scholarly journals OPTIMIZING LOW-COST UAV AERIAL IMAGE MOSAICING FOR CROP GROWTH MONITORING

2021 ◽  
Vol XLIV-M-3-2021 ◽  
pp. 7-12
Author(s):  
P. Bupathy ◽  
R. Sivanpillai ◽  
V. V. Sajithvariyar ◽  
V. Sowmya
Keyword(s):  
Management Practices ◽  
Low Cost ◽  
Optimal Number ◽  
Aerial Image ◽  
Growth Monitoring ◽  
Image Mosaic ◽  
Yield Data ◽  
Matching Process ◽  
Crop Field ◽  
Data Gaps

Abstract. High spatial resolution images acquired with drones can provide useful information to farmers for devising suitable management practices and increase crop yield. Data collected as individual frames or images have to be mosaiced using pattern recognition and matching process. Most flight missions collect hundreds of photos with high overlap and side overlap in order to generate mosaic without data gaps or distortion. These frames are aligned using the location information associated with each image. The same features are identified in multiple frames for generating the mosaic. In this process, it is common to use all or most of the images which requires a lot of resources. Uploading and processing hundreds of images could take several hours to days. Many farmers and crop consultants in developing countries may not have the necessary resources to upload hundreds of images. This study assessed the optimal number of images required to generate an image mosaic for a crop field without any data gaps or distortion. Images were collected at two different heights and directions. First, the mosaic was generated using all (100%) frames followed by subsets containing 90%, through 50% of images. Results obtained will assist us to plan the settings in future flight missions for acquiring optimal number of images required for generating image mosaic.

scholarly journals Validation of Rapid and Low-Cost Approach for the Delineation of Zone Management Based on Machine Learning Algorithms

Agronomy ◽  
2022 ◽  
Vol 12 (1) ◽  
pp. 183
Author(s):  
Michele Denora ◽  
Marco Fiorentini ◽  
Stefano Zenobi ◽  
Paola A. Deligios ◽  
Roberto Orsini ◽  
...  
Keyword(s):  
Low Cost ◽  
Optimal Number ◽  
Machine Learning Algorithms ◽  
Yield Data ◽  
Management Zones ◽  
Soil Sensors ◽  
Zone Management ◽  
Gap Statistic ◽  
Vegetation Indexes ◽  
Significant Difference

Proximal soil sensors are receiving strong attention from several disciplinary fields, and this has led to a rise in their availability in the market in the last two decades. The aim of this work was to validate agronomically a zone management delineation procedure from electromagnetic induction (EMI) maps applied to two different rainfed durum wheat fields. The k-means algorithm was applied based on the gap statistic index for the identification of the optimal number of management zones and their positions. Traditional statistical analysis was performed to detect significant differences in soil characteristics and crop response of each management zones. The procedure showed the presence of two management zones at both two sites under analysis, and it was agronomically validated by the significant difference in soil texture (+24.17%), bulk density (+6.46%), organic matter (+39.29%), organic carbon (+39.4%), total carbonates (+25.34%), total nitrogen (+30.14%), protein (+1.50%) and yield data (+1.07 t ha−1). Moreover, six unmanned aerial vehicle (UAV) flight missions were performed to investigate the relationship between five vegetation indexes and the EMI maps. The results suggest performing the multispectral images acquisition during the flowering phenological stages to attribute the crop spatial variability to different soil proprieties.

