連關鍵技術研究，Fully Scalable 之媒體編解碼系統設計，以及階層式叢集拓樸 設計繞徑協定。在整合方面，子計畫一與子計畫七針對可能的使用情境及網路技
設計以及篩選最佳LED組之演算法。前者可以用來提升發光效率，並可進一步改 利用一維光子晶體之白光LED，激發光效率及螢光粉轉換效率，俾可雙管齊下共 同提昇白光LED的發光效率。後者提出一從市售LED群組中篩選最佳LED組之演 算法，做為重建陽光之依據，可使日後我們所使用照明光可為更健康，另一方面 也可做情境照明，使我們有色彩的生活。做為智慧校園我們利用上述方法，在台 灣挑選適當的LED製做可變頻譜日光燈，並提供子計劃七照明情境模樣以達成較 舒適、方便與人性化之設計。
子計畫六為「普及資訊擷取架構」。子計畫六藉由子計畫七所提供之各種豐 富情境劇本以及多樣性的服務，建構出一個能為教師及學生提供智慧型服務的智 慧型教室，以研究情境感知系統的理論與實務，其核心技術是情境資訊的收集、
使用者所處情境的判斷以及週邊設備的驅動。在整合交流部分，子計畫六與子計 畫一、子計畫七之核心技術進行整合，以達成智慧型教室環境服務，整合成果曾 於2007年3月30日及2008年5月30日國科會「前瞻優質生活環境」專案暨「前瞻工 程科技之未來性產品概念設計」專案計畫聯合發表會進行實地展示。
子計畫七為「未來生活情境模擬與概念產品設計」。與前述六個子計畫偏向 工程技術的背景不同，子計畫七由本校設計學院主持，擬從人文角度出發，針對 各子計畫不同技術及研究方向，架構出未來智慧型校園可能的運用方式與模擬情 境，並提供給各子計畫作使用。子計畫七同時完成了介面的設計與實作，本介面 設計，是以拓蹼理論進行介面架構，並提出三種設計案，且用專家會議歸納出介 面設計之優缺點。子計劃七也曾架構出智慧型辦公室飲水機與智慧型校園飲水機 之設計，並於2007年3月30日及2008年5月30日國科會「前瞻優質生活環境」專案 暨「前瞻工程科技之未來性產品概念設計」專案計畫聯合發表會進行實地展示，
獲得廣泛之迴響。
總結而言，本整合型計畫成功研發智慧型校園環境之必要核心技術，並創造 出核心技術間的整合與實際應用。本計畫之研究成果，對於創造可兼顧安全、健 康、便利、舒適與永續之五大願景的校園生活，具有顯著之前瞻意義。本計畫結 案後，各研究團隊仍將繼續透過校內五年五百億之研究案，繼續為本校校園建立 創意智慧生活空間，營造出智慧生活與科技化的多元整合環境。
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可供推廣之研發成果資料表
□ 可申請專利 ▇ 可技術移轉 日期：97 年 10 月 18 日
國科會補助計畫
計畫名稱：智慧型校園生活環境研擬與建置 計畫主持人：陳金蓮
計畫編號：NSC94-2218-E011-011、NSC95-2218-E011-008、
NSC96-2218-E011-001 學門領域：EX
技術/創作名稱
高效能白光發光二極體發明人/創作人
蘇忠傑,陳仙瑋中文：
利用紫外光發光二極體激發多種瑩光粉混合層，以產生各種顏色或 白色光。因此可用來滿足應用需求之光譜並應用光子晶體隔絕與循 環使用未轉換可見光之紫外光以強化發光效率。
技術說明 英文：
A white LED was fabricated by using UV LED and multiple-phosphors to generate different color or white light. Therefore, this white LED can meet the spectra requirement of various applications. Photonic crystal has been used to block, recycle and convert the reflected UV light into luminosity.
可利用之產業 及 可開發之產品
LCD 背光源,照明,一般光源
技術特點
光譜可調式白光發光二極體光源推廣及運用的價值
取代傳統光源照明可供推廣之研發成果資料表
將 SQL 2005 資料庫中的 Analysis Server 內嵌(embedded)到應用 系統中作為推論的核心，建立了一個可以因應使用者及其位置、亮 度及時間的不同，動態控制電燈的開跟關、 選擇適當的投影片及 其上次播放的位置與麥克風因量大小的智慧型教室展示系統。本方 法著重於系統設計的方法論與將 Analysis Server 內嵌在應用系統 的實作方式。在實際應用時，可因需求而增加所欲控制的設備，只 要提供適當的介面與修改資料庫的表格結構即可。
技術說明
英文：
In this project we developed a smart space system which can dynamically adjust the settings of devices to fit the requirement of different users under different contexts (situations). We model the context management problem as a classification problem in data mining. In the training phase, we record the values of environmental variables,user’sID,user’slocationsand theexisting settingsof devices in a table. Then, we perform a training based on the data in the table to build a prediction model. In the prediction phase, we use the model to get suitable settings of the controlled devices. This research emphasizes on the methodology in building the prediction model and the way of embedding the Analysis Server of SQL 2005 into our application program. To build another smart space for a different application, one needs to provide suitable interface devices and control
In this project we developed a smart space system which can dynamically adjust the settings of devices to fit the requirement of different users under different contexts (situations). We model the context management problem as a classification problem in data mining. In the training phase, we record the values of environmental variables,user’sID,user’slocationsand theexisting settingsof devices in a table. Then, we perform a training based on the data in the table to build a prediction model. In the prediction phase, we use the model to get suitable settings of the controlled devices. This research emphasizes on the methodology in building the prediction model and the way of embedding the Analysis Server of SQL 2005 into our application program. To build another smart space for a different application, one needs to provide suitable interface devices and control