Evidence map›Paper›PMID 37539206›Full record

ReviewHeliyon2023

Internet of things based visualisation of effect of air pollution on the lungs using HEPA filters air cleaner.

Calorine Katushabe, Santhi Kumaran, Emmanuel Masabo

Open access · goldAbstract readReview
In one paragraph

Review in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.3field-weighted citation impact, top 43% of its field
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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 3 institutions in 3 countries.

Calorine KatushabeAfrican Center of Excellence in Internet of Things (ACEIoT), College of Science and Technology (C.S.T.), University of Rwanda, Nyarugenge, Kigali, P.O. Box 3900, Kigali, Rwanda.
Santhi KumaranSchool of ICT, Copperbelt University, KITWE, KITWE, P.O. Box: 21692, KITWE, Zambia.
Emmanuel MasaboAfrican Center of Excellence in Data Science (ACEDS), College of Business and Economics (CBE), University of Rwanda, Kigali, Kigali, P.O. Box 3900, Kigali, Rwanda.
Copperbelt University · ZMKabale University · UGUniversity of Rwanda · RW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The impact of air quality on human health and the environment is very significant, with poor air quality being responsible for numerous deaths and environmental damage worldwide. Whereas a number of studies have been done to monitor the quality of air with help of emerging technologies, little has been done to visualize its effect on health particularly on the lungs. The study explores an approach that combines Internet of Things (IoT) technology with High Efficiency Particulate Air (HEPA) filters air cleaner to monitor and visualize the effects of air pollution on lung health, highlighting the significant damage that poor air quality causes particularly on the lungs graphically. To achieve this, a 3D display of the lungs is modelled using HEPA filters, which changes colour based on the air pollutant concentrations detected by IoT-based sensors. The collected air quality data is then transmitted to Thingspeak, a visualization platform for further analysis. It is observed that the colour of the 3D lung display changed to black over time as air pollutant concentrations increased which in our study is an indicator of unhealthy lung. The study presents an innovative approach to visualize the effects of air pollution on lung health using IoT and HEPA filters air cleaner, which could have significant implications for public health policies aimed at mitigating the harmful effects of air pollution, particularly on lung health.

Indexed as

3D lung displayAir pollutionHEPA filterInternet of thingsThingspeak

Identifiers

PMID37539206
PMCPMC10395148
OpenAlexW4382933266

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.