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unmanned aerial vehicle

Laura N Kloepper, Morgan Kinniry
Unmanned aerial vehicles (UAVs) are rising in popularity for wildlife monitoring, but direct recordings of animal vocalizations have not yet been accomplished, likely due to the noise generated by the UAV. Echolocating bats, especially Tadarida brasiliensis, are good candidates for UAV recording due to their high-speed, high-altitude flight. Here, we use a UAV to record the signals of bats during morning roost re-entry. We designed a UAV to block the noise of the propellers from the receiving microphone, and report on the characteristics of bioacoustic recordings from a UAV...
May 17, 2018: Scientific Reports
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
Farhan Aadil, Ali Raza, Muhammad Fahad Khan, Muazzam Maqsood, Irfan Mehmood, Seungmin Rho
Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy and the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time and inefficient routing. In this paper, we try to address both of these problems by means of efficient clustering. First, we adjust the transmission power of the UAVs by anticipating their operational requirements. Optimal transmission range will have minimum packet loss ratio (PLR) and better link quality, which ultimately save the energy consumed during communication...
May 3, 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
Zhong Liu, Xiaoguang Gao, Xiaowei Fu
In this paper, we mainly study a cooperative search and coverage algorithm for a given bounded rectangle region, which contains several unknown stationary targets, by a team of unmanned aerial vehicles (UAVs) with non-ideal sensors and limited communication ranges. Our goal is to minimize the search time, while gathering more information about the environment and finding more targets. For this purpose, a novel cooperative search and coverage algorithm with controllable revisit mechanism is presented. Firstly, as the representation of the environment, the cognitive maps that included the target probability map (TPM), the uncertain map (UM), and the digital pheromone map (DPM) are constituted...
May 8, 2018: Sensors
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
Chang Chun Li, Peng Chen, Guo Zheng Lu, Chun Yan Ma, Xiao Xiao Ma, Shuang Ting Wang
Nitrogen balance index (NBI) is one of the important indicators for crop growth. The high and low status of nitrogen can be quickly monitored by measuring NBI, which can provide accurate information of agricultural production and management. The relationship between NBI and original spectrum and derivative spectrum of infrared and near infrared wavelength from flowering to maturity stage was analyzed based on high definition digital image and hyperspectral data on unmanned aerial vehicles. Then, the sensitive bands were selected and the vegetation indexes were calculated...
April 2018: Ying Yong Sheng Tai Xue Bao, the Journal of Applied Ecology
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
Huasheng Huang, Jizhong Deng, Yubin Lan, Aqing Yang, Xiaoling Deng, Lei Zhang
Appropriate Site Specific Weed Management (SSWM) is crucial to ensure the crop yields. Within SSWM of large-scale area, remote sensing is a key technology to provide accurate weed distribution information. Compared with satellite and piloted aircraft remote sensing, unmanned aerial vehicle (UAV) is capable of capturing high spatial resolution imagery, which will provide more detailed information for weed mapping. The objective of this paper is to generate an accurate weed cover map based on UAV imagery. The UAV RGB imagery was collected in 2017 October over the rice field located in South China...
2018: PloS One
Jinshui Zhang, Bruno Basso, Richard F Price, Gregory Putman, Guanyuan Shuai
Distance between rows and plants are essential parameters that affect the final grain yield in row crops. This paper presents the results of research intended to develop a novel method to quantify the distance between maize plants at field scale using an Unmanned Aerial Vehicle (UAV). Using this method, we can recognize maize plants as objects and calculate the distance between plants. We initially developed our method by training an algorithm in an indoor facility with plastic corn plants. Then, the method was scaled up and tested in a farmer's field with maize plant spacing that exhibited natural variation...
2018: PloS One
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
Celia Seguin, Gilles Blaquière, Anderson Loundou, Pierre Michelet, Thibaut Markarian
BACKGROUND: Drowning literature have highlighted the submersion time as the most powerful predictor in assessing the prognosis. Reducing the time taken to provide a flotation device and prevent submersion appears of paramount importance. Unmanned aerial vehicles (UAVs) can provide the location of the swimmer and a flotation device. OBJECTIVE: The objective of this simulation study was to evaluate the efficiency of a UAV in providing a flotation device in different sea conditions, and to compare the times taken by rescue operations with and without a UAV (standard vs UAV intervention)...
