• International conference on construction engineering and project management
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• 2009.05a
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• pp.472-478
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• 2009

The scopes of the supply chain management in construction projects has expanded from the field management focusing on field storage, transportation, and lifting to the whole supply chain from the materials to field. The expansion of the supply chain management can raise the possibilities of leaner production, which enables shortened lead time of the difficult-to-operate materials, and prevents the work interference or delay. However, the expanded management range requires more information and management than an existing management style currently used for factory production of iron frame, curtain wall, PC, etc. In addition, there are limitations that expand the existing management style into the new supply chain management in construction projects and therefore it is required to automate the existing management style in order to extend the management range. The objective of this study is to propose the process and equipment that can manage the supply chain of the materials which range from the factory production to the field storage based on RFID/USN techniques, introducing small-sized transportation equipment(intelligent pallet), the vehicle tool kit(intelligent trailer), and in-and-out management equipment(Gate Sensor) as a prototype to effectively develop the appliances for operating the proposed process, and present the application possibility of the appliances. The full paper will present then the test results that the proposed appliances for the supply chain management automatically transmit and receive the generated information between the appliances or the appliance and sever under various wireless network circumstances such as zigbee, wibro, Wi-Fi, and CDMA.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.1-10
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• 2023

With the advent of the 4th industrial revolution era, interest in autonomous driving technology is increasing. Accordingly it is necessary to seek safe driving by recognizing surrounding situations using sensors attached to autonomous vehicles along with the applicability of existing traffic facilities to autonomous driving lanes and the utilization of HD maps. In this study, in order to deduce the role of sensor only physical facilities which recognized through a laser scanner on an autonomous vehicle developed to improve road and traffic infrastructure, through comparative analysis with existing road facilities such as road signs, safety signs, and gaze guidance facilities. Sign facilities can promote driving safety by allowing autonomous vehicles to perform specific actions directly. In order to promote safe driving by recognizing sign facilities by using sensors for autonomous vehicles, it is necessary to prepare standards for installation, management, and use, and it is considered that management and supervision should be carried out continuously according to the standards.

• Proceedings of the Korean Society of Computer Information Conference
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• 2021.01a
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• pp.177-178
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• 2021

우리나라 차량의 수는 매년 증가한다. 한 가구당 2대 이상의 차량을 가지고 있는 경우는 드물지 않다. 이는 도로의 포화를 발생시키고 교통사고의 원인이 된다. 본 연구에서는 안전성을 더욱 증가시키는 것을 전제로 아두이노를 이용한 초음파 센서와 라즈베리를 통한 블루투스 기술을 통해 LED 패널에 적용하고자 한다. 현재 많은 차량에는 후방 감지 센서와 차량 후방에서 다가오는 차량을 감지하는 센서 등을 사용하고 있다. 이 기술들은 운전자를 보호하는 장치이지만 모두 개인적으로 사용되는 장치이므로 다른 운전자를 보호하기 위한 장치가 필요하다. 또한, 이러한 시스템이 설치되어 있지 않은 차량이 많다. 추가로 설치하기 위해서 보다 큰 비용을 내야 하므로 적은 비용에 비해 큰 효율을 발생할 수 있는 가성비 좋은 장치가 필요하다. 본 논문은 이러한 문제점들을 개선하기 위해 버스에 장착된 LED 패널과 도로정비 차량 후방에 장착된 LED 패널에서 아이디어에 착안하여 '차량용 후방 안전 LED 패널' 기술을 제안한다. 기존에 글자를 이용해 단순히 의사소통이 가능한 LED 패널을 아두이노와 라즈베리 파이를 통해 사용자가 출력하고 싶은 문구를 실시간으로 출력하여 다른 운전자에게 정보를 전달할 수 있다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.6
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• pp.69-74
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• 2022

Even after the drunk driving law was revised through the Yoon Chang-ho Act in 2019, the proportion of habitual offenders among all drunk drivers in 2021 was 4.7%, up 0.5% from 2018. In addition, drunk driving is not easily stopped due to the addiction of alcohol, and there is a high probability of recidivism in accidents as it is often driven again. Therefore, in this paper, to prevent this, when alcohol is measured using its own sensor rather than a manual police measure, the vehicle stops and related data such as the current location and time are automatically saved. Since it is not possible to develop directly on the car, this system was developed by converging various technologies and sensors such as Arduino board, Firebase, and GPS based on the IoT environment in consideration of the simulation environment.

• Journal of the Society of Naval Architects of Korea
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• v.60 no.3
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• pp.155-164
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• 2023

About 75% of vessel collision accidents are caused by human error, which causes enormous economic loss, environmental pollution, and human casualties, thus research on automatic collision avoidance of vessels is being actively conducted. In addition, vessels must comply with the COLREGs rules stipulated by IMO when performing collision avoidance with other vessels in motion. In this study, the collision risk was calculated by estimating the position and velocity of other vessels through the Probabilistic Data Association Filter (PDAF) algorithm based on RADAR sensor data. When a collision risk is detected, we propose an event-triggered Nonlinear Model Predict Control (NMPC) algorithm that geometrically creates waypoints that satisfy COLREGs and follows them. To verify the proposed algorithm, simulations through MATLAB are performed.

