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检索条件"任意字段=2nd IFIP International Conference on Computer and Computing Technologies in Agriculture"

共 694 条记录，以下是91-100 订阅

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Design and Implementation of Smart Hydroponics Farming for Growing Lettuce Plantation under Nutrient Film Technology 2

Design and Implementation of Smart Hydroponics Farming for G...

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2nd international conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Venkatraman, M. Surendran, R. Saveetha School of Engineering Saveetha Institute of Medical and Technical Science Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9781665456302

Smart hydroponics farming is a modern technique for growing plants in nutrient-rich water rather than soil. The Nutrient Film Technology is a hydroponic system that circulates a thin film of nutrient-rich water over the roots of the plants, allowing for optional nutrient and oxygen absorption. The lettuce varieties that can thrive under NFT and are suitable for hydroponic cultivation. Automation robotics and IoT have enabled farmers to monitor all variations in the plant, root zone, and environment using smart hydroponics. The findings of this study are presented in the design of real-time operating systems based on microcontrollers. Robotics in hydroponic systems, additional technologies in hydroponic systems, and automated drip irrigation in conjunction with hydroponic systems;expert system-based automation system;automated Smart hydroponics nutrition plants system;smart hydroponic management and monitoring system for an intelligent smart hydroponic system using internet of things and web technology;deep neural network-based fault detection in hydroponics lettuce plantation being g hydroponic smart lettuce is a promising technology for producing high-quality, sustainable lettuce in cities and other areas where traditional agriculture is difficult or impractical. The obtains simulation result on could base Environment with IoT disclose superior performance. © 2023 IEEE.

关键词： Hydroponics

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computer and computing technologies in agriculture IV 1

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丛书名： ifip Advances in Information and Communication Technology

1000年

作者： Daoliang Li Yingyi Chen Yande Liu

ISBN: (数字)9783642183362

ISBN: (纸本)9783642183355;9783642267147

This book constitutes Part II of the refereed four-volume post-conference proceedings of the 4th ifip TC 12 international conference on computer and computing technologies in agriculture, CCTA 2010, held in Nanchang, China, in October 2010. The 352 revised papers presented were carefully selected from numerous submissions. They cover a wide range of interesting theories and applications of information technology in agriculture, including simulation models and decision-support systems for agricultural production, agricultural product quality testing, traceability and e-commerce technology, the application of information and communication technology in agriculture, and universal information service technology and service systems development in rural areas.

关键词： Artificial Intelligence Information Systems Applications (incl. Internet) Special Purpose and Application-Based Systems computer Communication Networks Software Engineering Simulation and Modeling

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Apperception of Plant Disease with avail of algorithm 2

Apperception of Plant Disease with avail of algorithm

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2nd international conference on Power, Control and computing technologies, ICPC2T 2022

作者： Gutte, Vitthal S Mundhe, Pramod Bhandari, Mahesh Dr. Vishwanath Karad MIT World Peace University School of Computer Engineering and Technology Pune India

ISBN: (纸本)9781665458580

In today's world, agriculture is the most important source of growth. It is an essential component of both economic and social life. Plant disease is becoming an important field in India, in the literal sense of the word. In the past, disease detection systems were designed for monocot or dicot plant families. Gradually, as scientific and special to some science or trade progress, more safe, good, ready, and working well methods are offered and have undergone growth for early detection of plant disease through the smallest wide space for turning time. We have instrumented a careful way to show monocot and dicot disease in this paper. Our methodical approach aids in the treatment of the disease by reducing the number of errors. To detect plant leaf disease, we took three steps. It primarily takes three forms: first, breaking down the leaf into parts, then removing the points, and finally, ordering. It has come to be part of the acted-on part of plant leaf using the k-means quince into group's expert way in the breaking down into parts process. The material's feel, appearance, and color are revealed after it is broken down into primarily form parts. Finally, the information gleaned from the features is applied to the order using the Support Guide Machine to detect plant disease. © 2022 IEEE.

关键词： Image color analysis Instruments Power control Clustering algorithms Filtering algorithms Turning Information filters

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Artificial Intelligence in Business Development and Agile SoftwarePaper 2

Artificial Intelligence in Business Development and Agile So...

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2nd international conference on Advance computing and Innovative technologies in Engineering, ICACITE 2022

作者： Panesar, Gurpreet Singh Chadha, Raman Sharma, Ashim Tinna, Mandeep Singh Gupta, Anish Puri, Digvijay Chandigarh University Computer Science and Engineering Department Chandigarh India

