Evidence map›Paper›PMID 34960347›Full record

ReviewSensors (Basel, Switzerland)2021

Sensors and Measurements for UAV Safety: An Overview.

Eulalia Balestrieri, Pasquale Daponte, Luca De Vito, Francesco Picariello, Ioan Tudosa

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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

  1. Article
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  5. Review
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  7. 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

5 authors.

Eulalia BalestrieriDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.ORCID 0000-0002-9155-5989
Pasquale DaponteDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.
Luca De VitoDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.ORCID 0000-0003-1896-2614
Francesco PicarielloDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.ORCID 0000-0001-6854-3026
Ioan TudosaDepartment of Engineering, University of Sannio, 82100 Benevento, Italy.ORCID 0000-0002-5127-578X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unmanned aerial vehicles' (UAVs) safety has gained great research interest due to the increase in the number of UAVs in circulation and their applications, which has inevitably also led to an increase in the number of accidents in which these vehicles are involved. The paper presents a classification of UAV safety solutions that can be found in the scientific literature, putting in evidence the fundamental and critical role of sensors and measurements in the field. Proposals from research on each proposed class concerning flight test procedures, in-flight solutions including soft propeller use, fault and damage detection, collision avoidance and safe landing, as well as ground solution including testing and injury and damage quantification measurements are discussed.

Indexed as

Unmanned Aerial Deviceschallengesdesigndiagnosissafetysense and avoidsensorstestingUAV

Identifiers

PMID34960347
PMCPMC8704263

What OpenQuestion holds

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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.