Applications and classifications of unmanned aerial vehicles: A literature review with focus on multi-rotors

Sabour, Mohammad Hossein; Jafary, P.; Nematiyan, S.

doi:10.1017/aer.2022.75

Cited by 14 publications

(10 citation statements)

References 139 publications

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“…Quadcopters have rapidly become one of the most ubiquitous drone categories deployed across metropolitan areas due to their exceptional maneuverability and ability to take off, land, and hover in confined spaces. As rotorcrafts, quadcopters utilize four horizontally oriented lifting rotors to generate the vertical thrust needed for hovering and low-speed flights [55]. Unlike helicopters relying on a single main rotor for lift, quadcopters distribute thrust across four smaller rotors, providing a higher payload capacity for a given size and improved control redundancy and safety [3].…”

Section: Uav Platforms Based On Aerodynamic Featuresmentioning

confidence: 99%

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Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Bayomi,

Fernandez

2023

Drones

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This paper reviews the diverse applications of drone technologies in the built environment and their role in climate change research. Drones, or unmanned aerial vehicles (UAVs), have emerged as valuable tools for environmental scientists, offering new possibilities for data collection, monitoring, and analysis in the urban environment. The paper begins by providing an overview of the different types of drones used in the built environment, including quadcopters, fixed-wing drones, and hybrid models. It explores their capabilities and features, such as high-resolution cameras, LiDAR sensors, and thermal imaging, which enable detailed data acquisition for studying climate change impacts in urban areas. The paper then examines the specific applications of drones in the built environment and their contribution to climate change research. These applications include mapping urban heat islands, assessing the energy efficiency of buildings, monitoring air quality, and identifying sources of greenhouse gas emissions. UAVs enable researchers to collect spatially and temporally rich data, allowing for a detailed analysis and identifying trends and patterns. Furthermore, the paper discusses integrating UAVs with artificial intelligence (AI) to derive insights and develop predictive models for climate change mitigation and adaptation in urban environments. Finally, the paper addresses drone technologies’ challenges and the future directions in the built environment. These challenges encompass regulatory frameworks, privacy concerns, data management, and the need for an interdisciplinary collaboration. By harnessing the potential of drones, environmental scientists can enhance their understanding of climate change impacts in urban areas and contribute to developing sustainable strategies for resilient cities.

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Section: Uav Platforms Based On Aerodynamic Featuresmentioning

confidence: 99%

“…Ducting also streamlines the airflow, increasing the efficiency over open rotors [59]. This provides greater endurance than quadcopters, with flight times of around 45-60 minutes, depending on the conditions [55]. Ducted fans typically have a fixed wing for a forward flight, such as conventional UAVs.…”

Section: Uav Platforms Based On Aerodynamic Featuresmentioning

confidence: 99%

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Bayomi,

Fernandez

2023

Drones

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“…Multiple types of UAVs are used for EO including drones, multirotors, and fixed-wing UAVs [30]. Drones flight time vary based on its type, hence military drone MQ-C Gray Eagle achieved the longest flight time of 25 hours and a range of 400km [31].…”

Section: Uavmentioning

confidence: 99%

Formalization of BPMN Gateways using the DD-LOTOS Formal Language

Zidic,

Culic Gambiroza,

Mastelic

et al. 2023

JCOMSS

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Earth observation (EO) significantly increased in the second half of the 20th century and continues to advance rapidly, with remote sensing being a key component for gathering Earth-related information. Nowadays, satellites, manned aircraft, helicopters, UAVs and drones are used to capture aerial imagery in a periodic or schedule-based manner. This paper examine the feasibility of creating a novel remote sensing system by mounting cameras on commercial flights. The study evaluates flight coverage, including spatial and temporal resolutions, and considers the impact of clouds on image usability. We have compared flight coverage with cloud-inclusive flight coverage, which represents reduced flight coverage based on cloud quantity. Results show that entire country of Croatia is covered between 95% and 100% during the day and night. However, when clouds are included in the calculation, it is important to consider different altitudes and periods of the year because their distribution is not the same. In a less cloudy month (August), the highest differences between flight coverage and cloud-inclusive flight coverage for high-altitude flights are 70% for the worst-case scenario and 25% for the best-case scenario. Results show it is feasible to use commercial flights as a new remote sensing system.

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“…With the rapid development of target detection and UAV technology, the application of UAV target detection has been extensively researched [1]. UAVs are widely used in scenarios such as oil pipeline inspection, electric power inspection, crop analysis, and disaster rescue due to their unique high-altitude perspective and efficient data acquisition capabilities [2].…”

Section: Introductionmentioning

confidence: 99%

MCA-YOLOv7: An Improved UAV Target Detection Algorithm Based on YOLOv7

Qin,

Chen,

Wang

2024

IEEE Access

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Aiming at the problems of tiny targets, large target scale changes, and background information interference in target detection of UAV(Unmanned Aerial Vehicle) aerial images, a revised UAV target detection algorithm MCA-YOLOv7 based on YOLOv7 is proposed, and the algorithm advances from the following points: optimizing the FPN(Feature Pyramid Networks) structure to increase the small-target detection layer, and boosting the network's detection ability for small targets. To enhance the multi-scale feature extraction capability, the Efficient Multi-Scale Attention(EMA) is added. In order to reduce the complexity of the model and reduce the confusion of background information, the context aggregation block (CABlock) was introduced and improved, and an effective context aggregation block (ECABlock) was proposed. The loss function CIoU is enhanced and a new loss function FCIoU is proposed, which accelerates the convergence speed of the model, and obtains more accurate regression results. The experimental results demonstrate that the MCA-YOLOv7 model reduces the number of model parameters by 4.7 M and increases the average accuracy (

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Applications and classifications of unmanned aerial vehicles: A literature review with focus on multi-rotors

Cited by 14 publications

References 139 publications

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Eyes in the Sky: Drones Applications in the Built Environment under Climate Change Challenges

Formalization of BPMN Gateways using the DD-LOTOS Formal Language

MCA-YOLOv7: An Improved UAV Target Detection Algorithm Based on YOLOv7

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