UAV routing by simulation-based optimization approaches for forest fire risk mitigation

Özkan, Ömer; Kιlιç, Sezgin

doi:10.1007/s10479-021-04393-6

Cited by 14 publications

(3 citation statements)

References 47 publications

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“…The bio-inspired algorithms emulate biological behavior to obtain path solutions, while the multi-fusion based algorithms combine two or more of the priors. In this work, we employ a multi-fusion based methodology which integrates samplingbased and node-based algorithms as in Algorithm 1, and our UAV routing strategy is an exponential distribution-based given that our strategy uses a novel dynamic dispatching rule with priority given to the grids with the dynamically and continuously highest fire risk, taking into account both historical data and other factors that may influence wildfire occurrence [31].…”

Section: Image Acquisition and Processingmentioning

confidence: 99%

An Optimization of UAV-Based Remote Monitoring for Improving Wildfire Response in Power Systems

Umunnakwe,

Davis

2023

IEEE Open J. Power Energy

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Wildfires lead to colossal losses on territory, local, state and federal levels, affecting critical infrastructure, the economy, decarbonization goals, social sustainability and more. Although wildfire impacts highlight the urgent need for resilience-comprehensive methods in power system wildfire response, existing techniques often focus on a single phase, usually wildfire progression. In this work, a comprehensive approach is proposed to provide optimal and real-time information toward mitigating wildfire risk in all resilience phases, necessary to decompartmentalize wildfire response. This paper focuses on the optimal routing of the remote monitoring resources for a selfsufficient low-cost wildfire mitigation model (SL-PWR), which utilizes predicted spatio-temporal wildfire probability maps of the utility service area and optimized unmanned aerial vehicle (UAV) monitoring trees to obtain input images for training the SL-PWR modules. Results show that optimizing the SL-PWR's UAV monitoring using predicted wildfire threat parameters can improve situational awareness and rapidity of detection during wildfire incidents.

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Section: Image Acquisition and Processingmentioning

confidence: 99%

An Optimization of UAV-Based Remote Monitoring for Improving Wildfire Response in Power Systems

Umunnakwe,

Davis

2023

IEEE Open J. Power Energy

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“…A multi-objective evolutionary algorithm searches the space of potential field parameters to maximize fire coverage while minimizing energy consumption. Fire spread is modeled [ 22 ]. Mathematical models are used to generate UAV routes used to detect fires, such as forest fires.…”

Section: Possibility For Determining Optimal Paths To Reach a Threat-...mentioning

confidence: 99%

Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies

Robakowska

Ślęzak

Żuratyński

et al. 2022

IJERPH

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The term unmanned aerial vehicle (UAV) was post-applied in the 1980s to describe remotely piloted multi-purpose, unmanned, autonomous aircraft. The terms unmanned aircraft systems with data terminal connectivity (UAS) and remotely piloted aircraft systems (RPV, RPAS—military systems) are also used. This review aims to analyze the feasibility of using UAVs to support emergency medical systems in the supply and urgent care ranges. The implementation of drones in the medical security system requires proper planning of service cooperation, division of the area into sectors, assessment of potential risks and opportunities, and legal framework for the application. A systematic literature search was conducted to assess the applicability based on published scientific papers on possible medical drone applications in the field of urgent mode. The widespread applications of UAVs in healthcare are concerned with logistics, scope, and transportability, with framework legal constraints to effectively exploit opportunities for improving population health, particularly for costly critical situations.

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“…In recent years, with the continuous development of unmanned aerial vehicle (UAV) technology, the application of UAVs in area coverage tasks such as plant protection, target search, and forest fire prevention has gradually become a reality [1][2][3][4][5]. UAVs have the advantages of high flexibility and task efficiency compared to traditional manual or mechanical operations in area coverage tasks [6,7]. Particularly in harsh environments, complex terrains, and areas with limited accessibility, using UAVs for search or agricultural operations can overcome environmental constraints, significantly reduce labor costs, and demonstrate the significant value of UAV applications [8,9].…”

Section: Introductionmentioning

confidence: 99%

UAV Cluster Mission Planning Strategy for Area Coverage Tasks

Yan,

Chen,

Jiang

2023

Sensors

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In the context of area coverage tasks in three-dimensional space, unmanned aerial vehicle (UAV) clusters face challenges such as uneven task assignment, low task efficiency, and high energy consumption. This paper proposes an efficient mission planning strategy for UAV clusters in area coverage tasks. First, the area coverage search task is analyzed, and the coverage scheme of the task area is determined. Based on this, the cluster task area is divided into subareas. Then, for the UAV cluster task allocation problem, a step-by-step solution is proposed. Afterward, an improved fuzzy C-clustering algorithm is used to determine the UAV task area. Furthermore, an optimized particle swarm hybrid ant colony (PSOHAC) algorithm is proposed to plan the UAV cluster task path. Finally, the feasibility and superiority of the proposed scheme and improved algorithm are verified by simulation experiments. The simulation results show that the proposed method achieves full coverage of the task area and efficiently completes the task allocation of the UAV cluster. Compared with related comparison algorithms, the method proposed in this paper can achieve a maximum improvement of 21.9% in balanced energy consumption efficiency for UAV cluster task search planning, and the energy efficiency of the UAV cluster can be improved by up to 7.9%.

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UAV routing by simulation-based optimization approaches for forest fire risk mitigation

Cited by 14 publications

References 47 publications

An Optimization of UAV-Based Remote Monitoring for Improving Wildfire Response in Power Systems

An Optimization of UAV-Based Remote Monitoring for Improving Wildfire Response in Power Systems

Possibilities of Using UAVs in Pre-Hospital Security for Medical Emergencies

UAV Cluster Mission Planning Strategy for Area Coverage Tasks

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