The system of indicators of the quality of the carbon-carbon composite materials and technologies of their production

2018 ◽  
pp. 127-132
Author(s):  
T. N. Antipova ◽  
D. S. Shiroyan
Keyword(s):  
Composite Material ◽  
Low Cost ◽  
Experimental Studies ◽  
Carbon Matrix ◽  
Carbon Composite ◽  
Optimal Number ◽  
Laboratory Equipment ◽  
Carbon Composite Material ◽  
Carbon Composite Materials

The system of indicators of quality of carbon-carbon composite material and technological operations of its production is proved in the work. As a result of the experimental studies, with respect to the existing laboratory equipment, the optimal number of cycles of saturation of the reinforcing frame with a carbon matrix is determined. It was found that to obtain a carbon-carbon composite material with a low cost and the required quality indicators, it is necessary to introduce additional parameters of the pitch melt at the impregnation stage.

scholarly journals Tracking the Evolution of Riverbed Morphology on the Basis of UAV Photogrammetry

2021 ◽  
Vol 13 (4) ◽  
pp. 829
Author(s):  
Teresa Gracchi ◽  
Guglielmo Rossi ◽  
Carlo Tacconi Stefanelli ◽  
Luca Tanteri ◽  
Rolando Pozzani ◽  
...  
Keyword(s):  
Management Practices ◽  
Low Cost ◽  
3D Models ◽  
Vegetation Coverage ◽  
Detection Analysis ◽  
Digital Terrain ◽  
Fluvial Dynamics ◽  
Aerial Vehicle ◽  
One Year ◽  
Short Time

Unmanned aerial vehicle (UAV) photogrammetry has recently become a widespread technique to investigate and monitor the evolution of different types of natural processes. Fluvial geomorphology is one of such fields of application where UAV potentially assumes a key role, since it allows for overcoming the intrinsic limits of satellite and airborne-based optical imagery on one side, and in situ traditional investigations on the other. The main purpose of this paper was to obtain extensive products (digital terrain models (DTMs), orthophotos, and 3D models) in a short time, with low costs and at a high resolution, in order to verify the capability of this technique to analyze the active geomorphic processes on a 12 km long stretch of the French–Italian Roia River at both large and small scales. Two surveys, one year apart from each other, were carried out over the study area and a change detection analysis was performed on the basis of the comparison of the obtained DTMs to point out and characterize both the possible morphologic variations related to fluvial dynamics and modifications in vegetation coverage. The results highlight how the understanding of different fluvial processes may be improved by appropriately exploiting UAV-based products, which can thus represent a low-cost and non-invasive tool to crucially support decisionmakers involved in land management practices.

Optimizing Convolutional Neural Network Accelerator on Low-Cost FPGA

2021 ◽  
pp. 2150193
Author(s):  
Truong Quang Vinh ◽  
Dinh Viet Hai
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Low Cost ◽  
Optimal Number ◽  
Data Reuse ◽  
Logic Element ◽  
Input Buffer ◽  
Classification Tasks ◽  
Processing Engine ◽  
Better Than

Convolutional neural network (CNN) is one of the most promising algorithms that outweighs other traditional methods in terms of accuracy in classification tasks. However, several CNNs, such as VGG, demand a huge computation in convolutional layers. Many accelerators implemented on powerful FPGAs have been introduced to address the problems. In this paper, we present a VGG-based accelerator which is optimized for a low-cost FPGA. In order to optimize the FPGA resource of logic element and memory, we propose a dedicated input buffer that maximizes the data reuse. In addition, we design a low resource processing engine with the optimal number of Multiply Accumulate (MAC) units. In the experiments, we use VGG16 model for inference to evaluate the performance of our accelerator and achieve a throughput of 38.8[Formula: see text]GOPS at a clock speed of 150[Formula: see text]MHz on Intel Cyclone V SX SoC. The experimental results show that our design is better than previous works in terms of resource efficiency.

