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Unmanned aerial system*

Jongtack Jung, Seungho Yoo, Woong Gyu La, Dongkyu Roy Lee, Mungyu Bae, Hwangnam Kim
Most surveillance systems only contain CCTVs. CCTVs, however, provide only limited maneuverability against dynamic targets and are inefficient for short term surveillance. Such limitations do not raise much concern in some cases, but for the scenario in which traditional surveillance systems do not suffice, adopting a fleet of UAVs can help overcoming the limitations. In this paper, we present a surveillance system implemented with a fleet of unmanned aerial vehicles (UAVs). A surveillance system implemented with a fleet of UAVs is easy to deploy and maintain...
June 14, 2018: Sensors
Lili Shen, Jiming Guo, Lei Wang
The network real-time kinematic (RTK) technique can provide centimeter-level real time positioning solutions and play a key role in geo-spatial infrastructure. With ever-increasing popularity, network RTK systems will face issues in the support of large numbers of concurrent users. In the past, high-precision positioning services were oriented towards professionals and only supported a few concurrent users. Currently, precise positioning provides a spatial foundation for artificial intelligence (AI), and countless smart devices (autonomous cars, unmanned aerial-vehicles (UAVs), robotic equipment, etc...
June 6, 2018: Sensors
Heino Kuuluvainen, Mikko Poikkimäki, Anssi Järvinen, Joel Kuula, Matti Irjala, Miikka Dal Maso, Jorma Keskinen, Hilkka Timonen, Jarkko V Niemi, Topi Rönkkö
The vertical profiles of lung deposited surface area (LDSA) concentration were measured in an urban street canyon in Helsinki, Finland, by using an unmanned aerial system (UAS) as a moving measurement platform. The street canyon can be classified as an avenue canyon with an aspect ratio of 0.45 and the UAS was a multirotor drone especially modified for emission measurements. In the experiments of this study, the drone was equipped with a small diffusion charge sensor capable of measuring the alveolar LDSA concentration of particles...
May 23, 2018: Environmental Pollution
Phong Ha Nguyen, Muhammad Arsalan, Ja Hyung Koo, Rizwan Ali Naqvi, Noi Quang Truong, Kang Ryoung Park
Autonomous landing of an unmanned aerial vehicle or a drone is a challenging problem for the robotics research community. Previous researchers have attempted to solve this problem by combining multiple sensors such as global positioning system (GPS) receivers, inertial measurement unit, and multiple camera systems. Although these approaches successfully estimate an unmanned aerial vehicle location during landing, many calibration processes are required to achieve good detection accuracy. In addition, cases where drones operate in heterogeneous areas with no GPS signal should be considered...
May 24, 2018: Sensors
Sara Arabi, Essaid Sabir, Halima Elbiaze, Mohamed Sadik
Recently, Unmanned Aerial Vehicles (UAVs) have emerged as an alternative solution to assist wireless networks, thanks to numerous advantages they offer in comparison to terrestrial fixed base stations. For instance, a UAV can be used to embed a flying base station providing an on-demand nomadic access to network services. A UAV can also be used to wirelessly recharge out-of-battery ground devices. In this paper, we aim to deal with both data collection and recharging depleted ground Internet-of-Things (IoT) devices through a UAV station used as a flying base station...
May 11, 2018: Sensors
Dongyan Zhang, Xingen Zhou, Jian Zhang, Yubin Lan, Chao Xu, Dong Liang
Detection and monitoring are the first essential step for effective management of sheath blight (ShB), a major disease in rice worldwide. Unmanned aerial systems have a high potential of being utilized to improve this detection process since they can reduce the time needed for scouting for the disease at a field scale, and are affordable and user-friendly in operation. In this study, a commercialized quadrotor unmanned aerial vehicle (UAV), equipped with digital and multispectral cameras, was used to capture imagery data of research plots with 67 rice cultivars and elite lines...
