• Proceedings of the Korean Society of Broadcast Engineers Conference
• /
• 2022.06a
• /
• pp.475-476
• /
• 2022

Internet of Media Things (IoMT)는 Internet of Things (IoT) 기술을 기반으로 미디어 기반 제어를 지원하고자 하는 표준으로 진행되고 있으며, 다양한 미디어 관련 기기를 크게 네 종류의 카테고리로 구분하여 미디어 기반 서비스를 제공하기 위한 인터페이스 표준을 정의하고 있다. 또한 미디어 기반 서비스 제공을 위한 다양한 유즈 케이스를 제공하고 있으며 이는 서비스 구성 및 활용에 대한 레퍼런스로 제공되고 있다. 본 논문에서는 이와 같은 IoMT 기술을 활용하여 정밀 농업 서비스를 제공하는 구성 기술을 제안한다. 정밀 농업 기술은 영상을 포함한 센서 기술들을 사용하여 농업 환경을 분석하고 이를 기반으로 사용자에게 의사결정을 지원하는 도구로 제시되고 있으며, 기존 온도 습도 등 센서 기반의 환경으로부터 영상 정보를 포함한 분석 기술을 활용하는 형상으로 확장되고 있다. 이는 기존의 IoT 기술에 대한 미디어 기술의 접목이 반드시 요구되는 부분으로, 정밀 농업을 위한 분석 기술의 활용에 대한 IoMT 기술의 새로운 사용 시나리오를 제시할 수 있다. 본 논문에서는 딸기 작물을 대상으로 스마트팜에서의 영상 정보를 활용한 분석 기법을 제안한다.

• Journal of Biosystems Engineering
• /
• v.41 no.3
• /
• pp.255-262
• /
• 2016

Purpose: Fuji apples are one of the top selling exports for South Korea bringing in over $233.4 million in 2013. However, during the last few decades, about half of the Fuji apple orchards have been infected by Apple Marssonina Blotch disease (AMB), a fungal disease caused by Diplocarpon mali., which takes about 40 days to exhibit obvious visible symptoms. Infected leaves turn yellow and begin growing brown lesions. AMB promotes early defoliation and reduces the quality and quantity of apples an infected tree can produce. Currently, there is no prediction model for AMB on the market. Methods: The Precision Agriculture Laboratory (PAL) at the University of Florida (UF) has been working with the National Academy of Agricultural Science, Rural Development Administration, South Korea to investigate the use of hyperspectral data in creating an early detection method for AMB. The RDA has been researching hyperspectral techniques for disease detection at their Apple Research Station in Gunwi since 2012 and disseminates its findings to the local farmers. These farmers were surveyed to assess the state of knowledge of AMB in the area. Out of a population of about 750 growers, 111 surveys were completed (confidence interval of +/- 8.59%, confidence level of 95%, p-value of 0.05). Results: The survey revealed 32% of the farmers did not know what AMB was, but 45% of farmers have had their orchards infected by AMB. Twenty-five percent could not distinguish AMB from other symptoms. Overwhelmingly, 80% of farmers strongly believed an early detection method for AMB was necessary. Conclusions: The results of the survey will help to evaluate the outreach programs of the RDA so they can more effectively educate farmers on the identifying, treating, and mediating AMB.