Managerial Practices in a High Cost Manufacturing Environment

2018 ◽  
pp. 1749-1768
Author(s):  
Renu Agarwal ◽  
Christopher Bajada ◽  
Paul J. Brown ◽  
Roy Green
Keyword(s):  
New Zealand ◽  
Best Practice ◽  
Management Practices ◽  
Management Practice ◽  
Low Cost ◽  
Management Strategies ◽  
Manufacturing Firms ◽  
Labour Cost ◽  
Managerial Practices ◽  
Management Capability

This chapter explores the management strategies adopted by manufacturing firms operating in high versus low cost economies and investigates the reasons for differences in the management practice choices. The study reported in this chapter identifies a subset of countries that have either high or low labour costs, with USA, Sweden, and Japan being high, and India, China, and Brazil being low labour cost economies. The high labour cost manufacturing firms are found to have better management practices. In this chapter, the authors find that Australia and New Zealand manufacturing firms face relatively high labour cost but lag behind world best practice in management performance. The chapter concludes by highlighting the need for improvement in management capability for Australian and New Zealand manufacturing firms if they are to experience a reinvigoration of productivity, competitiveness, and long-term growth.

scholarly journals Performance and Profitability of Fungicides for Managing Soybean White Mold: A 10-Year Summary of Cooperative Trials

Plant Disease ◽  
2019 ◽  
Vol 103 (9) ◽  
pp. 2212-2220
Author(s):  
Jhonatan P. Barro ◽  
Maurício C. Meyer ◽  
Claúdia V. Godoy ◽  
Alfredo R. Dias ◽  
Carlos M. Utiamada ◽  
...  
Keyword(s):  
Low Cost ◽  
Disease Incidence ◽  
Network Models ◽  
Field Trials ◽  
White Mold ◽  
Yield Data ◽  
Soybean Price ◽  
Cost Treatment ◽  
Untreated Check ◽  
Yield Responses

White mold, caused by Sclerotinia sclerotiorum, is a yield-limiting disease of soybean in Brazil. Uniform fungicide trials have been conducted annually since 2009. Data from 74 cooperative field trials conducted over a 10-year period were assembled. We selected five fungicides applied two times around flowering: dimoxystrobin plus boscalid (DIMO+BOSC), carbendazim plus procymidone (CARB+PROC), fluazinam (FLUZ), fluopyram (FLUO), and procymidone (PROC). For comparison, thiophanate-methyl (TMET) applied four times was also included as a low-cost treatment. Network models were fitted to the log of white mold incidence (percentages) and log of sclerotia mass data (grams/hectare) and to the nontransformed yield data (kilograms/hectare) for each treatment, including the untreated check. Back-transformation of the meta-analytic estimates indicated that the lowest and highest mean (95% confidence interval [CI]) percent reductions in incidence and sclerotia mass were 54.2 (49.3 to 58.7) and 51.6% (43.7 to 58.3) for TMET and 83.8 (79.1 to 87.5) and 87% (81.9 to 91.6) for CARB+PROC, respectively. The overall mean (95% CI) yield responses ranged from 323 kg/ha (247.4 to 400.3) for TMET to 626 kg/ha (521.7 to 731.7) for DIMO+BOSC, but the variance was significantly reduced by a binary variable (30% threshold) describing disease incidence in the untreated check. On average, an increment of 352 kg/ha was estimated for trials where the incidence was >30% compared with the low-disease scenario. Hence, the probability of breaking even on fungicide costs for the high-disease scenario was >65% for the more effective, but more expensive fungicide (FLUZ) than TMET. For the low-disease scenario, profitability was less likely and depended more on variations in fungicide cost and soybean price.

Crossing the Valley of Death: Managing the When, What, and How of Innovative Development Projects

2019 ◽  
Vol 50 (4) ◽  
pp. 447-459 ◽  
Author(s):  
Christophe Midler
Keyword(s):  
Project Management ◽  
Product Development ◽  
Management Practices ◽  
Low Cost ◽  
Innovation Process ◽  
Development Projects ◽  
Development Phase ◽  
Specific Content ◽  
Global Innovation ◽  
Valley Of Death

