• The Journal of the Convergence on Culture Technology
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• v.6 no.4
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• pp.493-498
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• 2020

The fourth industrial revolution is the first topic thrown by Klaus Schwab at the Davos World Economic Forum in January 2016, meaning the next industrial revolution led by the Internet of Things (IOT), artificial intelligence (AI), robot technology and life sciences. In addition, in our lives, humans, computers and machines are connected organically, and organic relationships are evolving and developing at a furious rate in all areas of life. Since the 1953 armistice agreement, South Korea has remained in a state of confrontation with North Korea, and there have been continued fighting by the North, including naval skirmishes in the West Sea, artillery attacks on Yeonpyeong Island, the sinking of the Cheonan warship, and unmanned aerial vehicles and ankle mines. To prepare for such a local initiative, our military is constantly preparing and will have to strengthen its combat capabilities by developing and introducing advanced military equipment. After all, the military drone industry linked to the Fourth Industrial Revolution following the development of new war should continue its research on military drones in line with accurate diagnosis and the rapid development of future science and technology and IT technologies.

• Journal of Digital Convergence
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• v.16 no.8
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• pp.71-79
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• 2018

This study discussed the meaning of a drone, and especially drone journalism and legal and ethical issues around that, at an introductory dimension, which is used in various social bases, but is still just an academic discussion at the beginning stage. As a methodology, content analysis was used. It seems that drone journalism has high diffusibility as a technology with high 'relative advantage', 'compatibility', 'trial ability' and 'observability' and low 'complexity' in terms of the diffusion of innovation theory. However, it will be very likely that controversies will be raised, such as safety issue due to collision and crash, a dispute over violation of privacy that may seriously infringe privacy like individual portrait rights and a controversy about the accuracy and source of information as drone filming low price and ease of use. Suggest solutions to legal and ethical issues based on existing research. Technical stability is required. Also, it is necessary to change the awareness of journalists about the drones coverage and to educate ethics, and it is necessary to establish social public opinion on issues such as privacy violation and establish system and legal measures through it. Future research is expected to carry out empirical research including journalists and public awareness surveys.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.4
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• pp.117-122
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• 2021

In recent years, human damage and loss of money due to various disasters such as typhoons, earthquakes, forest fires, landslides, and wars are steadily occurring, and a lot of manpower and funds are required to prevent and recover them. In this paper, we designed and developed a disaster drone system based on artificial intelligence in order to monitor these various disaster situations in advance and to quickly recognize and respond to disaster occurrence. In this study, multiple disaster drones are used in areas where it is difficult for humans to monitor, and each drone performs an efficient search with an optimal path by applying a deep learning-based optimal path algorithm. In addition, in order to solve the problem of insufficient battery capacity, which is a fundamental problem of drones, the optimal route of each drone is determined using Ant Colony Optimization (ACO) technology. In order to implement the proposed system, it was applied to a forest fire situation among various disaster situations, and a forest fire map was created based on the transmitted data, and a forest fire map was visually shown to the fire fighters dispatched by a drone equipped with a beam projector. In the proposed system, multiple drones can detect a disaster situation in a short time by simultaneously performing optimal path search and object recognition. Based on this research, it can be used to build disaster drone infrastructure, search for victims (sea, mountain, jungle), self-extinguishing fire using drones, and security drones.

• Korean Journal of Remote Sensing
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• v.39 no.5_2
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• pp.827-835
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• 2023

Drone light detection and ranging (LiDAR) is a state-of-the-art surveying technology that enables close investigation of the top of the mountain slope or the inaccessible slope, and is being used for field surveys in mountainous terrain. To build topographic information using Drone LiDAR, a preprocessing process is required to effectively separate ground and non-ground points from the acquired point cloud. Therefore, in this study, the point group data of the mountain topography was acquired using an aerial LiDAR mounted on a commercial drone, and the application and accuracy of the cloth simulation filtering algorithm, one of the ground separation techniques, was verified. As a result of applying the algorithm, the separation accuracy of the ground and the non-ground was 84.3%, and the kappa coefficient was 0.71, and drone LiDAR data could be effectively used for landslide field surveys in mountainous terrain.

• The Journal of the Convergence on Culture Technology
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• v.9 no.1
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• pp.697-702
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• 2023

Recently, with the introduction of drones, a core technology of the 4th industrial revolution, various convergence education using drones is being conducted in school education sites. In particular, drone theory and practice education is being conducted in connection with free semester classes and career exploration. The drone convergence education program has higher learner satisfaction than simple demonstration and practice education, and the learning effect is high due to direct practical experience. However, since practical education is being conducted for a large number of learners, it is impossible to restrict and control the flight of a large number of drones in a limited place. In this paper, we propose a monitoring system that allows the instructor to monitor multiple drones in real time and learners to recognize collisions between drones in advance when multiple drones are operated, focusing on education operated in schools. The communication module used in the experiment was equipped with GPS in Murata LoRa, and the server and client were configured to enable monitoring based on the location data received in real time. The performance of the proposed system was evaluated in an open space, and it was confirmed that the communication signal was good up to a distance of about 120m. In other words, it was confirmed that 25 educational drones can be controlled within a range of 240m and the instructor can monitor them.

