• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.8
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• pp.671-680
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• 2021

This paper deals with the contents of designing and producing reconnaissance hardware and software, and verifying the functions after being installed on the CanSat platform and ground stations. The main reconnaissance mission is largely composed of two things: terrain search that renders the surrounding terrain in 3D using radar, GPS, and IMU sensors, and real-time detection of major objects through optical camera image analysis. In addition, data analysis efficiency was improved through GUI software to enhance the completeness of the CanSat system. Specifically, software that can check terrain information and object detection information in real time at the ground station was produced, and mission failure was prevented through abnormal packet exception processing and system initialization functions. Communication through LTE and AWS server was used as the main channel, and ZigBee was used as the auxiliary channel. The completed CanSat was tested for air fall using a rocket launch method and a drone mount method. In experimental results, the terrain search and object detection performance was excellent, and all the results were processed in real-time and then successfully displayed on the ground station software.

• Journal of Cadastre & Land InformatiX
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• v.52 no.1
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• pp.105-118
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• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Korean Journal of Remote Sensing
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• v.39 no.6_1
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• pp.1195-1210
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• 2023

Coastal debris has emerged as a salient issue due to its adverse effects on coastal aesthetics, ecological systems, and human health. In pursuit of effective countermeasures, the present study delineated the construction of a specialized image dataset for coastal debris detection and embarked on a comparative analysis between two paramount real-time object detection algorithms, YOLOv8 and RT-DETR. Rigorous assessments of robustness under multifarious conditions were instituted, subjecting the models to assorted distortion paradigms. YOLOv8 manifested a detection accuracy with a mean Average Precision (mAP) value ranging from 0.927 to 0.945 and an operational speed between 65 and 135 Frames Per Second (FPS). Conversely, RT-DETR yielded an mAP value bracket of 0.917 to 0.918 with a detection velocity spanning 40 to 53 FPS. While RT-DETR exhibited enhanced robustness against color distortions, YOLOv8 surpassed resilience under other evaluative criteria. The implications derived from this investigation are poised to furnish pivotal directives for algorithmic selection in the practical deployment of marine debris monitoring systems.

• Journal of the Korean Geotechnical Society
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• v.40 no.3
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• pp.41-54
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• 2024

Regular monitoring plays a crucial role in ensuring the safety of geotechnical structures. Currently, nondestructive methods are employed to monitor such structures to minimize the impact, e.g., sensor-based accelerometers, displacement meters, image-based lasers, and drone imaging. These technologies can observe surface changes; however, they frequently suffer difficulties in terms of identifying changes in internal properties. To monitor changes in internal properties, in situ geotechnical investigations can be employed. A nondestructive test that can be used for this purpose is the spectral analysis of surface wave (SASW) test using geophones. The SASW test is a nondestructive method; however, due to the time required for data interpretation and the difficulty in analyzing the data, it is challenging to use the SASW test for monitoring applications that require frequent observations. However, it is possible to apply the first-step analysis, which yields the dispersion curve, for monitoring rather than the complete SASW analysis, which yields the shear wave velocity. Thus, this paper presents a fundamental study on the phase difference that derives the dispersion curve to utilize the SASW test for monitoring. The reliability of each phase difference interval is examined to determine the boundary to the subjected monitor. The study used phase difference data obtained using a geophone from a single-layered, homogeneous ground site to evaluate reliable boundaries. The findings of this study are expected to improve the utility of monitoring by identifying the ideal boundary for phase difference data.

• Journal of Cadastre & Land InformatiX
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• v.54 no.1
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• pp.19-32
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• 2024

This study examined the feasibility of image-based surveys by detecting objects in facilities and agricultural land using the YOLO algorithm based on drone images and comparing them with the land category by law. As a result of detecting objects through the YOLO algorithm, buildings showed a performance of detecting objects corresponding to 96.3% of the buildings provided in the existing digital map. In addition, the YOLO algorithm developed in this study detected 136 additional buildings that were not located in the digital map. Plastic greenhouses detected a total of 297 objects, but the detection rate was low for some plastic greenhouses for fruit trees. Also, agricultural land had the lowest detection rate. This result is because agricultural land has a larger area and irregular shape than buildings, so the accuracy is lower than buildings due to the inconsistency of training data. Therefore, segmentation detection, rather than box-shaped detection, is likely to be more effective for agricultural fields. Comparing the detected objects with the land category by law, it was analyzed that some buildings exist in agricultural and forest areas where it is difficult to locate buildings. It seems that it is necessary to link with administrative information to understand that these buildings are used illegally. Therefore, at the current level, it is possible to objectively determine the existence of buildings in fields where it is difficult to locate buildings.