April 10, 2018: Resuscitation
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
Thi-Dieu-Hien Vo, Chitsan Lin, Chien-Erh Weng, Chung-Shin Yuan, Chia-Wei Lee, Chung-Hsuang Hung, Xuan-Thanh Bui, Kuo-Cheng Lo, Jun-Xian Lin
High emissions of volatile organic compounds (VOCs) from the petrochemical industry and vehicle exhaust may contribute to high ozone formation potential (OFP) and secondary organic aerosol formation potential (SOAFP). In this study, the vertical profiles of VOCs were created for the southern Taiwan industrial city of Kaohsiung. Vertical air samples were collected up to 1000 m using an unmanned aerial vehicle (UAV). In Renwu District, VOC distribution was affected by the inversion layer up to 200 m height...
March 31, 2018: Journal of Environmental Management
Jerry H Moxley, Andrea Bogomolni, Mike O Hammill, Kathleen M T Moore, Michael J Polito, Lisa Sette, W Brian Sharp, Gordon T Waring, James R Gilbert, Patrick N Halpin, David W Johnston
As the sampling frequency and resolution of Earth observation imagery increase, there are growing opportunities for novel applications in population monitoring. New methods are required to apply established analytical approaches to data collected from new observation platforms (e.g., satellites and unmanned aerial vehicles). Here, we present a method that estimates regional seasonal abundances for an understudied and growing population of gray seals (Halichoerus grypus) in southeastern Massachusetts, using opportunistic observations in Google Earth imagery...
August 1, 2017: Bioscience
Fuxiang Xu, Zhiqiang Gao, Xiaopeng Jiang, Weitao Shang, Jicai Ning, Debin Song, Jinquan Ai
Previous studies have shown that the initial biomass of green tide was the green algae attaching to Pyropia aquaculture rafts in the Southern Yellow Sea. In this study, the green algae was identified with unmanned aerial vehicle (UAV), an biomass estimation model was proposed for green algae biomass in the radial sand ridge area based on Sentinel-2A image (S2A) and UAV images. The result showed that the green algae was detected highly accurately with the normalized green-red difference index (NGRDI); approximately 1340 tons and 700 tons of green algae were attached to rafts and raft ropes respectively, and the lower biomass might be the main cause for the smaller scale of green tide in 2017...
March 2018: Marine Pollution Bulletin
Nuno C de Sá, Paula Castro, Sabrina Carvalho, Elizabete Marchante, Francisco A López-Núñez, Hélia Marchante
Invasion by alien species is a worldwide phenomenon with negative consequences at both natural and production areas. Acacia longifolia is an invasive shrub/small tree well known for its negative ecological impacts in several places around the world. The recent introduction of a biocontrol agent ( Trichilogaster acaciaelongifoliae ), an Australian bud-galling wasp which decreases flowering of A. longifolia , in Portugal, demands the development of a cost-efficient method to monitor its establishment. We tested how unmanned aerial vehicles (UAV) can be used to map A...
2018: Frontiers in Plant Science
Juan Sandino, Geoff Pegg, Felipe Gonzalez, Grant Smith
The environmental and economic impacts of exotic fungal species on natural and plantation forests have been historically catastrophic. Recorded surveillance and control actions are challenging because they are costly, time-consuming, and hazardous in remote areas. Prolonged periods of testing and observation of site-based tests have limitations in verifying the rapid proliferation of exotic pathogens and deterioration rates in hosts. Recent remote sensing approaches have offered fast, broad-scale, and affordable surveys as well as additional indicators that can complement on-ground tests...
March 22, 2018: Sensors
Zohaib Khan, Vahid Rahimi-Eichi, Stephan Haefele, Trevor Garnett, Stanley J Miklavcic
Background: Unmanned aerial vehicles offer the opportunity for precision agriculture to efficiently monitor agricultural land. A vegetation index (VI) derived from an aerially observed multispectral image (MSI) can quantify crop health, moisture and nutrient content. However, due to the high cost of multispectral sensors, alternate, low-cost solutions have lately received great interest. We present a novel method for model-based estimation of a VI using RGB color images. The non-linear spatio-spectral relationship between the RGB image of vegetation and the index computed by its corresponding MSI is learned through deep neural networks...
2018: Plant Methods
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