State-of-the-art Activity Recognition and Prediction Techniques Applicable to the Home Energy Management System

Hossein Nourollahi Hokmabad, J. Belikov, Oleksander Husev, D. Vinnikov
{"title":"State-of-the-art Activity Recognition and Prediction Techniques Applicable to the Home Energy Management System","authors":"Hossein Nourollahi Hokmabad, J. Belikov, Oleksander Husev, D. Vinnikov","doi":"10.1109/energycon53164.2022.9830154","DOIUrl":null,"url":null,"abstract":"Owing to the tendency to convert ordinary homes to smart ones, there are novel opportunities for home energy management systems to exploit the binary and analog sensors collected information to enhance their performance. Having accurate forecasting about the behavior of house inhabitants, and their preferences could help the system be more efficient and reliable. In this paper, some state-of-the-art activity recognition and prediction techniques are reviewed and we introduce a conceptual platform for interactive collaboration between smart homes and energy management systems.","PeriodicalId":106388,"journal":{"name":"2022 IEEE 7th International Energy Conference (ENERGYCON)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 7th International Energy Conference (ENERGYCON)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/energycon53164.2022.9830154","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

Owing to the tendency to convert ordinary homes to smart ones, there are novel opportunities for home energy management systems to exploit the binary and analog sensors collected information to enhance their performance. Having accurate forecasting about the behavior of house inhabitants, and their preferences could help the system be more efficient and reliable. In this paper, some state-of-the-art activity recognition and prediction techniques are reviewed and we introduce a conceptual platform for interactive collaboration between smart homes and energy management systems.
适用于家庭能源管理系统的最先进的活动识别和预测技术
由于将普通家庭转换为智能家庭的趋势,家庭能源管理系统有新的机会利用二进制和模拟传感器收集的信息来提高其性能。准确预测房屋居民的行为和偏好,有助于提高系统的效率和可靠性。在本文中,我们回顾了一些最先进的活动识别和预测技术,并介绍了智能家居和能源管理系统之间交互协作的概念平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信