scholarly journals A New Optical Sensor Based on Laser Speckle and Chemometrics for Precision Agriculture: Application to Sunflower Plant-Breeding

Sensors ◽  
2020 ◽  
Vol 20 (16) ◽  
pp. 4652
Author(s):  
Maxime Ryckewaert ◽  
Daphné Héran ◽  
Emma Faur ◽  
Pierre George ◽  
Bruno Grèzes-Besset ◽  
...  
Keyword(s):  
Precision Agriculture ◽  
Measurement Errors ◽  
Low Cost ◽  
Laser Speckle ◽  
Average Error ◽  
Accurate Information ◽  
Promising Tool ◽  
Cost Constraints ◽  
Speckle Patterns ◽  
Set Up

New instruments to characterize vegetation must meet cost constraints while providing accurate information. In this paper, we study the potential of a laser speckle system as a low-cost solution for non-destructive phenotyping. The objective is to assess an original approach combining laser speckle with chemometrics to describe scattering and absorption properties of sunflower leaves, related to their chemical composition or internal structure. A laser diode system at two wavelengths 660 nm and 785 nm combined with polarization has been set up to differentiate four sunflower genotypes. REP-ASCA was used as a method to analyze parameters extracted from speckle patterns by reducing sources of measurement error. First findings have shown that measurement errors are mostly due to unwilling residual specular reflections. Moreover, results outlined that the genotype significantly impacts measurements. The variables involved in genotype dissociation are mainly related to scattering properties within the leaf. Moreover, an example of genotype classification using REP-ASCA outcomes is given and classify genotypes with an average error of about 20%. These encouraging results indicate that a laser speckle system is a promising tool to compare sunflower genotypes. Furthermore, an autonomous low-cost sensor based on this approach could be used directly in the field.

scholarly journals Development of an Estimation Instrument of Acoustic Lens Properties for Medical Ultrasound Transducers

2017 ◽  
Vol 2017 ◽  
pp. 1-7 ◽  
Author(s):  
Hojong Choi ◽  
Jongseon Johnson Jeong ◽  
Jungsuk Kim
Keyword(s):  
Attenuation Coefficient ◽  
Cost Estimation ◽  
Measurement Errors ◽  
Low Cost ◽  
Accurate Information ◽  
Ultrasound Transducers ◽  
Medical Ultrasound ◽  
Acoustic Lens ◽  
Pass Through ◽  
Lens Material

In medical ultrasound transducers, the transmission mode (pass-through) approach has been used to estimate the characteristics of the acoustic lens. However, it is difficult to measure the acoustic lens properties with high precision because of human, systemic, or mechanical measurement errors. In this paper, we propose a low-cost estimation instrument for acoustic lens properties connected with a customized database. In the instrument, three-axis and one-axis transmitting and material fixtures accurately align the transmitting and receiving transducers separately. Through the developed instrument, we obtained a precise standard deviation of the attenuation coefficient and velocity of the acoustic lens material of 0.05 dB/cm and 2.62 m/s, respectively. Additionally, the simultaneous alignment between the fixtures is controllable with developed programs, thus generating very accurate information of the acoustic lens about the testing ultrasound transducer. In our instrument, the database could support users in managing the result data efficiently. User programs developed using LabVIEW provide the capability to obtain precise values of the attenuation coefficient and velocity, which represent the fundamental material characteristics of the acoustic lens of the medical ultrasound transducers. The developed review program of the customized database can also search the acoustic lens information and store the experimental results.

scholarly journals Terrain Analytics for Precision Agriculture with Automated Vehicle Sensors and Data Fusion

2021 ◽  
Vol 13 (5) ◽  
pp. 2905
Author(s):  
Wei Zhao ◽  
Tianxin Li ◽  
Bozhao Qi ◽  
Qifan Nie ◽  
Troy Runge
Keyword(s):  
Data Fusion ◽  
Precision Agriculture ◽  
Low Cost ◽  
Measurement Unit ◽  
Nutrient Runoff ◽  
Automated Vehicle ◽  
Terrain Attributes ◽  
Simulated Environments ◽  
Set Up ◽  
Vehicle Sensors

