• Title/Summary/Keyword: Cloud Farm

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Goal-driven Optimization Strategy for Energy and Performance-Aware Data Centers for Cloud-Based Wind Farm CMS

  • Elijorde, Frank;Kim, Sungho;Lee, Jaewan
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.10 no.3
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    • pp.1362-1376
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    • 2016
  • A cloud computing system can be characterized by the provision of resources in the form of services to third parties on a leased, usage-based basis, as well as the private infrastructures maintained and utilized by individual organizations. To attain the desired reliability and energy efficiency in a cloud data center, trade-offs need to be carried out between system performance and power consumption. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. The work presented in this paper is directed towards the development of an Energy-efficient and Performance-aware Cloud System equipped with strategies for dynamic switching of optimization approach. Moreover, a platform is also provided for the deployment of a Wind Farm CMS (Condition Monitoring System) which allows ubiquitous access. Due to the geographically-dispersed nature of wind farms, the CMS can take advantage of the cloud's highly scalable architecture in order to keep a reliable and efficient operation capable of handling multiple simultaneous users and huge amount of monitoring data. Using the proposed cloud architecture, a Wind Farm CMS is deployed in a virtual platform to monitor and evaluate the aging conditions of the turbine's major components in concurrent, yet isolated working environments.

Cloud Platform for Smartfarm (스마트팜을 위한 클라우드 플랫폼)

  • Lee, Meong-hun;Yi, Se-yong;Kim, Joon-yong;Yoe, Hyun
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2016.10a
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    • pp.496-499
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    • 2016
  • The smartfarm is a leader in the Field of environmental monitoring in agriculture. By the use of wireless remote systems, monitoring applications of the smartfarm are able to provide vital information to the farmer wherever he may be. Absentee farmers are finding the ease of viewing the application graphs on their mobile phone is providing them with peace of mind. We design system and technical requirements of service for managing and operating smart-farm based on cloud technology. It describes requirements of cloud technology for monitoring, controlling, managing, and operating cloud-based smart farm. Smart farm system and service with cloud platform contains 3 interfaces and 3 services. In addition, smart-farm using cloud platform could have several cases so it should be established and managed in varying way depending on cultivars, its size and type. This paper will focus the industry's attention on the importance of Open/Standard Cloud platform thereby stimulating the smartfarm in agriculture.

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Building a Private Cloud-Computing System for Greenhouse Control

  • Kim, JoonYong;Lee, Chun Gu;Park, Dong-Hyeok;Park, Heun Dong;Rhee, Joong-Yong
    • Journal of Biosystems Engineering
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    • v.43 no.4
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    • pp.440-444
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    • 2018
  • Purpose: Cloud-computing technology has several advantages, including maintenance, management, accessibility, and computing power. A greenhouse-control system utilizing these advantages was developed using a private cloud-computing system. Methods: A private cloud needs a collection of servers and a suite of software tools to monitor and control cloud-computing resources. In this study, a server farm, operated by OpenStack as a cloud platform, was constructed using servers, and other network devices. Results: The greenhouse-control system was developed according to the fundamental cloud service models: infrastructure as a service, platform as a service, and software as a service. This system has four additional advantages - security, control function, public data use, and data exchange. There are several considerations that must be addressed, such as service level agreement, data ownership, security, and the differences between users. Conclusions: When the advantages are utilized and the considerations are addressed, cloud-computing technology will be beneficial for agricultural use.

IoT Collaboration System Based on Edge Computing for Smart Livestock System (스마트 축사를 위한 에지 컴퓨팅 기반 IoT 협업 시스템)

  • Ahn, Chi-Hyun;Lee, Hyungtak;Chung, Kwangsue
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.26 no.2
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    • pp.258-264
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    • 2022
  • The smart farm for livestock, in which information and communication technology (ICT) is combined with livestock farm, is mostly based on the cloud computing paradigm. A cloud-based smart livestock farm has disadvantages such as increased response time, burden on cloud resource caused by the increased number of IoT sensors, traffic burden on the network, and lack of failure resilience mechanisms through collaboration with adjacent IoT devices. In this paper, with these problems in mind, we propose an IoT collaboration system based on edge computing. By using the relatively limited computing resources of the edge device to share the cloud's web server function, we aim to reduce the cloud's resources needed and improve response time to user requests. In addition, through the heartbeat-based failure recovery mechanism, IoT device failures were detected and appropriate measures were taken.

A Study on the Efficient Implementation Method of Cloud-based Smart Farm Control System (효율적인 클라우드 기반 스마트팜 제어 시스템 구현 방법)

  • Choi, Minseok
    • Journal of Digital Convergence
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    • v.18 no.3
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    • pp.171-177
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    • 2020
  • Under the influence of the Fourth Industrial Revolution, there are many tries to promote productivity enhancement and competitiveness by adapting smart farm technology that converges ICT technologies in agriculture. This smart farming technology is emerging as a new paradigm for future growth in agriculture. The development of real-time cultivation environment monitoring and automatic control system is needed to implement smart farm. Furthermore, the development of intelligent system that manages cultivation environment using monitoring data of the growth of crops is required. In this paper, a fast and efficient development method for implementing a cloud-based smart farm management system using a highly compatible and scalable web platform is proposed. It was verified that the proposed method using the web platform is effective and stable system implementation through the operation of the actual implementation system.