• Tunnel and Underground Space
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• v.34 no.1
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• pp.1-14
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• 2024

An image-reconstruction technology, involving the deployment of an unmanned mobility equipped with high-speed LiDAR (Light Detection And Ranging) has been proposed to reconstruct the shape of abandoned mine. Unmanned mobility operation is remarkably useful in abandoned mines fraught with operational difficulties including, but not limited to, obstacles, sludge, underwater and narrow tunnel with the diameter of 1.5 m or more. For cases of real abandoned mines, quadruped robots, quadcopter drones and underwater drones are respectively deployed on land, air, and water-filled sites. In addition to the advantage of scanning the abandoned mines with 2D solid-state lidar sensors, rotation of radiation at an inclination angle offers an increased efficiency for simultaneous reconstruction of mineshaft shapes and detecting obstacles. Sensor and robot posture were used for computing rotation matrices that helped compute geographical coordinates of the solid-state lidar data. Next, the quadruped robot scanned the actual site to reconstruct tunnel shape. Lastly, the optimal elements necessary to increase utility in actual fields were found and proposed.

• The Transactions of the Korea Information Processing Society
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• v.13 no.3
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• pp.111-121
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• 2024

Recently, thanks to the development of artificial intelligence technologies such as image recognition, research on unmanned aerial vehicles is being actively conducted. In particular, related research is increasing in the field of military drones, which costs a lot to foster professional pilot personnel, and one of them is the study of an intelligent framework for autonomous mission performance of reconnaissance drones. In this study, we tried to design an intelligent framework for unmanned aerial vehicles using the methodology of designing an intelligent framework for service robots. For the autonomous mission performance of unmanned aerial vehicles, the intelligent framework and unmanned aerial vehicle module must be smoothly linked. However, it was difficult to provide interworking for drones using periodic message protocols with model-based interfaces of intelligent frameworks for existing service robots. First, the message model lacked expressive power for periodic message protocols, followed by the problem that interoperability of asynchronous data exchange methods of periodic message protocols and intelligent frameworks was not provided. To solve this problem, this paper proposes a message model extension method for message periodic description to secure the model's expressive power for the periodic message model, and proposes periodic and asynchronous data exchange methods using the extended model to provide interoperability of different data exchange methods.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.53-65
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• 2022

According to the advancement of the GNSS satellite positioning system, the module of hardware and operation software reflecting accuracy and economical efficiency is implemented in the user sector including the multi-channel GNSS receiver, the multi-frequency external antenna and the mobile app (App) base public positioning analysis software etc., and the multichannel GNSS RTK positioning of the active configuration method (DIY, Do it yourself) is possible according to the purpose of user. Especially, as the infrastructure of multi-GNSS satellite is expanded and the potential of expansion of utilization according to various modules is highlighted, interest in the utilization of multi-channel low-cost GNSS receiver module is gradually increasing. The purpose of this study is to review the multi-channel low-cost GNSS receivers that are appearing in the mass market in various forms and to analyze the utilization plan of the "address information facility investigation project" of the Ministry of Public Administration and Security by constructing the multi-channel low-cost GNSS positioning module based RTK survey system (hereinafter referred to as "multi-channel GNSS RTK module positioning system"). For this purpose, we constructed a low-cost "multi-channel GNSS RTK module positioning system" by combining related modules such as U-blox's F9P chipset, antenna, Ntrip transmission of GNSS observation data and RTK positioning analysis app through smartphone. Kinematic positioning was performed for circular trajectories, and static positioning was performed for address information facilities. The results of comparative analysis with the Static positioning performance of the geodetic receivers were obtained with 5 fixed points in the experimental site, and the good static surveying performance was obtained with the standard deviation of average ±1.2cm. In addition, the results of the test point for the outline of the circular structure in the orthogonal image composed of the drone image analysis and the Kinematic positioning trajectory of the low cost RTK GNSS receiver showed that the trajectory was very close to the standard deviation of average ±2.5cm. Especially, as a result of applying it to address information facilities, it was possible to verify the utility of spatial information construction at low cost compared to expensive commercial geodetic receivers, so it is expected that various utilization of "multi-channel GNSS RTK module positioning system"

