An Open-Sourced Web Application for Aerial Applicators to Avoid Spray Drift Caused by Temperature Inversion

2021 ◽  
Vol 37 (1) ◽  
pp. 77-84
Author(s):  
Yanbo Huang ◽  
D. K. Fisher
Keyword(s):  
Open Source ◽  
Web Application ◽  
Mississippi Delta ◽  
Temperature Inversion ◽  
Weather Data ◽  
List Type ◽  
Spray Drift ◽  
Atmospheric Conditions ◽  
Weather Stations ◽  
Open Source Hardware

HighlightsA web application for guiding data calculated from distributed weather data through open-source cloud service.A design scheme of portable weather stations built from inexpensive open-source electronics.Integration of open-source hardware and software for online guiding data to avoid drift caused by temperature inversion.Abstract. It is important for agricultural chemical applicators to follow proper spray procedures to prevent susceptible crops, animals, people, or other living organisms from being injured far downwind. Spraying during stable atmospheric conditions should be avoided to prevent surface-temperature inversion-induced off-target drift of crop protection materials. Previous statistical analysis determined times of high likelihood of stable atmospheric conditions, which are unfavorable for spraying, during the day under clear and cloudy conditions in hot summer months in the Mississippi Delta. Results validated the thresholds of temperature increase in the morning and temperature drop in the afternoon with wind speeds and the transition between stable and unstable atmospheric conditions. With this information, an algorithm was developed to calculate if atmospheric conditions were favorable for spraying based on field temperature and wind speed at any instant. With this algorithm, a web application was built to provide real-time determination of atmospheric stability and hourly online recommendation of whether aerial applications were appropriate for a location and time in the Mississippi Delta. This study further developed another web application specifically for Stoneville, Mississippi, with data measured from weather stations constructed from inexpensive open-source electronics, accessories, and software for more accurate online guidance for site-specific drift management. The web application is adapted for accessing on mobile terminals, such as smartphones and tablets, and provides timely guidance for aerial applicators and producers to avoid spray drift and air quality issues long distances downwind in the area. Keywords: Open-source hardware, Open-source software, Spray drift, Temperature inversion, Web application.

A Real-time Web Tool for Safe Aerial Application to Avoid Off-target Movement of Spray Induced by Stable Atmospheric Conditions in the Mississippi Delta

2019 ◽  
Vol 35 (1) ◽  
pp. 31-38
Author(s):  
Yanbo Huang ◽  
Daniel K Fisher ◽  
Mark Silva ◽  
Steven J Thomson
Keyword(s):  
Real Time ◽  
Web Application ◽  
Mississippi Delta ◽  
Crop Protection ◽  
Atmospheric Stability ◽  
Temperature Inversion ◽  
Crop Damage ◽  
Atmospheric Conditions ◽  
Aerial Application ◽  
Target Movement

Abstract. Susceptible crops can be injured far downwind if proper application spray procedure is not followed. Avoidance of stable atmospheric conditions while spraying is important to prevent surface temperature inversion-induced off-target drift of crop protection materials. Our previous studies consistently indicated high likelihood (>90%) of stable atmospheric conditions (unfavorable for spraying) primarily between the hours of 6:00 pm and 6:00 am during clear conditions in the hot summer months at the Mississippi Delta. With the requirement of timely farm operations, a web application has been developed to provide real-time determination of atmospheric stability and to recommend whether aerial applications are appropriate for a particular location and time. An algorithm was developed to determine atmospheric conditions likely for occurrence of a temperature inversion. This algorithm was programmed using the Python programming language and uploaded to an internet-cloud application platform for publication via HTML. The algorithm calculates the potential of a temperature inversion every hour based on air temperature and wind speed data measured at weather stations deployed over the Mississippi Delta and surrounding areas. The web application is adapted for mobile terminals, such as smartphones and tablets, and can provide timely guidance for aerial applicators and producers to avoid crop damage and air quality issues long distances downwind. Keywords: Aerial application, Spray drift, Temperature inversion, Atmospheric stability, Crop protection, Web application, Mobile terminal.

scholarly journals Democratising “Microscopi”: a 3D printed automated XYZT fluorescence imaging system for teaching, outreach and fieldwork

