Advances in Wearable Sensors: Signalling the Provenance of Garments Using Radio Frequency Watermarks.

Javad Foroughi, Farzad Safaei, Raad Raad, Teodor Mitew

Open access · goldAbstract read

In one paragraph

Article in Sensors (Basel, Switzerland), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

0.3field-weighted citation impact, top 32% 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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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 at 1 institution in 2 countries.

Javad ForoughiSchool of Electrical, Computer and Telecommunications Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2522, Australia.ORCID 0000-0003-1979-5213

Farzad SafaeiSchool of Electrical, Computer and Telecommunications Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2522, Australia.ORCID 0000-0002-4322-4448

Raad RaadSchool of Electrical, Computer and Telecommunications Engineering, Faculty of Engineering and Information Sciences, University of Wollongong, Wollongong, NSW 2522, Australia.ORCID 0000-0002-2347-4837

Teodor MitewSchool of the Arts, English and Media, University of Wollongong, Wollongong, NSW 2522, Australia.ORCID 0000-0002-0830-0863

University of Wollongong · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

There is a significant nascent market for ethically produced products with enormous commercial potential around the world. A reliable method to signal the provenance of products is therefore critical for industry, given that competition based on price is not a viable strategy. The ability to trace and signal ethical treatment of animals is also of significant value to textiles manufactures. The efficacy of such a method can be measured with respect to the cost of implementation, scalability, and the difficulty of counterfeiting. The key to traceability is to win the trust of the consumer about the veracity of this information. Wearable sensors make it possible to monitor and improve the management of traceability and/or provenance. In this paper, we introduce a method for signalling the provenance of garments using radio frequency watermarks. The proposed model consists of two levels of authentication that are easy to use by legitimate vendors, but extremely difficult to imitate or hack, because the watermark is built-in and based on the radiation signature of electroactive materials.

Indexed as

chipless RFIDgarmentprovenanceradio frequencysmart textilestraceabilitywatermarkswearable sensors

Identifiers

PMID33233745

DOI10.3390/s20226661

PMCPMC7699914

OpenAlexW3099187539

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.