Developing a Cloud-Based Air Quality Monitoring Platform Using Low-Cost Sensors.

Abdul Samad, Joschka Kieser, Ioannis Chourdakis, Ulrich Vogt

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.

GEMS satellite data fusion for hourly air quality prediction in Taiwan.Scientific reports · 2026
Article
Design and Enhancement of a Fog-Enabled Air Quality Monitoring and Prediction System: An Optimized Lightweight Deep Learning Model for a Smart Fog Environmental Gateway.Sensors (Basel, Switzerland) · 2024
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

4 authors.

Abdul SamadInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany.ORCID 0000-0002-9862-9354

Joschka KieserInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany.

Ioannis ChourdakisInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany.

Ulrich VogtInstitute of Combustion and Power Plant Technology (IFK), Department of Flue Gas Cleaning and Air Quality Control, University of Stuttgart, Pfaffenwaldring 23, 70569 Stuttgart, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional air quality monitoring has been traditionally carried out in a few fixed places with expensive measuring equipment. This results in sparse spatial air quality data, which do not represent the real air quality of an entire area, e.g., when hot spots are missing. To obtain air quality data with higher spatial and temporal resolution, this research focused on developing a low-cost network of cloud-based air quality measurement platforms. These platforms should be able to measure air quality parameters including particulate matter (PM10, PM2.5, PM1) as well as gases like NO, NO

Indexed as

air pollutantsair quality monitoringair quality sensorselectrochemical low-cost sensorsgas sensorslow-cost sensorsPM sensors

Identifiers

PMID38339662

DOI10.3390/s24030945

PMCPMC10857248

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.