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研究生:江集祥
研究生(外文):Chiang Chi-Hsiang
論文名稱:MA4:使用Android MID與Arduino平台之行動式動作分析
論文名稱(外文):MA4: Mobile Activity Analysis using Android MID and Arduino Platform
指導教授:鄭福炯鄭福炯引用關係
指導教授(外文):Cheng Fu-Chiung
學位類別:碩士
校院名稱:大同大學
系所名稱:資訊工程學系(所)
學門:工程學門
學類:電資工程學類
論文種類:學術論文
論文出版年:2010
畢業學年度:98
語文別:中文
論文頁數:51
中文關鍵詞:情境感知動作分析AndroidArduino嵌入式系統
外文關鍵詞:Context AwarenessActivity AnalysisAndroidArduinoEmbedded system
相關次數:
  • 被引用被引用:23
  • 點閱點閱:1992
  • 評分評分:
  • 下載下載:593
  • 收藏至我的研究室書目清單書目收藏:0
許多研究與報告都證明情境感知的高度需求,但至今卻極少成功商業化的產品,即便研究人員在相關的研究上,也常受限於使用者活動分析設備、系統的低相容性與高整合難度,無法專注於其專門的項目,必須先花費時間在克服各種介面的差異或是設備的規格,進度無法加快,在本論文中,我們提出MA4平台(Mobile Activity Analysis using Android MID and Arduino Platform),運用被使用者廣泛接受的Android MID(Mobile Internet Device),做為使用者終端設備,因其已具備如GPS、電子羅盤等基礎收集使用者狀態與活動的設備,且它是基於開放式Android作業系統開發,這個開放原始碼的作業系統適合研究人員、開發人員,甚至一般個人自行修改使用。
我們同時搭配一個完全開放的Arduino軟硬體開發平台,可連結各式的感測器與傳輸模組,與Android MID以精簡的開發流程,實作用線性加速度計,對使用者移動式動作姿態的分析。我們也以此實作結果,搭配情境推論引擎,以一般使用者日常生活的情境,完成一個能收集使用者即時狀態,並提供適切服務資訊的情境感知系統,證明它的結果符合預期。
我們相信,以我們實作的MA4平台為基礎,將大幅提升情境感知研究的質量,甚至讓使用者在短時間內,就可以不高的價格,藉由Android MID這類智慧型嵌入式系統,享受到情境感知的便利。
Many research and reports prove a high requirement of context awareness applications, but up to now, these are rarely successful commercial products. Current research, focus on user motion analysis equipment, system compatibility, low difficulty and high integration. In this paper, we use Android MID (Mobile Internet Device) together with a completely open Arduino hardware and software development platform to streamline the mobile activity analysis of mobile users. The platform is called MA4(Mobile Activity Analysis using Android MID and Arduino Platform). We also use MA4 platform to carry out a small project of context awareness, specifically recording daily life activities of general users, to prove that the results confirm with expectations.
致謝 i
摘要 ii
ABSTRACT iii
內容目錄 iv
圖目錄 vi
表目錄 viii
第一章 前言 1
1.1 研究背景 1
1.2 研究動機 2
1.3 論文結構 2
第二章 相關工作 3
2.1 情境感知 3
2.2 情境感知之動作偵測 4
第三章 背景知識 8
3.1 感測器 8
3.1.1 全球定位系統 8
3.1.2 線性加速度計 8
3.1.3 溫濕度感測器 11
3.2 Android作業系統 12
3.3 Arduino軟硬體開發平台 14
3.4 SOAP(Simple Object Access Protocol) 18
3.5 推論引擎 21
第四章 系統架構 23
4.1 使用者資訊分類 24
4.2 情境服務推論引擎 27
第五章 移動式動作分析與設計 28
5.1 移動式動作分析 28
5.2 動態比例分析法 32
第六章 實作與結果 38
6.1 實體架構 38
6.2 動作分析結果數據 41
6.3 衍生情境資訊 42
6.4 情境實例與結果 43
第七章 結論與未來工作 46
7.1 結論 46
7.2 未來工作 47
參考文獻 48
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[7]D. Malan, T. Fulford-Jones, M. Welsh, and S. Moulton. “Codeblue: An ad hoc sensor network infrastructure for emergency medical care.” In Proceeding of the International Workshop on Wearable and Implantable Body Sensor Networks, 2004.
