• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.1
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• pp.1-9
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• 2011

In this paper, Wireless sensor network technology applied to various greenhouse agro-industry items such as horticulture and local specialty etc., we was constructed automatic control system for optimum growth environment by measuring growth status and environmental change. existing monitoring systems of greenhouse gather information about growth environment depends on the temperature. but in this system, Can be efficient collection and control of information to construct wireless sensor network by growth measurement sensor and environment monitoring sensor inside of the greenhouse. The system is consists of sensor manager for information processing, an environment database that stores information collected from sensors, the GUI of show the greenhouse status, it gather soil and environment information to soil and environment(including weather) sensors, growth measurement sensor. In addition to support that soil information service shows the temperature, moisture, EC, ph of soil to user through the interaction of obtained data and Complex Growth Environment information service for quality and productivity can prevention and response by growth disease or disaster of greenhouse agro-industry items how temperature, humidity, illumination acquiring informationin greenhouse(strawberry, ginseng). To verify the executability of the system, constructing the complex growth environment measurement system using wireless sensor network in greenhouse and we confirmed that it is can provide our optimized growth environment information.

• IEMEK Journal of Embedded Systems and Applications
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• v.7 no.6
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• pp.301-309
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• 2012

In this paper, a real-time monitoring system based on WSN is designed and implemented to monitor livestock growth environment information which includes the temperature, humidity and harmful gases such as $CO_{2},\;CO,\;NH_{3},\;H_{2}S$ and so on. The proposed system consists of the wireless sensor nodes, the monitoring management device, the management server and the user interface program based on PC/Smart phone. To verify the performance of the implemented system, gas measurement experiments are performed in laboratory environment by using the designed wireless sensor nodes. And it is able to estimate the concentration of gases. The implemented system is able to monitor the proposed environmental element information through the developed GUI.

• Korean Journal of Soil Science and Fertilizer
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• v.50 no.3
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• pp.162-178
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• 2017

Remote sensing can be used to provide information about the monitoring of crop growth condition. Recently Unmanned Aerial Vehicle (UAV) technology offers new opportunities for assessing crop growth condition using UAV imagery. The objective of this study was to assess weather UAV aerial images are suitable for the monitoring of highland Kimchi cabbage. This study was conducted using a fixed-wing UAV (Model : Ebee) with Cannon S110, IXUS/ELPH camera during farming season from 2015 to 2016 in the main production area of highland Kimchi cabbage, Anbandegi, Maebongsan, and Gwinemi. The Normalized Difference Vegetation Index (NDVI) by using UAV images was stable and suitable for monitoring of Kimchi cabbage situation. There were strong relationships between UAV NDVI and the growth parameters (the plant height and leaf width) ($R^2{\geq}0.94$). The tendency of UAV NDVI according to Kimchi cabbage growth was similar in the same area for two years (2015~2016). It means that if UAV image may be collected several years, UAV images could be used for estimation of the stage of growth and situation of Kimchi cabbage cultivation.

• Korean Journal of Agricultural Science
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• v.46 no.1
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• pp.57-65
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• 2019

The purpose of this study was to develop an environment field monitoring system to measure crop growth. The environment field monitoring system consisted of sensors, a data acquisition system, and GPS. The sensors used in the environment field monitoring system consisted of an ambient sensor, a soil sensor, and an intensity sensor. The temperature and humidity of the atmosphere were measured with the ambient sensor. The temperature, humidity, and EC of the soil were measured with the soil sensor. The data acquisition system was developed using the Arduino controller. The field monitoring data were collected before a rainy day, on a rainy day, and after the rainy day. The measured data using the environment field monitoring system were compared with the Daejeon regional meteorological office data. The correlation between the data from the environment field monitoring system and the data from the Daejeon regional meteorological office was analyzed for performance evaluation. The correlation of the temperature and humidity of the atmosphere was analyzed because the Daejeon regional meteorological office only provided data for the temperature and humidity of the atmosphere. The correlation coefficients were 0.86 and 0.90, respectively. The result showed a good correlation between the data from the environment field monitoring system and the data from the Daejeon regional meteorological office. Therefore, the developed system could be applied to monitoring the field environment of agricultural crops.

