• Title/Summary/Keyword: Smart Greenhouse

검색결과 142건 처리시간 0.031초

이동평균 알고리즘을 적용한 스마트 그린하우스 자동제어 시스템 (An Smart Greenhouse Automation System Applying Moving Average Algorithm)

  • 바스넷버룬;이인재;노명준;천현준;자파르아만;방준호
    • 전기학회논문지
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    • 제65권10호
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    • pp.1755-1760
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    • 2016
  • Automation of greenhouses has proved to be extremely helpful in maximizing crop yields and minimizing labor costs. The optimum conditions for cultivating plants are regularly maintained by the use of programmed sensors and actuators with constant monitoring of the system. In this paper, we have designed a prototype of a smart greenhouse using Arduino microcontroller, simple yet improved in feedbacks and algorithms. Only three important microclimatic parameters namely moisture level, temperature and light are taken into consideration for the design of the system. Signals acquired from the sensors are first isolated and filtered to reduce noise before it is processed by Arduino. With the help of LabVIEW program, Time domain analysis and Fast Fourier Transform (FFT) of the acquired signals are done to analyze the waveform. Especially, for smoothing the outlying data digitally, Moving average algorithm is designed. With the implement of this algorithm, variations in the sensed data which could occur from rapidly changing environment or imprecise sensors, could be largely smoothed and stable output could be created. Also, actuators are controlled with constant feedbacks to ensure desired conditions are always met. Lastly, data is constantly acquired by the use of Data Acquisition Hardware and can be viewed through PC or Smart devices for monitoring purposes.

적엽작업을 반영하기 위한 시설토마토 생육모형(GreenTom) 개선 및 검증 (Improving and Validating a Greenhouse Tomato Model "GreenTom" for Simulating Artificial Defoliation)

  • 김연욱;김진현;이변우
    • 한국농림기상학회지
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    • 제21권4호
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    • pp.373-379
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    • 2019
  • 스마트팜은 원예작물의 생산성과 품질을 제고하기 위한 생력화 방법으로 최근 많은 주목을 받고 있다. 하지만 국내의 스마트팜은 단순한 환경 모니터링과 환경제어만 가능한 초기단계에 머물고 있으며, 작물 생육에 최적화된 환경을 모의하는 의사결정도구의 개발은 미흡한 상태이다. 본 연구에서는 의사결정도구로써의 작물생육모형의 활용가능성을 확인하기 위해 국내에서 개발된 GreenTom모형의 품종모수를 추정하고 모형의 모의 성능을 검증하였다. 적엽은 시설토마토 재배에서 흔히 행해지는 농작업이지만 기존 모형은 이를 모의하지 않아 지상부 생육 모의에 문제를 나타냈다. 이를 해결하기 위해 적엽 알고리즘을 개발하여 기존 모형에 추가하고 모의 성능을 검증한 결과, 개선된 모형은 시설재배 토마토의 발달과 생육을 비교적 잘 모의하여 본 모형이 의사결정도구로 활용될 수 있음을 확인하였다.

비표준 센서 및 구동기 노드를 지원하는 표준사양 기반 스마트팜 연구 (A Study on the Standard-interfaced Smart Farm Supporting Non-Standard Sensor and Actuator Nodes)

  • 방대욱
    • 한국IT서비스학회지
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    • 제19권3호
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    • pp.139-149
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    • 2020
  • There are now many different commercial weather sensors suitable for smart farms, and various smart farm devices are being developed and distributed by companies participating in the government-led smart farm expansion project. However, most do not comply with standard specifications and are therefore limited to use in smart farms. This paper proposed the connecting structure of operating non-standard node devices in smart farms following standard specifications supporting smart greenhouse. This connecting structure was proposed as both a virtual node module method and a virtual node wrapper method. In addition, the SoftFarm2.0 system was experimentally operated to analyze the performance of the implementation of the two methods. SoftFarm2.0 system complies with the standard specifications and supports non-standard smart farm devices. According to the analysis results, both methods do not significantly affect performance in the operation of the smart farm. Therefore, it would be good to select and implement the method suitable for each non-standard smart farm device considering environmental constraints such as power, space, distance of communication between the gateway and the node of the smart farm, and software openness. This will greatly contribute to the spread of smart farms by maximizing deployment cost savings.

