臺灣博碩士論文加值系統

感測器裝置具有體積小和價格便宜，可快速回傳重要資料的特性，使得感測器網路很適合嵌入像建築物、衣物、車子等地方，即時監控和報告我們想知道的資料。所以近幾年來，感測器網路應用的開發成為很熱門的一項研究。如居家環境自動調控、火災逃生系統、位置追蹤和即時犯罪回報系統等。但通常感測器網路回傳的資料只是一些數值，如某處可能溫度異常、建築物有人進入等等。過於單調而資料不足，如果每次都處理可能會花很多不必要的effort，但如果訂立一個 threshold value 來過濾可能無法最即時的處理事件而造成最大的損失。所以我們提出一個系統，將感測器網路結合影像裝置的即時影像監控系統(real-time video surveillance system with sensor network)。這套系統其主要目的是:在一個建築物當中，當有事件發生時，經由感測器網路回報和攝影機的拍攝，可以即時掌握事件的狀態。如此一來，得到的資訊不只是回傳的數值，還包括可供判斷的影像，讓使用者可以快速的判斷並處理事件。事件偵測再加上即時的判斷，讓系統對事件的掌控更新完全。而我們提出的系統，是以 MICAZ mote 所組成的感測器網路做為回報系統，結合攝影機而成的。因為攝影機鏡頭可以擷取到的影像範圍大，而且鏡頭還可以上下左右調整，可視範圍比不能動的 CMOS sensor 大了非常多，最重要的是只要幾台就可以涵蓋整個範圍而不會有死角的問題。因此不但具有無線感測器網路即時回報事件發生的優點，還能夠快速擷取適當影像，提供管理者足夠的資料，來做出適當的應變措施。

One goal of surveillance systems is to collect information about the behavior and position of interested targets in sensing environments. These systems can find applications in fire emergency, security, smart home and agriculture. Recently, surveillance systems combining wireless sensor networks with inexpensive web cameras or high quality Pan-Tilt-Zoom (PTZ) cameras have become more and more popular. In traditional video surveillance systems, a number of video cameras are required in order to achieve a desirable system performance. Another shortcoming is that it is not easy to adapt to environmental variations. In this paper, we proposed and implemented an integrated real time video surveillance system consisting of a large number of low cost sensors with a few wireless video cameras. The system allows a group of cooperating sensor devices to detect and track the positions of mobile objects and to report the results to sink nodes in a sensing environment. Then the sink nodes can control the video cameras for taking images of these events to display the present situations. We also propose a camera control scheme to better cover the sensing area and to support coverage allocation of the video cameras. We have implemented the proposed system with 16 sensor nodes and two PTZ wireless video cameras to evaluate the system performance. The result shows that our surveillance system is adaptable to various environments and is capable of providing real time information of the monitored environment

第一章 簡 介……………………………………………………………………1
第二章 網路模型…………………………………………………………………7
第三章 系統設計…………………………………………………………………10
第四章 系統實作…………………………………………………………………14
第五章 效能評估…………………………………………………………………16
第六章 結 論……………………………………………………………………17