• Ecology and Resilient Infrastructure
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• v.6 no.3
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• pp.171-177
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• 2019

The hyperspectral images can be analyzed in more detail compared to the conventional multispectral images so they can be used for analyzing surface properties which are difficult to detect. Therefore, the purpose of this study is to obtain information on river environment by using actual depth data and drone-based images. For this purpose, this study acquired the image values for 100 points of 1 survey line using drone-based hyperspectral sensors and analyzed the correlation in comparison with the actual depth information obtained through ADCP. The ADCP measurements showed that the depth tended to get deeper toward the center and that the average water depth was 0.81 m. As a result of analyzing the hyperspectral images, the value of maximum intensity was 645 and the value of minimum intensity was 278, and the correlation between the actual depth and the results of analyzing the hyperspectral images showed that the depth increased as the value of maximum intensity decreased.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.37 no.4
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• pp.243-251
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• 2019

The road sign location information installed on national roads is continuously updated using MMS (Mobile Mapping System) technology. It is possible to map accurate road facilities by MMS, but the equipment is very expensive and requires specialized technology. Also, the accuracy of the position of the object greatly depends on the GPS (Global Positioning System) accuracy. In the case of road facility mapping, the advantage of drone is more remarkable than that of field survey or conventional aerial photogrammetry. In particular, it is more efficient than field surveying and it is possible to acquire high resolution images with low budget compared to conventional aerial photogrammetry. In this study, the accuracy of the location information measured by the existing MMS is compared with the GPS survey result and the accuracy analysis is performed by the drone aerial photogrammetry. In order to confirm the space accuracy that can be obtained when conducting drone aerial photogrammetry, the accuracy of the change in the number of ground control points and the degree of overlap was evaluated. As a result of the experiment, it was possible to obtain sufficient accuracy with two ground control points distributed at both ends of the road and 60% overlap.

• Journal of the Korea Society of Computer and Information
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• v.21 no.9
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• pp.79-84
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• 2016

In this paper we consider the problem of finding the triplet (S,${\pi}$,f), where $S{\subseteq}V$, ${\pi}$ is a sequence of nodes in S and $f:V{\backslash}S{\rightarrow}S$ for a given complete graph G=(V,E). In particular, there exist two costs, $c^V_{uv}$ and $c^D_{uv}$ for $(u,v){\in}E$, and the cost of triplet (S,${\pi}$,f) is defined as $\sum_{i=1}^{{\mid}S{\mid}}c^V_{{\pi}(i){\pi}(i+1)}+2$ ${\sum_{u{\in}V{\backslash}S}c^D_{uf(u)}$. This problem is motivated by the integrated routing of the vehicle and drone for urban delivery services. Since a well-known NP-complete TSP (Traveling Salesman Problem) is a special case of our problem, we cannot expect to have any polynomial-time algorithm unless P=NP. Furthermore, for practical purposes, we may not rely on time-exhaustive enumeration method such as branch-and-bound and branch-and-cut. This paper suggests the simple heuristic which is motivated by the MST (minimum spanning tree)-based approximation algorithm and neighborhood search heuristic for TSP.

• Electronics and Telecommunications Trends
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• v.36 no.6
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• pp.46-54
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• 2021

Drone remote identification (ID) capability is essential to ensure public safety, help law enforcement, and secure the safety and efficiency of the national airspace. Remote ID technology can be used to differentiate compliant drones from illegal drones that pose a potential security risk by providing airspace awareness to the civil aviation agency and law enforcement entities. In addition, the increased safety and efficiency obtained by mandating remote ID will make it possible to operate drones over populated areas and beyond visual lines of sight. In addition, remote ID will allow drones to be safely integrated into unmanned traffic management systems and the national airspace. Remote ID devices can be categorized by type, i.e., broadcast remote ID or network remote ID. The broadcast remote ID, which has high technical maturity and will be applied in the near future, is primarily considered to ensure the security of drones. The network remote ID, which is being developed and tested and will be applied in the distant future, can be used additionally to ensure the safety and the efficiency of the national airspace. In this paper, we analyze the trends on regulation and standardization activities for drone remote ID primarily in the United State and Europe.

• Journal of Korea Multimedia Society
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• v.25 no.2
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• pp.237-246
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• 2022

Among the technologies of the 4th industrial revolution, drones that have grown rapidly and are being used in various industries can be operated by the pilot directly or can be operated automatically through programming. In order to be controlled by a pilot or to operate automatically, it is essential to predict and analyze the optimal path for the drone to move without obstacles. In this paper, after securing and analyzing the pilot training dataset through the unmanned aerial vehicle piloting training platform designed through prior research, the profile of the dataset that should be preceded to search and derive the optimal route of the unmanned aerial vehicle was designed. The drone pilot training data includes the speed, movement distance, and angle of the drone, and the data set is visualized to unify the properties showing the same pattern into one and preprocess the properties showing the outliers. It is expected that the proposed big data-based profile can be used to predict and analyze the optimal movement path of an unmanned aerial vehicle.