scholarly journals Optimizing precision agricultural operations by standardized cloud-based functions

2021 ◽  
Vol 19 (4) ◽  
pp. e0212-e0212
Author(s):  
Markus Jackenkroll ◽  
Keyword(s):  
Precision Agriculture ◽  
Relevant Information ◽  
Research Station ◽  
Data Sampling ◽  
It Infrastructure ◽  
Software Products ◽  
Actual Application ◽  
Starting Point ◽  
Open Geospatial Consortium ◽  
On Farm

Aim of study: An approach to integrate knowledge into the IT-infrastructure of precision agriculture (PA) is presented. The creation of operation relevant information is analyzed and explored to be processed by standardized web services and thereby to integrate external knowledge into PA. The target is to make knowledge integrable into any software solution. Area of study: The data sampling took place at the Heidfeld Hof Research Station in Stuttgart, Germany. Material and methods: This study follows the information science’s idea to separate the process from data sampling into the final actuation through four steps: data, information, knowledge, and wisdom. The process from the data acquisition, over a professional data treatment to the actual application is analyzed by methods modelled in the Unified Modelling Language (UML) for two use-cases. It was further applied for a low altitude sensor in a PA operation; a data sampling by UAV represents the starting point. Main results: For the implemented solution, the Web Processing Service (WPS) of the Open Geospatial Consortium (OGC) is proposed. This approach reflects the idea of a function as a service (FaaS), in order to develop a demand-driven and extensible solution for irregularly used functionalities. PA benefits, as on-farm processes are season oriented and a FaaS reflects the farm’s variable demands over time by origin and extends the concept to offer external know-how for the integration into specific processes. Research highlights: The standardized implementation of knowledge into PA software products helps to generate additional benefits for PA.

scholarly journals Measuring Canopy Geometric Structure Using Optical Sensors Mounted on Terrestrial Vehicles: A Case Study in Vineyards

Agriculture ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 208
Author(s):  
Daniel Queirós da Silva ◽  
André Silva Aguiar ◽  
Filipe Neves dos Santos ◽  
Armando Jorge Sousa ◽  
Danilo Rabino ◽  
...  
Keyword(s):  
Leaf Area Index ◽  
Leaf Area ◽  
Optical Sensors ◽  
Precision Agriculture ◽  
Real Data ◽  
Relevant Information ◽  
Normal Operation ◽  
Area Index ◽  
Sensory Data ◽  
The Right

Smart and precision agriculture concepts require that the farmer measures all relevant variables in a continuous way and processes this information in order to build better prescription maps and to predict crop yield. These maps feed machinery with variable rate technology to apply the correct amount of products in the right time and place, to improve farm profitability. One of the most relevant information to estimate the farm yield is the Leaf Area Index. Traditionally, this index can be obtained from manual measurements or from aerial imagery: the former is time consuming and the latter requires the use of drones or aerial services. This work presents an optical sensing-based hardware module that can be attached to existing autonomous or guided terrestrial vehicles. During the normal operation, the module collects periodic geo-referenced monocular images and laser data. With that data a suggested processing pipeline, based on open-source software and composed by Structure from Motion, Multi-View Stereo and point cloud registration stages, can extract Leaf Area Index and other crop-related features. Additionally, in this work, a benchmark of software tools is made. The hardware module and pipeline were validated considering real data acquired in two vineyards—Portugal and Italy. A dataset with sensory data collected by the module was made publicly available. Results demonstrated that: the system provides reliable and precise data on the surrounding environment and the pipeline is capable of computing volume and occupancy area from the acquired data.

Numerical Analysis of the Deterministic Stresses Associated to Impeller-Tongue Interactions in a Single Volute Centrifugal Pump

2019 ◽  
Vol 141 (9) ◽  
Author(s):  
J. M. Fernández Oro ◽  
J. González ◽  
R. Barrio Perotti ◽  
M. Galdo Vega
Keyword(s):  
Numerical Analysis ◽  
Numerical Model ◽  
Centrifugal Pump ◽  
Turbulence Intensity ◽  
Three Dimensional ◽  
Relevant Information ◽  
Three Dimensional Flow ◽  
Deterministic Analysis ◽  
Starting Point ◽  
Flow Features

