• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.6
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• pp.626-632
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• 2017

Since natural disaster occurs increasingly and becomes complicated, it causes deaths, disappearances, and damage to property. As a result, there is a growing interest in the development of ICT-based natural disaster response technology which can minimize economic and social losses. In this letter, we introduce the main functions of the forest fire management platform by using images from an UAV. In addition, we propose a disaster image analysis technology based on the deep learning which is a key element technology for disaster detection. The proposed deep learning based disaster image analysis learns repeatedly generated images from the past, then it is possible to detect the disaster situation of forest-fire similar to a person. The validity of the proposed method is verified through the experimental performance of the proposed disaster image analysis technique.

• Journal of the Korean Institute of Gas
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• v.19 no.6
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• pp.22-27
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• 2015

Hydrogen features highest energy density per mass and is expected to be desirable as a fuel of HALE(High altitude long endurance) UAV(Unmanned aerial vehicle). A reciprocating internal combustion engine is known to be a reliable and economic power source for this kind of UAV. Therefore, the combination of hydrogen and engine is worth of doing research. Test bench with 2.4L Spark-Ignited engine was prepared for the experiment in which start and combustion characteristics at idle condition were examined in this study. Stable hydrogen supply system and a universal ECU(Engine control unit) were also utilized for the test engine. Equivalence ratio and spark timings at idle operation were investigated and compared to the data of gasoline engine. The results will be a starting point for full-scale research of hydrogen engine for HALE UAV.

• Journal of Broadcast Engineering
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• v.24 no.5
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• pp.802-812
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• 2019

With the rapid development in the field of unmanned aerial vehicles(UAVs) and drones, higher request to development of a surveillance system for a drone is putting forward. Since surveillance systems with fixed cameras have a limited range, a development of surveillance systems with a moving camera applicable to PTZ(Pan-Tilt-Zoom) cameras is required. Selecting the features for object plays a critical role in tracking, and the object has to be represented by their shapes or appearances. Considering these conditions, in this paper, an object tracking method with optical flow is introduced to track a tiny drone with a moving camera. In addition, a tracking method combined with kalman filter is proposed to track continuously even when tracking is failed. Experiments are tested on sequences which have a target from the minimal 12 pixels to the maximal 56337 pixels, the proposed method achieves average precision of 175% improvement. Also, experimental results show the proposed method tracks a target which has a size of 12pixels.

• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.807-817
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• 2019

Airborne Gamma Ray Spectrometry (AGRS) with its important applications such as gathering radiation information of ground surface, geochemistry measuring of the abundance of Potassium, Thorium and Uranium in outer earth layer, environmental and nuclear site surveillance has a key role in the field of nuclear science and human life. The Broyden-Fletcher-Goldfarb-Shanno (BFGS), with its advanced numerical unconstrained nonlinear optimization in collaboration with Artificial Neural Networks (ANNs) provides a noteworthy opportunity for modern AGRS. In this study a new AGRS system empowered by ANN-BFGS has been proposed and evaluated on available empirical AGRS data. To that effect different architectures of adaptive ANN-BFGS were implemented for a sort of published experimental AGRS outputs. The selected approach among of various training methods, with its low iteration cost and nondiagonal scaling allocation is a new powerful algorithm for AGRS data due to its inherent stochastic properties. Experiments were performed by different architectures and trainings, the selected scheme achieved the smallest number of epochs, the minimum Mean Square Error (MSE) and the maximum performance in compare with different types of optimization strategies and algorithms. The proposed method is capable to be implemented on a cost effective and minimum electronic equipment to present its real-time process, which will let it to be used on board a light Unmanned Aerial Vehicle (UAV). The advanced adaptation properties and models of neural network, the training of stochastic process and its implementation on DSP outstands an affordable, reliable and low cost AGRS design. The main outcome of the study shows this method increases the quality of curvature information of AGRS data while cost of the algorithm is reduced in each iteration so the proposed ANN-BFGS is a trustworthy appropriate model for Gamma-ray data reconstruction and analysis based on advanced novel artificial intelligence systems.

