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A Risk Assessment Technique for Energy-Efficient Drones to Support Pilots and Ensure Safe Flying

Auteur(s): ORCID (Central Campus Győr, Széchenyi István University, H-9026 Gyor, Hungary)
(Central Campus Győr, Széchenyi István University, H-9026 Gyor, Hungary)
(Central Campus Győr, Széchenyi István University, H-9026 Gyor, Hungary)
ORCID (Department of Transport Infrastructure, Ukrainian State University of Science and Technologies, UA-49005 Dnipro, Ukraine)
ORCID (Department of Planning and Design of Railway Infrastructure, Technical University Dresden, D-01069 Dresden, Germany)
ORCID (Central Campus Győr, Széchenyi István University, H-9026 Gyor, Hungary)
Médium: article de revue
Langue(s): anglais
Publié dans: Infrastructures, , n. 4, v. 8
Page(s): 67
DOI: 10.3390/infrastructures8040067
Abstrait:

Unmanned Aerial Vehicles, also known as UAVs, play an increasingly important part in daily life. However, the ever-increasing number of UAVs pose an ever-increasing threat to the transportation infrastructure. Despite their precision and general efficiency, infrastructural-scale Unmanned Aerial Systems (UASs) have a disadvantage regarding their capability of being implanted in the ecosystem. There are several reasons for this, but the primary bottleneck is that their systems are not transparent to society and have very complicated processes. As a result, the authors decided to investigate the functional properties of UASs and make improvements to those properties. Throughout the study, the authors’ primary focus was on analysis, which boosts productivity and ensures a significant level of safety for routine flights. The amount of power that a UAV uses depends on several variables, including the amount of power that its individual components require, the temperature of its surroundings, and the condition of the battery that it is powered by. Therefore, critical parameters and interdependencies are taken into account in the risk assessment strategy for energy-efficient Unmanned Aerial Vehicles (UAVs). In the case of UAVs, the algorithm performs a risk calculation before take-off to estimate the amount of risk that can be associated with the given flight time when using the provided battery. On the one hand, several instances of the pre-take-off state and how its parameters interact are investigated. On the other hand, they demonstrate the calculation of the risk while in flight, which is based on actual flight data.

Copyright: © 2023 the Authors. Licensee MDPI, Basel, Switzerland.
License:

Cette oeuvre a été publiée sous la license Creative Commons Attribution 4.0 (CC-BY 4.0). Il est autorisé de partager et adapter l'oeuvre tant que l'auteur est crédité et la license est indiquée (avec le lien ci-dessus). Vous devez aussi indiquer si des changements on été fait vis-à-vis de l'original.

  • Informations
    sur cette fiche
  • Reference-ID
    10722704
  • Publié(e) le:
    22.04.2023
  • Modifié(e) le:
    10.05.2023
 
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