Precision agriculture aims to use minimal inputs to generate maximal yields by managing the plant and its environment at a discrete instead of a field level. This new farming methodology requires localized field data including topological terrain attributes, which influence irrigation, field moisture, nutrient runoff, soil compaction, and traction and stability for traversing agriculture machines. Existing research studies have used different sensors, such as distance sensors and cameras, to collect topological information, which may be constrained by energy cost, performance, price, etc. This study proposed a low-cost method to perform farmland topological analytics using sensor implementation and data processing. Inertial measurement unit sensors, which are widely used in automated vehicle study, and a camera are set up on a robot vehicle. Then experiments are conducted under indoor simulated environments that include five common topographies that would be encountered on farms, combined with validation experiments in a real-world field. A data fusion approach was developed and implemented to track robot vehicle movements, monitor the surrounding environment, and finally recognize the topography type in real time. The resulting method was able to clearly recognize topography changes. This low-cost and easy-mount method will be able to augment and calibrate existing mapping algorithms with multidimensional information. Practically, it can also achieve immediate improvement for the operation and path planning of large agricultural machines.

scholarly journals Smart System for Automated Irrigation Using Internet of Things Devices

2021 ◽  
pp. 1-10
Author(s):  
Rhuanito Soranz Ferrarezi ◽  
Tzu Wei Peng
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Data Transfer ◽  
Low Cost ◽  
The Internet ◽  
Online Application ◽  
Crop Field ◽  
Set Up ◽  
The Right ◽  
Python Programming

Precision agriculture involves applying artificial intelligence, computers, sensors, and automation to improve crop field productivity while monitoring environmental conditions to conserve soil, water, and other natural resources focusing on agricultural sustainability. Despite many applications in agriculture, data monitoring and recording technologies have limited use due to the price. Low-cost open-source systems, like the ones available with the Internet of things (IoT) world, can potentially be developed as a universal-fit and cloud-connected technology for multiple applications. We designed and built a basic data collecting system using a commercial standalone embedded computer with Python programming language, serial data interface (SDI)-12/analog sensor adaptor, and digital sensors to monitor soil moisture and transmit the data remotely. SDI-12 is a standard communication protocol that transfers digital sensor measurements to a data recorder. We set up a pilot study that automatically collected and uploaded the data into the Internet to allow remote data transfer and access. The system performed reliably over 1 week with potting soil under field conditions without maintenance and successfully recorded data in real-time. The volumetric water content ranged from 0.03 to 0.23 m3·m−3, dielectric permittivity from 3.3 to 18.9 (unitless), EC from 0.0 to 0.3 dS·m−1, and soil temperature from 20.7 to 44.8 °C. All the data were successfully collected and uploaded to the cloud every 20 min, allowing users to remotely monitor the data using a free online application. However, heavy rainfall and high insolation could damage the system through excessive moisture or overheating, requiring a waterproof and heavy-duty protection case. The ThingSpeak channel allows customizing to suit a user’s specific requirements or adding more features for further development, such as automated irrigation, which can improve irrigation and fertilization efficiency by applying water and fertilizers at the right time based on sensor readings.

scholarly journals Using prediction markets to estimate the reproducibility of scientific research

2015 ◽  
Vol 112 (50) ◽  
pp. 15343-15347 ◽  
Author(s):  
Anna Dreber ◽  
Thomas Pfeiffer ◽  
Johan Almenberg ◽  
Siri Isaksson ◽  
Brad Wilson ◽  
...  
Keyword(s):  
Temporal Dynamics ◽  
Scientific Discovery ◽  
Low Cost ◽  
Prediction Markets ◽  
Significant Finding ◽  
Prior Probabilities ◽  
Market Participants ◽  
Promising Tool ◽  
Scientific Results ◽  
Set Up

Concerns about a lack of reproducibility of statistically significant results have recently been raised in many fields, and it has been argued that this lack comes at substantial economic costs. We here report the results from prediction markets set up to quantify the reproducibility of 44 studies published in prominent psychology journals and replicated in the Reproducibility Project: Psychology. The prediction markets predict the outcomes of the replications well and outperform a survey of market participants’ individual forecasts. This shows that prediction markets are a promising tool for assessing the reproducibility of published scientific results. The prediction markets also allow us to estimate probabilities for the hypotheses being true at different testing stages, which provides valuable information regarding the temporal dynamics of scientific discovery. We find that the hypotheses being tested in psychology typically have low prior probabilities of being true (median, 9%) and that a “statistically significant” finding needs to be confirmed in a well-powered replication to have a high probability of being true. We argue that prediction markets could be used to obtain speedy information about reproducibility at low cost and could potentially even be used to determine which studies to replicate to optimally allocate limited resources into replications.

scholarly journals Rapid antimicrobial susceptibility test using spatiotemporal analysis of laser speckle dynamics of bacterial colonies

