• Title/Summary/Keyword: sensors

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Development of Continuous Monitoring Method of Root-zone Electrical Conductivity using FDR Sensor in Greenhouse Hydroponics Cultivation (시설 수경재배에서 FDR 센서를 활용한 근권 내 농도의 연속적 모니터링 방법)

  • Lee, Jae Seong;Shin, Jong Hwa
    • Journal of Bio-Environment Control
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    • v.31 no.4
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    • pp.409-415
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    • 2022
  • Plant growth and development are also affected by root-zone environment. Therefore, it is important to consider the variables of the root-zone environment when establishing an irrigation strategy. The purpose of this study is to analyze the relationship between the volumetric moisture content (VWC), Bulk EC (ECb), and Pore EC (ECp) used by plant roots using FDR sensors in two types of rockwool media with different water transmission characteristics, using the method above this was used to establish a method for collecting and correcting available root-zone environmental data. For the experiment, two types of rockwool medium (RW1, RW2) with different physical characteristics were used. The moisture content (MC) and ECb were measured using an FDR sensor, ECp was measured after extracting the residual nutrient solution from the medium using a disposable syringe in the center of the medium at a volumetric moisture content (VWC) of 10-100%. Then, ECb and ECp are measured by supplying nutrient solution having different concentration (distilled water, 0.5-5.0) to two types of media (RW1, RW2) in each volume water content range (0 to 100%). The relationship between ECb and ECp in RW1 and RW2 media is best suited for cubic polynomial. The relationship between ECb and ECp according to volume moisture content (VWC) range showed a large error rate in the low volume moisture content (VWC) range of 10-60%. The correlation between the sensor measured value (ECb) and the ECp used by plant roots according to the volumetric water content (VWC) range was the most suitable for the Paraboloid equation in both media (RW1, RW2). The coefficient of determination the calibration equation for RW1 and RW2 media were 0.936, 0.947, respectively.

Comparisons of Soil Water Retention Characteristics and FDR Sensor Calibration of Field Soils in Korean Orchards (노지 과수원 토성별 수분보유 특성 및 FDR 센서 보정계수 비교)

  • Lee, Kiram;Kim, Jongkyun;Lee, Jaebeom;Kim, Jongyun
    • Journal of Bio-Environment Control
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    • v.31 no.4
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    • pp.401-408
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    • 2022
  • As research on a controlled environment system based on crop growth environment sensing for sustainable production of horticultural crops and its industrial use has been important, research on how to properly utilize soil moisture sensors for outdoor cultivation is being actively conducted. This experiment was conducted to suggest the proper method of utilizing the TEROS 12, an FDR (frequency domain reflectometry) sensor, which is frequently used in industry and research fields, for each orchard soil in three regions in Korea. We collected soils from each orchard where fruit trees were grown, investigated the soil characteristics and soil water retention curve, and compared TEROS 12 sensor calibration equations to correlate the sensor output to the corresponding soil volumetric water content through linear and cubic regressions for each soil sample. The estimated value from the calibration equation provided by the manufacturer was also compared. The soil collected from all three orchards showed different soil characteristics and volumetric water content values by each soil water retention level across the soil samples. In addition, the cubic calibration equation for TEROS 12 sensor showed the highest coefficient of determination higher than 0.95, and the lowest RMSE for all soil samples. When estimating volumetric water contents from TEROS 12 sensor output using the calibration equation provided by the manufacturer, their calculated volumetric water contents were lower than the actual volumetric water contents, with the difference up to 0.09-0.17 m3·m-3 depending on the soil samples, indicating an appropriate calibration for each soil should be preceded before FDR sensor utilization. Also, there was a difference in the range of soil volumetric water content corresponding to the soil water retention levels across the soil samples, suggesting that the soil water retention information should be required to properly interpret the volumetric water content value of the soil. Moreover, soil with a high content of sand had a relatively narrow range of volumetric water contents for irrigation, thus reducing the accuracy of an FDR sensor measurement. In conclusion, analyzing soil water retention characteristics of the target soil and the soil-specific calibration would be necessary to properly quantify the soil water status and determine their adequate irrigation point using an FDR sensor.

Evaluation of Sensitivity and Retrieval Possibility of Land Surface Temperature in the Mid-infrared Wavelength through Radiative Transfer Simulation (복사전달모의를 통한 중적외 파장역의 민감도 분석 및 지표면온도 산출 가능성 평가)

  • Choi, Youn-Young;Suh, Myoung-Seok;Cha, DongHwan;Seo, DooChun
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1423-1444
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    • 2022
  • In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.

