Drones · 2022 · 69 citations · 8 references
EngineeringAerospace EngineeringPrecision AgricultureAerial RoboticsTransportationUnmanned Aircraft SystemsAgricultural ApplicationsReconnaissance ApplicationsAir Mobility OperationsPublic AcceptanceRescueUnmanned Aerial Vehicle SensingUnmanned Aerial Vehicle-based ApplicationUrban Air Mobility
The continuous development of technical innovations provides the opportunity to create new economic markets and a wealth of new services. However, these innovations sometimes raise concerns, notably in terms of societal, safety, and environmental impacts. This is the case for services related to the operation of unmanned aerial vehicles (UAV), which are emerging rapidly. Unmanned aerial vehicles, also called drones, date back to the first third of the twentieth century in aviation industry, when they were mostly used for military purposes. Nowadays, drones of various types and sizes are used for many purposes, such as precision agriculture, search and rescue missions, aerial photography, shipping and delivery, etc. Starting to operate in areas with low population density, drones are now looking for business in urban and suburban areas, in what is called urban air mobility (UAM). However, this rapid growth of the drone industry creates psychological fear of the unknown in some parts of society. Reducing this fear will play an important role in public acceptance of drone operations in urban areas. This paper presents the main concerns of society with regard to drone operations, as already captured in some public surveys, and proposes a list of mitigation measures to reduce these concerns. The proposed list is then analyzed, and its applicability to individual, urban, very large demonstration flights is explained, using the feedback from the CORUS-XUAM project. CORUS-XUAM will organize a set of very large drone flight demonstrations across seven European countries to investigate how to safely integrate drone operations into airspace with the support of the U-space.
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Risk Perception and the Public Acceptance of Drones
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Deep Neural Networks and Transfer Learning for Food Crop Identification in UAV Images
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Agriculture, Agronomy, Crop Sciences +17