過去資訊系統所有資訊流程是固定的,若面對環境的變化而需要考量新的因素時, 勢必要修改原來系統程式,造成系統建置及維護上的負擔與不便。 因此,加入環境感知因子的資訊系統, 將成為未來軟體的趨勢。由於環境感知因子隨時在改變,一個具有環境感知能力的系統,必須可以不斷偵測到這些環境因子的變化,並且能根據實際情況主動地提供服務給使用者,讓使用者在無形之中享受到系統所提供的服務。 本研究結合環境感知技術、知識本體描述 (ontology)、及人工智慧規劃(AI planning),輔以多代理人技術來達成環境感知服務整合之應用(context-aware service integration)。 我們採用多代理人架構, 結合語意網(Semantic Web)及規則式推論技術, 來建制環境感知推論機制。人工智慧規劃方法可以協助系統在眾多的服務之中找尋到合適的軟體來提供服務;當使用者所需的服務過於複雜時,也可結合數個小型服務來達到最後的目的。
Ubiquitous computing technology plays a key role for providing context information and makes context-aware services can be delivered in a smart space. As the contextual information changing rapidly, context resources must continuously be gathered from sensors, mobile devices, and personal information softwares. Consequently, a context-aware system must be aware of such environment changes so that it can provide adaptive and proactive services to the users. In addition, all the inner computing operations have to be hidden behind the users. This research proposes an approach to achieve the Context-aware Service Integration, which is implemented in JADE agent platform and utilizes Semantic Web technologies, to analyze the ambient contexts and contrive service plans. We integrated ontology and rule-based reasoning to automatically infer high-level contexts and deduce a goal of context-aware services. An AI planner decomposes complex services and establishes the execution plan. Agents perform the specified task to accomplish the service. Some scenarios (context-aware pill reminder, smart alarm clock, and smart furniture) demonstrate the detail functions of each agent and shows how these agents incorporate with each others.