[8]MARGARIA, R.: Biomechanics and energetics of muscular exercise, Oxford: Clarendon. Press 67-139, 1976.
[9]Chin Lai, Yueh-Min Huang, Han-Chieh Chao, Jong-Hyuk Park, "Adaptive Body Posture Analysis Using Collaborative Multi-Sensors for Elderly Falling Detection," IEEE Intelligent Systems, 18 Jan. 2010. IEEE computer Society Digital Library. IEEE Computer Society.
[10]C. W. Lin, and Z. H. Ling, “Automatic Fall Incident Detection in Compressed Video for Intelligent Homecare,” in Proc. of 16th International Conference on Computer Communications and Networks, 2007.
[11]Y. Ziegel, D. Litvak and I. Gannot, ”A Method for Automatic Fall Detection of Elderly People using Floor Vibrations and Sound - Proof of concept on human mimicking doll falls,” IEEE Transactions on Biomedical Engineering, vol. 56, no11, 2009, Forthcoming.
[12]Gao, J., Wactlar, H., Hauptmann, A., Collins, R.T., “Articulated Motion Modeling for Activity Analysis” IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'04), Workshop on Articulated and Nonrigid Motion (ANM'04), Washington, DC, vol. 1, pp. 20, July 27-July 2, 2004
[13]Nadia Zouba, Francois Bremond, Monique Thonnat, "Multisensor Fusion for Monitoring Elderly Activities at Home," avss, pp.98-103, 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance, 2009
[14]Park S, Jayaraman S, “Enhanceing the Quality of Lify Through Wearable Technology.” IEEE Engineering in Medicine and Biology Magazine 2003, 33(3):41-48.
[15]Raskovic D, Martin T, Jovanov E, “Medical Monitoring Applicateions for Wearable Computing.” The Computer Joumal 2004, 47(4):495-504.
[16]Anh Dinh Teng, D. Li Chen Seok-Bum Ko Yang Shi McCrosky, C. Basran, J. Del Bello-Hass, V. Univ. of Saskatchewan, Saskatoon, SK, Canada “A Wearable Device for Physical Activity Monitoring With Built-in Heart Rate Variability ” Bioinformatics and Biomedical Engineering , 2009. ICBBE 2009. 3rd ,11-13 June 2009, pp.1-4
[17]Wood, J. Stankovic, G. Virone, L. Selavo, Z. He, Q. Cao, T. Doan, Y. Wu, L. Fang, R. Stoleru, “Context-Aware Wireless Sensor Networks for Assisted-Living and Residential Monitoring,” In IEEE Network, 2008
[18]C. Randall, H. Muller, “Context awareness by analysing accelerometer data,” In Proc. 4th Int’l Symp. on Wearable Computers (ISWC) 2000. Oct. 16-17, pp. 175 – 176. <1000537>
[19]K. Laerhoven and O. Cakmakci, “What Shall We Teach Our Pants?”, Proceedings Fourth International Symposium on Wearable Computers, 2000, pp. 77-83
[20]Kenta Cho, Naoki Iketani, Hisao Setoguchi, Masanori Hattori, "Human Activity Recognizer for Mobile Devices with Multiple Sensors," uic-atc, Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, 2009, pp.114-119
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[29]Kuan Ming, “Using SWRL and OWL DO to Develop an Inference System for Course Scheduling”, Master Thesis, Chung Yuan Christian University, Taiwan, R.O.C. 2004
[30] GPS Wing Reaches GPS III IBR Milestone in InsideGNSS November 10, 2008
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[32] Edward, 推論引擎, http://microbuddy.blogspot.com/2008/12/blog-post.html
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