Overview of Sensor Technologies Used for 3D Localization of Asparagus Spears for Robotic Harvesting

2018 ◽  
Vol 884 ◽  
pp. 77-85 ◽  
Author(s):  
Matthew Peebles ◽  
Shen Hin Lim ◽  
Mike Duke ◽  
Chi Kit Au
Keyword(s):  
Response Times ◽  
Time Of Flight ◽  
High Sensitivity ◽  
Microsoft Kinect ◽  
Robust Detection ◽  
Ambient Lighting ◽  
General Decline ◽  
Detection And Localization ◽  
Robotic Harvesting ◽  
Detection Technologies

Advances in agricultural automation, coupled with a general decline of available labour hasgenerated interest in automated harvesting of various crops. Paramount to the success of such systemsis the development of accurate, robust detection technologies and localization strategies. This paperpresents an overview of sensor technologies used in the detection and localization of green aspara-gus spears for robotic harvesting. Tactile, photoelectric, machine vision and time-of-flight sensors areinvestigated and their applicability for use in robotic asparagus harvesting is evaluated. Investigationof previous asparagus harvesting devices has revealed that no such device has yet achieved commer-cial viability. It was identified that this is likely due to weaknesses in currently employed detectiontechnologies, namely slow response times, high sensitivity to changes in ambient lighting conditionsand requirement for frequent manual calibration. Of the sensor technologies investigated it was foundthat time-of-flight cameras, such as the Microsoft Kinect V2 are the most feasible for the detectionof asparagus spears for robotic harvesting. It was concluded that further research would be conductedinto the application of such sensors into a commercially viable harvester.

scholarly journals Mid-infrared photoacoustic gas monitoring driven by a gas-filled hollow-core fiber laser

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yazhou Wang ◽  
Yuyang Feng ◽  
Abubakar I. Adamu ◽  
Manoj K. Dasa ◽  
J. E. Antonio-Lopez ◽  
...  
Keyword(s):  
Fiber Laser ◽  
Signal To Noise Ratio ◽  
High Sensitivity ◽  
Laser Source ◽  
High Signal ◽  
Mid Infrared ◽  
Raman Fiber Laser ◽  
Custom Made ◽  
Core Fiber ◽  
Detection Technologies

AbstractDevelopment of novel mid-infrared (MIR) lasers could ultimately boost emerging detection technologies towards innovative spectroscopic and imaging solutions. Photoacoustic (PA) modality has been heralded for years as one of the most powerful detection tools enabling high signal-to-noise ratio analysis. Here, we demonstrate a novel, compact and sensitive MIR-PA system for carbon dioxide (CO2) monitoring at its strongest absorption band by combining a gas-filled fiber laser and PA technology. Specifically, the PA signals were excited by a custom-made hydrogen (H2) based MIR Raman fiber laser source with a pulse energy of ⁓ 18 μJ, quantum efficiency of ⁓ 80% and peak power of ⁓ 3.9 kW. A CO2 detection limit of 605 ppbv was attained from the Allan deviation. This work constitutes an alternative method for advanced high-sensitivity gas detection.

Capacitive Humidity Sensors With High Sensitivity and Subsecond Response Times

2007 ◽  
Vol 7 (6) ◽  
pp. 955-956 ◽  
Author(s):  
John J. Steele ◽  
Glen A. Fitzpatrick ◽  
Michael J. Brett
Keyword(s):  
Response Times ◽  
High Sensitivity ◽  
Humidity Sensors

Evaluation Humidity Sensing Properties of Graphene/HS-TiO2 Nanocomposites

2021 ◽  
Vol 21 (10) ◽  
pp. 5143-5149
Author(s):  
Zhen Zhu ◽  
Wang-De Lin
Keyword(s):  
Room Temperature ◽  
Response Times ◽  
Sol Gel ◽  
Hollow Spheres ◽  
High Sensitivity ◽  
Humidity Sensing ◽  
X Ray ◽  
Transmission Electron ◽  
Recovery Times ◽  
Relative Humidity Range

This paper reports on a nanocomposite synthesized by sol–gel procedure comprising graphene sheets with hollow spheres of titanium dioxide (G/HS-TiO2) with varying weight percentages of graphene for the purpose of humidity sensors. The surface morphology of the nanocomposite was characterized using transmission electron microscopy (TEM) and energy dispersive X-ray spectroscopy (EDX). The structural properties were examined using X-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR). The response to 12–80% RH at room temperature exhibited sensitivity (S = 135). However, the relative humidity range of 12–90% at room temperature exhibited higher sensitivity (S = 557). Sensors fabricated using the proposed nanocomposite exhibited high sensitivity to humidity, high stability, rapid response times, and rapid recovery times with hysteresis error of less than 1.79%. These results demonstrate the outstanding potential of his material for the monitoring of atmospheric humidity. This study also sought to elucidate the mechanisms underlying humidity sensing performance.

