scholarly journals From Smart Farming towards Unmanned Farms: A New Mode of Agricultural Production

Agriculture ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 145
Author(s):  
Tan Wang ◽  
Xianbao Xu ◽  
Cong Wang ◽  
Zhen Li ◽  
Daoliang Li
Keyword(s):  
Agricultural Production ◽  
Rapid Development ◽  
Agricultural Labor ◽  
Agricultural Work ◽  
Fifth Generation ◽  
Current State ◽  
Smart Farming ◽  
Agriculture Labor ◽  
Near Future ◽  
Severe Shortage

Agriculture is the most important industry for human survival and solving the hunger problem worldwide. With the growth of the global population, the demand for food is increasing, which needs more agriculture labor. However, the number of people willing to engage in agricultural work is decreasing, causing a severe shortage of agricultural labor. Therefore, it is necessary to study the mode of agricultural production without labor force participation. With the rapid development of the Internet of Things, Big Data, artificial intelligence, robotics and fifth-generation (5G) communication technology, robots can replace humans in agricultural operations, thus enabling the establishment of unmanned farms in the near future. In this review, we have defined unmanned farms, introduced the framework of unmanned farms, analyzed the current state of the technology and how these technologies can be used in unmanned farms, and finally discuss all the technical challenges. We believe that this review will provide guidance for the development of unmanned farms and provide ideas for further investigation of these farms.

scholarly journals Plant Disease Identification Based on Deep Learning Algorithm in Smart Farming

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Yan Guo ◽  
Jin Zhang ◽  
Chengxin Yin ◽  
Xiaonan Hu ◽  
Yu Zou ◽  
...  
Keyword(s):  
Deep Learning ◽  
Agricultural Production ◽  
Plant Disease ◽  
Learning Algorithm ◽  
Rapid Development ◽  
Deep Learning Algorithm ◽  
Rust Diseases ◽  
Ecological Protection ◽  
Smart Farming ◽  
Bacterial Plaque

The identification of plant disease is the premise of the prevention of plant disease efficiently and precisely in the complex environment. With the rapid development of the smart farming, the identification of plant disease becomes digitalized and data-driven, enabling advanced decision support, smart analyses, and planning. This paper proposes a mathematical model of plant disease detection and recognition based on deep learning, which improves accuracy, generality, and training efficiency. Firstly, the region proposal network (RPN) is utilized to recognize and localize the leaves in complex surroundings. Then, images segmented based on the results of RPN algorithm contain the feature of symptoms through Chan–Vese (CV) algorithm. Finally, the segmented leaves are input into the transfer learning model and trained by the dataset of diseased leaves under simple background. Furthermore, the model is examined with black rot, bacterial plaque, and rust diseases. The results show that the accuracy of the method is 83.57%, which is better than the traditional method, thus reducing the influence of disease on agricultural production and being favorable to sustainable development of agriculture. Therefore, the deep learning algorithm proposed in the paper is of great significance in intelligent agriculture, ecological protection, and agricultural production.

Rationale and Design Considerations for a Semantic Mediator in Health Information Systems

1998 ◽  
Vol 37 (04/05) ◽  
pp. 518-526 ◽  
Author(s):  
D. Sauquet ◽  
M.-C. Jaulent ◽  
E. Zapletal ◽  
M. Lavril ◽  
P. Degoulet
Keyword(s):  
Information Systems ◽  
Software Engineering ◽  
Health Information ◽  
Rapid Development ◽  
Heterogeneous Systems ◽  
Health Information Systems ◽  
Semantic Interoperability ◽  
Point Of View ◽  
Current State ◽  
Engineering Environment

AbstractRapid development of community health information networks raises the issue of semantic interoperability between distributed and heterogeneous systems. Indeed, operational health information systems originate from heterogeneous teams of independent developers and have to cooperate in order to exchange data and services. A good cooperation is based on a good understanding of the messages exchanged between the systems. The main issue of semantic interoperability is to ensure that the exchange is not only possible but also meaningful. The main objective of this paper is to analyze semantic interoperability from a software engineering point of view. It describes the principles for the design of a semantic mediator (SM) in the framework of a distributed object manager (DOM). The mediator is itself a component that should allow the exchange of messages independently of languages and platforms. The functional architecture of such a SM is detailed. These principles have been partly applied in the context of the HEllOS object-oriented software engineering environment. The resulting service components are presented with their current state of achievement.