• Journal of Advanced Navigation Technology
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• v.15 no.5
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• pp.795-800
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• 2011

In this paper, to promote the production of agricultural products, it is goal to design and implement the growth environmental management monitoring system. Based on the IT convergence technology, it consists of four components such as sensor nodes to sense environmental factors, sink nodes to communicate with sensors, gateway to link sinknodes to monitoring system, and monitoring software. With monitoring process for temperature and humidity, we can obtain the bast growth environment to be maintained deviation value 10% for temperature and humidity.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.25-30
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• 1999

The effectiveness of many greenhouse environment control methodologies depends on the growth information of crops. Acquisition of the growth information of crops requires a non-invasive and continuous monitoring method. Crop growth monitoring system using digital imaging technique was developed to conduct non-destructive and intact plant growth analyses. The monitoring system automatically measures crop growth information sends an appropriate control signal to the nutrient solution supplying system. To develop the monitoring system, a linear model that explains the relationship between the fresh weight and the top projected leaf area of a lettuce plant was developed from an experiment. The monitoring system was evaluated buy successive lettuce growing experiments. Results of the experiments showed that the developed system could estimate the fresh weight of lettuce from a lettuce image by using the linear model and generate an EC control signal according to the lettuce growth stage.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.4
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• pp.155-159
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• 2018

In this paper, we designed and built a system that is site manager can be monitored remotely to the growth of the fishery environment. To this end, modular distribution system and environmental monitoring of live fishery products. Simulation results, were building a purification system and the oxygen supply to the fishery living inside the container was to build a system that can be monitored in real time. As a result, it was able to raise the necessary environment for the storage and distribution of fisheries products. We constructed a monitoring system with database and communication environment and created the optimal environment suitable for growth with sensor. As a result, it was possible to monitor the environment for the storage and distribution of fishery products and to build a suitable fishery products management system.

• Journal of Practical Agriculture & Fisheries Research
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• v.24 no.4
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• pp.53-61
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• 2022

Growing agricultural products in greenhouses controlled by creating suitable climatic conditions and root zone of crop has been an important research and application subject. Appropriate environmental conditions in greenhouse are necessary for optimum plant growth improved crop yields. This study aimed to establish web-based remote monitoring system which monitors crops growth environment and status of crop on a real-time basis by applying to greenhouses IT technology connecting greenhouse equipment such as temperature sensors, soil sensors, crop sensors and camera. The measuring items were air temperature, relative humidity, solar radiation, CO₂ concentration, EC and pH of nutrient solution, medium temperature, EC of medium, water content of medium, leaf temperature, sap flow, stem diameter, fruit diameter, etc. The developed greenhouse monitoring system was composed of the network system, the data collecting device with sensors, and cameras. Remote monitoring system was implemented in a server/client environment. Information on greenhouse environment and crops is stored in a database. Items on growth and environment is extracted from stored information, could be compared and analyzed. So, A integrated monitoring system for smart greenhouse would be use in application practice and understanding the environment and crop growth for smart greenhouse management. sap flow, stem diameter and pant-water relations

• Journal of KIISE:Computing Practices and Letters
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• v.15 no.5
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• pp.331-344
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• 2009

Recently, it is expected that the agricultural and stockbreeding industry are damaged by the China-Japan-South Korea FTA and FTA between the United States and South Korea. After free trade, it is increasing to import crops, aquatic products, and livestock which are produced in a foreign land. But it is affected negatively to the trust relationships and markets, because of breaking it out that low grade foreign products are turned into domestic products. For this reason, we need the traceability management system. In this paper, it designs and implements the traceability management system using RFID and USN providing distribution traceability information as well as the traceability information of the growth environment, automatic control according to the facility growing and monitoring of the storehouse. The implemented whole systems consist of the growth environment monitoring and the traceability management. First, the growth environment monitoring shows the environment of plantation and automatic controller of the storehouse and growing facility. This growth environment monitoring information provides the detailed information about growth environment and writing the farming diary automatically by producer. Second, the traceability management provides all of the traceability information such as production, shipment and consumption to consumers. The traceability management system that has been designed and implemented using RFID and USN in this paper, provides the u-IT agriculture to producer and the reliability about agricultural products. In addition, this system provides the foundation data to operate GAP and HACCP, and becomes the advantaged agricultural products of the interior of a country by application of this system.

• International journal of advanced smart convergence
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• v.12 no.3
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• pp.104-108
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• 2023

This paper deals with research on innovative systems using Python-based artificial intelligence technology in the field of plant growth monitoring. The importance of monitoring and analyzing the health status and growth environment of plants in real time contributes to improving the efficiency and quality of crop production. This paper proposes a method of processing and analyzing plant image data using computer vision and deep learning technologies. The system was implemented using Python language and the main deep learning framework, TensorFlow, PyTorch. A camera system that monitors plants in real time acquires image data and provides it as input to a deep neural network model. This model was used to determine the growth state of plants, the presence of pests, and nutritional status. The proposed system provides users with information on plant state changes in real time by providing monitoring results in the form of visual or notification. In addition, it is also used to predict future growth conditions or anomalies by building data analysis and prediction models based on the collected data. This paper is about the design and implementation of Python-based plant growth monitoring systems, data processing and analysis methods, and is expected to contribute to important research areas for improving plant production efficiency and reducing resource consumption.