{"title":"节能智能家居知识库","authors":"M. Kofler, W. Kastner","doi":"10.1109/ENERGYCON.2010.5771803","DOIUrl":null,"url":null,"abstract":"With the rise of energy costs for heating, cooling and ventilation and an increasing amount of energy consuming appliances (e.g. white goods, consumer electronic devices), hidden saving potentials can be found in numerous areas of a modern smart home. To manually enforce an energy-saving policy is a tedious procedure which needs the user to be aware of all kinds of equipment as well as building information. Especially the thermal properties of a building are generally unknown to the occupant of a residential home. Information already collected in the architecture, engineering and construction (AEC) industry is often not considered and neglected as soon as the project is finished. Reusing this knowledge to optimize energy consumption seems natural, as nowadays the information is often already available in a structured form as building information model (BIM). The more knowledge is available about building properties of the smart home, the better the system can act as an autonomous caretaker in order to create an environmental-friendly and comfortable ambience. Therefore, the transition of information from a building information model into a more intelligent knowledge base as foundation of an autonomous automation system is desirable.","PeriodicalId":386008,"journal":{"name":"2010 IEEE International Energy Conference","volume":"71 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":"{\"title\":\"A knowledge base for energy-efficient smart homes\",\"authors\":\"M. Kofler, W. Kastner\",\"doi\":\"10.1109/ENERGYCON.2010.5771803\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"With the rise of energy costs for heating, cooling and ventilation and an increasing amount of energy consuming appliances (e.g. white goods, consumer electronic devices), hidden saving potentials can be found in numerous areas of a modern smart home. To manually enforce an energy-saving policy is a tedious procedure which needs the user to be aware of all kinds of equipment as well as building information. Especially the thermal properties of a building are generally unknown to the occupant of a residential home. Information already collected in the architecture, engineering and construction (AEC) industry is often not considered and neglected as soon as the project is finished. Reusing this knowledge to optimize energy consumption seems natural, as nowadays the information is often already available in a structured form as building information model (BIM). The more knowledge is available about building properties of the smart home, the better the system can act as an autonomous caretaker in order to create an environmental-friendly and comfortable ambience. Therefore, the transition of information from a building information model into a more intelligent knowledge base as foundation of an autonomous automation system is desirable.\",\"PeriodicalId\":386008,\"journal\":{\"name\":\"2010 IEEE International Energy Conference\",\"volume\":\"71 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"20\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Energy Conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ENERGYCON.2010.5771803\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENERGYCON.2010.5771803","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
With the rise of energy costs for heating, cooling and ventilation and an increasing amount of energy consuming appliances (e.g. white goods, consumer electronic devices), hidden saving potentials can be found in numerous areas of a modern smart home. To manually enforce an energy-saving policy is a tedious procedure which needs the user to be aware of all kinds of equipment as well as building information. Especially the thermal properties of a building are generally unknown to the occupant of a residential home. Information already collected in the architecture, engineering and construction (AEC) industry is often not considered and neglected as soon as the project is finished. Reusing this knowledge to optimize energy consumption seems natural, as nowadays the information is often already available in a structured form as building information model (BIM). The more knowledge is available about building properties of the smart home, the better the system can act as an autonomous caretaker in order to create an environmental-friendly and comfortable ambience. Therefore, the transition of information from a building information model into a more intelligent knowledge base as foundation of an autonomous automation system is desirable.