The last few decades have seen a profound transformation of innovation project management within automobile firms. During the 1990s, the product development phase was revolutionized by the deployment of heavyweight project management, project portfolio processes, and platform strategies. The 2000s saw the forces of change move upstream in the innovation process, with the development of new methodologies intended to develop and orient creativity, as well as new upfront units acting as innovation labs. However, many upfront creative endeavors still encounter an innovation valley of death when they move into the rigid and risk-averse development phase. Thus, the frontier of innovative project organization seems to be the ongoing quest to reconcile the emergence of breakthrough innovations in the upfront phase with the more rationalized nature of development phases. Based on a case study of a disruptive low-cost car, this article analyzes how the product development phase can support innovative exploration to overcome the challenge of achieving a major cost breakthrough. We analyze the specific content of the project’s innovations ( fractal innovation) and the management practices and organizations used to implement them. We characterize how such innovative product development can contribute to a new economy of innovative effort within the global innovation funnel of the firm. We compare this global innovation process, where development projects play a major role as a locus for organizational learning, to the customary one in automotive firms, where learning happens essentially in front-end marketing and engineering departments.

scholarly journals Evaluation of an Easy-to-Install, Low-Cost Dendrometer Band for Citizen-Science Tree Research

2019 ◽  
Vol 117 (4) ◽  
pp. 317-322
Author(s):  
Michael G Just ◽  
Steven D Frank
Keyword(s):  
Citizen Science ◽  
Urban Areas ◽  
Large Scale ◽  
Low Cost ◽  
Acer Rubrum ◽  
Cost Effective ◽  
Stem Growth ◽  
Growth Monitoring ◽  
Eastern United States ◽  
Highly Correlated

AbstractTree-stem growth is an important metric for evaluating many ecological and silvicultural research questions. However, answering these questions may require monitoring growth on many individual trees that span changing environments and geographies, which can incur significant costs. Recently, citizen science has been successfully employed as a cost-effective approach to collect data for large-scale projects that also increases scientific awareness. Still, citizen-science-led tree-growth monitoring requires the use of tools that are affordable, understandable, and accurate. Here, we compare an inexpensive, easy-to-install dendrometer band to two other bands that are more expensive with more complex installations. We installed a series of three dendrometers on 31 red maples (Acer rubrum) in two urban areas in the eastern United States. We found that the stem-growth measurements reported by these dendrometers were highly correlated and, thus, validate the utility of the inexpensive band.

Simulation of the effect of chilling injury and nitrogen supply on floret fertility and yield in rice

1994 ◽  
Vol 34 (7) ◽  
pp. 921 ◽  
Author(s):  
DC Godwin ◽  
WS Meyer ◽  
U Singh
Keyword(s):  
Management Practices ◽  
New South ◽  
Chilling Injury ◽  
New South Wales ◽  
Growth And Yield ◽  
Comprehensive Model ◽  
Night Time ◽  
Yield Data ◽  
South Wales ◽  
High Yields

Evidence exists that night temperatures <18�C immediately preceding flowering in rice crops can adversely affect floret fertility and, hence, yields. It has been suggested that sterility induced by low temperature is also influenced by floodwater depth and nitrogen (N) rate. In southern New South Wales, low night-time temperatures are believed to be a major constraint to the achievement of consistently high yields. The availability of a comprehensive model of rice growth and yield that is sensitive to this constraint would aid the development of better management practices. CERES RICE is a comprehensive model that simulates the phasic development of a rice crop, the growth of its leaves, stems, roots, and panicles, and their response to weather. It also simulates the water and N balances of the crop and the effects of stresses of water and N on the yield-forming processes. The model has been extensively tested in many rice-growing systems in both tropical and temperate environments. However, the original model was unable to simulate the level of chilling injury evident from yield data from southern New South Wales. This paper reports modifications made in the model to simulate these effects and the evaluation of the model in environments of low night temperature. Inclusion of the chilling injury effect greatly improved the accuracy of estimated yields from treatments in an extensive field experiment. However, additional testing with a wider range of data sets is needed to confirm the international applicability of the modifications.

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