{"title":"智能家居环境感知智能控制系统","authors":"Minbo Li, Yu Wu","doi":"10.1177/15501329221082030","DOIUrl":null,"url":null,"abstract":"In recent years, the rapid development of Internet of Things smart hardware has increased the demand for intelligent control of devices, mainly in the smart home industry. The framework to solve the problem of equipment intelligent control is studied. The advantages and disadvantages of existing context modeling strategies are analyzed. According to the characteristics of household context activities, combined with the design principles of graph databases, a new context modeling method based on object and attribute graph is proposed, which is suitable for Internet of Things scenarios with limited resources. Rule control, mode control, and voice control approaches of smart home interaction are designed. An inference engine is used to map the data of context awareness to the Internet of Things control services that executed automatic control of the system, and a framework of smart control system based on context awareness of Internet of Things is proposed. Considering the behavior habits of users, the concept of user preference is introduced to provide more personalized services. Performance tests with simulated data show that the new context modeling method has a faster system response time than the ontology modeling control mode.","PeriodicalId":50327,"journal":{"name":"International Journal of Distributed Sensor Networks","volume":" ","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2022-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":"{\"title\":\"Intelligent control system of smart home for context awareness\",\"authors\":\"Minbo Li, Yu Wu\",\"doi\":\"10.1177/15501329221082030\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the rapid development of Internet of Things smart hardware has increased the demand for intelligent control of devices, mainly in the smart home industry. The framework to solve the problem of equipment intelligent control is studied. The advantages and disadvantages of existing context modeling strategies are analyzed. According to the characteristics of household context activities, combined with the design principles of graph databases, a new context modeling method based on object and attribute graph is proposed, which is suitable for Internet of Things scenarios with limited resources. Rule control, mode control, and voice control approaches of smart home interaction are designed. An inference engine is used to map the data of context awareness to the Internet of Things control services that executed automatic control of the system, and a framework of smart control system based on context awareness of Internet of Things is proposed. Considering the behavior habits of users, the concept of user preference is introduced to provide more personalized services. Performance tests with simulated data show that the new context modeling method has a faster system response time than the ontology modeling control mode.\",\"PeriodicalId\":50327,\"journal\":{\"name\":\"International Journal of Distributed Sensor Networks\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2022-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Distributed Sensor Networks\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://doi.org/10.1177/15501329221082030\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Distributed Sensor Networks","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1177/15501329221082030","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Intelligent control system of smart home for context awareness
In recent years, the rapid development of Internet of Things smart hardware has increased the demand for intelligent control of devices, mainly in the smart home industry. The framework to solve the problem of equipment intelligent control is studied. The advantages and disadvantages of existing context modeling strategies are analyzed. According to the characteristics of household context activities, combined with the design principles of graph databases, a new context modeling method based on object and attribute graph is proposed, which is suitable for Internet of Things scenarios with limited resources. Rule control, mode control, and voice control approaches of smart home interaction are designed. An inference engine is used to map the data of context awareness to the Internet of Things control services that executed automatic control of the system, and a framework of smart control system based on context awareness of Internet of Things is proposed. Considering the behavior habits of users, the concept of user preference is introduced to provide more personalized services. Performance tests with simulated data show that the new context modeling method has a faster system response time than the ontology modeling control mode.
期刊介绍:
International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.