Evidence map›Paper›PMID 40218583›Full record

ReviewSensors (Basel, Switzerland)2025

Innovations in Air Quality Monitoring: Sensors, IoT and Future Research.

Saim Shahid, David J Brown, Philip Wright, Ahmad M Khasawneh, Bryn Taylor, Omprakash Kaiwartya

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Article
  4. Review
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

6 authors.

Saim ShahidDepartment of Computer Science, Nottingham Trent University, Nottingham NG1 8NS, UK.ORCID 0000-0001-6764-2268
David J BrownDepartment of Computer Science, Nottingham Trent University, Nottingham NG1 8NS, UK.ORCID 0000-0002-1677-7485
Philip WrightCobac Security Limited, The Granary, Church Street, Thrumpton, Nottingham NG11 0AX, UK.
Ahmad M KhasawnehSchool of Computing, Skyline University College, University City of Sharjah, Sharjah P.O. Box 1797, United Arab Emirates.ORCID 0000-0002-1850-3269
Bryn TaylorCobac Security Limited, The Granary, Church Street, Thrumpton, Nottingham NG11 0AX, UK.
Omprakash KaiwartyaDepartment of Computer Science, Nottingham Trent University, Nottingham NG1 8NS, UK.ORCID 0000-0001-9669-8244

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, Air Quality Monitoring (AQM) has gained significant R&D attention from academia and industries, leading to advanced sensor-enabled IoT solutions. Literature highlights the use of nanomaterials in sensor design, emphasising miniaturisation, enhanced calibration, and low voltage, room-temperature operation. Significant efforts are aimed at improving sensitivity, selectivity, and stability, while addressing challenges like high power consumption and drift. The integration of sensors with IoT technology is driving the development of accurate, scalable, and real-time AQM systems. This paper provides technical insights into recent AQM advancements, focusing on air pollutants, sensor technologies, IoT frameworks, performance evaluation, and future research directions. It presents a detailed analysis of air quality composition and potential air pollutants. Relevant sensors are examined in terms of design, materials and methodologies for pollutant monitoring. A critical review of IoT frameworks for AQM is conducted, highlighting their strengths and weaknesses. As a technical contribution, an experimental performance evaluation of three commercially available AQM systems in the UK is discussed, with a comparative and critical analysis of the results. Lastly, future research directions are also explored with a focus on AQM sensor design and IoT framework development.

Indexed as

air pollutantsair quality monitoringinternet of thingssensorssensors design

Identifiers

PMID40218583
PMCPMC11991194

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.