Gene Expression of Detoxification Enzymes in Tenebrio molitor after Fungicide Captan Exposure (살진균제인 캡탄 처리 후 갈색거저리의 해독효소 유전자 발현)

  • Jang, Ho am;Baek, Hyoung-Seon;Kim, Bo Bae;Kojour, Maryam Ali Mohammadie;Patnaik, Bharat Bhusan;Jo, Yong Hun;Han, Yeon Soo
    • Korean journal of applied entomology
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    • v.61 no.1
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    • pp.155-163
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    • 2022
  • The application of fungicides is indispensable to global food security, and their use has increased in recent times. Fungicides, directly or indirectly, have impacted insects, leading to genetic and molecular-level changes. Various detoxification mechanisms allow insects to eliminate reactive oxygen species (ROS) toxicity induced by agrochemicals including fungicides. In the present study, we analyzed the mRNA expression levels of detoxifying enzymes in Tenebrio molitor larvae following exposure to non-lethal doses (0.2, 2, and 20 ㎍/µL) of a fungicide captan. Transcripts of peroxidases (POXs), catalases (CATs), superoxide dismutases (SODs), and glutathione-s-transferases (GSTs) were screened from the T. molitor transcriptome database. RT-qPCR analysis showed that TmPOX5 mRNA increased significantly 24 h post-captan exposure. A similar increase was noticed for TmSOD4 mRNA 3 h post-captan exposure. Moreover, the expression of TmCAT2 mRNA increased significantly 24 h post-treatment with 2 ㎍/µL captan. TmGST1 and TmGST3 mRNA expression also increased noticeably after captan exposure. Taken together, these results suggest that TmPOX5 and TmSOD4 mRNA can be used as biomarkers or xenobiotics sensors for captan exposure in T. molitor, while other detoxifying enzymes showed differential expression.

Estimation of High Resolution Sea Surface Salinity Using Multi Satellite Data and Machine Learning (다종 위성자료와 기계학습을 이용한 고해상도 표층 염분 추정)

  • Sung, Taejun;Sim, Seongmun;Jang, Eunna;Im, Jungho
    • Korean Journal of Remote Sensing
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    • v.38 no.5_2
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    • pp.747-763
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    • 2022
  • Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

Machine Learning Based MMS Point Cloud Semantic Segmentation (머신러닝 기반 MMS Point Cloud 의미론적 분할)

  • Bae, Jaegu;Seo, Dongju;Kim, Jinsoo
    • Korean Journal of Remote Sensing
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    • v.38 no.5_3
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    • pp.939-951
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    • 2022
  • The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

Study on High Sensitivity Metal Oxide Nanoparticle Sensors for HNS Monitoring of Emissions from Marine Industrial Facilities (해양산업시설 배출 HNS 모니터링을 위한 고감도 금속산화물 나노입자 센서에 대한 연구)

  • Changhan Lee;Sangsu An;Yuna Heo;Youngji Cho;Jiho Chang;Sangtae Lee;Sangwoo Oh;Moonjin Lee
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.spc
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    • pp.30-36
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    • 2022
  • A sensor is needed to continuously and automatically measure the change in HNS concentration in industrial facilities that directly discharge to the sea after water treatment. The basic function of the sensor is to be able to detect ppb levels even at room temperature. Therefore, a method for increasing the sensitivity of the existing sensor is proposed. First, a method for increasing the conductivity of a film using a conductive carbon-based additive in a nanoparticle thin film and a method for increasing ion adsorption on the surface using a catalyst metal were studied.. To improve conductivity, carbon black was selected as an additive in the film using ITO nanoparticles, and the performance change of the sensor according to the content of the additive was observed. As a result, the change in resistance and response time due to the increase in conductivity at a CB content of 5 wt% could be observed, and notably, the lower limit of detection was lowered to about 250 ppb in an experiment with organic solvents. In addition, to increase the degree of ion adsorption in the liquid, an experiment was conducted using a sample in which a surface catalyst layer was formed by sputtering Au. Notably, the response of the sensor increased by more than 20% and the average lower limit of detection was lowered to 61 ppm. This result confirmed that the chemical resistance sensor using metal oxide nanoparticles could detect HNS of several tens of ppb even at room temperature.

