{"title":"A Smart Edge-Based Energy-Efficient Green Home","authors":"Kamya Johar, B. Ramesh, Ramneek Kalra","doi":"10.1109/CCGE50943.2021.9776383","DOIUrl":null,"url":null,"abstract":"With the prediction of billions and trillions connected devices in the upcoming decades, researchers are exploring daily about the ways of making technology as a companion to help consumers/users with better picture of their appliances/products at their homes. With the upcoming fear of controlling and managing appliances as data complexity and usage of same will be increased many folds, there's a need for smarter and green home for everyone in the society. In this paper, authors are focusing to provide a proposed framework for Solar powered home and grid powered home with Edge-based approach to save the electricity consumption. This is reflected by using Machine Learning Regression algorithm over the battery usage and giving required notification through an Android Application to the consumer/home user. The proposed model gives insightful further opportunities to researchers to work on energy-efficient based green home infrastructure.","PeriodicalId":130452,"journal":{"name":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 International Conference on Computing, Communication and Green Engineering (CCGE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGE50943.2021.9776383","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
With the prediction of billions and trillions connected devices in the upcoming decades, researchers are exploring daily about the ways of making technology as a companion to help consumers/users with better picture of their appliances/products at their homes. With the upcoming fear of controlling and managing appliances as data complexity and usage of same will be increased many folds, there's a need for smarter and green home for everyone in the society. In this paper, authors are focusing to provide a proposed framework for Solar powered home and grid powered home with Edge-based approach to save the electricity consumption. This is reflected by using Machine Learning Regression algorithm over the battery usage and giving required notification through an Android Application to the consumer/home user. The proposed model gives insightful further opportunities to researchers to work on energy-efficient based green home infrastructure.