Evidence map›Paper›PMID 37448035›Full record

ReviewSensors (Basel, Switzerland)2023

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

Bin Yang, Shuang Yang, Xin Zhu, Min Qi, He Li, Zhihan Lv, Xiaogang Cheng, Faming Wang

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed.

  1. Review
  2. Microbial community assembly in the fermentation of cigar tobacco leaves.Frontiers in bioengineering and biotechnology · 2026
    Review
  3. Review
  4. Article
  5. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Bin YangSchool of Energy and Safety Engineering, Tianjin Chengjian University, Tianjin 300384, China.ORCID 0000-0003-4015-199X
Shuang YangSchool of Energy and Safety Engineering, Tianjin Chengjian University, Tianjin 300384, China.
Xin ZhuSchool of Energy and Safety Engineering, Tianjin Chengjian University, Tianjin 300384, China.ORCID 0000-0002-7671-323X
Min QiSchool of Energy and Safety Engineering, Tianjin Chengjian University, Tianjin 300384, China.
He LiSchool of Energy and Safety Engineering, Tianjin Chengjian University, Tianjin 300384, China.
Zhihan LvDepartment of Game Design, Faculty of Arts, Uppsala University, SE-62167 Uppsala, Sweden.
Xiaogang ChengCollege of Telecommunications and Information Engineering, Nanjing University of Posts and Telecommunications, Nanjing 210042, China.
Faming WangDepartment of Biosystems, KU Leuven, 3001 Leuven, Belgium.ORCID 0000-0002-2945-4685

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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.

Indexed as

Artificial IntelligenceComputersTechnologybehavior patternscomputer visionequipment health monitoringfault diagnosis and detectionnon-contact measurementremote sensing

Identifiers

PMID37448035
PMCPMC10346506

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.