2019 ◽  
Author(s):  
SeungYun Han ◽  
Hojun No ◽  
YoonSeok Baek ◽  
Huijun Park ◽  
KyeoReh Lee ◽  
...  
Keyword(s):  
Bacterial Growth ◽  
Antimicrobial Susceptibility ◽  
Susceptibility Testing ◽  
Low Cost ◽  
Bacterial Species ◽  
Spatiotemporal Analysis ◽  
Laser Speckle ◽  
Antimicrobial Susceptibility Test ◽  
Speckle Patterns ◽  
Autocorrelation Value

ABSTRACTAntimicrobial susceptibility testing (AST) is crucial for providing appropriate choices and doses of antibiotics to patients. However, standard ASTs require a time-consuming incubation of about 16-20 h for visual accumulation of bacteria, limiting the use of AST for an early prescription. In this study, we propose a rapid AST based on laser speckle formation (LSF) that enables rapid detection of bacterial growth, with the same sample preparation protocol as in solid-based ASTs. The proposed method exploits the phenomenon that well-grown bacterial colonies serve as optical diffusers, which convert a plane-wave laser beam into speckles. The generation of speckle patterns indicates bacterial growth at given antibiotic concentrations. Speckle formation is evaluated by calculating the spatial autocorrelation of speckle images, and bacterial growth is determined by tracking the autocorrelation value over time. We demonstrated the performance of the proposed method for several combinations of bacterial species and antibiotics to achieve the AST in 2-4.5 hours. Furthermore, we also demonstrated the sensitivity of the technique for low bacterial density. The proposed method can be a powerful tool for rapid, simple, and low-cost AST.Abstract Figure

scholarly journals Low Cost Locating Method of Wireless Sensor Network in Precision Agriculture

2016 ◽  
Vol 16 (6) ◽  
pp. 123-132 ◽  
Author(s):  
Cunjiang Yu
Keyword(s):  
Wireless Sensor Network ◽  
Sensor Network ◽  
Precision Agriculture ◽  
Low Cost ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Average Error ◽  
Actual Application ◽  
Locating Error ◽  
Positioning Method

Abstract The wireless sensor network covers more scale with more sensor nodes for larger scale agriculture. The article describes improvement of DV-Hop Algorithm to locate the nodes with quadrilateral range positioning method, so that the difficulty of dilatation method in agriculture actual application to be solved. The analog test for the algorithm is conducted and is mainly developed for the average locating error with illustration and discussion on the proportion relations of average error, average connectivity and anchor nodes. According to the analog results, the algorithm obtains better effect on the average locating error, which improves the accuracy of the algorithm.

Development of a Capacitor Probe to Detect Subsurface Deterioration in Concrete

1997 ◽  
Vol 503 ◽  
Author(s):  
B. K. Diefenderfer ◽  
I. L. Al-Qadi ◽  
J. J. Yoho ◽  
S. M. Riad ◽  
A. Loulizi
Keyword(s):  
Dielectric Constant ◽  
Portland Cement ◽  
Electromagnetic Waves ◽  
Low Cost ◽  
Complex Dielectric Constant ◽  
Life Cycle Costs ◽  
Parallel Plates ◽  
Portland Cement Concrete ◽  
Cement Concrete ◽  
Set Up

ABSTRACTPortland cement concrete (PCC) structures deteriorate with age and need to be maintained or replaced. Early detection of deterioration in PCC (e.g., alkali-silica reaction, freeze/thaw damage, or chloride presence) can lead to significant reductions in maintenance costs. However, it is often too late to perform low-cost preventative maintenance by the time deterioration becomes evident. By developing techniques that would enable civil engineers to evaluate PCC structures and detect deterioration at early stages (without causing further damage), optimization of life-cycle costs of the constructed facility and minimization of disturbance to the facility users can be achieved.Nondestructive evaluation (NDE) methods are potentially one of the most useful techniques ever developed for assessing constructed facilities. They are noninvasive and can be performed rapidly. Portland cement concrete can be nondestructively evaluated by electrically characterizing its complex dielectric constant. The real part of the dielectric constant depicts the velocity of electromagnetic waves in PCC. The imaginary part, termed the “loss factor,” describes the conductivity of PCC and the attenuation of electromagnetic waves.Dielectric properties of PCC have been investigated in a laboratory setting using a parallel plate capacitor operating in the frequency range of 0.1 to 40.1MIHz. This capacitor set-up consists of two horizontal-parallel plates with an adjustable separation for insertion of a dielectric specimen (PCC). While useful in research, this approach is not practical for field implementation. A new capacitor probe has been developed which consists of two plates, located within the same horizontal plane, for placement upon the specimen to be tested. Preliminary results show that this technique is feasible and results are promising; further testing and evaluation is currently underway.