In this paper, a deterministic stress decomposition is applied over the numerical three-dimensional flow solution available for a single volute centrifugal pump. The numerical model has proven in previous publications its robustness to obtain the impeller to volute-tongue flow interaction, and it is now used as starting point for the current research. The main objective has been oriented toward a detailed analysis of the lack of uniformity in the flow that the volute tongue promotes on the blade-to-blade axisymmetric pattern. Through this analysis, the fluctuation field may be retrieved and main interaction sources have been pinpointed. The results obtained with the deterministic analysis become of paramount interest to understand the different flow features found in a typical centrifugal pump as a function of the flow rate. Moreover, this postprocessing tool provides an economic and easy procedure for designers to compare the different deterministic terms, also giving relevant information on the unresolved turbulence intensity scales. Complementarily, a way to model the turbulent effects in a systematic way is also presented, comparing their impact on the performance with respect to deterministic sources in a useful framework, that may be applied for similar kinds of pumps.

scholarly journals BioTextRetriever

2011 ◽  
Vol 2 (3) ◽  
pp. 21-36 ◽  
Author(s):  
Célia Talma Gonçalves ◽  
Rui Camacho ◽  
Eugénio Oliveira
Keyword(s):  
Web Sites ◽  
Large Data ◽  
Relevant Information ◽  
Alignment Algorithm ◽  
Data Bases ◽  
Starting Point ◽  
Good Starting Point

Whenever new sequences of DNA or proteins have been decoded it is almost compulsory to look at similar sequences and papers describing those sequences in order to both collect relevant information concerning the function and activity of the new sequences and/or know what is known already about similar sequences. In current web sites and data bases of sequences there are, usually, a set of curated paper references linked to each sequence. Those links are a good starting point to look for relevant information related to a set of sequences. One way to implement such approach is to do a blast with the new decoded sequences, and collect similar sequences. Then one looks at the papers linked with the similar sequences. Most often the number of retrieved papers is small and one has to search large data bases for relevant papers. This paper proposes a process of generating a classifier based on the initially set of relevant papers. First, the authors collect similar sequences using an alignment algorithm like Blast. Then, the authors use the enlarges set of papers to construct a classifier. Finally a classifier is used to automatically enlarge the set of relevant papers by searching the MEDLINE using the automatically constructed classifier.

Introduction to Precision Agriculture

2021 ◽  
pp. 1-22
Author(s):  
Akalpita Tendulkar
Keyword(s):  
Precision Agriculture ◽  
Fertilizer Application ◽  
Farm Management ◽  
Global Positioning ◽  
Soil Variation ◽  
On Farm ◽  
Field Variability ◽  
Global Population ◽  
The Internet Of Things ◽  
Yield Monitoring

The global population is increasing at a tremendous speed; thus, the demand for safe and secure food to meet this population is in demand. Therefore, traditional farming methods are insufficient to meet this demand; thus, the next revolution in agriculture is required, which is Precision Agriculture (PA), the Fourth Agriculture Revolution. PA is a technology where the concept of farm management is based on observation, measuring, and responding to inter- and intra-field variability in crops. The technologies used for performing precision agriculture are mapping, global positioning system (GPS), yield monitoring and mapping, grid soil sampling application, variable-rate fertilizer application, remote sensing, geographic information systems (GIS), quantifying on farm variability, soil variation, variability of soil water content, time and space scales, robots, drones, satellite imagery, the internet of things, smartphone, and machine learning. Hence, the current chapter will be emphasizing the overview, concepts, history, world interest, benefits, disadvantages, and precision farming needs.

scholarly journals Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi

2020 ◽  
Vol 86 (2) ◽  
pp. 107-119 ◽  
Author(s):  
Brad G. Peter ◽  
Joseph P. Messina ◽  
Jon W. Carroll ◽  
Junjun Zhi ◽  
Vimbayi Chimonyo ◽  
...  
Keyword(s):  
Chlorophyll Content ◽  
Precision Agriculture ◽  
Strongly Correlated ◽  
Multispectral Images ◽  
Green Band ◽  
Smallholder Farms ◽  
On Farm ◽  
Linear Regressions ◽  
Crop Health ◽  
Sentinel 2

A collection of spectral indices, derived from a range of remote sensing imagery spatial resolutions, are compared to on-farm measurements of maize chlorophyll content and yield at two trial farms in central Malawi to evaluate what spatial resolutions are most effective for relating multispectral images with crop status. Single and multiple linear regressions were tested for spatial resolutions ranging from 7 cm to 20 m using a small unmanned aerial system (<small>sUAS</small>) and satellite imagery from Planet, <small>SPOT</small> 6, Pléiades, and Sentinel-2. Results suggest that imagery with spatial resolutions nearer the maize plant scale (i.e., 14–27 cm) are most effective for relating spectral signals with crop health on smallholder farms in Malawi. Consistent with other studies, green-band indices were more strongly correlated with maize chlorophyll content and yield than conventional red-band indices, and multivariable models often outperformed single variable models.