2018: PloS One
Zhi Gao, Mingjie Lao, Yongsheng Sang, Fei Wen, Bharath Ramesh, Ruifang Zhai
Light detection and ranging (LiDAR) sensors have been widely deployed on intelligent systems such as unmanned ground vehicles (UGVs) and unmanned aerial vehicles (UAVs) to perform localization, obstacle detection, and navigation tasks. Thus, research into range data processing with competitive performance in terms of both accuracy and efficiency has attracted increasing attention. Sparse coding has revolutionized signal processing and led to state-of-the-art performance in a variety of applications. However, dictionary learning, which plays the central role in sparse coding techniques, is computationally demanding, resulting in its limited applicability in real-time systems...
May 6, 2018: Sensors
Sanaz Shafian, Nithya Rajan, Ronnie Schnell, Muthukumar Bagavathiannan, John Valasek, Yeyin Shi, Jeff Olsenholler
Unmanned Aerial Vehicles and Systems (UAV or UAS) have become increasingly popular in recent years for agricultural research applications. UAS are capable of acquiring images with high spatial and temporal resolutions that are ideal for applications in agriculture. The objective of this study was to evaluate the performance of a UAS-based remote sensing system for quantification of crop growth parameters of sorghum (Sorghum bicolor L.) including leaf area index (LAI), fractional vegetation cover (fc) and yield...
2018: PloS One
Seth T Sykora-Bodie, Vanessa Bezy, David W Johnston, Everette Newton, Kenneth J Lohmann
A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has been fixed in the paper.
April 19, 2018: Scientific Reports
Mohamed Hassanein, Zahra Lari, Naser El-Sheimy
Over the last decade, the use of unmanned aerial vehicle (UAV) technology has evolved significantly in different applications as it provides a special platform capable of combining the benefits of terrestrial and aerial remote sensing. Therefore, such technology has been established as an important source of data collection for different precision agriculture (PA) applications such as crop health monitoring and weed management. Generally, these PA applications depend on performing a vegetation segmentation process as an initial step, which aims to detect the vegetation objects in collected agriculture fields’ images...
April 18, 2018: Sensors
Weilong Zhang, Bingxuan Guo, Ming Li, Xuan Liao, Wenzhuo Li
Ghosting and seams are two major challenges in creating unmanned aerial vehicle (UAV) image mosaic. In response to these problems, this paper proposes an improved method for UAV image seam-line searching. First, an image matching algorithm is used to extract and match the features of adjacent images, so that they can be transformed into the same coordinate system. Then, the gray scale difference, the gradient minimum, and the optical flow value of pixels in adjacent image overlapped area in a neighborhood are calculated, which can be applied to creating an energy function for seam-line searching...
April 16, 2018: Sensors
João Flavio da Silveira Petruci, Andreas Wilk, Arnaldo Alves Cardoso, Boris Mizaikoff
Following the Kyoto protocol, all signatory countries must provide an annual inventory of greenhouse-gas emission including N2 O. This fact associated with the wide variety of sources for N2 O emissions requires appropriate sensor technologies facilitating in-situ monitoring, compact dimensions, ease of operation, and sufficient sensitivity for addressing such emission scenarios. In this contribution, we therefore describe an innovative portable mid-infrared chemical sensor system for quantifying gaseous N2 O via coupling a substrate-integrated hollow waveguide (iHWG) simultaneously serving as highly miniaturized mid-infrared photon conduit and gas cell to a custom-made preconcentrator...
April 12, 2018: Scientific Reports
Colin J Torney, Myles Lamont, Leon Debell, Ryan J Angohiatok, Lisa-Marie Leclerc, Andrew M Berdahl
Social interactions are a significant factor that influence the decision-making of species ranging from humans to bacteria. In the context of animal migration, social interactions may lead to improved decision-making, greater ability to respond to environmental cues, and the cultural transmission of optimal routes. Despite their significance, the precise nature of social interactions in migrating species remains largely unknown. Here we deploy unmanned aerial systems to collect aerial footage of caribou as they undertake their migration from Victoria Island to mainland Canada...
