T. Nguyen, Viet Khang Tran, Tan Duy Nguyen, N. Le, M. Le
{"title":"IoT-Based Smart Plug-In Device for Home Energy Management System","authors":"T. Nguyen, Viet Khang Tran, Tan Duy Nguyen, N. Le, M. Le","doi":"10.1109/GTSD.2018.8595615","DOIUrl":null,"url":null,"abstract":"Identification of in-home electrical appliances is an important task for the home energy management system in order to surveillance and control the home electrical usage. In this paper, we propose a Smart Plug device prototype that can that can recognize the type of electric appliances according to the measured voltage, current and power factor. Our device includes two modules. The power interface with the appliance is based on the voltage and current sensors connected to the Arduino Uno. The processing module uses the machine learning approaches such as neural network or K Nearest Neighborhood (KNN) to recognize the electrical appliances plugged into in real time. All of the recognized in-home appliances datasets then can be uploaded to the home energy management system for further applications. For instance, the system gives a warning message to the user when the appliance has an unusual power factor or an outlier in power consumption. This warning is sent via email or mobile phone. Compare to other commercial smart plug devices, our device has more functionalities at a low price.","PeriodicalId":344653,"journal":{"name":"2018 4th International Conference on Green Technology and Sustainable Development (GTSD)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 4th International Conference on Green Technology and Sustainable Development (GTSD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GTSD.2018.8595615","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
Identification of in-home electrical appliances is an important task for the home energy management system in order to surveillance and control the home electrical usage. In this paper, we propose a Smart Plug device prototype that can that can recognize the type of electric appliances according to the measured voltage, current and power factor. Our device includes two modules. The power interface with the appliance is based on the voltage and current sensors connected to the Arduino Uno. The processing module uses the machine learning approaches such as neural network or K Nearest Neighborhood (KNN) to recognize the electrical appliances plugged into in real time. All of the recognized in-home appliances datasets then can be uploaded to the home energy management system for further applications. For instance, the system gives a warning message to the user when the appliance has an unusual power factor or an outlier in power consumption. This warning is sent via email or mobile phone. Compare to other commercial smart plug devices, our device has more functionalities at a low price.