臺灣博碩士論文加值系統

隨著科技發展日新月異，智慧家庭(Smart Homes)也正快速的興起，各家廠商也推出一些智慧型家電使居家生活更加安全、舒適與便利，但如何整合家庭中異質性的設備並依據使用者的需求及喜好提供合適的服務，便成為一個很重要的課題。本論文加入了情境感知系統的推理技術建構在服務導向的OSGi平台上，情境感知系統透過OSGi平台便能方便的溝通與運作。情境感知系統應具有將情境資訊做有效的歸類和儲存之能力，並依據情境資訊推論出使用者的行為，提供合適的服務，本研究利用本體論建構情境模型，因為本體論具有豐富的資訊表達能力。此外，在情境推論中採用案例式推理，此推論是參考使用者過去之歷史資訊做為推論依據，隨著案例的增加系統的推論能力越強也越貼近使用者。了解使用者之行為後，本研究也建構了個人化本體論來表達使用者對於服務的習慣與偏好，並利個人化本體論來選擇出適合的服務，最後透過OSGi平台提供服務來滿足使用者的需求。本研究的領域為智慧型空間系統的發展，目標為一般家庭，系統會提供居家的服務，如：空調、音樂、燈光、鈴聲...等，系統會整合這些服務資訊並在合適的時間提供合適的服務給使用者。

With the growing popularity of smart homes, companies provide their own home devices to make daily life more comfortable and convenient. Without the open standard, communication between different devices and platforms has become an issue. Therefore, how to combine these devices for meeting user requirements is challenging. In this thesis, I have developed a context-aware system which using ontology and a case base. I integrated the context-aware system with the OSGi platform. The context-aware system can operate home devices easily through the OSGi platform. The main advantage of using ontology is to express machine-interpretable definitions on basic concept and interrelation that enable it to reuse the constructed context models. Besides, I use case-based reasoning (CBR) as the reasoning method to know what behaviors a user engages in. The CBR mechanism not only reuses previous cases, but also stores new cases for future reference. In addition, I also constructed personal ontology that represents user’s preferences and the system will use this information to choose the suitable service for the user. Finally, the context-aware system will operate home devices by using the OSGi platform to provide suitable services to users.

摘 要 1
第一章 緒論 7
1.1背景 8
1.2動機與目的 8
1.3論文架構 9
第二章 相關文獻探討 10
2.1智慧家庭 10
2.2開放性的服務平台(Open Service Gateway initiative：OSGi) 12
2.2.1 OSGi架構 12
2.2.2 OSGi的優點 14
2.3 情境感知系統 15
2.3.1 情境感知的定義 15
2.3.2 情境模型 16
2.3.3 情境推理 21
2.4相關研究 24
2.5總結 33
第三章 研究方法 34
3.1情境模型的建構 34
3.1.1概念的分類 35
3.1.2小節 42
3.2 案例式推理於使用者的行為推論 44
3.2.1 案例表示 45
3.2.2 案例擷取 46
3.2.3 案例使用 49
3.2.4 案例修正 50
3.2.5案例保留 51
3.3建構Personal Ontology 51
3.3.1概念分類 51
3.3.2概念之間的關係 54
3.3.3 Personal Ontology建構流程 56
3.3.4應用例子 58
3.4 信賴度擷取 60
3.4.1 模糊變數與模糊集合 60
3.4.2模糊規則與解模糊化方法 62
第四章 系統實作 63
4.1 OSGi開發平台與服務包開發 63
4.1.1 OSGi framework平台 63
4.1.2 服務包開發範例 65
4.2系統架構 67
4.3各個元件的實現 71
4.3.1 Sensor Platform 71
4.3.2 Sensor Information 72
4.3.3 Sensor Receive Bundle 73
4.3.4 Behavior Reasoner Bundle 75
4.3.5 Previous Case 77
4.3.6 User Profiles 78
4.3.7 Device Manager Bundle 83
4.3.8 UPnP Base Driver Bundle 85
4.3.9 Interface 87
4.4 實驗劇本與結果 89
4.4.1劇本1：行為推論 89
4.4.2劇本2：服務推論 97
第五章 結論與未來展望 103
參考文獻 106

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