• Journal of Biosystems Engineering
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• v.35 no.2
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• pp.132-137
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• 2010

Site-specific N application for corn is one of the precision crop management. To implement the site-specific N application, various nitrogen stress sensing methods, including aerial image, tissue analysis, soil sampling analysis, and SPAD meter readings, have been used. Use of side-dressing, an efficient nitrogen application method than a uniform application in either late fall or early spring, relies mainly on the capability of nitrogen deficiency detection. This paper presents map-based variable rate nitrogen application based using a multi-spectral corn nitrogen deficiency(CND) sensor. This sensor assess the nitrogen stress by means of the estimated SPAD reading calculated from the corn leave reflectance. The estimated SPAD value from the CND sensor system and location information form DGPS of each field block was combined into the field map using a ArcView program. Then this map was converted into a raster file for a map-based variable rate application software. The relative SPAD (RSPAD = SPAD over reference SPAD) was investigated 2 weeks after the treatments. The results showed that the map-based variable rate application system was feasible.

• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.361-367
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• 2009

The criteria such as ASTM recommends that the zero reading process of CPT must be performed in the same temperature condition with underground in order to reduce the effect of temperature. However, this method can not consider the change of temperature occurred during penetration. In this study, ultra small size temperature sensor with 0.5mm in diameter is manufactured to estimate and compensate the effect of temperature by using FBG sensor. The continuous temperature changes are monitored during cone penetration by using FBG temperature sensor installed in cone penetrometer. The temperature compensated tip resistances show the uniform and similar distributions with depth in different with originally measured tip resistance in cohesive soil. This study verifies that the tip resistances measured by previous zero reading method are affected by the change of underground temperature, and suggests the new temperature compensation technique using by FBG temperature sensor.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.9
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• pp.92-97
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• 2022

In this paper, as a research on autonomous steering for agriculture, a sensor module for furrow recognition was developed through a low-cost distance sensor combination. The developed sensor module was applied to the vehicle, and when driving in a furrow curve, the autonomous steering success rate was 100% at a curvature of 20 m or more, and 70% at a curvature of 15 m or less. The self-steering success rate according to the ground condition showed a 100% success rate regardless of soil, weeds, or mulching film.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2022.11a
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• pp.29-30
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• 2022

The unit-water content has a very significant effect on the durability of the construction structure and the quality of concrete. Although there are various methods for measuring the unit-water content, there are problems of time required for measurement, precision, and reproducibility. Recently, there is an FDR sensor capable of measuring moisture content in real time through an apparent dielectric constant change of electromagnetic waves. In addition, various artificial intelligence techniques that can non-linearly supplement the accuracy of FDR sensors are being studied. In this study, the accuracy of unit-water content measurement was compared and evaluated using machine learning and deep learning techniques after normalizing the data secured in concrete using frequency domain reflectometry (FDR) sensors used to measure soil moisture at home and abroad. The result of comparing the accuracy of machine learning and deep learning is judged to be excellent in the accuracy of deep learning, which can well express the nonlinear relationship between FDR sensor data and concrete unit-water content.

• International Journal of Computer Science & Network Security
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• v.24 no.4
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• pp.197-205
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• 2024

This paper presents a fully automated stand-alone irrigation system with GSM (Global System for Mobile Communication) module. Solar energy is utilized to power the system and it is aimed to conserve water by reducing water losses. The system is based on a DC water pump that draws energy from solar panels along with automated water flow control using a moisture sensor. It is also fitted with alert and protection system that consists of an ultrasonic sensor and GSM messages sender that transmits signals showing the levels of the water in the reservoir and the battery charge. The control system is designed to stop the water pump from pumping water either when the battery level drops to equal or less than 10% of its full charge, or when the water level becomes less than 10 cm high in the reservoir. The experimental results revealed that the system is appropriate to use in remote areas with water scarcity and away from the national grid.

