• Journal of The Korean Society of Agricultural Engineers
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• v.64 no.1
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• pp.15-26
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• 2022

3D open-field farm model developed from UAV (Unmanned Aerial Vehicle) data could make crop monitoring easier, also could be an important dataset for various fields like remote sensing or precision agriculture. It is essential to separate crops from the non-crop area because labeling in a manual way is extremely laborious and not appropriate for continuous monitoring. We, therefore, made a 3D open-field farm model based on UAV images and developed a crop segmentation model using a supervised machine learning algorithm. We compared performances from various models using different data features like color or geographic coordinates, and two supervised learning algorithms which are SVM (Support Vector Machine) and KNN (K-Nearest Neighbors). The best approach was trained with 2-dimensional data, ExGR (Excess of Green minus Excess of Red) and z coordinate value, using KNN algorithm, whose accuracy, precision, recall, F1 score was 97.85, 96.51, 88.54, 92.35% respectively. Also, we compared our model performance with similar previous work. Our approach showed slightly better accuracy, and it detected the actual crop better than the previous approach, while it also classified actual non-crop points (e.g. weeds) as crops.

• Smart Media Journal
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• v.13 no.2
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• pp.52-61
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• 2024

In the shipyard, aerial images are acquired at regular intervals using Unmanned Aerial Vehicles (UAVs) for the management of external storage yards. These images are then investigated by humans to manage the status of the storage yards. This method requires a significant amount of time and manpower especially for large areas. In this paper, we propose an automated management technology based on a semantic segmentation foundation model to address these challenges and accurately assess the status of external storage yards. In addition, as there is insufficient publicly available dataset for external storage yards, we collected a small-scale dataset for external storage yards objects and equipment. Using this dataset, we fine-tune an object detector and extract initial object candidates. They are utilized as prompts for the Segment Anything Model(SAM) to obtain precise semantic segmentation results. Furthermore, to facilitate continuous storage yards dataset collection, we propose a training data generation pipeline using SAM. Our proposed method has achieved 4.00%p higher performance compared to those of previous semantic segmentation methods on average. Specifically, our method has achieved 5.08% higher performance than that of SegFormer.

• Journal of The Korean Society of Agricultural Engineers
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• v.66 no.3
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• pp.1-14
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• 2024

Gaining an accurate 3D stream geometry has become feasible with Unmanned Aerial Vehicle (UAV), which is crucial for better understanding stream hydrodynamic processes. The objective of this study was to investigate series of filters to remove stream vegetation and propose the best method for generating Digital Terrain Models (DTMs) using UAV-based point clouds. A stream reach approximately 500 m of the Bokha stream in Icheon city was selected as the study area. Point clouds were obtained in August 1st, 2023, using Phantom 4 multispectral and Zenmuse L1 for Structure from Motion (SfM) and Light Detection And Ranging (LiDAR) respectively. Three vegetation filters, two morphological filters, and six composite filters which combined vegetation and morphological filters were applied in this study. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) were used to assess each filters comparing with the two cross-sections measured by leveling survey. The vegetation filters performed better in SfM, especially for short vegetation areas, while the morphological filters demonstrated superior performance on LiDAR, particularly for taller vegetation areas. Overall, the composite filters combining advantages of two types of filters performed better than single filter application. The best method was the combination of Progressive TIN (PTIN) and Color Indicies of Vegetation Extraction (CIVE) for SfM, showing the smallest MAE of 0.169 m. The proposed method in this study can be utilized for constructing DTMs of stream and thus contribute to improving the accuracy of stream hydrodynamic simulations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.1
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• pp.53-60
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• 2017

This paper is to design and implement the drone that supports a wideband multimedia communication and a long-range to save people in maritime. The drone is an Unnamed Aerial Vehicle (UAV) that is controlled by a radio wave not by people boarding the machine. We use the drone to respond quickly to the boating accident. To develop a smart drone for the high speed seamless video streaming in a long-range maritime, a necessary techniques are hardware design techniques that design structure of a drone, controlling techniques that operate a drone and communication techniques that control a drone in a long distance. In this paper, the limitations and techniques to design and implement the structure of drone supporting wideband multimedia communication for long-range maritime are explained. By expanding this communication drone network, it is aimed at improving utility of a drone.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.62-68
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• 2023

An aerial relay system utilizing an unmanned aerial vehicle(UAV) or drone is addressed for event-driven operations such as temporary communication services for disaster affected area, military and first responder support. UAV relay system (URS) targets to provide a reliable communication service to a remote user equipment or an operator, therefore, a fast UAV placement to guarantee a minimum quality of service(QoS) is important when an operation is requested. Researches on UAV utilization in communication systems mostly target to derive the optimal position of UAV to maximize the performance, however, fast deployment of UAV is much more important than optimal placement under emergency situations. To this end, this paper derives the feasible area for UAV placement, investigates the effect of performance requirements on that area, and suggests UAV placement to certainly guarantee the performance requirements. Simulation results demonstrate that the feasible area derived in this paper matches that obtained by an exhaustive search.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2006.11a
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• pp.281-284
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• 2006