• Journal of Urban Science
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• v.7 no.2
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• pp.53-60
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• 2018

Digital Twin is a technology that creates a photocopy of real-world objects on a computer and analyzes the past and present operational status by fusing the structure, context, and operation of various physical systems with property information, and predicts the future society's countermeasures. In particular, 3D rendering technology (UAS, LiDAR, GNSS, etc.) is a core technology in digital twin. so, the research and application are actively performed in the industry in recent years. However, UAS (Unmanned Aerial System) and LiDAR (Light Detection And Ranging) have to be solved by compensating blind spot which is not reconstructed according to the object shape. In addition, the terrestrial LiDAR can acquire the point cloud of the object more precisely and quickly at a short distance, but a blind spot is generated at the upper part of the object, thereby imposing restrictions on the forward digital twin modeling. The UAS is capable of modeling a specific range of objects with high accuracy by using high resolution images at low altitudes, and has the advantage of generating a high density point group based on SfM (Structure-from-Motion) image analysis technology. However, It is relatively far from the target LiDAR than the terrestrial LiDAR, and it takes time to analyze the image. In particular, it is necessary to reduce the accuracy of the side part and compensate the blind spot. By re-optimizing it after fusion with UAS and Terrestrial LiDAR, the residual error of each modeling method was compensated and the mutual correction result was obtained. The accuracy of fusion-based 3D model is less than 1cm and it is expected to be useful for digital twin construction.

• Journal of Practical Engineering Education
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• v.9 no.1
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• pp.15-21
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• 2017

In order to satisfy the graduation requirements, the graduation work should be presented as an engineering dissertation system of the produced work and an outline of the procedure made by the major unit in accordance with the graduation thesis submission rules, and suggests necessary matters for improvement. The design content relates to a small unmanned aerial vehicle configuration for detecting personnel or objects in a disaster area. It is equipped with an infrared sensor and a GPS in the drone, the drone is control by using Blutooth communications. The drones detect the target and use the GPS to determine the location. As a result of the experiment, it was possible to detect the structure object within the range of 3~4 m, confirm the transmission of the position value in real time, and increase the communication distance by using RF communication.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.114-124
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• 2019

The drone market, an unmanned aerial vehicle, is rapidly expanding and developing into an important area related to the huge changes in the traffic system of the future. With various technologies on the fourth industrial revolution, including drones, mentioned at the Davos Forum in January 2016, interest in drones is emerging as an explosive demand for national certificates. The number of drone pilots, which was only 400 in 2015, is continuing to surpass 17,000 as of 2018. Therefore, this study analyzed the safety perception of the pilots based on the DREEM (Dundee ready environmental assessment) model designed to evaluate the educational environment along with the current state of drone education in Korea. This led to the conclusion that the high level of satisfaction of the pilot with the educational environment contributes to the overall safety perception, including compliance with procedures.

• Journal of the Korea Institute of Building Construction
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• v.19 no.3
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• pp.239-246
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• 2019

According to the survey on the status of aged buildings in Korea, A number of concrete buildings deterioration such as houses and apartment buildings has been increased rapidly. To solve this problem, the research related to the facility management, that is one of the importance factor, for monitoring buildings has been increased. The research is divided into Survey-based and Technique-based. However, the problem is that Survey-based research is required a lot of time, money and manpower for management. Also, safety cannot be guaranteed in the case of high-rise buildings. Technique-based research has limitations to applying to the current facility maintenance system, as detailed information of deteriorated facilities is difficult to grasp and errors in accuracy are feared. Therefore, this paper contribute to improve the environment of facility management by 4D maps using UAV, camera and Pix4D mapper program to make 3D model. In addition, it is expected to suggest that residents will be offered easy verification to their buildings deterioration.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.1
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• pp.108-114
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• 2021

AVTE(Air Vehicle Test Equipment) is a device to check status of on-board aircraft equipment before and after flight for performing successful UAV(Unmanned Aerial Vehicle) missions. This paper describes software design and test sequence of the AVTE for enabling easy-manual check by the operator and convenient automatic check of on-board electric equipment respectively. The proposed AVTE inspects BIT(Built-In Test) results of on-board LRUs(Line Replacement Units) including avionics and sensor sub-system devices. Also, it monitors all the LRU status and check the normality of aircraft equipment by means of setting specific values of the LRUs and confirming the expected test results. The AVTE prints the test results as a form of report to easily check the normal conditions of the aircraft equipment and operates automatically without operator interaction, thus being thought to effectively reduce workload of the operator.

• Journal of Advanced Navigation Technology
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• v.25 no.4
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• pp.273-279
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• 2021

A flight control computer(FLCC) applied to an unmanned aerial vehicle(UAV) is a safety-critical item, and which is designed in a multiple structure to increase the reliability of operation by securing fault tolerance. These FLCC of multiple structure should be designed so that each independent processing/control components can perform the same operation at the same time. And for this reason, a synchronization algorithm for synchronizing the operation between FLCCs should be included in an operational flight program. In this paper, we propose a software design method for synchronization between dual FLCCs applied to UAVs. The proposed synchronization method is designed to synchronize using only the minimum hardware resources to reduce a failure rate. In addition, the proposed synchronization method is designed to minimized synchronization errors due to a timer operation by designing in consideration of operation characteristics of the hardware timer used for the synchronization.