Evidence map›Paper›PMID 38894441›Full record

ReviewSensors (Basel, Switzerland)2024

Challenges and Opportunities in Calibrating Low-Cost Environmental Sensors.

Naga Venkata Sudha Rani Nalakurthi, Ismaila Abimbola, Tasneem Ahmed, Iulia Anton, Khurram Riaz, Qusai Ibrahim, Arghadyuti Banerjee, Ananya Tiwari, Salem Gharbia

Abstract readReview
In one paragraph

Review 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 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Metrological Characterization of Low-Cost COSensors (Basel, Switzerland) · 2026
    Article
  5. Review
  6. Ambient PMCurrent environmental health reports · 2026
    Review
  7. Article
  8. Review
  9. Review
  10. Article
  11. Review
  12. Article
  13. Article
  14. Article
  15. Review
  16. Article
  17. Article
  18. 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.

Naga Venkata Sudha Rani NalakurthiSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.
Ismaila AbimbolaSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.
Tasneem AhmedSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.ORCID 0000-0002-7087-6230
Iulia AntonSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.ORCID 0000-0001-6491-4096
Khurram RiazSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.ORCID 0000-0002-0634-1426
Qusai IbrahimSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.ORCID 0000-0002-2252-5153
Arghadyuti BanerjeeSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.
Ananya TiwariSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.ORCID 0000-0001-6573-3043
Salem GharbiaSmart Earth Innovation Hub (Earth-Hub), Atlantic Technological University, F91 YW50 Sligo, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The use of low-cost environmental sensors has gained significant attention due to their affordability and potential to intensify environmental monitoring networks. These sensors enable real-time monitoring of various environmental parameters, which can help identify pollution hotspots and inform targeted mitigation strategies. Low-cost sensors also facilitate citizen science projects, providing more localized and granular data, and making environmental monitoring more accessible to communities. However, the accuracy and reliability of data generated by these sensors can be a concern, particularly without proper calibration. Calibration is challenging for low-cost sensors due to the variability in sensing materials, transducer designs, and environmental conditions. Therefore, standardized calibration protocols are necessary to ensure the accuracy and reliability of low-cost sensor data. This review article addresses four critical questions related to the calibration and accuracy of low-cost sensors. Firstly, it discusses why low-cost sensors are increasingly being used as an alternative to high-cost sensors. In addition, it discusses self-calibration techniques and how they outperform traditional techniques. Secondly, the review highlights the importance of selectivity and sensitivity of low-cost sensors in generating accurate data. Thirdly, it examines the impact of calibration functions on improved accuracies. Lastly, the review discusses various approaches that can be adopted to improve the accuracy of low-cost sensors, such as incorporating advanced data analysis techniques and enhancing the sensing material and transducer design. The use of reference-grade sensors for calibration and validation can also help improve the accuracy and reliability of low-cost sensor data. In conclusion, low-cost environmental sensors have the potential to revolutionize environmental monitoring, particularly in areas where traditional monitoring methods are not feasible. However, the accuracy and reliability of data generated by these sensors are critical for their successful implementation. Therefore, standardized calibration protocols and innovative approaches to enhance the sensing material and transducer design are necessary to ensure the accuracy and reliability of low-cost sensor data.

Indexed as

air qualitycalibrationslow-cost sensorswater quality

Identifiers

PMID38894441
PMCPMC11175279

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.