An intelligent performance diagnostic program using the Neural Network was proposed for PW206C turboshaft engine. It was selected as a power plant for the tilt rotor type Smart UAV (Unmanned Aerial Vehicle) which has been developed by KARI (Korea Aerospace Research Institute). The measurement parameters of Smart UAV propulsion system are gas generator rotational speed, power turbine rotational speed, exhaust gas temperature and torque. But two measurement such as compressor exit pressure and compressor turbine exit temperature were added because they were difficult each component diagnostics using the default measurement parameter. The performance parameters for the estimate of component performance degradation degree are flow capacities and efficiencies for compressor, compressor turbine and power turbine. Database for network learning and test was constructed using a gas turbine performance simulation program. From application results for diagnostics of the PW206C turboshaft engine using the learned networks, it was confirmed that the proposed diagnostics could detect well the single fault types such as compressor fouling and compressor turbine erosion.

• Journal of Advanced Navigation Technology
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• v.28 no.1
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• pp.68-76
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• 2024

With the recent rapid growth of the domestic and international unmanned aerial vehicle (UAV) market and the increasing importance of UAV operations in urban centers, such as UAMs, the safety management and regulatory framework for human life and property damage caused by UAV failures has been emphasized. In this study, we conducted a comparative analysis of risk-cost models that evaluate the risk of an operating area for safe UAM flight path planning, and identified the main limitations of each model to derive considerations for future model development. By providing a basic model for improving the safety of UAM operations, this study is expected to make an important contribution to technical improvements and policy decisions in the field of UAM flight path planning.

• Korean Journal of Remote Sensing
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• v.36 no.6_1
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• pp.1393-1405
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• 2020

UAV (Unmanned Aerial Vehicle) can acquire high-resolution images due to low-altitude flight, and it can be photographed at any time. Therefore, the UAV images can be updated at any time in map production. Due to these advantages, studies on the possibility of producing large-scale digital maps using UAV images are actively being conducted. Precise digital maps can be used as base data for digital twins or smart cites. For producing a precise digital map, precise sensor modeling using GCPs (Ground Control Points) must be preceded. In this study, geometric models of UAV images were established through a precision sensor modeling algorithm developed in house. Then, a digital map by stereo plotting was produced to evaluate the possibility of large-scale digital map. For this study, images and GCPs were acquired for Ganseok-dong, Incheon and Yeouido, Seoul. As a result of precision sensor modeling accuracy analysis, high accuracy was confirmed within 3 pixels of the average error of the checkpoints and 4 pixels of the RMSE was confirmed for the two study regions. As a result of the mapping accuracy analysis, it satisfied the 1:1,000 mapping accuracy announced by the NGII (National Geographic information Institute). Therefore, the precision sensor modeling technology suggested the possibility of producing a 1:1,000 large-scale digital map by UAV images.

• Journal of Advanced Navigation Technology
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• v.27 no.4
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• pp.382-390
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• 2023

The Korea market for LUAV (Light Unmanned Aerial Vehicle) weighing less than 150 kg is growing rapidly. As a result, the market for manufacturing and operating LUAV is expanding, and domestic development of parts and finished products is actively taking place. However, the flight control system and onboard software, which are key components of domestic LUAV, are largely dependent on overseas products due to the excessive cost and period required for development. This paper presented a domestic software development and certification procedure using DO-178C, a guideline for aircraft software development, and the Model-based Development method, and conducted a survey of those involved in the development, manufacturing, and certification of LUAV and analyzed the results. In addition, a case study was conducted to apply the software development plan to the helicopter FCC (Flight Control Computer).

• Smart Structures and Systems
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• v.22 no.2
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• pp.201-207
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• 2018

This paper proposes a line laser thermography scanning (LLTS) system for multiple crack evaluation on a concrete structure, as the core technology for unmanned aerial vehicle-mounted crack inspection. The LLTS system consists of a line shape continuous-wave laser source, an infrared (IR) camera, a control computer and a scanning jig. The line laser generates thermal waves on a target concrete structure, and the IR camera simultaneously measures the corresponding thermal responses. By spatially scanning the LLTS system along a target concrete structure, multiple cracks even in a large scale concrete structure can be effectively visualized and evaluated. Since raw IR data obtained by scanning the LLTS system, however, includes timely- and spatially-varying IR images due to the limited field of view (FOV) of the LLTS system, a novel time-spatial-integrated (TSI) coordinate transform algorithm is developed for precise crack evaluation in a static condition. The proposed system has the following technical advantages: (1) the thermal wave propagation is effectively induced on a concrete structure with low thermal conductivity of approximately 0.8 W/m K; (2) the limited FOV issues can be solved by the TSI coordinate transform; and (3) multiple cracks are able to be visualized and evaluated by normalizing the responses based on phase mapping and spatial derivative processes. The proposed LLTS system is experimentally validated using a concrete specimen with various cracks. The experimental results reveal that the LLTS system successfully visualizes and evaluates multiple cracks without false alarms.