以 OWL 與 SWRL來促進監控系統的維護性與彈性

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姓名

蘇友信(You-Sin Su) 查詢紙本館藏

畢業系所

資訊工程學系

論文名稱

以 OWL 與 SWRL來促進監控系統的維護性與彈性
(An OWL and SWRL Based Surveillance System that Facilitates Maintainability and Flexibility)

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摘要(中)

近年來監控系統導入 context-awareness 技術，描述受監控的環境，使系統可瞭解環境中的資訊，並提供有效的危險偵測。隨著系統日漸複雜，也面臨 maintainability 與 flexibility 的問題。本文提出以 web ontology language (OWL) 與 semantic web rule language (SWRL) 為基礎的監控系統，使用 OWL 描述環境資訊，並配合 Protégé 圖形化工具方便 user 維護，改進系統的 maintainability；使用 SWRL 描述環境中的危險狀況，降低 rules 與 rule engine 之間的 coupling，提昇系統選用 rule engine的 flexibility。

摘要(英)

Recently, surveillance systems have implemented context-awareness techniques to monitor context, and thus to provide efficient danger detection. As these systems get more and more complicated, they face maintainability and flexibility issues. Therefore, we propose a web ontology language (OWL) and semantic web rule language (SWRL) based surveillance system. By using OWL to describe context, user can use the Protégé graphical tool to maintain it. This improves system maintainability. Further, by using SWRL to describe rules of dangerous situation, the coupling between rules and rule engine is greatly reduced. This improves system flexibility in choosing alternative rule engines.

關鍵字(中)

★ 監控系統
★ 語意網規則語言
★ 網路知識本體語言

關鍵字(英)

★ Surveillance system
★ Web ontology language (OWL)
★ Semantic web rule language (SWRL)

論文目次

中文摘要 i
英文摘要 ii
誌謝 iii
目錄 iv
圖目錄 vi
表目錄 vii
一、 Introduction 1
二、 Related Work 2
三、 An OWL and SWRL Based Surveillance System 4
3-1 Architecture 4
3-2 Implementation 6
3-3 Inference Performance 7
四、 An Example 9
五、 Conclusions 11
References 12
附錄一 14
附錄二 18
附錄三 20
附錄四 24
附錄五 30
附錄六 40

參考文獻

[1] Stanford University. The Protégé Ontology Editor and Knowledge Acquisition System. [Online]. Available: http://protege.stanford.edu/.
[2] World Wide Web Consortium. OWL Web Ontology Language Overview. [Online]. Available: http://www.w3.org/TR/owl-features/.
[3] World Wide Web Consortium. SWRL: A Semantic Web Rule Language Combining OWL and RuleML. [Online]. Available: http://www.w3.org/Submission/SWRL/.
[4] Stanford University. SWRLTab. [Online]. Available: http://protege.cim3.net/cgi-bin/wiki.pl?SWRLTab.
[5] S. Thomas and L. P. Claudia, “A Context Modeling Survey,” in Workshop on Advanced Context Modeling, Reasoning and Management as Part of UbiComp 2004, The 6th International Conference on Ubiquitous Computing, Sept. 2004, pp.33-40.
[6] V. D. Shet, D. Harwood, L. S. Davis, “VidMAP: Video Monitoring of Activity with Prolog,” Advanced Video and Signal Based Surveillance, IEEE Conference Sept. 2005, p.224-229.
[7] K. Barbara and H. Rainer, “Event Detection for Video Surveillance Using an Expert System,” International Multimedia Conference, Proceeding of the 1st ACM workshop on Analysis and retrieval of events/actions and workflows in video streams. Oct. 2008, p.49-55
[8] L. W. Goix, M. Valla, L. Cerami and P. Falcarin, “Situation Inference for Mobile Users: a Rule Based Approach,” Mobile Data Management, International Conference, May 2007, p.299-303.
[9] E.J. Ko, H.J. Lee and J.W. Lee, “Ontology-Based Context Modeling and Reasoning for U-HealthCare,” IEICE Transactions on Information and Systems, 2007, Vol.e90-d(No.8).
[10] L. Snidaro, M. Belluz, G. L. Foresti, “Representing and Recognizing Complex Events in Surveillance Applications,” Advanced Video and Signal Based Surveillance, IEEE Conference Sept. 2007, p.493-498.
[11] Sandia National Laboratories, Jess, the Rule Engine for the Java Platform, [Online] Available: http://www.jessrules.com/.
[12] Research Center for Information Technologies (FZI), University of Karlsruhe and University of Manchester. KAON2: Ontology Management for the Semantic Web. [Online]. Available: http://kaon2.semanticweb.org/.
[13] Clark & Parsia, LLC. Pellet: The Open Source OWL DL Reasoner. [Online]. Available: http://clarkparsia.com/pellet/.
[14] Ontotext lab, Sirma group corp. OWLIM: OWL Semantic Repository. [Online]. Available: http://www.ontotext.com/owlim/.

指導教授

陳振炎(Jen-Yen Chen)

審核日期

2009-6-23

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