• Journal of The Korean Society of Grassland and Forage Science
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• v.43 no.2
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• pp.103-108
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• 2023

Due to the recent impact of global warming, heavy rainfall and droughts have been occurring regardless of the season, affecting the growth of Italian ryegrass (IRG), a winter forage crop. Particularly, delayed sowing due to frequent heavy rainfall or autumn droughts leads to poor growth and reduced winter survival rates. Therefore, techniques to improve yield through additional sowing in spring have been implemented. In this study, the growth of IRG sown in Spring and Autumn was compared and analyzed using vegetation indices during the months of April and May. Spectral data was collected using an Unmanned Aerial Vehicle (UAV) equipped with a hyperspectral sensor, and the following vegetation indices were utilized: Normalized Difference Vegetation Index; NDVI, Normalized Difference Red Edge Index; NDRE (I), Chlorophyll Index, Red Green Ratio Index; RGRI, Enhanced Vegetation Index; EVI and Carotenoid Reflectance Index 1; CRI1. Indices related to chlorophyll concentration exhibited similar trends. RGRI of IRG sown in autumn increased during the experimental period, while IRG sown in spring showed a decreasing trend. The results of RGRI in IRG indicated differences in optical characteristics by sowing seasons compared to the other vegetation indices. Our findings showed that the timing of sowing influences the optical growth characteristics of crops by the results of various vegetation indices presented in this study. Further research, including the development of optimal vegetation indices related to IRG growth, is necessary in the future.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.88-88
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• 2022

Detection of stress responses in crops is important to diagnose crop growth and evaluate yield. Also, the multi-spectral sensor is effectively known to evaluate stress caused by nutrient and moisture in crops or biological agents such as weeds or diseases. Therefore, in this experiment, multispectral images were taken by an unmanned aerial vehicle(UAV) under field condition. The experiment was conducted in the long-term fertilizer field in the National Institute of Crop Science, and experiment area was divided into different status of NPK(Control, N-deficiency, P-deficiency, K-deficiency, Non-fertilizer). Total 11 vegetation indices were created with RGB and NIR reflectance values using python. Variations in nutrient content in plants affect the amount of light reflected or absorbed for each wavelength band. Therefore, the objective of this experiment was to evaluate vegetation indices derived from multispectral reflectance data as input into machine learning algorithm for the classification of nutritional deficiency in rice. RandomForest model was used as a representative ensemble model, and parameters were adjusted through hyperparameter tuning such as RandomSearchCV. As a result, training accuracy was 0.95 and test accuracy was 0.80, and IPCA, NDRE, and EVI were included in the top three indices for feature importance. Also, precision, recall, and f1-score, which are indicators for evaluating the performance of the classification model, showed a distribution of 0.7-0.9 for each class.

• Journal of Korea Society of Industrial Information Systems
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• v.28 no.6
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• pp.99-105
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• 2023

Submarines, which require a high degree of survivability, are among the most critical combat weapon systems in military strategic assets. Conventional submarines need air to operate their propulsion systems. Exhaust gases released into the water during snorkel navigation heat the surrounding fluid, producing a temperature wake. This wake, in turn, reduces the submarine's survivability. In this study, we conducted a preliminary experiment on the temperature traces formed by an underwater submarine's waste discharge. For this purpose, we collected propulsion system and navigation condition data from domestically introduced submarines and developed an experimental system to measure the temperature traces. As a result, we observed that high-temperature bubbles injected into the tank broke down into smaller sizes, and their temperature dropped to levels similar to the surrounding fluid. This observation was confirmed using a thermocouple sensor. Consequently, the thermal imaging system designed to measure the temperature trace of the water's surface did not detect any significant temperature traces.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.123-133
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• 2024

Existing autonomous driving technology has been developed based on sensors attached to the vehicles to detect the environment and formulate driving plans. On the other hand, it has limitations, such as performance degradation in specific situations like adverse weather conditions, backlighting, and obstruction-induced occlusion. To address these issues, cooperative autonomous driving technology, which extends the perception range of autonomous vehicles through the support of road infrastructure, has attracted attention. Nevertheless, the real-time analysis of the 3D centroids of objects, as required by international standards, is challenging using single-lens cameras. This paper proposes an approach to detect objects and estimate the centroid of vehicles using the fixed field of view of road infrastructure and pre-measured geometric information in real-time. The proposed method has been confirmed to effectively estimate the center point of objects using GPS positioning equipment, and it is expected to contribute to the proliferation and adoption of cooperative autonomous driving infrastructure technology, applicable to both vehicles and road infrastructure.

• Korean Journal of Agricultural Science
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• v.49 no.4
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• pp.845-855
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• 2022

The purpose of this study is to develop a self-propelled underground crop harvester and its performance was evaluated by measuring the load during actual potato harvesting operations. This study was conducted at a constant working speed of 1 km·h^-1. A load measurement system was installed to measure the actual load and the required working power was analyzed. A hydraulic pressure sensor was also installed to measure the hydraulic pressure. The required hydraulic power was calculated using the hydraulic pressure and flow rate. The results showed that the engine speed, torque, and power during harvesting operation were in the range of 845 - 1,423 rpm, 95 - 228 Nm, and 9 - 31 kW, respectively. Traction power, excluding the hydraulic pump of the tractor and power take-off (PTO) output, was in the range of 9 - 28 kW, and it was confirmed that it occupies a ratio of 16.2 to 50% of the engine rated output. The engine can supply the minimum required traction power to move the vehicle. This means that the engine used in this study could be down-sized to be suitable for an underground crop harvester. In this study, the gear stages of the tractor were not considered. This research thus shows the possibility of developing a self-propelled underground crop harvester.