Fault Localization of Power-Ground Short via Signal Injection and Oscilloscope Technique

2010 ◽  
Author(s):  
Binh Nguyen
Keyword(s):  
Low Cost ◽  
Short Circuit ◽  
Fault Localization ◽  
Fault Isolation ◽  
Test Apparatus ◽  
Good Working ◽  
Signal Injection ◽  
Set Up ◽  
Non Destructive ◽  
Short Circuit Condition

Abstract For those attempting fault isolation on computer motherboard power-ground short issues, the optimal technique should utilize existing test equipment available in the debug facility, requiring no specialty equipment as well as needing a minimum of training to use effectively. The test apparatus should be both easy to set up and easy to use. This article describes the signal injection and oscilloscope technique which meets the above requirements. The signal injection and oscilloscope technique is based on the application of Ohm's law in a short-circuit condition. Two experiments were conducted to prove the effectiveness of these techniques. Both experiments simulate a short-circuit condition on the VCC3 power rail of a good working PC motherboard and then apply the signal injection and oscilloscope technique to localize the short. The technique described is a simple, low cost and non-destructive method that helps to find the location of the power-ground short quickly and effectively.

Optimum Design for the Frame of Open Type Abrasive Flow Polish Machine

2012 ◽  
Vol 497 ◽  
pp. 89-93
Author(s):  
Liang Liang Yuan ◽  
Ke Hua Zhang ◽  
Li Min
Keyword(s):  
Finite Element ◽  
Natural Frequency ◽  
Finite Element Methods ◽  
Optimization Design ◽  
Low Cost ◽  
Three Dimensional ◽  
Force Model ◽  
Optimization Analysis ◽  
Open Type ◽  
Set Up

In order to process heterotype hole of workpiece precisely, an open abrasive flow polish machine is designed, and the optimization design of machine frame is done for low cost. Firstly, basing on the parameters designed with traditional ways, three-dimensional force model is set up with the soft of SolidWorks. Secondly, the statics and modal analysis for machine body have been done in Finite element methods (FEM), and then the optimization analysis of machine frame has been done. At last, the model of rebuild machine frame has been built. Result shows that the deformation angle value of machine frame increased from 0.72′ to 1.001′, the natural frequency of the machine decreased from 75.549 Hz to 62.262 Hz, the weight of machine decreased by 74.178 Kg after optimization. It meets the strength, stiffness and angel stiffness requirement of machine, reduces the weight and cost of machine.

scholarly journals Satellite-Based Personal UV Dose Estimation

Atmosphere ◽  
2021 ◽  
Vol 12 (2) ◽  
pp. 268
Author(s):  
Todd C. Harris ◽  
Laurent Vuilleumier ◽  
Claudine Backes ◽  
Athanasios Nenes ◽  
David Vernez
Keyword(s):  
Measurement Errors ◽  
Low Cost ◽  
Public Health Research ◽  
Mobile App ◽  
Population Exposure ◽  
Dose Estimation ◽  
Annual Dose ◽  
Significant Step ◽  
Uv Dose ◽  
Dosimetry Measurement

Epidemiology and public health research relating to solar ultraviolet (UV) exposure usually relies on dosimetry to measure UV doses received by individuals. However, measurement errors affect each dosimetry measurement by unknown amounts, complicating the analysis of such measurements and their relationship to the underlying population exposure and the associated health outcomes. This paper presents a new approach to estimate UV doses without the use of dosimeters. By combining new satellite-derived UV data to account for environmental factors and simulation-based exposure ratio (ER) modelling to account for individual factors, we are able to estimate doses for specific exposure periods. This is a significant step forward for alternative dosimetry techniques which have previously been limited to annual dose estimation. We compare our dose estimates with dosimeter measurements from skiers and builders in Switzerland. The dosimetry measurements are expected to be slightly below the true doses due to a variety of dosimeter-related measurement errors, mostly explaining why our estimates are greater than or equal to the corresponding dosimetry measurements. Our approach holds much promise as a low-cost way to either complement or substitute traditional dosimetry. It can be applied in a research context, but is also fundamentally well-suited to be used as the basis for a dose-estimating mobile app that does not require an external device.

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