scholarly journals Assessment of the Accuracy of a Multi-Beam LED Scanner Sensor for Measuring Olive Canopies

Sensors ◽  
2018 ◽  
Vol 18 (12) ◽  
pp. 4406 ◽  
Author(s):  
Rafael Sola-Guirado ◽  
Sergio Bayano-Tejero ◽  
Antonio Rodríguez-Lizana ◽  
Jesús Gil-Ribes ◽  
Antonio Miranda-Fuentes

Canopy characterization has become important when trying to optimize any kind of agricultural operation in high-growing crops, such as olive. Many sensors and techniques have reported satisfactory results in these approaches and in this work a 2D laser scanner was explored for measuring canopy trees in real-time conditions. The sensor was tested in both laboratory and field conditions to check its accuracy, its cone width, and its ability to characterize olive canopies in situ. The sensor was mounted on a mast and tested in laboratory conditions to check: (i) its accuracy at different measurement distances; (ii) its measurement cone width with different reflectivity targets; and (iii) the influence of the target’s density on its accuracy. The field tests involved both isolated and hedgerow orchards, in which the measurements were taken manually and with the sensor. The canopy volume was estimated with a methodology consisting of revolving or extruding the canopy contour. The sensor showed high accuracy in the laboratory test, except for the measurements performed at 1.0 m distance, with 60 mm error (6%). Otherwise, error remained below 20 mm (1% relative error). The cone width depended on the target reflectivity. The accuracy decreased with the target density.

2006 ◽  
Vol 527-529 ◽  
pp. 1031-1034 ◽  
Author(s):  
K. Kakubari ◽  
R. Kuboki ◽  
Yasuto Hijikata ◽  
Hiroyuki Yaguchi ◽  
Sadafumi Yoshida

Real time observation of SiC oxidation was performed using an in-situ ellipsometer over the temperature range from 900°C to 1150°C. The relations between oxide thickness and oxidation time were obtained precisely by virtue of the real time measurements. We analyzed the relations between oxide thickness and oxidation time by applying the Deal and Grove model to obtain the linear and parabolic rate constants. Taking advantage of in-situ measurements, we successfully obtained the oxidation rate constants with high accuracy.


2017 ◽  
Vol 29 (4) ◽  
pp. 649-659 ◽  
Author(s):  
Ryohsuke Mitsudome ◽  
◽  
Hisashi Date ◽  
Azumi Suzuki ◽  
Takashi Tsubouchi ◽  
...  

In order for a robot to provide service in a real world environment, it has to navigate safely and recognize the surroundings. We have participated in Tsukuba Challenge to develop a robot with robust navigation and accurate object recognition capabilities. To achieve navigation, we have introduced the ROS packages, and the robot was able to navigate without major collisions throughout the challenge. For object recognition, we used both a laser scanner and camera to recognize a person in specific clothing, in real time and with high accuracy. In this paper, we evaluate the accuracy of recognition and discuss how it can be improved.


2013 ◽  
Vol 333-335 ◽  
pp. 1492-1495 ◽  
Author(s):  
Yan Ping Feng ◽  
Tian Zhu Zheng

Deformation monitoring is one of the engineering measurement tasks. Three-dimensional laser scanning technology as a new technology has developed in recent years. With its high accuracy, high density, real-time and initiative, it wins great favor of people in the industry. Its unique technical advantages and characteristics make it widely used in many fields. The article summarizes the application of deformation monitoring methods and discusses the characteristics of ground 3D laser scanner, its working principles, its application in the field of deformation monitoring and some problems that should be considered.


Author(s):  
S. Schraml ◽  
T. Hinterhofer ◽  
M. Pfennigbauer ◽  
M. Hofstätter

<p><strong>Abstract.</strong> In this work we propose an effective radiation source localization device employing a RIEGL VUX-1UAV laser scanner and a highly sensitive Hotzone Technologies gamma radiation probe mounted on a RiCOPTER UAV combined with real-time data processing. The on-board processing and radio communication system integrated within the UAV enables instant and continuously updated access to georeferenced 3D lidar point clouds and gamma radiation intensities. Further processing is done fully automated on the ground. We present a novel combination of both the 3D laser data and the gamma readings within an optimization algorithm that can locate the radioactive source in real-time. Furthermore, this technique can be used to estimate an on-ground radiation intensity, which also considers the actual topography as well as radiation barriers like vegetation or buildings. Results from field tests with real radioactive sources show that single sources can be located precisely, even if the source was largely covered. Outcomes are displayed to the person in charge in an intuitive and user-friendly way, e.g. on a tablet. The whole system is designed to operate in real-time and while the UAV is in the air, resulting in a highly flexible and possibly life-saving asset for firstresponders in time-critical scenarios.</p>


Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.


2018 ◽  
Author(s):  
Elaine A. Kelly ◽  
Judith E. Houston ◽  
Rachel Evans

Understanding the dynamic self-assembly behaviour of azobenzene photosurfactants (AzoPS) is crucial to advance their use in controlled release applications such as<i></i>drug delivery and micellar catalysis. Currently, their behaviour in the equilibrium <i>cis-</i>and <i>trans</i>-photostationary states is more widely understood than during the photoisomerisation process itself. Here, we investigate the time-dependent self-assembly of the different photoisomers of a model neutral AzoPS, <a>tetraethylene glycol mono(4′,4-octyloxy,octyl-azobenzene) </a>(C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>) using small-angle neutron scattering (SANS). We show that the incorporation of <i>in-situ</i>UV-Vis absorption spectroscopy with SANS allows the scattering profile, and hence micelle shape, to be correlated with the extent of photoisomerisation in real-time. It was observed that C<sub>8</sub>AzoOC<sub>8</sub>E<sub>4</sub>could switch between wormlike micelles (<i>trans</i>native state) and fractal aggregates (under UV light), with changes in the self-assembled structure arising concurrently with changes in the absorption spectrum. Wormlike micelles could be recovered within 60 seconds of blue light illumination. To the best of our knowledge, this is the first time the degree of AzoPS photoisomerisation has been tracked <i>in</i><i>-situ</i>through combined UV-Vis absorption spectroscopy-SANS measurements. This technique could be widely used to gain mechanistic and kinetic insights into light-dependent processes that are reliant on self-assembly.


2017 ◽  
Vol 2017 (4) ◽  
pp. 5598-5617
Author(s):  
Zhiheng Xu ◽  
Wangchi Zhou ◽  
Qiuchen Dong ◽  
Yan Li ◽  
Dingyi Cai ◽  
...  

2021 ◽  
Vol 11 (11) ◽  
pp. 4758
Author(s):  
Ana Malta ◽  
Mateus Mendes ◽  
Torres Farinha

Maintenance professionals and other technical staff regularly need to learn to identify new parts in car engines and other equipment. The present work proposes a model of a task assistant based on a deep learning neural network. A YOLOv5 network is used for recognizing some of the constituent parts of an automobile. A dataset of car engine images was created and eight car parts were marked in the images. Then, the neural network was trained to detect each part. The results show that YOLOv5s is able to successfully detect the parts in real time video streams, with high accuracy, thus being useful as an aid to train professionals learning to deal with new equipment using augmented reality. The architecture of an object recognition system using augmented reality glasses is also designed.


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