[1] Crossbow. MOTE-KIT2400 - MICAz Developers Kit, http://www.xbow.com, 2004.
[2] Deluge-TinyOS Network Programming http://www.cs.berkeley.edu/ jwhui/research/deluge/
[3] J. Hill, R. Szewczyk, A. Woo, S. Hollar, D. E. Culler, and K. S. J. Pister. System Architecture Directions for Networked Sensors. In Proc. of Architectural Support for Programming Languages and Operating Systems (ASPLOS), pages 93V104, 2000.
[4] Kanoun. O, Trankler. H.-R; Sensor Technology Advances and Future Trends, Instrumentation and Measurement, IEEE Transactions on Volume 53, Issue 6, Dec. 2004 Page(s):1497 – 1501
[5] Trankler. H.-R, Kanoun. O; Recent Advances in Sensor Technology ,Instrumentation and Measurement Technology Conference, 2001. IMTC 2001. Proceedings of the 18th IEEE Volume 1, 21-23 May 2001 Page(s):309 - 316 vol.1
[6] Cote, G.L., Lec, R.M., Pishko, M.V.;Emerging biomedical sensing technologies
and their applications, Sensors Journal, IEEE Volume 3, Issue 3, June 2003 Page(s):251 - 266
[7] Widya, I.; van Halteren, A.; Jones, V.; Bults, R.; Konstantas, D.; Vierhout, P.; Peuscher, J.;Telematic requirements for a mobile and wireless healthcare system derived from enterprise models ,Telecommunications, 2003. ConTEL 2003. Proceedings of the 7th International Conference on Volume 2, 11-13 June 2003 Page(s):527 - 534 vol.2
[8] Vipul Singhvi, Andreas Krause, Carlos Guestrin, James H. Garrett, H. Scott Matthews,Intelligent light control using sensor networks , November 2005 Proceedings of the 3rd international conference on Embedded networked sensor systems SenSys ’05
[9] Murat Demirbas, Ken Yian Chow, Chieh Shyan Wan;Internet-Sensor Integration for Habitat Monitoring Proceedings of the 2006 International Symposium on on World of Wireless, Mobile and Multimedia Networks WOWMOM ’06
[10] J. Burrell, T. Brooke, and R. Beckwith. Vineyard computing: sensor networks in agricultural production. IEEE Pervasive Computing, 3(1):38V45, 2004.
[11] Younis, O.; Fahmy, S.; Santi, P.; Robust communications for sensor networks in hostile environments. Quality of Service, 2004. IWQOS 2004. Twelfth IEEE International Workshop on 7-9 June 2004 Page(s):10 - 19
[12] Xun Wang; Wenjun Gu; Chellappan, S.; Schosek, K.; Dong Xuan;Lifetime optimization of sensor networks under physical attacks . Communications, 2005. ICC 2005. 2005 IEEE International Conference on Volume 5, 16-20 May 2005 Page(s):3295 - 3301 Vol. 5
[13] Kui Wu; Chong Liu; King, V.;Very low cost sensor localization for hostile environments . Communications, 2005. ICC 2005. 2005 IEEE International Conference on Volume 5, 16-20 May 2005 Page(s):3197 - 3201 Vol. 5
[14] Bramberger, M.; Doblander, A.; Maier, A.; Rinner, B.; Schwabach, H.;Distributed embedded smart cameras for surveillance applications, Computer Volume 39, Issue 2, Feb. 2006 Page(s):68 – 75
[15] Bakhtari, A.; Naish, M.D.; Eskandari, M.; Croft, E.A.; Benhabib, B.;Active-Vision-Based Multisensor Surveillance- An Implementation; Systems, Man and Cybernetics, Part C, IEEE Transactions on Volume 36, Issue 5, Sept. 2006 Page(s):668 – 680
[16] Petrushin, V.A.; Gang Wei; Shakil, O.; Roqueiro, D.; Gershman, V.;Multiple-Sensor Indoor Surveillance System , Computer and Robot Vision, 2006. The 3rd Canadian Conference on 07-09 June 2006 Page(s):40 - 40
[17] Snidaro, L.; Foresti, G.L.;A multi-camera approach to sensor evaluation in video surveillance; Image Processing, 2005. ICIP 2005. IEEE International Conference on Volume 1, 11-14 Sept. 2005 Page(s):I - 1101- 4
[18] Micheloni, C.; Salvador, E.; Bigaran, F.; Foresti, G.L.;An integrated surveillance system for outdoor security ; Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2005. 15-16 Sept. 2005 Page(s):480 - 485
[19] Vijay Kumar; Rus, D.; Sanjiv Singh; Robot and sensor networks for first responders ;Pervasive Computing, IEEE Volume 3, Issue 4, Oct-Dec 2004 Page(s):24 – 33
[20] Yu-Chee Tseng; You-Chiun Wang; Kai-Yang Cheng; An integrated mobile surveillance and wireless sensor (iMouse) system and its detection delay analysis ;Proceedings of the 8th ACM international symposium on Modeling, analysis and simulation of wireless and mobile systems MSWiM ’05
[21] Micheloni, C.; Salvador, E.; Bigaran, F.; Foresti, G.L.;An integrated surveillance system for outdoor security ; Proceedings. IEEE Conference on Advanced Video and Signal Based Surveillance, 2005. 15-16 Sept. 2005 Page(s):480 - 485
[22] Bakhtari, A.; Naish, M.D.; Eskandari, M.; Croft, E.A.; Benhabib, B.;Active-vision-based multisensor surveillance - an implementation; Systems, Man and Cybernetics, Part C, IEEE Transactions on Volume 36, Issue 5, Sept. 2006 Page(s):668 - 680
[23] Qiong Liu; Don Kimber; Jonathan Foote; Lynn Wilcox; John Boreczky; FlySPEC: a multi-user video camera system with hybrid human and automatic control; December 2002 ;Proceedings of the tenth ACM international conference on Multimedia [24] X. Ji; H. Zha; J. J. Metzner; and G. Kesidis; Dynamic cluster structure for object detection and tracking in wireless ad-hoc sensor networks. In
IEEE Intl Conf. on Communications, pages 3807V3811, 2004.
[25] A.S. Sekmen; M. Wilkes; and K. Kawamura.; An application of passive human-robot interaction: Human-tracking based on attention distraction. IEEE Transaction on Systems, Man, and Cybernetics, 32(2):248V259, March 2002