• KOREAN JOURNAL OF CROP SCIENCE
• /
• v.43 no.2
• /
• pp.113-119
• /
• 1998

Spatial patterns of soil temperature on sloping lands are related to the amount of solar irradiance at the surface. Since soil temperature is a critical determinant of many biological processes occurring in the soil, an accurate prediction of soil temperature distribution could be beneficial to agricultural and environmental management. However, at least two problems are identified in soil temperature prediction over natural sloped surfaces. One is the complexity of converting solar irradiances to corresponding soil temperatures, and the other, if the first problem could be solved, is the difficulty in handling large volumes of geo-spatial data. Recent developments in geographic information systems (GIS) provide the opportunity and tools to spatially organize and effectively manage data for modeling. In this paper, a simple model for conversion of solar irradiance to soil temperature is developed within a GIS environment. The irradiance-temperature conversion model is based on a geophysical variable consisting of daily short- and long-wave radiation components calculated for any slope. The short-wave component is scaled to accommodate a simplified surface energy balance expression. Linear regression equations are derived for 10 and 50 cm soil temperatures by using this variable as a single determinant and based on a long term observation data set from a horizontal location. Extendability of these equations to sloped surfaces is tested by comparing the calculated data with the monthly mean soil temperature data observed in Iowa and at 12 locations near the Tennessee - Kentucky border with various slope and aspect factors. Calculated soil temperature variations agreed well with the observed data. Finally, this method is applied to a simulation study of daily mean soil temperatures over sloped corn fields on a 30 m by 30 m resolution. The outputs reveal potential effects of topography including shading by neighboring terrain as well as the slope and aspect of the land itself on the soil temperature.

• Proceedings of the Korean Society of Crop Science Conference
• /
• 2023.04a
• /
• pp.79-79
• /
• 2023

With the development of digital technology, the size of the smart agriculture market at home and abroad is rapidly expanding. It is necessary to establish a foundation for sustainable precision agriculture in order to respond to the aging of rural areas and labor shortages. This study was conducted to establish an automated digital agricultural test bed for soybean production management using data suitable for agricultural environmental conditions in Korea and to demonstrate the field of leading complexes. In order to manage water smartly, we installed a subsurface drip irrigation system in the upland field and an underground water level control system in the paddy field. Based on data collected from sensors, water management was controlled by utilizing an integrated control system. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. The main growth characteristics and yield, such as stem length, number of branches, and number of nodes of the main stem, were investigated during the main growth period. During the operation of the test bed, drought appeared during the early vegetative growth period and maturity period, but in the open field smart agriculture test bed, water was automatically supplied, reducing labor by 53% and increasing yield by 2%. A test bed was installed for each field digital farming element technology, and it is planned to verify it once more this year. In the future, we plan to expand the field digital farming technology developed for leading farmers to the field.

• Journal of Drive and Control
• /
• v.21 no.2
• /
• pp.36-43
• /
• 2024

The yield is basic and necessary information in precision agriculture that reduces input resources and enhances productivity. Yield information is important because it can be used to set up farming plans and evaluate farming results. Yield monitoring systems are commercialized in the United States and Japan but not in Korea. Therefore, such a system must be developed. This study was conducted to develop a yield monitoring system that improved performance by correcting a previously developed flow sensor using a grain tank-weighing system. An impact-plated type flow sensor was installed in a grain tank where grains are placed, and grain tank-weighing sensors were installed under the grain tank to estimate the weight of the grain inside the tank. The grain flow rate and grain weight prediction models showed high correlations, with coefficient of determinations (R2) of 0.9979 and 0.9991, respectively. A main controller of the yield monitoring system that calculated the real-time yield using a sensor output value was also developed and installed in a combine harvester. Field tests of the combine harvester yield monitoring system were conducted in a rice paddy field. The developed yield monitoring system showed high accuracy with an error of 0.13%. Therefore, the newly developed yield monitoring system can be used to predict grain weight with high accuracy.

• Agricultural and Biosystems Engineering
• /
• v.7 no.1
• /
• pp.18-26
• /
• 2006

In-field site-specific nitrogen (N) management increases crop yield, reduces N application to minimize the risk of nitrate contamination of ground water, and thus reduces farming cost. Real-time N sensing and fertilization is required for efficient N management. An 'on-the-go' site-specific N management system was developed and evaluated for the supplemental N application to com (Zea mays L.). This real-time N sensing and fertilization system monitored and assessed N fertilization needs using a vision-based spectral sensor and controlled the appropriate variable N rate according to N deficiency level estimated from spectral signature of crop canopies. Sensor inputs included ambient illumination, camera parameters, and image histogram of three spectral regions (red, green, and near-infrared). The real-time sensor-based supplemental N treatment improved crop N status and increased yield over most plots. The largest yield increase was achieved in plots with low initial N treatment combined with supplemental variable-rate application. Yield data for plots where N was applied the latest in the season resulted in a reduced impact on supplemental N. For plots with no supplemental N application, yield increased gradually with initial N treatment, but any N application more than 101 kg/ha had minimal impact on yield.