Design and Construction of Urban-type Energy Self-Supporting Smart-Farm Service Model (도심형 에너지 자립 스마트팜 서비스 모델 설계 및 구축)

  • Kim, Gwan-Hyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.23 no.10
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    • pp.1305-1310
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    • 2019
  • Modern agriculture is changing from resource-oriented agriculture to technology-oriented agriculture. Agriculture, which combines science and technology, is recognized as a new growth engine, and governments, local governments, research institutes, and industry are working together to develop and disseminate various devices necessary for smart farms to build intelligent smart farms. Recently, research is being conducted to build a more intelligent agricultural environment by building a cloud platform. In this paper, we propose a plan to build an urban energy - independent smart farm that can utilize leisure time and agricultural activities by utilizing the rooftop of a city. Also, by using IT technology, various data of smart farm can be managed on remote server, and HMI module for controlling internal environment of smart farm can be developed to manage smart farm automatically or semi-automatically. The service model suggests a model that can manage the internal environment of the smart farm based on mobile.

Livestock Disease Forecasting and Smart Livestock Farm Integrated Control System based on Cloud Computing (클라우드 컴퓨팅기반 가축 질병 예찰 및 스마트 축사 통합 관제 시스템)

  • Jung, Ji-sung;Lee, Meong-hun;Park, Jong-kweon
    • Smart Media Journal
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    • v.8 no.3
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    • pp.88-94
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    • 2019
  • Livestock disease is a very important issue in the livestock industry because if livestock disease is not responded quickly enough, its damage can be devastating. To solve the issues involving the occurrence of livestock disease, it is necessary to diagnose in advance the status of livestock disease and develop systematic and scientific livestock feeding technologies. However, there is a lack of domestic studies on such technologies in Korea. This paper, therefore, proposes Livestock Disease Forecasting and Livestock Farm Integrated Control System using Cloud Computing to quickly manage livestock disease. The proposed system collects a variety of livestock data from wireless sensor networks and application. Moreover, it saves and manages the data with the use of the column-oriented database Hadoop HBase, a column-oriented database management system. This provides livestock disease forecasting and livestock farm integrated controlling service through MapReduce Model-based parallel data processing. Lastly, it also provides REST-based web service so that users can receive the service on various platforms, such as PCs or mobile devices.

Research-platform Design for the Korean Smart Greenhouse Based on Cloud Computing (클라우드 기반 한국형 스마트 온실 연구 플랫폼 설계 방안)

  • Baek, Jeong-Hyun;Heo, Jeong-Wook;Kim, Hyun-Hwan;Hong, Youngsin;Lee, Jae-Su
    • Journal of Bio-Environment Control
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    • v.27 no.1
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    • pp.27-33
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    • 2018
  • This study was performed to review the domestic and international smart farm service model based on the convergence of agriculture and information & communication technology and derived various factors needed to improve the Korean smart greenhouse. Studies on modelling of crop growth environment in domestic smart farms were limited. And it took a lot of time to build research infrastructure. The cloud-based research platform as an alternative is needed. This platform can provide an infrastructure for comprehensive data storage and analysis as it manages the growth model of cloud-based integrated data, growth environment model, actuators control model, and farm management as well as knowledge-based expert systems and farm dashboard. Therefore, the cloud-based research platform can be applied as to quantify the relationships among various factors, such as the growth environment of crops, productivity, and actuators control. In addition, it will enable researchers to analyze quantitatively the growth environment model of crops, plants, and growth by utilizing big data, machine learning, and artificial intelligences.

Classification of Summer Paddy and Winter Cropping Fields Using Sentinel-2 Images (Sentinel-2 위성영상을 이용한 하계 논벼와 동계작물 재배 필지 분류 및 정확도 평가)

  • Hong, Joo-Pyo;Jang, Seong-Ju;Park, Jin-Seok;Shin, Hyung-Jin;Song, In-Hong
    • Journal of The Korean Society of Agricultural Engineers
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    • v.64 no.1
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    • pp.51-63
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    • 2022
  • Up-to-date statistics of crop cultivation status is essential for farm land management planning and the advancement in remote sensing technology allows for rapid update of farming information. The objective of this study was to develop a classification model of rice paddy or winter crop fields based on NDWI, NDVI, and HSV indices using Sentinel-2 satellite images. The 18 locations in central Korea were selected as target areas and photographed once for each during summer and winter with a eBee drone to identify ground truth crop cultivation. The NDWI was used to classify summer paddy fields, while the NDVI and HSV were used and compared in identification of winter crop cultivation areas. The summer paddy field classification with the criteria of -0.195

A Study on Security Threats and Countermeasures in Smart Farm Environments (스마트 팜 환경에서 보안 위협 및 대응 방안에 관한 연구)

  • Sun-Jib Kim
    • Journal of Internet of Things and Convergence
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    • v.10 no.1
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    • pp.53-58
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    • 2024
  • IoT, Big-data, AI, and Cloud technologies, which are core technologies of the 4th Industrial Revolution, have recently been applied to various fields and are being used as core technologies for new growth engines. Accordingly, these core technologies are applied to the agricultural field without exception, contributing to solving the problem of labor shortage, reducing production costs, and reducing environmental burden through remote and automated production without time and space constraints. However, as these core technologies are utilized, security incidents are occurring in the agricultural field as well. Accordingly, this study divides smart farms into three stages(Basic, Middle, and High) and presents the characteristics and security threats of each stage. In particular, as the number of container-based services and research increases under cloud platforms, we would like to suggest countermeasures focusing on security threats.