節能減碳一直是世界各國所關注的議題，再加上世界能源價格上漲，各國面臨經濟危機的情況下，如何有效的節省能源以及減少費用支出是目前大家所關注的問題。從家庭中節省電力似乎是常見的方法，如果家庭能改變用電習慣，對於家庭用電支出將能大大改善，但還是有許多的家庭沒有依照節電的行為來實行，其原因可能包括此節電規則是否方便去實行、缺乏行動力、以及規則使日常行為變的困難等一系列障礙，因此人工智慧及自動化的技術就顯得格外重要，故本研究提出以本體論(Ontology)為基礎之節電本體論模型，並使用其延伸語言SWRL(Semantic Web Rule Language)做為節電規則的描述，建立往後人工智慧所需的知識庫。 本研究首先收集國內外各種節電知識並分析出各個規則中的參數，在節電本體論模型建立上先以UML(Unified Modeling Language)分析設計出電器、房間、環境和節電規則四種類別的屬性以及定義各個類別之間的關聯性，再轉換成本體論模型，其次，將分析過後的節電規則以SWRL來描述，輔助節電本體論模型做邏輯上的判斷，最後透過Pellet與SQWRL將結果推論出來。本研究也模擬一個情境來進行測試驗證，測試結果顯示此模型與SWRL規則能正確判斷出不符合節電規則的電器。透過本研究所設計之節電本體論模型可以讓使用者方便管理家中電器，得知電器的位置、狀態、用電情況。 ;Carbon reduction has been the subject of concern to the world. Because of the energy price fluctuates significantly and many countries face economic crisis, it will be an important issue to conserve the energy and reduce expense. Saving energy from the family seems to be a common method. It will be greatly improved for household electricity consumption when the family can change the habits about using home appliances. But there are still many families do not follow the energy-saving behavior. The reason may include a series of obstacles such as whether the energy-saving rules are easy to implement, lack of execution, and the difficulties of the rules making the daily behavior become difficult. Therefore artificial intelligence and automation technology is particularly important. In this regard, this paper attempts to establish an energy-saving ontology model based on Ontology, and uses its extended language SWRL (Semantic Web Rule Language) for describing the rules of energy-saving to establish the knowledge base. In this paper, first we collect the knowledge of energy-saving both at domestic and abroad and analyze the parameters in each rule. We design the properties of appliances, room, environment and energy-saving rules by UML (Unified Modeling Language) and define the association between each properties, then transform it into the ontology model. Secondly, we use SWRL to describe the energy saving rules which we analyzed previously. Finally, the results are deduced by Pellet and SQWRL. This study also simulates a situation for testing and verification. The test results show that this model and SWRL rules can correctly determine the appliances that don’t conform the energy-saving rules. Through the study of the energy-saving ontology model designed to allow users to easily manage the home appliances, that electrical location, status, electricity situation. The energy-saving ontology model designed by this study allows users to easily manage the electrical appliances at home, and know the location, status and power consumption of the appliances.