• Korean Journal of Agricultural Science
• /
• v.43 no.4
• /
• pp.634-640
• /
• 2016

The objective of this study was to evaluate the effectiveness of using HR-GC/MS for the rapid screening of dieldrin residues in soils. Persistent organic pollutants (POPs) of organochlorine pesticides such as dieldrin, were analyzed in sedimentary rock and granite rock collected from greenhouses, Niigata, Japan. Dieldrin remains in Japanese farming soils, more than 40 years after their use as insecticides was prohibited. The averages in soil moisture ranged from 2.79% to 7.20% in soils derived from sedimentary rock and from 25.59% to 31.40% in soils derived from granite rock. Mean concentrations of dieldrin residues in sedimentary rock and granite rock were $39.7ng\;g^{-1}$ and $40.51ng\;g^{-1}$, respectively. Dieldrin residue was detected at a slightly higher concentration in granite rock than sedimentary rock samples. There was no consistency between the two soils or between surface and subsurface soils. The coefficients of variation of the two soils were 10.6% and 8.7%, respectively. These results suggest that our high-resolution mass spectrometry detector (HR-GC/MS) is effective at analyzing residual organochlorine pesticides in soil. In order to increase the precision and sensitivity for chemical analysis of POPs, high-resolution gas chromatography coupled with a HR-GC/MS is highly recommended.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.15 no.9
• /
• pp.1881-1888
• /
• 2011

Red tide is a natural phenomenon to bloom harmful algal, which fish and shellfish die en masse. Red tide damage with respect to sea farming has been occurred each year. Red tide damage can be minimized by means of prediction of red tide blooms. Red tide prediction using naive bayes classifier can be achieve good prediction results. The result of naive bayes method only determine red tide blooms, whereas the method can not know how increasing of red tide algae density. In this paper, we proposed the red tide blooms prediction method using fuzzy reasoning and naive bayes classifier. The proposed method can enhance the precision of red tide prediction and forecast the increasing density of red tide algae.

• Journal of Biosystems Engineering
• /
• v.32 no.5
• /
• pp.332-338
• /
• 2007

Yield mapping is necessary for precision farming. An on-site rice weighing system for a head-feed combine was developed to measure the total weight of rice grain harvested while the combine was operated. A load cell system was used to monitor rice weights accumulated into the combine grain tank using a load cell. This method gave cumulative grain weight readings as a function of time. The system consisted of a load cell, two supporting brackets, and a computer-based data acquisition system. The weights measured with the system from two fields were compared with those obtained with a commercially available electronic balance. The response of the load cell to varying grain weights was linearly modeled, showing a coefficient of determination of 0.998 and a standard error of ${\pm}4.09kg$.

• Asian-Australasian Journal of Animal Sciences
• /
• v.23 no.2
• /
• pp.279-286
• /
• 2010

Livestock production in Vietnam is, as in most Asian countries, increasing rapidly and changing into specialized highly intensified operations. The volume of animal excreta generated exceeds the capacity of the operation land base and cannot be utilized efficiently. As a consequence, there is a loss of plant nutrients from livestock farms that causes environmental pollution. This study carried out a feed and excretion experiment measuring fecal characteristic, daily fecal production, daily nitrogen and phosphorous excretion from grower-finisher pigs fed prevalent rations in Vietnam. Furthermore, equations for assessing the excretion were tested, which can be used in farm models for optimal recycling of manure while focusing on reducing pollution. The results indicated that fecal production and nutrient excretion were affected by the different rations tested. This study showed that five selected equations for predicting excretion from grower-finisher pigs in Danish conditions can also be used with precision in Vietnamese pig farming systems. The equations have been proven valid and can, therefore, be used as a much needed tool for assessing fecal production and nitrogen in excreta on pig farms. The study also showed that about 12% of nitrogen excreted was emitted during housing. Waste water contains more than half of the nitrogen excreted, mainly in ammonium form which has a high potential for gaseous emission.