Computer Vision Technology for Monitoring of Indoor and Outdoor Environments and HVAC Equipment: A Review.

Journal: Sensors (Basel, Switzerland)
Published Date: Jul 6, 2023

Abstract

Artificial intelligence technologies such as computer vision (CV), machine learning, Internet of Things (IoT), and robotics have advanced rapidly in recent years. The new technologies provide non-contact measurements in three areas: indoor environmental monitoring, outdoor environ-mental monitoring, and equipment monitoring. This paper summarizes the specific applications of non-contact measurement based on infrared images and visible images in the areas of personnel skin temperature, position posture, the urban physical environment, building construction safety, and equipment operation status. At the same time, the challenges and opportunities associated with the application of CV technology are anticipated.

Authors

  • Bin Yang
    School of Control Science and Engineering, Dalian University of Technology, Dalian 116024, PR China. Electronic address: yangbin@dlut.edu.cn.
  • Shuang Yang
    Key Laboratory of Grain and Oil Processing and Food Safety of Sichuan Province, College of Food and Bioengineering, Xihua University Chengdu 610039 China xingyage1@163.com.
  • Xin Zhu
    Biomedical Information Engineering Lab, The University of Aizu, Fukushima, Japan.
  • Min Qi
    Zhejiang Key Laboratory of Excited-State Energy Conversion and Energy Storage, Institute of Analytical Chemistry, Department of Chemistry, Zhejiang University, Hangzhou 310058, China.
  • He Li
    National Soybean Processing Industry Technology Innovation Center, Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Technology and Business University Beijing 100048 China lihe@btbu.edu.cn liuxinqi@btbu.edu.cn.
  • Zhihan Lv
    FIVAN, Valencia, Spain. lvzhihan@gmail.com.
  • Xiaogang Cheng
    College of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210042, China.
  • Faming Wang
    Department of Biosystems, KU Leuven, 3001 Leuven, Belgium.

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