• The Journal of Engineering Geology
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• v.14 no.4 s.41
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• pp.361-369
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• 2004

The authors designed a new technique to measure dielectric constant of a soil media by Frequency Domain Reflectometry (FDR) system and its measurement sensor probe with different length such as 7m, 10cm and 15cm for estimating the variations of dielectric constant. Measurement of dielectric constant of soil material is possible to measure an interference wave generated by between incidence wave and reflection wave which are detected to electro-magnetic wave through the directional coupler at the high frequency range,0.1 to 1.7GHz, by FDR system. The obtained experimental results verified that the technique is very promising for non-destructive and continuous soil volumetric water content measurement monitoring in a laboratory. The relationship between the soil volumetric water content and the dielectric constant of soil media (standard sand) was expressed by a single regression ewe independent of soil texture at a small experimental error. Also the derived regression curve coincided well with that obtained by Topp curve.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.3
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• pp.107-116
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• 2020

In this data paper, we share the dataset obtained during 2019 from the test-bed to develop soil moisture estimation technology for upland fields, which was built in Seosan and Taean, South Korea on May 3. T his dataset includes various eco-hydro-meteorological variables such as soil moisture, evapotranspiration, precipitation, radiation, temperature, humidity, and vegetation indices from the test-bed nearby the Automated Agricultural Observing System (AAOS) in Seosan operated by the Korea Meteorological Administration. T here are three remarkable points of the dataset: (1) It can be utilized to develop and evaluate spatial scaling technology of soil moisture because the areal measurement with wide spatial representativeness using a COSMIC-ray neutron sensor as well as the point measurement using frequency/time domain reflectometry (FDR/TDR) sensors were conducted simultaneously, (2) it can be used to enhance understanding of how soil moisture and crop growth interact with each other because crop growth was also monitored using the Smart Surface Sensing System (4S), and (3) it is possible to evaluate the surface water balance by measuring evapotranspiration using an eddy covariance system.

• Horticultural Science & Technology
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• v.30 no.5
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• pp.501-508
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• 2012

Reducing carbon dioxide ($CO_2$) exhaust has become a major issue for society in the last few years, especially since the initial release of the Kyoto Protocol in 1997 that strictly limited the emissions of greenhouse gas for each country. One of the primary sectors affecting the levels of atmospheric greenhouse gases is agriculture where $CO_2$ is not only consumed by plants but also produced from various types of soil and agricultural ecosystems including greenhouses. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Optimum control of greenhouse $CO_2$ enrichment based on accurate monitoring of the added $CO_2$ can improve profitability through efficient crop production and reduce environmental impact, compared to traditional management practices. In this study, a sensor-based control system that could estimate the required $CO_2$ concentration considering emission from soil for cucumber greenhouses was developed and evaluated. The relative profitability index (RPI) was defined by the ratio of growth rate to supplied $CO_2$. RPI for a greenhouse controlled at lower set point of $CO_2$ concentration (500 ${\mu}mol{\cdot}mol^{-1}$) was greater than that of greenhouse at higher set point (800 ${\mu}mol{\cdot}mol^{-1}$). Evaluation tests to optimize $CO_2$ enrichment concluded that the developed control system would be applicable not only to minimize over-exhaust of $CO_2$ but also to maintain the crop profitability.

• Journal of Korean Society of Disaster and Security
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• v.14 no.2
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• pp.43-50
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• 2021

In Korea, the frequency of soil disasters has soared recently due to increased torrential rains caused by abnormal weather conditions. In particular, soil generated from mountainous areas is flowing into small rivers along valleys, depositing rivers and adding to flood damage. In order to prevent damage from such soil disasters, it is important to predict sediments and to quantitatively identify bed load. In this work, we conducted an experiment to indirectly measure acoustic sensor-based bed load collision sounds using pipe hydrophones, and compared them with raw data by applying denoising methods to improve the reliability of the measured data. As a result, we derive results in a more clear analysis of bed load estimation by correcting noise when the denoising method is applied to raw data.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.130-136
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• 2020

There are many problems that occur currently in agriculture industries. The problems such as unexpected of changing weather condition, lack of labor, dry soil were some of the reasons that may cause the growth of the plants. Condition of the weather in local area is inconsistent due to the global warming effect thus affecting the production of the crops. Furthermore, the loss of farm labor to urban manufacturing jobs is also the problem in this industry. Besides, the condition for the plant like air humidity, air temperature, air quality index, and soil moisture are not being recorded automatically which is more reason for the need of implementation system to monitor the data for future research and development of agriculture industry. As of this, we aim to provide a solution by developing IoT-based platform along with the irrigation for increasing crop quality and productivity in agriculture field. We aim to develop a smart garden system environment which the system is able to auto-monitoring the humidity and temperature of surroundings, air quality and soil moisture. The system also has the capability of automating the irrigation process by analyzing the moisture of soil and the climate condition (like raining). Besides, we aim to develop user-friendly system interface to monitor the data collected from the respective sensor. We adopt an open source hardware to implementation and evaluate this research.