EVALUATING THE CONTRIBUTION OF TOTAL FACTOR PRODUCTIVITY ON AGRICULTURAL GROWTH IN AN GIANG PROVINCE

2018 ◽  
Vol 1 (29) ◽  
pp. 29-37
Author(s):  
Tan Van Truong
Keyword(s):  
Total Factor Productivity ◽  
Agricultural Production ◽  
Science And Technology ◽  
Agricultural Labor ◽  
Factor Productivity ◽  
Agricultural Growth ◽  
Regression Approach ◽  
Investment Capital ◽  
Agricultural Demand

By the growth regression approach, the research has identified that the investment capital contributed 1,939 and agricultural labor contributed 1,291 to the agricultural growth of An Giang province. More specifically, the contribution of TFP (Total Factor Productivity) to the agricultural growth in the period 2000 - 2004 was averagely 0,11%, in 2005 - 2010 was -5,03%, and in period 2011 - 2016 was 0,81%. The total factor productivity contributed to the agricultural growth slowly. In order to raise the contribution of TFP, the research represents 05 solutions including the increase of the effectiveness of using the investment capital, the increase of the quality of labor, the application of the science and technology into agricultural production, agriculturalrestructuring, and the increase of  agricultural demand.

scholarly journals Image-Based Automatic Watermeter Reading under Challenging Environments

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 434
Author(s):  
Qingqi Hong ◽  
Yiwei Ding ◽  
Jinpeng Lin ◽  
Meihong Wang ◽  
Qingyang Wei ◽  
...  
Keyword(s):  
Smart Cities ◽  
Rapid Development ◽  
Mobile Network ◽  
Spatial Layout ◽  
Single Image ◽  
Automatic Instrument ◽  
Intelligent Sensors ◽  
Fifth Generation ◽  
Instrument Reading ◽  
Network Technologies

With the rapid development of artificial intelligence and fifth-generation mobile network technologies, automatic instrument reading has become an increasingly important topic for intelligent sensors in smart cities. We propose a full pipeline to automatically read watermeters based on a single image, using deep learning methods to provide new technical support for an intelligent water meter reading. To handle the various challenging environments where watermeters reside, our pipeline disentangled the task into individual subtasks based on the structures of typical watermeters. These subtasks include component localization, orientation alignment, spatial layout guidance reading, and regression-based pointer reading. The devised algorithms for orientation alignment and spatial layout guidance are tailored to improve the robustness of our neural network. We also collect images of watermeters in real scenes and build a dataset for training and evaluation. Experimental results demonstrate the effectiveness of the proposed method even under challenging environments with varying lighting, occlusions, and different orientations. Thanks to the lightweight algorithms adopted in our pipeline, the system can be easily deployed and fully automated.

scholarly journals A decision model on the repair and maintenance of shipping containers

2020 ◽  
Vol 5 (1) ◽  
Author(s):  
Niclas Hoffmann ◽  
Robert Stahlbock ◽  
Stefan Voß
Keyword(s):  
Decision Model ◽  
Individual Decision ◽  
Microsoft Excel ◽  
Current State ◽  
Repair Costs ◽  
Transport Chain ◽  
Shipping Containers ◽  
Logistic Chain ◽  
Safe Transport ◽  
Near Future

Abstract The use of shipping containers for the transport of goods has become indispensable and a crucial factor for globalization by providing inexpensive and safe transport opportunities. It is expected that the number of globally operating containers will increase in the near future. Despite a high technical modernisation of the logistic chain, the container still faces a risk of damage at any time and any place within the transport chain. In principle, a container is taken out of service, when a damage is recognized. Different causes of damage exist and various types of damage could occur to the container, ranging from minor to substantial major ones that do not permit the continued proper use of the container. Thus, an individual decision on repair and maintenance (R&M) for each damaged container is necessary. Aside from technical aspects, it has to be decided from an economical perspective whether a repair should be performed. A profound decision should consider various criteria like, e.g., repair costs, lifespan of the container, future yields and possible sales price. Based on a regulatory, practical, and scientific view, this paper proposes a multi-criteria decision model for the economic decision on the R&M of a damaged container. Implemented in Microsoft Excel, this decision model is easily applicable. The user can deduce a first (limited) guidance for dealing with a respective damaged container based on its current state and general market conditions.

Product Data Management Systems: State-of-the-Art and the Future

1997 ◽  
Author(s):  
Taner Bilgiç ◽  
Dennis Rock
Keyword(s):  
Data Management ◽  
State Of The Art ◽  
Product Data Management ◽  
Management Systems ◽  
Systems Management ◽  
Engineering Project ◽  
Product Data ◽  
Current State ◽  
Functional Representation ◽  
Near Future

Abstract We survey the current state-of-the-art in (commercial) Product Data Management (PDM) systems. After identifying the major functions of PDM systems, we indicate various shortcomings of the current PDM technology. An important shortcoming is in the representation and use of functions. We review the functional representation literature in the context of PDM technology. Systems management aspects of an engineering project is also commented on. We believe these two areas are the next two challenges awaiting PDM technology in the near future.

