Evidence map›Paper›PMID 35270862›Full record

ArticleSensors (Basel, Switzerland)2022

Lessons Learned from a Distributed RF-EMF Sensor Network.

Sam Aerts, Günter Vermeeren, Matthias Van den Bossche, Reza Aminzadeh, Leen Verloock, Arno Thielens, Philip Leroux, Johan Bergs, Bart Braem, Astrid Philippron and 2 more

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. 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

12 authors.

Sam AertsWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.ORCID 0000-0002-7444-4312
Günter VermeerenWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.ORCID 0000-0002-5309-3808
Matthias Van den BosscheWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.
Reza AminzadehUnitron NV-Unitron Connect, Frankrijklaan 27, 8970 Poperinge, Belgium.ORCID 0000-0003-2309-6888
Leen VerloockWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.
Arno ThielensWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.ORCID 0000-0002-8089-6382
Philip LerouxIDLab, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.
Johan BergsIDLab, University of Antwerp/imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium.
Bart BraemIDLab, University of Antwerp/imec, Sint-Pietersvliet 7, 2000 Antwerp, Belgium.
Astrid PhilippronASTRID, 1000 Brussels, Belgium.
Luc MartensWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.
Wout JosephWAVES, Ghent University/imec, Technologiepark-Zwijnaarde 126, 9052 Ghent, Belgium.ORCID 0000-0002-8807-0673

Funding

French Agency for Food, Environmental and Occupational Health & Safety 2016-RF-04Research Foundation - Flanders 12S6118N
6 · The paper itself

Abstract

In an increasingly wireless world, spatiotemporal monitoring of the exposure to environmental radiofrequency (RF) electromagnetic fields (EMF) is crucial to appease public uncertainty and anxiety about RF-EMF. However, although the advent of smart city infrastructures allows for dense networks of distributed sensors, the costs of accurate RF sensors remain high, and dedicated RF monitoring networks remain rare. This paper describes a comprehensive study comprising the design of a low-cost RF-EMF sensor node capable of monitoring four frequency bands used by wireless telecommunications with an unparalleled temporal resolution, its application in a small-scale distributed sensor network consisting of both fixed (on building façades) and mobile sensor nodes (on postal vans), and the subsequent analysis of over a year of data between January 2019 and May 2020, during which slightly less than 10 million samples were collected. From the fixed nodes' results, the potential errors were determined that are induced when sampling at lower speeds (e.g., one sample per 15 min) and measuring for shorter periods of time (e.g., a few weeks), as well as an adequate resolution (30 min) for diurnal and weekly temporal profiles which sufficiently preserves short-term variations. Furthermore, based on the correlation between the sensors, an adequate density of 100 sensor nodes per km

Indexed as

Cell PhoneElectromagnetic FieldsCitiesEnvironmental ExposureRadio Wavesdistributed sensor networkradiofrequency electromagnetic fields (RF-EMF)sensor nodespatiotemporal exposure assessment

Identifiers

PMID35270862
PMCPMC8914968

What OpenQuestion holds

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LicenceCC BY
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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.