Robotics & Machine Learning Daily News2024,Issue(Jun.3) :12-13.

Studies from Technical University Munich (TU Munich) Have Provided New Data on M achine Learning (Occupancy Modeling On Non-intrusive Indoor Environmental Data T hrough Machine Learning)

慕尼黑工业大学(慕尼黑理工大学)的研究提供了机器学习的新数据(非侵入性室内环境数据占用建模与机器学习)

Robotics & Machine Learning Daily News2024,Issue(Jun.3) :12-13.

Studies from Technical University Munich (TU Munich) Have Provided New Data on M achine Learning (Occupancy Modeling On Non-intrusive Indoor Environmental Data T hrough Machine Learning)

慕尼黑工业大学(慕尼黑理工大学)的研究提供了机器学习的新数据(非侵入性室内环境数据占用建模与机器学习)

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摘要

机器人与机器学习每日新闻的一位新闻记者兼新闻编辑-机器学习的最新研究结果已经发表。根据NewsRx记者从德国慕尼黑发回的消息,研究表明:“建筑物内能耗的主要驱动因素是居住者。非侵入性物联网(IoT)技术可以在保护建筑物居住者隐私的同时,检测居住者的居住情况并优化能源性能。”这项研究的财政支持来自德国联邦宗教事务和气候行动部(BMWK)。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Current study results on Machine Learn ing have been published. According to news originating from Munich, Germany, by NewsRx correspondents, research stated, “The primary drivers of energy consumpti on within buildings are the occupants. Non-intrusive Internet of Things (IoT) te chnology can be utilized to detect occupancy and optimize energy performance whi le preserving the privacy of building occupants.” Financial support for this research came from German Federal Ministry for Econom ic Affairs and Climate Action (BMWK).

Key words

Munich/Germany/Europe/Cyborgs/Emergi ng Technologies/Machine Learning/Technical University Munich (TU Munich)

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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