scholarly journals RT-dPCR in Mosquito Samples for ZIKV Detection: Effects of RNA Extraction and Reverse Transcription in Target Concentration

Viruses ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 827
Author(s):  
Paula Rodrigues de Almeida ◽  
Ana Karolina Antunes Eisen ◽  
Meriane Demoliner ◽  
Fernando Rosado Spilki
Keyword(s):  
Reverse Transcription ◽  
Tissue Concentration ◽  
Critical Role ◽  
Rna Extraction ◽  
High Sensitivity ◽  
Clinical Samples ◽  
Assay Sensitivity ◽  
Robust Detection ◽  
Detection Techniques ◽  
Mosquito Pool

Zika virus (ZIKV) is an important arbovirus, responsible for recent outbreaks of Guillain Barré Syndrome and Congenital Zika Syndrome (CZS). After thousands of CZS cases, ZIKV is under constant surveillance in Brazil. Reliable and robust detection techniques are required to minimize the influence of host inhibitors from clinical samples and mosquito pool samples. Reverse transcription Digital Polymerase Chain Reaction (RT-dPCR) is a technique that allows the accurate quantification of DNA targets with high sensitivity, and it is usually less affected by inhibitors than RT-qPCR. This study aimed to assess the influence of mosquito tissue, RNA extraction and cDNA synthesis in ZIKV PCR detection. Samples containing 0, 3 and 10 mosquitoes were spiked with ZIKV MR766 and serially diluted prior to RNA extraction and RT-dPCR for ZIKV. Two reverse transcription protocols were tested. Assay sensitivity allowed the detection of 1.197 copies/µL. A higher correlation between dilution factor and target quantification was observed in 10 mosquito pool samples. The lower quantification in samples diluted without mosquitoes highlights the critical role of the reverse transcription step in RNA detection, since it could be attributed to reverse transcriptase variable performance in samples with low overall RNA concentration. The results in mosquito pools indicate that mosquito tissues do not inhibit ZIKV RT-dPCR, and the RT-dPCR technique has good sensitivity and robustness for ZIKV detection in mosquito pool samples regardless of mosquito tissue concentration.

scholarly journals Towards a hand-held, fast, and sensitive gas chromatograph-ion mobility spectrometer for detecting volatile compounds

2020 ◽  
Author(s):  
André Ahrens ◽  
Stefan Zimmermann
Keyword(s):  
Gas Phase ◽  
Ion Mobility ◽  
Atmospheric Pressure ◽  
Response Times ◽  
Atmospheric Pressure Chemical Ionization ◽  
Real Life ◽  
High Sensitivity ◽  
Resolving Power ◽  
Gas Chromatograph ◽  
Ionization Processes

AbstractIon mobility spectrometers can detect gaseous compounds at atmospheric pressure in the range of parts per trillion within a second. Due to their fast response times, high sensitivity, and limited instrumental effort, they are used in a variety of applications, especially as mobile or hand-held devices. However, most real-life samples are gas mixtures, which can pose a challenge for IMS with atmospheric pressure chemical ionization mainly due to competing gas-phase ionization processes. Therefore, we present a miniaturized drift tube IMS coupled to a compact gas chromatograph for pre-separation, built of seven bundled standard GC columns (Rtx-Volatiles, Restek GmbH) with 250 μm ID and 1.07 m in length. Such pre-separation significantly reduces chemical cross sensitivities caused by competing gas-phase ionization processes and adds orthogonality. Our miniaturized GC-IMS system is characterized with alcohols, halocarbons, and ketones as model substances, reaching detection limits down to 70 pptv with IMS averaging times of just 125 ms. It separates test mixtures of ketones and halocarbons within 180 s and 50 s, respectively. The IMS has a short drift length of 40.6 mm and reaches a high resolving power of RP = 68.

scholarly journals Defects Detection and Localization in Underwater Plates Using Laser Laterally Generated Pure Non-Dispersive S0 Mode

2019 ◽  
Vol 9 (3) ◽  
pp. 459 ◽  
Author(s):  
Qingnan Xie ◽  
Chenyin Ni ◽  
Zhonghua Shen
Keyword(s):  
Defect Detection ◽  
Lamb Waves ◽  
Mode Conversion ◽  
High Sensitivity ◽  
Laser Source ◽  
Dispersion Characteristics ◽  
High Attenuation ◽  
Corrosion Defects ◽  
Detection And Localization ◽  
Lateral Excitation

When working in humid environments, corrosion defects are easily produced in metallic plates. For defect detection in underwater plates, symmetric modes of Lamb waves are widely used because of their characteristics including long propagating distance and high sensitivity to defects. In this study, we extend our previous work by applying the laser laterally generated S0 mode to detection and localization of defects represented by artificial notches in an aluminum plate immersed in water. Pure non-dispersive S0 mode is generated in an underwater plate by lateral laser source irradiation and its fd (frequency·thickness) range is selected by theoretical calculation. Using this lateral excitation, the S0 mode is enhanced; meanwhile, the A0 mode is effectively suppressed. The mode-converted A0 mode from the incident S0 mode is used to detect and localize the defect. The results reveal a significantly improved capability to detect defects in an underwater plate using the laser laterally generated S0 mode, while that using A0 is limited due to its high attenuation. Furthermore, owing to the long propagating distance and the non-dispersion characteristics of the S0 generated by the lateral laser source, multiple defects can also be detected and localized according to the mode conversion at the defects.

