Evidence map›Paper›PMID 34770431›Full record

ReviewSensors (Basel, Switzerland)2021

Internet of Things Based Contact Tracing Systems.

Peng Hu, Philippe Lamontagne

Abstract readReview
In one paragraph

Review in Sensors (Basel, Switzerland), 2021. 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. 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

2 authors.

Peng HuDigital Technologies Research Center, National Research Council of Canada, Ottawa, ON K1A 0R6, Canada.ORCID 0000-0002-9069-0484
Philippe LamontagneDigital Technologies Research Center, National Research Council of Canada, Ottawa, ON K1A 0R6, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The COVID-19 pandemic has significantly threatened the health and well-being of humanity. Contact tracing (CT) as an important non-pharmaceutical intervention is essential to containing the spread of such an infectious disease. However, current CT solutions are fragmented with limited use of sensing and computing technologies in a scalable framework. These issues can be well addressed with the use of the Internet of Things (IoT) technologies. Therefore, we need to overview the principle, motivation, and architecture for a generic IoT-based CT system (IoT-CTS). A novel architecture for IoT-CTS solutions is proposed with the consideration of peer-to-peer and object-to-peer contact events, as well as the discussion on key topics, such as an overview of applicable sensors for CT needs arising from the COVID-19 transmission methods. The proposed IoT-CTS architecture aims to holistically utilize essential sensing mechanisms with the analysis of widely adopted privacy-preserving techniques. With the use of generic peer-to-peer and object-to-peer sensors based on proximity and environment sensing mechanisms, the infectious cases with self-directed strategies can be effectively reduced. Some open research directions are presented in the end.

Indexed as

COVID-19Internet of ThingsContact TracingHumansPandemicsSARS-CoV-2contact tracingCOVID-19environment sensingInternet of Thingsobject to peerpeer to peerprivacyproximity sensingSARS-CoV-2transmission methods

Identifiers

PMID34770431
PMCPMC8587965

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.