scholarly journals A bimodal extension of the Eriksen flanker task

2020 ◽  
Author(s):  
Rolf Ulrich ◽  
Laura Prislan ◽  
Jeff Miller
Keyword(s):  
Visual Target ◽  
Target Item ◽  
Flanker Task ◽  
Response Competition ◽  
Relevant Information ◽  
Irrelevant Information ◽  
Flanker Effect ◽  
Starting Point ◽  
Visual Targets ◽  
Task Irrelevant

Abstract The Eriksen flanker task is a traditional conflict paradigm for studying the influence of task-irrelevant information on the processing of task-relevant information. In this task, participants are asked to respond to a visual target item (e.g., a letter) that is flanked by task-irrelevant items (e.g., also letters). Responses are typically faster and more accurate when the task-irrelevant information is response-congruent with the visual target than when it is incongruent. Several researchers have attributed the starting point of this flanker effect to poor selective filtering at a perceptual level (e.g., spotlight models), which subsequently produces response competition at post-perceptual stages. The present study examined whether a flanker-like effect could also be established within a bimodal analog of the flanker task with auditory irrelevant letters and visual target letters, which must be processed along different processing routes. The results of two experiments revealed that a flanker-like effect is also present with bimodal stimuli. In contrast to the unimodal flanker task, however, the effect only emerged when flankers and targets shared the same letter name, but not when they were different letters mapped onto the same response. We conclude that the auditory flankers can influence the time needed to recognize visual targets but do not directly activate their associated responses.

Effects of summer irrigation and trampling in dairy pastures on soil physical properties and earthworm number and species composition

1997 ◽  
Vol 48 (7) ◽  
pp. 1059 ◽  
Author(s):  
Lisa A. Lobry de Bruyn ◽  
T. J. Kingston
Keyword(s):  
Soil Surface ◽  
Sampling Period ◽  
Study Data ◽  
Lumbricus Rubellus ◽  
Research Station ◽  
Pasture Production ◽  
North West ◽  
The North ◽  
Main Plot ◽  
On Farm

In 1989 a replicated split-plot trial on a Krasnozem soil was established at Elliott Research Station (ERS) in the north-west of Tasmania, as well as 14 on-farm trials in newly irrigated pastures on 3 different soil types (Alluvial, Podzolic, Krasnozem) in the dairy districts of Scottsdale, Smithton, and Deloraine. There were 3 main treatments at ERS: irrigated before grazing, irrigated after grazing, and grazed and not irrigated. Part of each main plot was fenced to prevent trampling but still allowed grazing. Effects of summer irrigation and trampling by dairy cows were examined for pasture production, and soil chemical and structural properties. Summer irrigation at ERS and on-farm trials has led to a decline in soil structure indicated by slower ponded water in filtration rates on irrigated plots compared with the dryland plots. The decline in ponded water in filtration rates suggests a reduction in macroporosity, especially in the soil surface. However, other indicators for soil structural change in the top 100 mm|percentage water-stable aggregates (>2·5 mm) and bulk density|revealed no significant variation between the irrigated and dryland paddocks. There were, however, higher water in filtration rates and lower bulk densities in the untrampled areas than the trampled areas at ERS. Pasture production at ERS was about 50% more with irrigation in each of the 2 years of the study. Data collected at ERS in autumn and spring on the numbers of Aporrectodea caliginosa(Savigny) and Lumbricus rubellus (Hoffmeister) earthworms showed that they respond quite differently to irrigation. After 2 irrigation seasons, A. caliginosa numbers in irrigated plots dropped by over 50%, whereas in the dryland plots densities of this earthworm have remained around 390 earthworms/m 2. In contrast the densities of L. rubellus at ERS rose under irrigation practices, especially in the autumn{winter sampling period. Therefore, with the advent of summer irrigation at ERS, there was a shift in earthworm composition from a fauna dominated by A. caliginosa to a fauna with an increasing proportion of L. rubellus and a decreasing number of A. caliginosa. The typical dairy pasture in the on-farm trials recorded 2 main species, A. caliginosa (70%) and L. rubellus (30%). Total earthworm densities were highest in the north-west (Smithton) region of the State (293{351 earthworms/m 2) regardless of soil type, and the lowest densities were recorded in the Alluvial soils of Deloraine (96 earthworms/m 2). The north-west area also had the most diverse earthworm fauna, with 5 species recorded in one site: A. caliginosa, A. longa, Allolobophora chlorotica, L. rubellus, and O. cyaneum. Summer irrigation effects after 2 seasons on earthworm composition and abundance on dairy farms caused no significant change in A. caliginosa numbers, but there was a 45% increase in the numbers of L. rubellus in irrigated treatments. L. rubellus was considerably more active over summer in irrigated paddocks (25 earthworms/m 2) than in non-irrigated paddocks (7 earthworms/m 2). In contrast the number of A. caliginosa recorded in dryland paddocks was not statistically different to the irrigated paddocks, but the A. caliginosa in dryland paddocks were mostly inactive 8-20 mm from the soil surface.

