及防瞌睡的影像處理系統," M416161, 2011.11.11, 2011.
[73] 趙海倫, ”可偵測血氧濃度之眼鏡," M410888, 2011.09.01, 2011.
[74] 郭博昭 and 楊靜修, ”車用健康管理之系統及其方法," I337587, 2011.02.21, 2011.
[75] 黃琮暉, 林家宏, 蕭英男, 李坤育, 徐廣君,and 邱任志, ”行車警示裝置," M395882, 2011.01.01, 2011.
[76] 陳炳煌, ” 瞌睡防止器," M381137, 2010.05.21, 2010.
[77] 陶德福, 汪泰宏, 蔡秉青, 張竣豪, 梁泰瑋,and 涂國賢, ”電子瞌睡提醒裝置," M377662, 2010.04.01, 2010.
[78] 郭博昭 and 楊靜修, ”太陽眼鏡型瞌睡防止器," I321227, 2010.03.01, 2010.
[79] Accelerometer [online] Available Telnet:http://en.wikipedia.org/wiki/Accelerometer
[80] D. M. Karantonis, M. R. Narayanan, M. Mathie, N. H. Lovell, and B. G.
Celler, “Implementation of a real-time human movement classifier using
a triaxial accelerometer for ambulatory monitoring,” IEEE Transactions
on Information Technology in Biomedicine, vol. 10, no. 1, pp. 156–167,
January 2006.
[81] D. Alvarez, R. C. Gonz´alez, A. M. L´opez, and J. C. Alvarez, “Comparison
of step length estimators from weareable accelerometer devices,” in
Proceedings of the 28th Annual International Conference of the IEEE
Engineering in Medicine and Biology Society (EMBS 2006), 30 August
- 3 September 2006, pp. 5964–5967.
[82] J.-H. Chen, S.-C. Lee, and D. B. DeBra, “Gyroscope free strapdown
inertial measurement unit by six linear accelerometers,” Journal of
Guidance, Control, and Dynamics, vol. 17, no. 2, pp. 286–290, March-
April 1994.
[83] A. Ofstad, E. Nicholas, R. Szcodronski, and R. R. Choudhury, “AAMPL:
accelerometer augmented mobile phone localization,” in Proceedings of
the first ACM international workshop on Mobile entity localization and
tracking in GPS-less environments (MELT 2008), 19 September 2008, pp.
13–18.
[84] J. C. Alvarez, R. C. Gonz´alez, D. Alvarez, A. M. L´opez, and J. Rodr´ıguez-
Ur´ıa, “Multisensor approach to walking distance estimation with foot inertial
sensing,” in Proceedings of the 29th Annual International Conference
of the IEEE Engineering in Medicine and Biology Society (EMBS 2007),
22-26 August 2007, pp. 5719–5722.
[85] A. M. Sabatini, C. Martelloni, S. Scapellato, and F. Cavallo, “Assessment
of walking features from foot inertial sensing,” IEEE Transactions on
Biomedical Engineering, vol. 52, no. 3, pp. 486–494, March 2005.
[86] K. Sagawa, H. Inooka, and Y. Satoh, “Non-restricted measurement
of walking distance,” in Proceedings of the 2000 IEEE International
Conference on Systems, Man, and Cybernetics, vol. 3, 8-11 October 2000,
pp. 1847–1852.
[87] X. Yun, E. R. Bachmann, H. Moore, and J. Calusdian, “Self-contained
position tracking of human movement using small inertial/magnetic sensor
modules,” in Proceedings of the 2007 IEEE International Conference
on Robotics and Automation, 10-14 April 2007, pp. 2526–2533.
[88] S.-C. Huang, L.-C. Chen, H.-C. Chang, and H.-Y. Chang, “The novel falling detection method with G-sensors on Waist,” ICCE , pp. 233-234, 2014.
[89] C.-M. Wang, J.-D. Hong, G.-C. Lin,J.-Y. Su, and Z.-F. Lin, “License plate location system using smart-phone with G-sensor,” Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing , pp. 451-454, 2014.
[90] C.-W. Yi, C.-M. Su, W.-T. Chai, J.-L. Huang, and T.-C. Chiang, “G-constellations: G-sensor motion tracking System,” IEEE, pp.1-5, 2010.