• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.12
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• pp.2853-2858
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• 2013

This paper proposes the ITMS(Intelligent Transport Monitoring System) which manages the route and state of freight by using the Meteorological Office, the Transportation Management Center, GPS and Sensors, etc. The ITMS consists of the CIMS(Container Inner Monitoring System) transmitting the inner temperature and humidity of a container, the TMM(Transport Management Module) computing an estimated time of arrival with Freight Vehicle location information and transmits the result to the CIMS, the FMM(Freight Management Module) checking and managing the freight freshness by using the temperature and humidity of the collected containers, and the SMM(Stevedoring Management Module) selecting the container loading and unloading places with the information transmitted from the CIMS, the TMM, and the FMM and attaching the freight formation to containers using an RFID label. The ITMS not only checks the freight condition at intervals but also acquires and manages the freight information with RFID labels rapidly and accurately.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.11
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• pp.5135-5142
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• 2011

A flexible mechanism is proposed in this paper to improve the dynamic response performance of a traffic flow control system in an urban area. The roads, vehicles, and traffic control systems are all modeled as intelligent systems, wherein a wireless communication network is used as the medium of communication between the vehicles and the roads. The necessary sensor networks are installed in the roads and on the roadside upon which reinforcement learning is adopted as the core algorithm for this mechanism. A traffic policy can be planned online according to the updated situations on the roads, based on all the information from the vehicles and the roads. This improves the flexibility of traffic flow and offers a much more efficient use of the roads over a traditional traffic control system. The optimum intersection signals can be learned automatically online. An intersection control system is studied as an example of the mechanism using Q-learning based algorithm, and simulation results showed that the proposed mechanism can improve the traffic efficiency and the waiting time at the signal light by more than 30% in various conditions compare to the traditional signaling system.

• Journal of Advanced Navigation Technology
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• v.17 no.6
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• pp.749-756
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• 2013

This paper presents an algorithm concerning the ground altitude measurement using a laser altimeter and an ultrasonic rangefinder for UAV(Unmanned Aerial Vehicle). A simple ground test conducted using the laser altimeter and ultrasonic rangefinder that are used for conducting the low altitude measurement of UAV and identify the characteristics of each sensor. Especially, the disadvantages of the laser altimeter were checked through the ground test. After that who those are participated in this paper planned the algorithm which is complemented by the ultrasonic rangefinder and the experiment was conducted. The laser altimeter and the ultrasonic rangefinder were fused by a loosely coupled method by Kalman filter. The paper shows that stable value of altitude complemented by the ultrasonic rangefinder that covers the laser altimeter's drawbacks can be measured through the ground test.

• Korean Journal of Remote Sensing
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• v.35 no.5_1
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• pp.727-736
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• 2019

In this paper, we present how to create a point cloud for a target area using multiple unmanned aerial vehicle images and to remove the gaps and overlapping points between datasets. For this purpose, first, IBA (Incremental Bundle Adjustment) technique was applied to correct the position and attitude of UAV platform. We generate a point cloud by using MDR (Multi-Dimensional Relaxation) matching technique. Next, we register point clouds based on observation vectors between stereo images by doing this we remove gaps between point clouds which are generated from different stereo pairs. Finally, we applied an occupancy grids based integration algorithm to remove duplicated points to create an integrated point cloud. The experiments were performed using UAV images, and our experiments show that it is possible to remove gaps and duplicate points between point clouds generated from different stereo pairs.

• The Journal of the Korea Contents Association
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• v.19 no.3
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• pp.261-274
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• 2019

This paper aims to develop an appropriate methodology for establishing an investment strategy for 'demonstration of artificial rainfall technology using UAV' and that include establishment of a technology classification, set of indicators for technology evaluation, suggestion of final key technology as a whole study area. It is designed to complement the latest research trend analysis results and expert committee opinions using quantitative analysis. The key indicators for technology evaluation consisted of three major items (activity, technology, marketability) and 10 detailed indicators. The AHP questionnaire was conducted to analyze the importance of indicators. As a result, it was analyzed that the attribute of the technology itself is most important, and the order of closeness to the implementation of the core function (centrality), feasibility (feasibility). Among the 16 technology groups, top investment priority groups were analyzed as ground seeding, artificial rainfall verification, spreading and diffusion of seeding material, artificial rainfall numerical modeling, and UAV sensor technology.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.9
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• pp.1088-1095
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• 2019

The information and communication technology that is being developed recently has been greatly influencing the automobile market. In recent years, devices equipped with IT technology have been installed for the safety and convenience of the driver. However, it has the advantage of increased convenience as well as the disadvantage of increasing traffic accidents due to driver's distraction. In order to prevent such accidents, it is necessary to develop safety systems of various types and ways. In this paper implements a platform that can recognize LDWS and FCWS and PDWS by using a single camera without using radar sensor and camera fusion and stereo camera method using two or more sensors, and proposes to study multi-function driving safety platform using a single camera by analyzing recognition rate evaluation and validity on a vehicle.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.1
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• pp.157-164
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• 2021