May 19, 2018: Philosophical Transactions of the Royal Society of London. Series B, Biological Sciences
Ali Bin Nadeem, Ysa Chandna
The majority of the Pakistani public has known little of the unmanned aerial vehicles, also known for their onomatopoeically inspired name "drones," except the fact that it regularly rains Hellfire missiles in Pakistan, claiming the lives of many innocent Pakistanis settled in the western provinces. In actuality, in addition to their destructive capacities, these remotely piloted vehicles have been used since the turn of the century in a variety of live-saving and risk-reducing roles. This research article primarily addresses the third stage of Emergency management-response, with Pakistan being the primary region of research...
January 2018: Journal of Emergency Management: JEM
J P T Lambert, H L Hicks, D Z Childs, R P Freckleton
Mapping weed densities within crops has conventionally been achieved either by detailed ecological monitoring or by field walking, both of which are time-consuming and expensive. Recent advances have resulted in increased interest in using Unmanned Aerial Systems (UAS) to map fields, aiming to reduce labour costs and increase the spatial extent of coverage. However, adoption of this technology ideally requires that mapping can be undertaken automatically and without the need for extensive ground-truthing. This approach has not been validated at large scale using UAS-derived imagery in combination with extensive ground-truth data...
February 2018: Weed Research
Charles Handford, F Reeves, P Parker
In order to continue to deliver outstanding medical care on the battlefield, the UK Defence Medical Services must continue to adapt, overcome and actively embrace change. One potential area is the rapid proliferation and sophistication of automated and remote systems such as unmanned aerial vehicles (UAVs). UAVs are already used to deliver blood to remote military locations in Afghanistan and defibrillators to those that need them in the USA and Sweden. An area of future opportunity would be to facilitate rapid evacuation of wounded personnel from high intensity, high threat, remote and austere areas directly to specialist care...
March 9, 2018: Journal of the Royal Army Medical Corps
F Morsdorf, D Kükenbrink, F D Schneider, M Abegg, M E Schaepman
Laser scanning with its unique measurement concept holds the potential to revolutionize the way we assess and quantify three-dimensional vegetation structure. Modern laser systems used at close range, be it on terrestrial, mobile or unmanned aerial platforms, provide dense and accurate three-dimensional data whose information just waits to be harvested. However, the transformation of such data to information is not as straightforward as for airborne and space-borne approaches, where typically empirical models are built using ground truth of target variables...
April 6, 2018: Interface Focus
Yi Zhao, Jiale Ma, Xiaohui Li, Jie Zhang
An unmanned aerial vehicle (UAV) equipped with global positioning systems (GPS) can provide direct georeferenced imagery, mapping an area with high resolution. So far, the major difficulty in wildfire image classification is the lack of unified identification marks, the fire features of color, shape, texture (smoke, flame, or both) and background can vary significantly from one scene to another. Deep learning (e.g., DCNN for Deep Convolutional Neural Network) is very effective in high-level feature learning, however, a substantial amount of training images dataset is obligatory in optimizing its weights value and coefficients...
February 27, 2018: Sensors
John Peterson, Haseeb Chaudhry, Karim Abdelatty, John Bird, Kevin Kochersberger
This work presents a collaborative unmanned aerial and ground vehicle system which utilizes the aerial vehicle's overhead view to inform the ground vehicle's path planning in real time. The aerial vehicle acquires imagery which is assembled into a orthomosaic and then classified. These terrain classes are used to estimate relative navigation costs for the ground vehicle so energy-efficient paths may be generated and then executed. The two vehicles are registered in a common coordinate frame using a real-time kinematic global positioning system (RTK GPS) and all image processing is performed onboard the unmanned aerial vehicle, which minimizes the data exchanged between the vehicles...
February 20, 2018: Sensors
Mohammad Ammad Uddin, Ali Mansour, Denis Le Jeune, Mohammad Ayaz, El-Hadi M Aggoune
In this study, a crop health monitoring system is developed by using state of the art technologies including wireless sensors and Unmanned Aerial Vehicles (UAVs). Conventionally data is collected from sensor nodes either by fixed base stations or mobile sinks. Mobile sinks are considered a better choice nowadays due to their improved network coverage and energy utilization. Usually, the mobile sink is used in two ways: either it goes for random walk to find the scattered nodes and collect data, or follows a pre-defined path established by the ground network/clusters...
February 11, 2018: Sensors
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