D. Ramasubbu, Krishnamoorthy Baskaran, Grynberg Yann
{"title":"Intrusive Plug Management System Using Chatbots in Office Environments","authors":"D. Ramasubbu, Krishnamoorthy Baskaran, Grynberg Yann","doi":"10.1109/ACEPT.2018.8610869","DOIUrl":null,"url":null,"abstract":"“Only 44 percent of computers, 32 percent of monitors, and 25 percent of printers were turned off at night” [1], with energy efficient appliances employed in office environments, occupant’s energy-conscious behavior plays a vital role in monitoring the plug load. In an attempt to involve the occupants to the building’s energy management suite, a natural language-based plug management system is proposed. This article aims to develop a rule-based chatbot that helps users manage (schedule) their plugged-in appliances through smart plugs in an office environment. Considering the nature of the application and the accuracy of the intended operation, a rule-based chatbot is developed to schedule the smart plugs. It is developed using Python to be integrated with instant messaging application Slack.","PeriodicalId":296432,"journal":{"name":"2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 Asian Conference on Energy, Power and Transportation Electrification (ACEPT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ACEPT.2018.8610869","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
“Only 44 percent of computers, 32 percent of monitors, and 25 percent of printers were turned off at night” [1], with energy efficient appliances employed in office environments, occupant’s energy-conscious behavior plays a vital role in monitoring the plug load. In an attempt to involve the occupants to the building’s energy management suite, a natural language-based plug management system is proposed. This article aims to develop a rule-based chatbot that helps users manage (schedule) their plugged-in appliances through smart plugs in an office environment. Considering the nature of the application and the accuracy of the intended operation, a rule-based chatbot is developed to schedule the smart plugs. It is developed using Python to be integrated with instant messaging application Slack.