Unmanned Aerial Vehicle LiDAR Scanning for Railway Security: Pre-and Post-Explosion Analysis

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG42__%2F26%3A00564887" target="_blank" >RIV/60162694:G42__/26:00564887 - isvavai.cz</a>

Výsledek na webu

<a href="http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11061248" target="_blank" >http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=11061248</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1109/ICMT65201.2025.11060900" target="_blank" >10.1109/ICMT65201.2025.11060900</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Unmanned Aerial Vehicle LiDAR Scanning for Railway Security: Pre-and Post-Explosion Analysis

Popis výsledku v původním jazyce

This study investigates the potential of utilizing unmanned aerial vehicles (UAVs) equipped with Light Detection and Ranging (LiDAR) sensors to detect track damage, perimeter fence integrity, and ground changes in the context of railway security. The data collected from the experiment were processed and analysed to evaluate the efficacy of the LiDAR technology in detecting blast-induced damage. The results indicate that LiDAR scanning is insufficient for detecting the presence of charges, owing to inadequate image resolution, and only substantial track damage is detectable by LiDAR. Conventional imagery is more suitable for detecting subtle damage. However, LiDAR imagery of the pit demonstrates its effectiveness in capturing three-dimensional scans, which could be beneficial for assessing terrain trafficability and identifying potential obstacles in military operations. This study suggests that future research should focus on utilizing conventional imagery of features in conjunction with automated assessment using artificial intelligence for critical infrastructure surveys.

Název v anglickém jazyce

Unmanned Aerial Vehicle LiDAR Scanning for Railway Security: Pre-and Post-Explosion Analysis

Popis výsledku anglicky

This study investigates the potential of utilizing unmanned aerial vehicles (UAVs) equipped with Light Detection and Ranging (LiDAR) sensors to detect track damage, perimeter fence integrity, and ground changes in the context of railway security. The data collected from the experiment were processed and analysed to evaluate the efficacy of the LiDAR technology in detecting blast-induced damage. The results indicate that LiDAR scanning is insufficient for detecting the presence of charges, owing to inadequate image resolution, and only substantial track damage is detectable by LiDAR. Conventional imagery is more suitable for detecting subtle damage. However, LiDAR imagery of the pit demonstrates its effectiveness in capturing three-dimensional scans, which could be beneficial for assessing terrain trafficability and identifying potential obstacles in military operations. This study suggests that future research should focus on utilizing conventional imagery of features in conjunction with automated assessment using artificial intelligence for critical infrastructure surveys.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

21100 - Other engineering and technologies

Projekt

<a href="/cs/project/CK03000182" target="_blank" >CK03000182: Výzkum stavebně-technických požadavků na využití národní pozemní infrastruktury TEN-T k řešení krizových situací velkého rozsahu</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2025

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

2025 10th International Conference on Military Technologies, ICMT 2025 - Proceedings

ISBN

979-8-3315-2338-1

ISSN

—

e-ISSN

—

Počet stran výsledku

7

Strana od-do

—

Název nakladatele

Institute of Electrical and Electronics Engineers Inc.

Místo vydání

—

Místo konání akce

Brno, Czech Republic

Datum konání akce

27. 5. 2025

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

001545807300004