Wind and temperature were measured with a three-dimensional ultrasonic anemometer and the carbon dioxide concentration was measured using an infrared sensor in the tidal flat of Suncheon Bay. In general, as the temperature increases, the concentration of carbon dioxide increases, and as the temperature decreases, the carbon dioxide also decreases in the atmosphere. However, since photosynthesis declined immediately after the sunset, the concentration of carbon dioxide increased as the temperature decreased. In addition, near the high tide when the tidal flat is covered with seawater, the atmospheric turbulence was strong despite an increase in temperature, resulting in a decrease in carbon dioxide concentration. It is necessary to quantitatively evaluated the effects of photosynthesis, respiration and atmospheric turbulence on the change of carbon dioxide concentration over tidal flat ecosystems.

• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.11-18
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• 2021

We propose a method that combines learning in a virtual environment and a real environment for indoor autonomous driving through reinforcement learning. In case of learning only in the real environment, it takes about 80 hours, but in case of learning in both the real and virtual environments, it takes 40 hours. There is an advantage in that it is possible to obtain optimized parameters through various experiments through fast learning while learning in a virtual environment and a real environment in parallel. After configuring a virtual environment using indoor hallway images, prior learning was carried out on the desktop, and learning in the real environment was conducted by connecting various sensors based on Jetson Xavier. In addition, in order to solve the accuracy problem according to the repeated texture of the indoor corridor environment, it was possible to determine the corridor wall object and increase the accuracy by learning the feature point detection that emphasizes the lower line of the corridor wall. As the learning progresses, the experimental vehicle drives based on the center of the corridor in an indoor corridor environment and moves through an average of 70 steering commands.

• Journal of Radiation Protection and Research
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• v.46 no.4
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• pp.194-203
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• 2021

Background: Surface soil radiation monitoring around nuclear facilities is important to classify and characterize the contaminated areas. A scanning and direct measurement technique can survey the sites rapidly before starting sampling analysis. Materials and Methods: Regarding this, we test and suggest a measurement technique for gross alpha/beta and ⁹⁰Sr activities in surface soil based on a mobile ZnS(Ag)/PVT (polyvinyltoluene) array and a handheld PVT rod, respectively. To detect ⁹⁰Sr selectively in soil mixed with naturally occurring radioactive materials, chosen energy channel counts from the multichannel analyzers were used instead of whole channel counts. Soil samples contaminated with exempt liquid ⁹⁰Sr with 1 Bq·g^-1, 3 Bq·g^-1, and 10 Bq·g^-1 were prepared and hardened by flocculation. Results and Discussion: The mobile ZnS(Ag)/PVT array could discriminate gross alpha, gross beta, and gamma radiation by the different pulse-shaped signal features of each sensor material. If the array is deployed on a vehicle, the scan minimum detectable concentration (MDC) range will be about 0.11-0.17 Bq·g^-1 at 18 km·h^-1 speed, highly sensitive to actual sites. The handheld PVT rod with 12 mm (Φ) × 20 mm (H) size can directly measure ⁹⁰Sr selectively if channels on which energies are from 1,470 and 2,279 keV are gated, minimizing crossdetection of other radionuclides. These methods were verified by measuring soil samples fabricated with homogeneous ⁹⁰Sr concentrations, showing static MDC of 2.16 Bq·g^-1 at a measurement time of 300 seconds. Conclusion: Based on the results, comprehensive procedures using these detectors are suggested to optimize soil sites survey.

• Smart Structures and Systems
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• v.31 no.4
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• pp.311-323
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• 2023

Ever since ancient times, earthquakes have been a major threat to the civil infrastructures and the safety of human beings. The majority of casualties in earthquake disasters are caused by the damaged civil infrastructures but not by the earthquake itself. Therefore, the efficient and accurate post-earthquake assessment of the conditions of structural damage has been an urgent need for human society. Traditional ways for post-earthquake structural assessment rely heavily on field investigation by experienced experts, yet, it is inevitably subjective and inefficient. Structural response data are also applied to assess the damage; however, it requires mounted sensor networks in advance and it is not intuitional. As many types of damaged states of structures are visible, computer vision-based post-earthquake structural assessment has attracted great attention among the engineers and scholars. With the development of image acquisition sensors, computing resources and deep learning algorithms, deep learning-based post-earthquake structural assessment has gradually shown potential in dealing with image acquisition and processing tasks. This paper comprehensively reviews the state-of-the-art studies of deep learning-based post-earthquake structural assessment in recent years. The conventional way of image processing and machine learning-based structural assessment are presented briefly. The workflow of the methodology for computer vision and deep learning-based post-earthquake structural assessment was introduced. Then, applications of assessment for multiple civil infrastructures are presented in detail. Finally, the challenges of current studies are summarized for reference in future works to improve the efficiency, robustness and accuracy in this field.