ISBN: (纸本)9781665437899

In this paper, I intend to investigate ways to maintain product quality while providing the goods to the customer as quickly as feasible. We will inspect how the six standards of constant design can help us in guaranteeing to accomplish the most elevated conceivable nature of the completed item in the briefest timeframe conceivable during the improvement interaction It is similarly critical to give great things rapidly for what it's worth to do as such effectively. There are a lot of tactics that we may use to do this, such as availability approaches, which allow us to maintain the best degree of quality that is achievable as a software development team. He describes such tactics, as well as a few methods for delivering the product quickly and integrating a superior driver software architecture in the driver software. India's food-based economy is a significant component of the country's economy. Agricultural production is the principal source of income for the vast majority of the people in this region, and it provides advantages to the whole community as a whole. Farmers are in charge of the production of food, which is a fundamental requirement for human survival. The salesmen are having difficulty finding the appropriate selling price for the shares that they are delivering. This company's losses outweigh its profits. Farmers may sell their goods at the highest offer price according to the stock market notion described above. Farmers that join in this manner will have access to a range of other services, such as assessments, communication with wholesalers, market notifications, and other similar features and benefits. Presumably, There are several applications for predictive analytics, including expert device manufacturing (including speech recognition and artificial vision), legal review, and a variety of other fields. (including legal precedent analysis), automated weapons systems (including drones), and precision agriculture, among others. The world's food de

关键词： Speech recognition

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An Accurate and Automated plant disease detection system using transfer learning based Inception V3Model 2

An Accurate and Automated plant disease detection system usi...

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2nd international conference on Advance computing and Innovative technologies in Engineering, ICACITE 2022

作者： Upadhyay, Santosh Kumar Kumar, Avadhesh Galgotias University School of Computer Science & Engineering Uttar Pradesh203201 India

ISBN: (纸本)9781665437899

Rice is one of the most widely grown crops across the globe, and it is susceptible to a variety of illnesses at various phases of production. Crop pathogens have a devastating influence on food safety, as well as a considerable loss in both the quantity and quality of production. Plant infections can damage the crop entirely in severe circumstances. Farmers' poor understanding makes it extremely difficult for them to visually diagnose these diseases. As a result, in agriculture domain, automatic recognition and diagnosis of crop diseases are greatly needed. Several approaches for solving this problem have been offered, including deep learning emerging as the best choice because of its excellent results. Recent advancements in Deep Learning have demonstrated that Automatic image identification methods based on CNN models can be extremely useful in such situations. We examine transfer learning of pre-trained deep CNN architectures for the recognition of infections found in plant leaves. We have utilized a pre-trained network trained on huge datasets and then applying it to our task using specific dataset. In our technique, we used the Inception V3pre-trained deep CNN model. Input samples of 2550 infected leaf images were acquired from the rice leaf dataset consisting of 5 disease classes. Contrast stretching procedure was applied on collected image samples to get good visual characteristics of the images. Image augmentation was used to avoid overfitting of the model during the training. Result analysis illustrated that the proposed strategy produced promising result with a 100 percent overall accuracy. © 2022 IEEE.

关键词： Crops

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ASSESSMENT And MAPPING OF HEAVY METALS POLLUTION IN TEA PLANTATION SOIL OF ZHEJIANG PROVINCE BASED ON GIS

ASSESSMENT AND MAPPING OF HEAVY METALS POLLUTION IN TEA PLAN...

引用

The Second ifip international conference on computer and computing technologies in agriculture (CCTA2008)

作者： Lianqing Zhou~(1 *) Zhou Shi~1 Youwei Zhu~2 1 Institute of Agricultural Remote Sensing and Information Technology Application Zhejiang University Hangzhou Zhejiang Province P.R.China 310029 2 Protection and Monitoring Station of Agricultural Environment Bureau of agriculture Zhejiang Province Hangzhou Zhejiang Province P.R.China 310020

According to the 2nd grade(pH<6.5) of GB1516-1995,Inverse Distance Weighted interpolation method of GIS,single and Nemeorow’s synthetic pollution indexes were used to assess and map heavy metals po

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Engaging the audience in augmented reality performance 07

Engaging the audience in augmented reality performance

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2nd international conference on Digital Interactive Media in Entertainment and Arts, DIMEA 2007

作者： De Bérigny Wall, Caitilin Riddell, Alistair Digital Media Faculty of Architecture Design and Planning University of Sydney 148 City Road Sydney 2006 Australia Lecturer in Computer Music Centre for New Media Art Australian National University Childers Street ACT 0200 Australia

ISBN: (纸本)9781595937087

If digital media performance continues to evolve through the convergence of diverse technologies, where does this leave the audience with respect to the creative experience? Is it important for the artist to understand how the audience understood the use of technology in their work? Should the artist care? This paper discusses the relationship between artist and audience through an examination of an Augmented Reality Performance Project Edible Audience1. © 2007 ACM.

