scholarly journals Advances in Drone Communications, State-of-the-Art and Architectures

Drones ◽  
2019 ◽  
Vol 3 (1) ◽  
pp. 21 ◽  
Author(s):  
Vishal Sharma

Unmanned aerial vehicle (UAV)-enabled networks and drone communications are emerging areas of research with a key focus on attaining high throughput, elongated range, and enhanced coverage over the existing networks [...]

2020 ◽  
Vol 12 (6) ◽  
pp. 998 ◽  
Author(s):  
GyuJin Jang ◽  
Jaeyoung Kim ◽  
Ju-Kyung Yu ◽  
Hak-Jin Kim ◽  
Yoonha Kim ◽  
...  

Utilization of remote sensing is a new wave of modern agriculture that accelerates plant breeding and research, and the performance of farming practices and farm management. High-throughput phenotyping is a key advanced agricultural technology and has been rapidly adopted in plant research. However, technology adoption is not easy due to cost limitations in academia. This article reviews various commercial unmanned aerial vehicle (UAV) platforms as a high-throughput phenotyping technology for plant breeding. It compares known commercial UAV platforms that are cost-effective and manageable in field settings and demonstrates a general workflow for high-throughput phenotyping, including data analysis. The authors expect this article to create opportunities for academics to access new technologies and utilize the information for their research and breeding programs in more workable ways.


2021 ◽  
Vol 296 ◽  
pp. 108231
Author(s):  
Fusang Liu ◽  
Pengcheng Hu ◽  
Bangyou Zheng ◽  
Tao Duan ◽  
Binglin Zhu ◽  
...  

2020 ◽  
Vol 11 ◽  
Author(s):  
Gregor Perich ◽  
Andreas Hund ◽  
Jonas Anderegg ◽  
Lukas Roth ◽  
Martin P. Boer ◽  
...  

Author(s):  
Mohammed S. Mayeed ◽  
Gabriel Darveau

In this study a gasoline powered hexa-copter unmanned aerial vehicle (UAV) has been designed as a solution to farmers’ need for a low cost, easy to maintain, long flight duration, and multi-purpose means of specific aerial applications for insecticides and herbicides. Application of herbicides and pesticides by airplane is an example of how farmers have used technology to improve their bottom line and overall quality of life. Fields can now be sprayed in under an hour instead of consuming an entire day. However, if a producer has noxious weeds in only a small area, fixed-wing aerial application cannot be used as it is only accurate enough to do an entire field. Currently there is no solution for small scale, accurate, aerial herbicide application to meet this need. The currently available Yamaha Rmax UAV costs a tremendous amount of money and also requires a lot of money to maintain. Though it may be useful in large scale aerial spraying on the farm land, it would not be used in targeted specific areas as it is not efficient in specific applications. The gasoline powered hexacopter UAV designed in this study is a low cost solution to farmers’ need for specific aerial applications of insecticides and herbicides. The UAV design can carry 2–3 gallons of herbicide (16.7–25.0 lbs.) for a flight time of more than 30 minutes without refueling. The design could be transported in a 60.3in × 56.7in pickup bed. Structural and fatigue analyses are performed on the complete structure using state of the art software SolidWorks Simulation. The minimum factor of safety is obtained to be 10 based on maximum von Mises stress failure criteria. Under normal conditions with an estimated commercial use of 100 cycles per day it is observed that the design would survive for about 13 years without any fatigue failure. A drop test analysis is performed to ensure the design can survive a 5 feet freefall and a frequency analysis is also performed to observe the critical natural frequency of the structure. Flow simulations are performed on the 6 propellers/blades model using state of the art software SolidWorks Flow Simulation to observe the effect of vorticity interactions on the lift force. The design has been reasonably optimized based on maximizing the lift force. With this new UAV design small scale and substantial farmers could afford a personal UAV for aerial applications with a small amount of capital whose absence hindered efficient and effective specific aerial application for many years.


2014 ◽  
Vol 494-495 ◽  
pp. 861-864
Author(s):  
Yi Peng Zhang ◽  
Ke Cai Cao

The reliability of unmanned aerial vehicles (UAVs) has caught the attention of many researchers in the past decades. This paper presents a review on the development and important issues of state-of-the-art researches in the field of fault detection and diagnosis (FDD) techniques. Faults on an individual unmanned aerial vehicle or a group of unmanned aerial vehicles are considered for providing an overall picture of fault detection and diagnosis approaches.


2021 ◽  
Vol 13 (6) ◽  
pp. 1187
Author(s):  
Rubén Rufo ◽  
Jose Miguel Soriano ◽  
Dolors Villegas ◽  
Conxita Royo ◽  
Joaquim Bellvert

The adaptability and stability of new bread wheat cultivars that can be successfully grown in rainfed conditions are of paramount importance. Plant improvement can be boosted using effective high-throughput phenotyping tools in dry areas of the Mediterranean basin, where drought and heat stress are expected to increase yield instability. Remote sensing has been of growing interest in breeding programs since it is a cost-effective technology useful for assessing the canopy structure as well as the physiological traits of large genotype collections. The purpose of this study was to evaluate the use of a 4-band multispectral camera on-board an unmanned aerial vehicle (UAV) and ground-based RGB imagery to predict agronomic traits as well as quantify the best estimation of leaf area index (LAI) in rainfed conditions. A collection of 365 bread wheat genotypes, including 181 Mediterranean landraces and 184 modern cultivars, was evaluated during two consecutive growing seasons. Several vegetation indices (VI) derived from multispectral UAV and ground-based RGB images were calculated at different image acquisition dates of the crop cycle. The modified triangular vegetation index (MTVI2) proved to have a good accuracy to estimate LAI (R2 = 0.61). Although the stepwise multiple regression analysis showed that grain yield and number of grains per square meter (NGm2) were the agronomic traits most suitable to be predicted, the R2 were low due to field trials were conducted under rainfed conditions. Moreover, the prediction of agronomic traits was slightly better with ground-based RGB VI rather than with UAV multispectral VIs. NDVI and GNDVI, from multispectral images, were present in most of the prediction equations. Repeated measurements confirmed that the ability of VIs to predict yield depends on the range of phenotypic data. The current study highlights the potential use of VI and RGB images as an efficient tool for high-throughput phenotyping under rainfed Mediterranean conditions.


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