2020 ◽  
Author(s):  
Matthew Wincott ◽  
Andrew Jefferson ◽  
Ian M. Dobbie ◽  
Martin J. Booth ◽  
Ilan Davis ◽  
...  
Keyword(s):  
Open Source ◽  
Fluorescence Imaging ◽  
Imaging System ◽  
Low Cost ◽  
Dark Field ◽  
List Type ◽  
Image Capture ◽  
Fluorescence Imaging System ◽  
3D Printed ◽  
Open Source Hardware

ABSTRACTCommercial fluorescence microscope stands and fully automated XYZt fluorescence imaging systems are generally beyond the limited budgets available for teaching and outreach. We have addressed this problem by developing “Microscopi”, an accessible, affordable, DIY automated imaging system that is built from 3D printed and commodity off-the-shelf hardware, including electro-mechanical, computer and optical components. Our design features automated sample navigation and image capture with a simple web-based graphical user interface, accessible with a tablet or other mobile device. The light path can easily be switched between different imaging modalities. The open source Python-based control software allows the hardware to be driven as an integrated imaging system. Furthermore, the microscope is fully customisable, which also enhances its value as a learning tool. Here, we describe the basic design and demonstrate imaging performance for a range of easily sourced specimens.HighlightsPortable, low cost, self-build from 3D printed and commodity componentsMultimodal imaging: bright field, dark field, pseudo-phase and fluorescenceAutomated XYZt imaging from a tablet or smartphone via a simple GUIWide ranging applications in teaching, outreach and fieldworkOpen source hardware and software design, allowing user modification

scholarly journals An open-source experimental framework for automation of cell biology experiments

2020 ◽  
Author(s):  
Pavel Katunin ◽  
Ashley Cadby ◽  
Anton Nikolaev
Keyword(s):  
Open Source ◽  
Cell Biology ◽  
Biological Data ◽  
List Type ◽  
Fluorescent Reporters ◽  
Fluorescent Microscope ◽  
Treatment Conditions ◽  
Key Points ◽  
Open Source Hardware ◽  
High Degree

AbstractModern data analysis methods, such as deep learning, have been successfully applied to a number of biological and medical questions. For these methods to be efficient, a large number of high quality experiments need to be conducted, which requires a high degree of automation. Here we report an open-source hardware that allows for automatic high-throughput generation of large amounts of biological data. The hardware consists of an automatic XY-stage for moving multiwell plates containing growing cells; a perfusion manifold allowing application (perfusion) of up to 8 different solutions; and a small epifluorescent microscope. It is extremely cheap (£300 without and £2500 with a fluorescent microscope) and can be quickly customised for individual experimental needs.Key points- We present an open source framework for automation of cell biology experiments- The framework consists of an XY platform, application of up to 8 solutions and a small epifluorescent microscope- Very cheap (£300 without a fluorescent microscope and £2500 with a fluorescent microscope), customisable, 3D printable- Can be used in a variety of biological applications such as imaging of fluorescent reporters, optimisation of treatment conditions and immuno-labelling

Open-source hardware and software and web application for gamma dose rate network operation

2014 ◽  
Vol 160 (4) ◽  
pp. 252-258 ◽  
Author(s):  
R. Luff ◽  
M. Zahringer ◽  
W. Harms ◽  
M. Bleher ◽  
B. Prommer ◽  
...  
Keyword(s):  
Dose Rate ◽  
Open Source ◽  
Web Application ◽  
Gamma Dose ◽  
Gamma Dose Rate ◽  
Network Operation ◽  
Open Source Hardware

ON METHODS OF OBJECT DETECTION IN VIDEO STREAMS

2017 ◽  
Vol 2 (1) ◽  
pp. 80-87
Author(s):  
Puyda V. ◽  
◽  
Stoian. A.
Keyword(s):  
Computer Vision ◽  
Object Detection ◽  
Open Source ◽  
Feature Detection ◽  
Video Stream ◽  
Object Identification ◽  
Vision Systems ◽  
Modern Computer ◽  
Computer Vision Systems ◽  
Open Source Hardware

