Ju-Kyoung Lee, Hyeong-Jun Kim, Suk Lee, J. Sohn, Hyun Hee Kim, K. Lee
{"title":"Estimation of metabolic rate for heart rate-based self-adaptive home appliance","authors":"Ju-Kyoung Lee, Hyeong-Jun Kim, Suk Lee, J. Sohn, Hyun Hee Kim, K. Lee","doi":"10.1109/GCCE.2014.7031329","DOIUrl":null,"url":null,"abstract":"In this study, we propose an algorithm that enables home appliances (air conditioners) and lighting fixtures to estimate real-time occupant metabolic rate based on their heart rate and provide better thermal conditions for occupants in smart home environment. Occupant metabolic rate refers to the heat production of occupants, and smart home appliances can use this data to control environment factors, including temperature and humidity for the optimal indoor climate. We also compared this heart rate-based method with the pre-existing location-based method in test bed to evaluate the effectiveness of both methods in estimating metabolic rate.","PeriodicalId":145771,"journal":{"name":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 3rd Global Conference on Consumer Electronics (GCCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/GCCE.2014.7031329","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this study, we propose an algorithm that enables home appliances (air conditioners) and lighting fixtures to estimate real-time occupant metabolic rate based on their heart rate and provide better thermal conditions for occupants in smart home environment. Occupant metabolic rate refers to the heat production of occupants, and smart home appliances can use this data to control environment factors, including temperature and humidity for the optimal indoor climate. We also compared this heart rate-based method with the pre-existing location-based method in test bed to evaluate the effectiveness of both methods in estimating metabolic rate.