Wilderness Search and Rescue (WSAR) focuses on locating and extricating missing persons in remote settings. As unmanned aerial vehicle (UAV) or "drone" technology has evolved, so has the literature describing its application in WSAR operations. We conducted a scoping review of literature that describes the use of UAVs in WSAR contexts. The Joanna Briggs Institute Framework for scoping reviews was followed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews method. Additional individual databases, article reference lists, and relevant grey literature were also included in the search to provide an impartial scope. Seven hundred forty-seven articles were identified. Of these, 56 were found to be duplicates. The remaining 691 were further screened and checked for eligibility. Ultimately, 21 studies were found that met our inclusion criteria. This literature supports the use of UAVs to increase the safety and efficiency of a WSAR operation for locating victims, assessing risks, carrying equipment, and restoring communication systems. Unmanned aerial vehicles are a potentially useful adjunct in the management of WSAR operations. Their limitations include objects obscuring victims, weather changes, uneven terrain, battery-limited flight time, and susceptibility to environmental damage.
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http://dx.doi.org/10.1016/j.wem.2023.08.022 | DOI Listing |
Sci Rep
January 2025
Department of Basic Courses, Xi'an Research Institute of Hi-Tech, Xi'an, 710025, China.
Unmanned aerial vehicle (UAV) path planning is a constrained multi-objective optimization problem. With the increasing scale of UAV applications, finding an efficient and safe path in complex real-world environments is crucial. However, existing particle swarm optimization (PSO) algorithms struggle with these problems as they fail to consider UAV dynamics, resulting in many infeasible solutions and poor convergence to optimal solutions.
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January 2025
Centre for Automation and Robotics (CAR), Spanish National Research Council (CSIC), 28006, Madrid, Spain.
This study highlights the vital role of high-resolution (HR), open-source land cover maps for food security, land use planning, and environmental protection. The scarcity of freely available HR datasets underscores the importance of multi-spectral HR aerial images. We used unmanned aerial vehicle (UAV) to capture images for a centimeter-level orthomosaics, facilitating advanced remote sensing and spatial analysis.
View Article and Find Full Text PDFData Brief
February 2025
Institute of Agricultural Sciences, Spanish National Research Council (ICA-CSIC), Serrano 115b, 28006 Madrid, Spain.
Identifying weed species at early-growth stages is critical for precision agriculture. Accurate classification at the species-level enables targeted control measures, significantly reducing pesticide use. This paper presents a dataset of RGB images captured with a Sony ILCE-6300L camera mounted on an unmanned aerial vehicle (UAV) flying at an altitude of 11 m above ground level.
View Article and Find Full Text PDFAnal Chim Acta
February 2025
Instituto de Química, Universidade Federal de Goiás, 74690-900, Goiânia, GO, Brazil; Instituto Nacional de Ciência e Tecnologia de Bioanalítica, Campinas, 13084-971, SP, Brazil. Electronic address:
Background: Distinct classes of environmental contaminants - such as microplastics, volatile organic compounds, inorganic gases, hormones, pesticides/herbicides, and heavy metals - have been continuously released into the environment from different sources. Anthropogenic activities with unprecedented consequences have impacted soil, surface waters, and the atmosphere. In this scenario, developing sensing materials and analytical platforms for monitoring water and air quality is essential to supporting worldwide environmental control agencies.
View Article and Find Full Text PDFSensors (Basel)
January 2025
Department of Control and Computer Engineering (DAUIN), Politecnico di Torino, Corso Duca degli Abruzzi, 24, 10129 Torino, Italy.
The increasing demand for hazelnut kernels is favoring an upsurge in hazelnut cultivation worldwide, but ongoing climate change threatens this crop, affecting yield decreases and subject to uncontrolled pathogen and parasite attacks. Technical advances in precision agriculture are expected to support farmers to more efficiently control the physio-pathological status of crops. Here, we report a straightforward approach to monitoring hazelnut trees in an open field, using aerial multispectral pictures taken by drones.
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