Evidence map›Paper›PMID 36501907›Full record

ArticleSensors (Basel, Switzerland)2022

Real-Time Gamma Radioactive Source Localization by Data Fusion of 3D-LiDAR Terrain Scan and Radiation Data from Semi-Autonomous UAV Flights.

Stephan Schraml, Michael Hubner, Philip Taupe, Michael Hofstätter, Philipp Amon, Dieter Rothbacher

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2022. 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. Review
  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.

Stephan SchramlAIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria.ORCID 0000-0002-3915-204X
Michael HubnerAIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria.ORCID 0000-0002-1640-5614
Philip TaupeAIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria.ORCID 0000-0003-4708-9455
Michael HofstätterAIT Austrian Institute of Technology GmbH, Giefinggasse 4, 1210 Vienna, Austria.
Philipp AmonRIEGL Laser Measurement Systems GmbH, Riedenburgstr. 48, 3580 Horn, Austria.ORCID 0000-0003-0071-6642
Dieter RothbacherCBRN Protection GmbH, 1200 Vienna, Austria.

Funding

Die Österreichische Forschungsförderungsgesellschaft 873433
6 · The paper itself

Abstract

Rapid and accurate reconnaissance in the event of radiological and nuclear (RN) incidents or attacks is vital to launch an appropriate response. This need is made stronger by the increasing threat of RN attacks on soft targets and critical infrastructure in densely populated areas. In such an event, even small radioactive sources can cause major disruption to the general population. In this work, we present a real-time radiological source localization method based on an optimization problem considering a background and radiation model. Supported by extensive real-world experiments, we show that an airborne system using this method is capable for reliably locating category 3-4 radioactive sources according to IAEA safety standards in real time from altitudes up to 150 m. A sensor bundle including a LiDAR sensor, a Gamma probe as well as a communication module was mounted on a UAV that served as a carrier platform. The method was evaluated on a comprehensive set of test flights, including 28 flight scenarios over 316 min using three different radiation sources. All additional gamma sources were correctly detected, multiple sources were detected if they were sufficiently separated from each other, with the distance between the true source position and the estimated source averaging 17.1 m. We also discuss the limitations of the system in terms of detection limit and source separation.

Indexed as

3D-LiDAR terrain modellingdata fusionhazard detectionmeasurements of CBRN agentsoptimizationreal-time gamma source localization

Identifiers

PMID36501907
PMCPMC9735945

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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.