An intelligent monitoring of greenhouse using wireless sensor networks

  • Touhami, Achouak;Benahmed, Khelifa;Parra, Lorena;Bounaama, Fateh;Lloret, Jaime
    • Smart Structures and Systems
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    • 제26권1호
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    • pp.117-134
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    • 2020
  • Over recent years, the interest for vegetables and fruits in all seasons and places has much increased, from where diverse countries have directed to the commercial production in greenhouse. In this article, we propose an algorithm based on wireless sensor network technologies that monitor the microclimate inside a greenhouse and linear equations model for optimization plant production and material cost. Moreover, we also suggest a novel design of an intelligent greenhouse. We validate our algorithms with simulations on a benchmark based on experimental data made at lNRA of Montfavet in France. Finally, we calculate the statistical estimators RMSE, TSSE, MAPE, EF and R2. The results obtained are promising, which shows the efficiency of our proposed system.

Comparison of Environment, Growth, and Management Performance of the Standard Cut Chrysanthemum 'Jinba' in Conventional and Smart Farms

  • Roh, Yong Seung;Yoo, Yong Kweon
    • 인간식물환경학회지
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    • 제23권6호
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    • pp.655-665
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    • 2020
  • Background and objective: This study was conducted to compare the cultivation environment, growth of cut flowers, and management performance of conventional farms and smart farms growing the standard cut chrysanthemum, 'Jinba'. Methods: Conventional and smart farms were selected, and facility information, cultivation environment, cut flower growth, and management performance were investigated. Results: The conventional and smart farms were located in Muan, Jeollanam-do, and conventional farming involved cultivating with soil culture in a plastic greenhouse, while the smart farm was cultivating with hydroponics in a plastic greenhouse. The conventional farm did not have sensors for environmental measurement such as light intensity and temperature and pH and EC sensors for fertigation, and all systems, including roof window, side window, thermal screen, and shading curtain, were operated manually. On the other hand, the smart farm was equipped with sensors for measuring the environment and nutrient solution, and was automatically controlled. The day and night mean temperatures, relative humidity, and solar radiation in the facilities of the conventional and the smart farm were managed similarly. But in the floral differentiation stage, the floral differentiation was delayed, as the night temperature of conventional farm was managed as low as 17.7℃ which was lower than smart farm. Accordingly, the harvest of cut flowers by the conventional farm was delayed to 35 days later than that of the smart farm. Also, soil moisture and EC of the conventional farm were unnecessarily kept higher than those of the smart farm in the early growth stage, and then were maintained relatively low during the period after floral differentiation, when a lot of water and nutrients were required. Therefore, growth of cut flower, cut flower length, number of leaves, flower diameter, and weight were poorer in the conventional farm than in the smart farm. In terms of management performance, yield and sales price were 10% and 38% higher for the smart farm than for the conventional farm, respectively. Also, the net income was 2,298 thousand won more for the smart farm than for the conventional farm. Conclusion: It was suggested that the improved growth of cut flowers and high management performance of the smart farm were due to precise environment management for growth by the automatic control and sensor.

온실 내 환경데이터 분석을 통한 파프리카 온실의 식별 (Identification of Sweet Pepper Greenhouse by Analysis of Environmental Data in Greenhouse)

  • 김나은;이경근;이덕현;문병은;박재성;김현태
    • 생물환경조절학회지
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    • 제30권1호
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    • pp.19-26
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    • 2021
  • 본 연구에서는 같은 지역에 위치한 온실 3곳의 식별을 위해 통계적인 방법으로 분류를 하고자 주성분 분석(PCA)과 선형 판별 분석(LDA)을 수행하였다. 온실 내의 환경데이터는 같은 지역의 온실 3곳을 대상으로 4월1일부터 4월28일 총4주간 1시간 간격으로 수집된 값을 사용하였다. 데이터를 분석하기 전, 데이터 정규화를 시키는 전처리를 거쳤으며, 전체의 80%인 훈련자료(training data)와 20%인 테스트 자료(test data)로 나누어 분석을 수행하였다. 분석을 수행한 결과, PC1은 57.51%의 설명력으로 PC1 = 0.7118112 × Tem. -0.6830065 × Humi. -0.1637892 × CO2.의 식을 가지며, LD1은 67.06%의 설명력으로 LD1 = 0.8622565 × Tem. -0.1805741 × Humi. + 1.4018140 × CO2. + 0.03040701의 식을 가지는 것으로 나타났다. 이렇게 미리 분류시켜놓은 온실의 데이터를 바탕으로 새로운 환경의 데이터를 입력하였을 때 특정 그룹으로의 분류가 가능함으로써 데이터의 성향을 파악할 수 있다. 이러한 데이터는 식별을 용이하게 함으로써 데이터의 활용도를 높여주는 방법이라고 판단된다.