scholarly journals Proposal for an Embedded System Architecture Using a GNDVI Algorithm to Support UAV-Based Agrochemical Spraying

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5397 ◽  
Author(s):  
Maik Basso ◽  
Diego Stocchero ◽  
Renato Ventura Bayan Henriques ◽  
André Luis Vian ◽  
Christian Bredemeier ◽  
...  
Keyword(s):  
Control System ◽  
Embedded System ◽  
Precision Agriculture ◽  
System Architecture ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Raspberry Pi ◽  
Research Station ◽  
High Definition ◽  
Cpu Usage

An important area in precision agriculture is related to the efficient use of chemicals applied onto fields. Efforts have been made to diminish their use, aiming at cost reduction and fewer chemical residues in the final agricultural products. The use of unmanned aerial vehicles (UAVs) presents itself as an attractive and cheap alternative for spraying pesticides and fertilizers compared to conventional mass spraying performed by ordinary manned aircraft. Besides being cheaper than manned aircraft, small UAVs are capable of performing fine-grained instead of the mass spraying. Observing this improved method, this paper reports the design of an embedded real-time UAV spraying control system supported by onboard image processing. The proposal uses a normalized difference vegetation index (NDVI) algorithm to detect the exact locations in which the chemicals are needed. Using this information, the automated spraying control system performs punctual applications while the UAV navigates over the crops. The system architecture is designed to run on low-cost hardware, which demands an efficient NDVI algorithm. The experiments were conducted using Raspberry Pi 3 as the embedded hardware. First, experiments in a laboratory were conducted in which the algorithm was proved to be correct and efficient. Then, field tests in real conditions were conducted for validation purposes. These validation tests were performed in an agronomic research station with the Raspberry hardware integrated into a UAV flying over a field of crops. The average CPU usage was about 20% while memory consumption was about 70 MB for high definition images, with 4% CPU usage and 20.3 MB RAM being observed for low-resolution images. The average current measured to execute the proposed algorithm was 0.11 A. The obtained results prove that the proposed solution is efficient in terms of processing and energy consumption when used in embedded hardware and provides measurements which are coherent with the commercial GreenSeeker equipment.

Cyber Insurance as a Way of Cyber Risks Management

2019 ◽  
Vol 7 (5) ◽  
pp. 35-42
Author(s):  
Александр Суворов ◽  
Aleksandr Suvorov ◽  
Мария Матанцева ◽  
Mariya Matanceva ◽  
Евгения Плотникова ◽  
...  
Keyword(s):  
Cyber Security ◽  
Insurance Industry ◽  
Security Level ◽  
Controversial Issues ◽  
It Infrastructure ◽  
Software Products ◽  
Cyber Insurance ◽  
Risk Insurance ◽  
Commercial Organization ◽  
Cyber Risk

A review of the cyber insurance domain has been carried out with a description of classical terms from the insurance industry. Have been considered two the most comprehensive today definitions of cyber risk in authors’ opinion. A diagram of processes for cyber risk management using insurance has been presented, and the place of cyber-risk among other company’s risks has been demonstrated, i. e. the context of cyber risk among the risks of any commercial organization has been shown. A typical cyber insurance process has been described, and a scheme of cyber insurance processes has been developed. A brief description of problem areas and controversial issues in cyber insurance, with which cyber-risk insurance practices may face, has been presented, as well as a table showing at which stage of cyber-insurance the specific problems may arise. Has been provided the basic economic utility function, which formalizes decision making for agents with a different attitude to risk. Standards in cyber security, and various software products that can be used as a tool for assessing the security level of an enterprise’s IT infrastructure have been presented, and it has been demonstrated how these products can help in cyber risk assessment. Different methods used at each stage of cyber insurance have been shown.

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