High sensitivity, homogeneous particle-based immunoassay for thyrotropin (Multipact).

1988 ◽  
Vol 34 (9) ◽  
pp. 1749-1752 ◽  
Author(s):  
T A Wilkins ◽  
G Brouwers ◽  
J C Mareschal ◽  
C L Cambiaso
Keyword(s):  
Detection Limit ◽  
Present Method ◽  
High Sensitivity ◽  
Modular System ◽  
Clinical Samples ◽  
Good Precision ◽  
Binding Properties ◽  
Low Concentrations ◽  
Homogeneous Particle ◽  
Detection Technologies

Abstract We describe the first homogeneous, nonradioactive, high-sensitivity assay for human thyrotropin (TSH). The assay is based on particle immunoassay techniques, wherein 800-nm particles form the basis for the immunochemistry, delivery, and the detection technologies, respectively. Our assay also is the first to involve the use of fragmented monoclonal antibodies (to eliminate serum interferences) covalently coupled to particles without loss of their binding properties. Assays are performed in a semiautomated mode with use of a new modular system (Multipact). Equilibrium is reached in less than 2 h. Precision profile, sensitivity, and clinical studies indicate that the assay is accurate, has good precision at low concentrations, and that detection-limit characteristics compare well with those of a leading commercial high-sensitivity immunoradiometric assay (IRMA) for TSH. Dilution characteristics were satisfactory down to the assay's detection limit for a range of clinical samples. Correlation studies vs a reference IRMA method yielded the regression equation, present method = 0.976 (IRMA) + 0.002 milli-int. unit/L (r = 0.98), for 223 samples with TSH concentrations in the range 0 to 30 milli-int. units/L. For 40 samples with TSH less than or equal to 1.0 milli-int. unit/L it was: present method = 0.94 (IRMA) + 0.005 milli-int. unit/L (r = 0.96).

scholarly journals Performance evaluation of a new high-sensitivity time-of-flight clinical PET/CT system

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Li Huo ◽  
Nan Li ◽  
Heyu Wu ◽  
Wenjia Zhu ◽  
Haiqun Xing ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Time Of Flight ◽  
High Sensitivity ◽  
Pet Ct ◽  
Ct System

scholarly journals A PointNet-Based Solution for 3D Hand Gesture Recognition

Sensors ◽  
2020 ◽  
Vol 20 (11) ◽  
pp. 3226
Author(s):  
Radu Mirsu ◽  
Georgiana Simion ◽  
Catalin Daniel Caleanu ◽  
Ioana Monica Pop-Calimanu
Keyword(s):  
Neural Network ◽  
Gesture Recognition ◽  
Deep Neural Network ◽  
Three Dimensional ◽  
Time Of Flight ◽  
Hand Gesture Recognition ◽  
Microsoft Kinect ◽  
Hand Gesture ◽  
Volume Of Interest ◽  
Hand Segmentation

Gesture recognition is an intensively researched area for several reasons. One of the most important reasons is because of this technology’s numerous application in various domains (e.g., robotics, games, medicine, automotive, etc.) Additionally, the introduction of three-dimensional (3D) image acquisition techniques (e.g., stereovision, projected-light, time-of-flight, etc.) overcomes the limitations of traditional two-dimensional (2D) approaches. Combined with the larger availability of 3D sensors (e.g., Microsoft Kinect, Intel RealSense, photonic mixer device (PMD), CamCube, etc.), recent interest in this domain has sparked. Moreover, in many computer vision tasks, the traditional statistic top approaches were outperformed by deep neural network-based solutions. In view of these considerations, we proposed a deep neural network solution by employing PointNet architecture for the problem of hand gesture recognition using depth data produced by a time of flight (ToF) sensor. We created a custom hand gesture dataset, then proposed a multistage hand segmentation by designing filtering, clustering, and finding the hand in the volume of interest and hand-forearm segmentation. For comparison purpose, two equivalent datasets were tested: a 3D point cloud dataset and a 2D image dataset, both obtained from the same stream. Besides the advantages of the 3D technology, the accuracy of the 3D method using PointNet is proven to outperform the 2D method in all circumstances, even the 2D method that employs a deep neural network.

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