Evidence map›Paper›PMID 36772436›Full record

ArticleSensors (Basel, Switzerland)2023

Comparing Efficiency and Performance of IoT BLE and RFID-Based Systems for Achieving Contract Tracing to Monitor Infection Spread among Hospital and Office Staff.

Maggie Ezzat Gaber Gendy, Phi Tham, Flynn Harrison, Mehmet Rasit Yuce

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2023. 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.

  1. Article
  2. 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

4 authors.

Maggie Ezzat Gaber GendyDepartment of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3800, Australia.ORCID 0000-0002-9556-9632
Phi ThamDepartment of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3800, Australia.
Flynn HarrisonDepartment of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3800, Australia.
Mehmet Rasit YuceDepartment of Electrical and Computer Systems Engineering, Monash University, Melbourne, VIC 3800, Australia.ORCID 0000-0002-4802-391X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 is highly contagious and spreads rapidly; it can be transmitted through coughing or contact with virus-contaminated hands, surfaces, or objects. The virus spreads faster indoors and in crowded places; therefore, there is a huge demand for contact tracing applications in indoor environments, such as hospitals and offices, in order to measure personnel proximity while placing as little load on them as possible. Contact tracing is a vital step in controlling and restricting pandemic spread; however, traditional contact tracing is time-consuming, exhausting, and ineffective. As a result, more research and application of smart digital contact tracing is necessary. As the Internet of Things (IoT) and wearable sensor device studies have grown in popularity, this work has been based on the practicality and successful implementation of Bluetooth low energy (BLE) and radio frequency identification (RFID) IoT based wireless systems for achieving contact tracing. Our study presents autonomous, low-cost, long-battery-life wireless sensing systems for contact tracing applications in hospital/office environments; these systems are developed with off-the-shelf components and do not rely on end user participation in order to prevent any inconvenience. Performance evaluation of the two implemented systems is carried out under various real practical settings and scenarios; these two implemented centralised IoT contact tracing devices were tested and compared demonstrating their efficiency results.

Indexed as

COVID-19Radio Frequency Identification DeviceWearable Electronic DevicesContact TracingHospitalsHumansBLEcontact tracingCOVID-19 pandemichospital/office settingshuman–human proximityindoor infection spreadIoTRFIDwireless sensing systems

Identifiers

PMID36772436
PMCPMC9919911

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.