Evidence map›Paper›PMID 33672458›Full record

ArticleSensors (Basel, Switzerland)2021

A Runway Safety System Based on Vertically Oriented Stereovision.

Dawid Gradolewski, Damian Dziak, Damian Kaniecki, Adam Jaworski, Michal Skakuj, Wlodek J Kulesza

Abstract read
In one paragraph

Article 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

6 authors.

Dawid GradolewskiBioseco Sp. z. o. o., Budowlanych 68, 80-298 Gdansk, Poland.
Damian DziakBioseco Sp. z. o. o., Budowlanych 68, 80-298 Gdansk, Poland.
Damian KanieckiBioseco Sp. z. o. o., Budowlanych 68, 80-298 Gdansk, Poland.
Adam JaworskiBioseco Sp. z. o. o., Budowlanych 68, 80-298 Gdansk, Poland.
Michal SkakujEkoaviation, ul. Piecewska 30B/16, 80-288 Gdansk, Poland.
Wlodek J KuleszaDepartment of Mathematics and Natural Sciences, Blekinge Institute of Technology, 371 79 Karlskrona, Sweden.

Funding

Narodowe Centrum Badań i Rozwoju POIR.01.01.01-00-0020/19
6 · The paper itself

Abstract

In 2020, over 10,000 bird strikes were reported in the USA, with average repair costs exceeding $200 million annually, rising to $1.2 billion worldwide. These collisions of avifauna with airplanes pose a significant threat to human safety and wildlife. This article presents a system dedicated to monitoring the space over an airport and is used to localize and identify moving objects. The solution is a stereovision based real-time bird protection system, which uses IoT and distributed computing concepts together with advanced HMI to provide the setup's flexibility and usability. To create a high degree of customization, a modified stereovision system with freely oriented optical axes is proposed. To provide a market tailored solution affordable for small and medium size airports, a user-driven design methodology is used. The mathematical model is implemented and optimized in MATLAB. The implemented system prototype is verified in a real environment. The quantitative validation of the system performance is carried out using fixed-wing drones with GPS recorders. The results obtained prove the system's high efficiency for detection and size classification in real-time, as well as a high degree of localization certainty.

Indexed as

bird monitoringbird strikedistributed computingenvironmental sustainabilityInternet of Thingslocalizationmonitoring of avifaunarunway safetysafety systemstereovisionvisual sensor network

Identifiers

PMID33672458
PMCPMC7923446

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.