Smart detection of indoor occupant thermal state via infrared thermography, computer vision, and machine learning

نویسندگان

چکیده

The ability to measure occupants’ thermal state in real time will enable major advances the control of air conditioning systems. This study proposes predicting occupant by a combination infrared thermography, computer vision, and machine learning. approach (1) uses cheek, nose, hand temperatures because they are least subject blockage hair, glasses, clothing; (2) measures distribution skin within geometrically defined sub-areas face hand; (3) temperature differences between these areas eliminate effects calibration drift that unavoidable (TIR) cameras. Two series tests were conducted, respectively an outdoor carport indoor environmental chamber, collecting total 48,422 sets using TIR camera computer-vision technology, coupled with 715 subjective responses sensations. To predict state, Random Forest classification models built either absolute (the maximum median cheek segments, central spot on nose), or intra- inter-segment cheeks, hands, nose. These measurements found accurately state. Using for hand, predicts accuracy 92–96%. only from nose is 83% accurate; adding increases 96%.

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Machine Learning in Computer Vision

No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser ...

متن کامل

Machine Learning in Computer Vision

In this editorial we brie ̄ y discuss interaction between two important areas of arti® cial intelligence: computer vision (CV ) and machine learning (ML ). Although the two ® elds have a long-standing tradition and can be considered technologically mature, past research in applying ML techniques to CV problems has been limited. After a short introduction in the ® elds of computer vision and mach...

متن کامل

Machine Learning and Computer Vision @ Cvprlab-uniparthenope

The report includes some recent research activities carried out by the Computer Vision and Pattern Recognition group of the Department of Science and Technology, University Parthenope of Naples (http://cvprlab.uniparthenope.it). The activities cover different aspects related to Machine Learning and Computer Vision and are carried out in the context of a variety of applied projects, where result...

متن کامل

Computer vision and machine learning for archaeology

Until now, computer vision and machine learning techniques barely contributed to the archaeological domain. The use of these techniques can support archaeologists in their assessment and classification of archaeological finds. The paper illustrates the use of computer vision techniques for archaeology with two examples: (1) a content-based image retrieval system for historical glass and (2) an ...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: Building and Environment

سال: 2023

ISSN: ['0360-1323', '1873-684X']

DOI: https://doi.org/10.1016/j.buildenv.2022.109811