• Science of Emotion and Sensibility
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• v.19 no.4
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• pp.21-32
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• 2016

Studies have observed various phenomena regarding the effect of the interaction between type, price, and brand image of a product on consumers' purchase intent and product quality perception. Yet, few have studied the effect of the interaction between product type and manufacturing method on these factors. However, the advent of three-dimensional (3D) printers added a new manufacturing method, 3D printing, to the traditional methods of handicraft and automated machine-based production, and research is necessary since this new framework might affect consumers' purchase intent and product quality perception. Therefore, this study aimed to verify the effects of the interaction between product type and manufacturing method on purchase intent and product quality perception. To achieve this, in our experiment 1, we selected product types with different characteristics (drone vs. violin vs. cup), and measured whether consumers preferred different manufacturing methods for each product type. The results showed that consumers preferred the 3D printing method for technologically advanced products such as drones, the handmade method for violins, and the automated machine-based manufacturing method, which allows mass production, for cups. Experiment 2 attempted to verify the effects of the differences in manufacturing method preferences for each product type on consumers' purchase intent and product quality perception. Our findings are as follows: for drones, the purchase intent was highest when 3D printing was used; for violins, the purchase intent was highest when the violins were handmade; for cups, the purchase intent was highest when machine-based manufacturing was used. Moreover, whereas the product quality perception for drones did not differ across different manufacturing methods, consumers perceived that handmade violins had the highest quality and that cups manufactured with 3D printing had the lowest quality (the purchase intent for cups was also lowest when 3D printing was used). This study is anticipated to provide a wide range of implications in various areas, including consumer psychology, marketing, and advertising.

• Proceedings of the Korean Society of Crop Science Conference
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• 2023.04a
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• pp.7-7
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• 2023

Currently, the main technologies of various fourth industries are big data, the Internet of Things, artificial intelligence, blockchain, mixed reality (MR), and drones. In particular, "digital twin," which has recently become a global technological trend, is a concept of a virtual model that is expressed equally in physical objects and computers. By creating and simulating a Digital twin of software-virtualized assets instead of real physical assets, accurate information about the characteristics of real farming (current state, agricultural productivity, agricultural work scenarios, etc.) can be obtained. This study aims to streamline agricultural work through automatic water management, remote growth forecasting, drone control, and pest forecasting through the operation of an integrated control system by constructing digital twin data on the main production area of the nojinot industry and designing and building a smart farm complex. In addition, it aims to distribute digital environmental control agriculture in Korea that can reduce labor and improve crop productivity by minimizing environmental load through the use of appropriate amounts of fertilizers and pesticides through big data analysis. These open-field agricultural technologies can reduce labor through digital farming and cultivation management, optimize water use and prevent soil pollution in preparation for climate change, and quantitative growth management of open-field crops by securing digital data for the national cultivation environment. It is also a way to directly implement carbon-neutral RED++ activities by improving agricultural productivity. The analysis and prediction of growth status through the acquisition of the acquired high-precision and high-definition image-based crop growth data are very effective in digital farming work management. The Southern Crop Department of the National Institute of Food Science conducted research and development on various types of open-field agricultural smart farms such as underground point and underground drainage. In particular, from this year, commercialization is underway in earnest through the establishment of smart farm facilities and technology distribution for agricultural technology complexes across the country. In this study, we would like to describe the case of establishing the agricultural field that combines digital twin technology and open-field agricultural smart farm technology and future utilization plans.