Evidence map›Paper›PMID 38894259›Full record

ArticleSensors (Basel, Switzerland)2024

Development and Validation of Low-Cost Indoor Air Quality Monitoring System for Swine Buildings.

Elanchezhian Arulmozhi, Anil Bhujel, Nibas Chandra Deb, Niraj Tamrakar, Myeong Yong Kang, Junghoo Kook, Dae Yeong Kang, Eun Wan Seo, Hyeon Tae Kim

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

9 authors.

Elanchezhian ArulmozhiDepartment of Bio-Systems Engineering, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.ORCID 0000-0003-2521-3769
Anil BhujelMinistry of Communication and Information Technology, Singhadurbar, Kathmandu 44600, Nepal.ORCID 0000-0002-0780-7216
Nibas Chandra DebDepartment of Bio-Systems Engineering, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.
Niraj TamrakarDepartment of Bio-Systems Engineering, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.ORCID 0009-0000-4693-6873
Myeong Yong KangDepartment of Smart Farm, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.
Junghoo KookDepartment of Smart Farm, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.
Dae Yeong KangDepartment of Smart Farm, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.
Eun Wan SeoDepartment of Smart Farm, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.
Hyeon Tae KimDepartment of Bio-Systems Engineering, Institute of Smart Farm, Gyeongsang National University, Jinju 52828, Republic of Korea.ORCID 0000-0003-0788-1536

Funding

Korea Institute of Planning and Evaluation for Technology in Food, Agriculture and Forestry (IPET) through Smart Farm Innovation Technology Development Program funded by Ministry of Agriculture, Food and Rural Affairs 421040-04
6 · The paper itself

Abstract

The optimal indoor environment is associated with comfortable temperatures along with favorable indoor air quality. One of the air pollutants, particulate matter (PM), is potentially harmful to animals and humans. Most farms have monitoring systems to identify other hazardous gases rather than PM due to the sensor cost. In recent decades, the application of environmental monitoring systems based on Internet of Things (IoT) devices that incorporate low-cost sensors has elevated extensively. The current study develops a low-cost air quality monitoring system for swine buildings based on Raspberry Pi single-board computers along with a sensor array. The system collects data using 11 types of environmental variables along with temperature, humidity, CO

Indexed as

Air Pollution, IndoorEnvironmental MonitoringParticulate MatterAir PollutantsAnimalsCarbon DioxideCarbon MonoxideHumansSwineAir PollutantsCarbon DioxideCarbon MonoxideParticulate Matterair qualityIoTRaspberry Pisensor networksswine building

Identifiers

PMID38894259
PMCPMC11174915

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.