Prospects for increasing the volume of agricultural production for export due to the expansion and intensification of the use of Russian land resources

2021 ◽  
pp. 40-47
Author(s):  
Gennadiy A. Polunin ◽  
Keyword(s):  
Agricultural Production ◽  
Agricultural Land ◽  
Arable Land ◽  
Agricultural Products ◽  
Land Resources ◽  
The Past ◽  
Federal Districts ◽  
Near Future

The article is devoted to substantiating the prospects for increasing the marginal volumes of agricultural production for export in the next four years. Two scenarios of such production are considered: 1) expansion and 2) intensification of the use of land resources. As part of the development of the first scenario, an analysis of the distribution of unused agricultural land, including arable land, by federal districts was carried out. Also, based on the forecast of the introduction of additional annual volumes of acreage in the subjects of the Federation, the calculation of additional volumes of agricultural production, which can be expected in the next four years, was carried out. The analysis of data on the increase in the yield of export-oriented crops over the past five years has been carried out, in the framework of the second scenario, the calculation of the projected additional yield due to the intensification of agriculture is presented. The results of the study indicate that the intensification of agriculture will have the greatest impact on the growth of production and export of agricultural products in the near future.

An Assessment on the Benefits of Additive Manufacturing Regarding New Swirler Geometries for Gas Turbine Burners

2018 ◽  
Author(s):  
Fabrice Giuliani ◽  
Nina Paulitsch ◽  
Daniele Cozzi ◽  
Michael Görtler ◽  
Lukas Andracher
Keyword(s):  
Additive Manufacturing ◽  
Gas Turbine ◽  
Inconel 718 ◽  
Advanced Materials ◽  
Gas Turbine Combustor ◽  
Engineering Research ◽  
Know How ◽  
Current State ◽  
Research And Education ◽  
Near Future

In the near future, combustion engineers will shape the burner according to the flame, and not the opposite way anymore. In this contribution, this idea is explored with the help of additive manufacturing (AM). The focus is put on the design and the production of swirlers using advanced materials with the least possible efforts in terms of manufacturing. The material chosen for this study is Inconel 718. There are three motivations to this project. The first one is to design new shapes and assess these in comparison to conventional ones. The second motivation is to be able to manufacture them using additive manufacturing, and to gather know-how on selective laser melting. The third motivation is to elaborate a methodology involving engineering, research and education to promote — only if and when this is desirable — the production of series of premium parts such as high-end components of gas turbine combustor using AM. First-of-a-kind swirler shapes are explained and designed. These are unlikely to be produced using conventional manufacturing. They are then successfully produced in Inconel 718 using AM. The raw parts are directly submitted for testing with no surface post-processing. The paper states why at current state-of-the-art the raw surface quality still needs improvement, and highlights the benefits of the new swirler shape versus conventional.

scholarly journals Agroecology in Canada: Towards an Integration of Agroecological Practice, Movement, and Science

2018 ◽  
Vol 10 (9) ◽  
pp. 3299 ◽  
Author(s):  
Marney Isaac ◽  
S. Isakson ◽  
Bryan Dale ◽  
Charles Levkoe ◽  
Sarah Hargreaves ◽  
...  
Keyword(s):  
Social Movements ◽  
Agricultural Production ◽  
Food Policy ◽  
Settler Colonialism ◽  
Policy And Practice ◽  
Current State ◽  
Ecological Problems

This article surveys the current state of agroecology in Canada, giving particular attention to agroecological practices, the related social movements, and the achievements of agroecological science. In each of these realms, we find that agroecology emerges as a response to the various social and ecological problems associated with the prevailing industrial model of agricultural production that has long been promoted in the country under settler colonialism. Although the prevalence and prominence of agroecology is growing in Canada, its presence is still small and the support for its development is limited. We provide recommendations to achieve a more meaningful integration of agroecology in Canadian food policy and practice.

scholarly journals Customer Segmentation Through Path Reconstruction

2020 ◽  
Author(s):  
Santiago García
Keyword(s):  
Rapid Development ◽  
Customer Segmentation ◽  
Smart Phones ◽  
Indoor Environments ◽  
Flow Conditions ◽  
Gps Receivers ◽  
Current State ◽  
Different Types

With the rapid development of smart phones, tablets and their operative systems, many positioning enabled sensors have been built into these devices. Users can now accurately fix their location according to the function of GPS receivers. For indoor environments, as in the case we are studying, WiFi based positioning is preferred to GPS due to the attenuation or obstruction of signals. This paper deals with the automatic classification of customers in a Sports Shop Center on the basis of their movements around the shop's premises. To achieve this goal, we start by collecting (x,y) coordinates from customers while they visit the store. Consequently, any costumer's path through the shop is formed by a list of coordinates, obtained with a frequency of one measurement per minute. Then, a guess about the full trajectory is constructed and a number of parameters about these trajectories is calculated before performing an Unsupervised Learning Clustering Process. As a result, we can identify several types of customers, and the dynamics of their behavior inside the shop. This information is of great value to the company, to be used both in the long term and also in short periods of time, monitoring the current state of the shop at any moment, identifying different types of situation appearing during restricted periods, or predicting customer flow conditions

Sign in / Sign up

Export Citation Format

Share Document