Detecting objects in a video stream is a typical problem in modern computer vision systems that are used in multiple areas. Object detection can be done on both static images and on frames of a video stream. Essentially, object detection means finding color and intensity non-uniformities which can be treated as physical objects. Beside that, the operations of finding coordinates, size and other characteristics of these non-uniformities that can be used to solve other computer vision related problems like object identification can be executed. In this paper, we study three algorithms which can be used to detect objects of different nature and are based on different approaches: detection of color non-uniformities, frame difference and feature detection. As the input data, we use a video stream which is obtained from a video camera or from an mp4 video file. Simulations and testing of the algoritms were done on a universal computer based on an open-source hardware, built on the Broadcom BCM2711, quad-core Cortex-A72 (ARM v8) 64-bit SoC processor with frequency 1,5GHz. The software was created in Visual Studio 2019 using OpenCV 4 on Windows 10 and on a universal computer operated under Linux (Raspbian Buster OS) for an open-source hardware. In the paper, the methods under consideration are compared. The results of the paper can be used in research and development of modern computer vision systems used for different purposes. Keywords: object detection, feature points, keypoints, ORB detector, computer vision, motion detection, HSV model color

Prediction of aircraft estimated time of arrival using machine learning methods

2021 ◽  
pp. 1-15
Author(s):  
O. Basturk ◽  
C. Cetek
Keyword(s):  
Machine Learning ◽  
Web Application ◽  
Absolute Error ◽  
Machine Learning Algorithms ◽  
Weather Data ◽  
Time Of Arrival ◽  
Learning Models ◽  
Trajectory Data ◽  
Different Sources ◽  
Machine Learning Models

ABSTRACT In this study, prediction of aircraft Estimated Time of Arrival (ETA) is proposed using machine learning algorithms. Accurate prediction of ETA is important for management of delay and air traffic flow, runway assignment, gate assignment, collaborative decision making (CDM), coordination of ground personnel and equipment, and optimisation of arrival sequence etc. Machine learning is able to learn from experience and make predictions with weak assumptions or no assumptions at all. In the proposed approach, general flight information, trajectory data and weather data were obtained from different sources in various formats. Raw data were converted to tidy data and inserted into a relational database. To obtain the features for training the machine learning models, the data were explored, cleaned and transformed into convenient features. New features were also derived from the available data. Random forests and deep neural networks were used to train the machine learning models. Both models can predict the ETA with a mean absolute error (MAE) less than 6min after departure, and less than 3min after terminal manoeuvring area (TMA) entrance. Additionally, a web application was developed to dynamically predict the ETA using proposed models.

scholarly journals Evaluation of NASA POWER Reanalysis Products to Estimate Daily Weather Variables in a Hot Summer Mediterranean Climate

Agronomy ◽  
2021 ◽  
Vol 11 (6) ◽  
pp. 1207
Author(s):  
Gonçalo C. Rodrigues ◽  
Ricardo P. Braga
Keyword(s):  
Wind Speed ◽  
Bias Correction ◽  
Goodness Of Fit ◽  
Mediterranean Climate ◽  
Weather Data ◽  
Coefficient Of Determination ◽  
Mean Bias Error ◽  
Bias Error ◽  
Weather Variables ◽  
Weather Stations

This study aims to evaluate NASA POWER reanalysis products for daily surface maximum (Tmax) and minimum (Tmin) temperatures, solar radiation (Rs), relative humidity (RH) and wind speed (Ws) when compared with observed data from 14 distributed weather stations across Alentejo Region, Southern Portugal, with a hot summer Mediterranean climate. Results showed that there is good agreement between NASA POWER reanalysis and observed data for all parameters, except for wind speed, with coefficient of determination (R2) higher than 0.82, with normalized root mean square error (NRMSE) varying, from 8 to 20%, and a normalized mean bias error (NMBE) ranging from –9 to 26%, for those variables. Based on these results, and in order to improve the accuracy of the NASA POWER dataset, two bias corrections were performed to all weather variables: one for the Alentejo Region as a whole; another, for each location individually. Results improved significantly, especially when a local bias correction is performed, with Tmax and Tmin presenting an improvement of the mean NRMSE of 6.6 °C (from 8.0 °C) and 16.1 °C (from 20.5 °C), respectively, while a mean NMBE decreased from 10.65 to 0.2%. Rs results also show a very high goodness of fit with a mean NRMSE of 11.2% and mean NMBE equal to 0.1%. Additionally, bias corrected RH data performed acceptably with an NRMSE lower than 12.1% and an NMBE below 2.1%. However, even when a bias correction is performed, Ws lacks the performance showed by the remaining weather variables, with an NRMSE never lower than 19.6%. Results show that NASA POWER can be useful for the generation of weather data sets where ground weather stations data is of missing or unavailable.

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