Home Energy Management System for Residential Customer: Present Status and Limitation

  • Lee, Sunguk;Park, Byungjoo
    • International Journal of Advanced Culture Technology
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    • 제6권4호
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    • pp.284-291
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    • 2018
  • As environmental pollution has become worse green technologies to replace or reduce consumption of fossil fuel get spotlight from government, industry and academia globally. It is reported that 40% of carbon dioxide emission is caused by electricity power generation. And 37% of end user electricity power is used by residential costumer in US. Smart Grid is considered as one of promising technology to alleviate severe environmental problem. In residential environment, Home Energy Management System (HEMS) can play a key role for green smart home. The HEMS can give several benefits like aslowering electric utility bill, improvement of efficiency of electric power consumption and integration of generator using renewable energy resources. However just limited functions of HEMS can be used for residential customer in real life because of lack of smart function in home appliances and optimal managing software for HEMS. This study provides comprehensive analysis for Home Energy Management System for residential customer. Simple HEMS system with real products on the market are explained and limitation of current HEMS are also discussed.

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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    • 제43권4호
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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.

Penman-Monteith을 이용한 토마토와 파프리카의 증발산 모델 평가 (Assessment of Water Control Model for Tomato and Paprika in the Greenhouse Using the Penman-Monteith Model)

  • 솜늑 시리락;홍영신;김민영;이상규;백정현;곽강수;이현동;이재수
    • 생물환경조절학회지
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    • 제29권3호
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    • pp.209-218
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    • 2020
  • ETc 손실을 보상하는데 필요한 물의 양을 작물 용수 요구량(Crop water requirement, CWR)로 정의되며, ETc 평가는 작물 필요 요구량을 정확하게 정량화하는 데 필요하며, 물 균형 계산에서 중요한 역할을 한다. 토마토와 파프리카의 실제 관수 요구량(Actual crop water, ACW)이 적절한 CWR인지 평가하였다. 토마토와 파프리카 재배에 적정한 AWC 예측 및 추정을 위하여 온실 내부 환경데이터를 Penman-Monteith을 이용하여 기준 작물 증발산(ET)을 계산한 후, 기준 증발산은 작물 상수(Kc;토마토-1.15, 파프리카-1.05)계수로 조정하였다. 토마토와 파프리카의 CWR과 ACW를 계산하여 비교 평가한 결과 ACW가 CWR을 대체할 수 있지만 파프리카의 ACW는 필요 이상으로 높게 나타났다. 또한, 토마토의 ACW는 1일 100 ~ 1,200 ml이고, 파프리카의 ACW는 1일 100 ~ 500 ml가 적절한 것으로 나타났다. 그러나, 스마트 온실에서 ETc의 정밀도를 높이려면, ETc가 CWR로 변환되고 ACW와 비교하기 위해서 클래스 A팬 설정이 필요하다. 향후 실시간으로 CWR을 측정하기 위한 시뮬레이션 프로그램 연구가 필요하다.

컨테이너 온실에서 폐열 활용 및 IOT 기반의 스마트 팜 연계 기술 (The waste heat utilization in container greenhouse and smart farm related technology based on IOT)

  • 황우정;정정훈
    • 한국정보통신학회:학술대회논문집
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    • 한국정보통신학회 2017년도 추계학술대회
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    • pp.415-418
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    • 2017
  • 최근 폐열에너지와 스마트 그리드 연계를 통한 에너지 효율 향상 기술 수요가 증가하고 있는 추세이다. 또한 컨테이너 온실을 이용한 식물공장 개념의 스마트팜과 폐열 에너지의 실시간 활용을 위한 융합기술에 대한 연구를 통하여 고부가가치 작물을 재배에 대한 투자가 증가하고 있다. 이런 관점에서 에너지 효율 측면에서 LED 기반의 식물공장에 대한 경제성을 높여 농가에 실질적인 도움이 되는 실용화 기술에 대한 연구를 수행 하였다. 이는 향후 자동화될 대규모의 스마트 팜과 연계할 수 있는 기회를 제공할 수 있다. 본 연구에서는 폐열 에너지를 이용한 컨테이너 온실에서 냉방기술을 이용하여 작물재배의 경제성에 대한 연구이다. 컨테이너 온실, 폐열을 이용한 흡수식 냉동기를 IOT 기술을 이용하여 실시간 모니터링/제어하기 위하여 라즈베리 파이 기반의 게이트웨이를 모바일 기반에서 운영함으로써 냉방 에너지의 효용을 최대화 할 수 있는 새로운 형태의 농업 기술에 대한 연구를 제안하고자 한다.

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