关键词： Augmented reality

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THE SPATIAL PATTERN CHARACTERISTICS OF SOIL NUTRIENTS AT THE FIELD SCALE 2nd

引用

2nd ifip international conference on computer and computing technologies in agriculture

作者： Yang, Yujian Zhu, Jianhua Tong, Xueqin Wang, Dianchang Shandong Acad Agr Sci S&T Informat Engn Res Ctr Jinan 250100 Shandong Peoples R China

ISBN: (纸本)9781441902085

This paper took the wheat field of typical alluvial soil area as the research site, aimed to explore the spatial pattern of the soil nutrients, such as soil available potassium, soil available phosphorus, soil organic matter (SOM) and soil alkali hydrolysable nitrogen. With the help of DGPS, a total of 104 topsoil(0-20cm) hydrolysable nitrogen samples were collected. Based on classical statistics, research results indicated the average content of soil availabie potassium was 287.476g/kg, the high value was 483.433g/kg, the low value was 119.435g/kg. The average content of soil available phosphorus was 54.228g/kg, the high value was 293.13g/kg, the low value was 18.77g/k. The average content of SOM was 36.901g/kg, the high value was 47.420g/kg, the low value was 21.110g/kg. The average content of soil alkali hydrolysable nitrogen was 66.444 g/kg, the high value was 166.474g/kg, the low value was 29.846g/kg. Geostatistical analysis, combined with geographical information system(GIS), the range. nugget and sill of soil nutrients characteristics were calculated, semivariogram model was established, ordinary kriging was applied, and the spatial disiributing map of Soil nutrients was drawn. It is shown that the semivariogram structures of the soil nutrients was spherical, the ratio of nugget/still of soil available potassium, SOM, soil alkali hydrolysable nitrogen was 0.399, 0.746 and 0.696, respectively, which belonged to the middle intensity, the ratio of nugget/sill of soil available phosphorus was 0.759, which belonged to the low intensity. Spatial variation of soil available potassium was mainly caused by structural factors(parent material, terrain, climate, water table etc.), the structure variability of it took 60.1% of the total variability, the spatial variation of soil available phosphorus, SOM and soil alkaline hydrolysis nitrogen were mainly caused by random factors(fertilization, environmental pollution. cultivation measures, management etc.), the random vari

关键词： soil nutrients spatial variability GIS precision agriculture

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SoyNet: Deep Learning Approaches for Automated Soybean Seed Quality Assessment 2

SoyNet: Deep Learning Approaches for Automated Soybean Seed ...

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2nd international conference on Advancement in Computation and computer technologies, InCACCT 2024

作者： Pratap, Harshita Guru Prasad, M.S. Agarwal, Poorvi Bhardwaj, Ayushi Mehra, Ayushi Mathpati, Shilpa Dept. of Computer Science and Engg Dehradun India Reva University School of computing & Information Technology Bengaluru India

ISBN: (纸本)9798350371314

In the realm of agriculture, soybeans have played a vital role in diets for centuries, providing a consistent source of plant protein. Beyond protein, soybeans offer essential components like fibres, vitamins (including B vitamins), minerals (such as iron, calcium, and magnesium), and antioxidants. This necessitates precise quality assessment for factors like size, shape, colour, and damage. Leveraging advanced machine learning techniques such as VGG16, AlexNet and CNN, the model aims to automate the identification and categorization of soybean quality. To implement the proposed work the standard soybean dataset is considered. It consists of five soybean seed types complete, spotted, immature, broken, and skin-damaged. The proposed work effectively categories the quality of soybean seeds and it has the potential to improve the agricultural process as compared to traditional work. In this work different pretrained models are experimented in that VGG16 provides the highest of all showing accuracy 90%, AlexNet accuracy 78.49% and CNN accuracy 74.55%. © 2024 IEEE.

关键词： Damage detection

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Integrating Cloud And Edge computing For Scalable Iot Applications 2

Integrating Cloud And Edge Computing For Scalable Iot Applic...

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2nd international conference on Advances in Computation, Communication and Information Technology, ICAICCIT 2024

作者： Nagarjuna, Pitty Sevuga Pandian, A. Sharma, Suresh Kumar Ramesh, T. Sohail, Mohammed Ali Dinesh Babu, M. Indian Institute of Science Karnataka Bengaluru India Department of Computer Science Kristu Jayanti College Karnataka Bengaluru India Dept. of Statistics Mathematics and Computer Science Sri Karan Narendra Agriculture University Jaipur Jobner India Department of CSE R.M.K Engineering College Chennai India Department of EEE Jazan University Jazan Saudi Arabia Department of Mechanical Rajalakshmi Institute of Technology Chennai India

ISBN: (纸本)9798331541217

The data from the Internet of Things (IoT) is essential in the modern data-driven digital economy since it inspires many new business models supplying a wide spectrum of services both ubiquitous and intelligent. The data transmitted using edge computing technologies is investigated in this paper. Under the framework of the trust model of the research, the data exchanged between the source block and the destination block generates direct, indirect, and reciprocal trust. Although cloud computing can serve as a paradigm for safe data flow, the results of the study revealed that a trust-based approach can avoid cloud intrusion. The simulation runs on numerous test beds using the presently in use cloud technique. The results clearly illustrate that the trust-based approach is effective in protecting data moved across edge computing. © 2024 IEEE.

关键词： Cloud platforms

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