A Study on Image-Based Mobile Robot Driving on Ship Deck (선박 갑판에서 이미지 기반 이동로봇 주행에 관한 연구)

  • Seon-Deok Kim;Kyung-Min Park;Seung-Yeol Wang
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.28 no.7
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    • pp.1216-1221
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    • 2022
  • Ships tend to be larger to increase the efficiency of cargo transportation. Larger ships lead to increased travel time for ship workers, increased work intensity, and reduced work efficiency. Problems such as increased work intensity are reducing the influx of young people into labor, along with the phenomenon of avoidance of high intensity labor by the younger generation. In addition, the rapid aging of the population and decrease in the young labor force aggravate the labor shortage problem in the maritime industry. To overcome this, the maritime industry has recently introduced technologies such as an intelligent production design platform and a smart production operation management system, and a smart autonomous logistics system in one of these technologies. The smart autonomous logistics system is a technology that delivers various goods using intelligent mobile robots, and enables the robot to drive itself by using sensors such as lidar and camera. Therefore, in this paper, it was checked whether the mobile robot could autonomously drive to the stop sign by detecting the passage way of the ship deck. The autonomous driving was performed by detecting the passage way of the ship deck through the camera mounted on the mobile robot based on the data learned through Nvidia's End-to-end learning. The mobile robot was stopped by checking the stop sign using SSD MobileNetV2. The experiment was repeated five times in which the mobile robot autonomously drives to the stop sign without deviation from the ship deck passage way at a distance of about 70m. As a result of the experiment, it was confirmed that the mobile robot was driven without deviation from passage way. If the smart autonomous logistics system to which this result is applied is used in the marine industry, it is thought that the stability, reduction of labor force, and work efficiency will be improved when workers work.

Review of Domestic Research Trends on Layered Double Hydroxide (LDH) Materials: Based on Research Articles in Korean Citation Index (KCI) (이중층수산화물(layered double hydroxide, LDH) 소재의 국내 연구동향 리뷰: 한국학술지인용색인(KCI)에 발표된 논문을 대상으로)

  • Seon Yong Lee;YoungJae Kim;Young Jae Lee
    • Economic and Environmental Geology
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    • v.56 no.1
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    • pp.23-53
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    • 2023
  • In this review paper, previous studies on layered double hydroxides (LDHs) published in the Korean Citation Index (KCI) were examined to investigate a research trend for LDHs in Korea. Since the first publication in 2002, 160 papers on LDHs have been published until January 2023. Among the 31 academic fields, top 5 fields appeared in the order of chemical engineering, chemistry, materials engineering, environmental engineering, and physics. The chemical engineering shows the highest record of published paper (71 papers) while around 10 papers have been published in the other four fields. All papers were reclassified into 15 research fields based on the industrial and academic purposes of using LDHs. The top 5 in these fields are in order of environmental purification materials, polymer catalyst materials, battery materials, pharmaceutical/medicinal materials, and basic physicochemical properties. These findings suggest that researches on the applications of LDH materials in the academic fields of chemical engineering and chemistry for the improvement of their functions such as environmental purification materials, polymer catalysts, and batteries have been being most actively conducted. The application of LDHs for cosmetic and agricultural purposes and for developing environmental sensors is still at the beginning of research. Considering a market-potential and high-efficiency-eco-friendly trend, however, it will deserve our attention as emerging application fields in the future. All reclassified papers were summarized in our tables and a supplementary file, including information on applied materials, key results, characteristics and synthesis methods of LDHs used. We expect that our findings of overall trends in LDH research in Korea can help design future researches with LDHs and suggest policies for resources and energies as well as environments efficiently.

K-DEV: A Borehole Deviation Logging Probe Applicable to Steel-cased Holes (철재 케이싱이 설치된 시추공에서도 적용가능한 공곡검층기 K-DEV)

  • Yoonho, Song;Yeonguk, Jo;Seungdo, Kim;Tae Jong, Lee;Myungsun, Kim;In-Hwa, Park;Heuisoon, Lee
    • Geophysics and Geophysical Exploration
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    • v.25 no.4
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    • pp.167-176
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    • 2022
  • We designed a borehole deviation survey tool applicable for steel-cased holes, K-DEV, and developed a prototype for a depth of 500 m aiming to development of own equipment required to secure deep subsurface characterization technologies. K-DEV is equipped with sensors that provide digital output with verified high performance; moreover, it is also compatible with logging winch systems used in Korea. The K-DEV prototype has a nonmagnetic stainless steel housing with an outer diameter of 48.3 mm, which has been tested in the laboratory for water resistance up to 20 MPa and for durability by running into a 1-km deep borehole. We confirmed the operational stability and data repeatability of the prototype by constantly logging up and down to the depth of 600 m. A high-precision micro-electro-mechanical system (MEMS) gyroscope was used for the K-DEV prototype as the gyro sensor, which is crucial for azimuth determination in cased holes. Additionally, we devised an accurate trajectory survey algorithm by employing Unscented Kalman filtering and data fusion for optimization. The borehole test with K-DEV and a commercial logging tool produced sufficiently similar results. Furthermore, the issue of error accumulation due to drift over time of the MEMS gyro was successfully overcome by compensating with stationary measurements for the same attitude at the wellhead before and after logging, as demonstrated by the nearly identical result to the open hole. We believe that the methodology of K-DEV development and operational stability, as well as the data reliability of the prototype, were confirmed through these test applications.