• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.4
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• pp.57-70
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• 2021

This study aims to investigate the security demand about the traffic policing by analyzing civil complaints. Latent Dirichlet Allocation(LDA) was applied to extract key topics for 2,062 civil complaints data related to traffic policing from e-People. And additional analysis was made of reports of violations, which accounted for a high proportion. In this process, the consistency and convergence of keywords and representative documents were considered together. As a result of the analysis, complaints related to traffic police could be classified into 41 topics, including traffic safety facilities, passing through intersections(signals), provisional impoundment of vehicle plate, and personal mobility. It is necessary to strengthen crackdowns on violations at intersections and violations of motorcycles and take preemptive measures for the installation and operation of unmanned traffic control equipments, crosswalks, and traffic lights. In addition, it is necessary to publicize the recently amended laws a implemented policies, e-fine, procedure after crackdown.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.842-849
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• 2022

With the development of deep learning technology, there are many cases of using DNNs in embedded systems such as unmanned vehicles, drones, and robotics. Typically, in the case of an autonomous driving system, it is crucial to run several DNNs which have high accuracy results and large computation amount at the same time. However, running multiple DNNs simultaneously in an embedded system with relatively low performance increases the time required for the inference. This phenomenon may cause a problem of performing an abnormal function because the operation according to the inference result is not performed in time. To solve this problem, the solution proposed in this paper first reduces the computation by applying the Tucker decomposition to DNN models with big computation amount, and then, make DNN models run in parallel as much as possible in the unit of hidden layer inside the GPU. The experimental result shows that the DNN inference time decreases by up to 75.6% compared to the case before applying the proposed technique.

• 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.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.381-404
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• 2022

Forest fires inflict great losses of human lives and serious damages to ecological systems. Hence, numerous fire detection methods have been proposed, one of which is fire detection based on sensors. However, these methods reveal several limitations when applied in large spaces like forests such as high cost, high level of false alarm, limited battery capacity, and other problems. In this research, we propose a novel forest fire detection method based on image processing and correlation coefficient. Firstly, two fire detection conditions are applied in RGB color space to distinguish between fire pixels and the background. Secondly, the image is converted from RGB to YCbCr color space with two fire detection conditions being applied in this color space. Finally, the correlation coefficient is used to distinguish between fires and objects with fire-like colors. Our proposed algorithm is tested and evaluated on eleven fire and non-fire videos collected from the internet and achieves up to 95.87% and 97.89% of F-score and accuracy respectively in performance evaluation.

• International Journal of Computer Science & Network Security
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• v.22 no.9
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• pp.183-188
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• 2022

Recently, more and more researches aimed at the development of automated and autonomous ships are appearing in the scientific environment. One of the main reason is the need to solve the problems of safe navigation and reducing accidents due to human factor, as well as the ever-increasing problem associated with the lack of qualified maritime personnel. Development of technologies based on application of artificial intelligence also plays important role, after all for realization of autonomous navigation concept and enhancement of ship automatic maneuvering processes, advancement of maneuvering functions and elaboration of specific algorithms on prevention of close quarter situations and dangerous approach of ships will be required. The purpose of this work is the review of preconditions of occurrence of the autonomous ship navigation conception, overview of introduction stages and prospects for ship remote control based on unmanned technologies, analysis of technical and intellectual decisions of autonomous surface ships, main research tendencies. The research revealed that the technology of autonomous ship navigation requires further development and improvement, especially in terms of the data transmission protocols upgrading, sensors of navigation information and automatic control systems modernization, which allows to perform monitoring of equipment with the aim of improving the functions of control over the autonomous surface ship operation.

• Industry Promotion Research
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• v.8 no.1
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• pp.35-45
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• 2023

This paper addressed the analysis of the trend and direction of the US defense strategy based on their third offset strategy and presented the practical policy implication of ensuring the security of South Korea appropriately in the future national defense environment. The countermeasures for the development ability of advanced weapon systems and secure core technologies for Korea were presented in consideration of the US third offset strategy for the future national defense environment. First, to carry out the innovation of national defense in Korea based on artificial intelligence(AI), the long-term basis strategy for the operation of the unmanned robot and autonomous weapon system should be suggested. Second, the platform for AI has to be developed to obtain the development of algorithms and computing abilities for securing the collection/storage/management of national defense data. Lastly, advanced components and core technologies are identified, which the Korean government can join to develop with the US on a basis of the Korea-US alliance, and the technical cooperation with the US should be stronger.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.250-252
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• 2022

Recently, with the development of IoT technology and AI, unmanned and automated systems are progressing in various fields, and various application technologies are being studied in systems using algorithms such as object detection, recognition, and tracking. In the case of a system operating based on an image, noise removal is performed as a pre-processing process, and precise noise removal is sometimes required depending on the environment of the system. In this paper, we propose a modified central weight filter algorithm using pixel division of local regions to minimize the blurring that tends to occur in the filtering process and to emphasize the details of the resulting image. In the proposed algorithm, when a pixel of a local area is divided into two areas, the center of the dominant area among the divided areas is set as a criterion for the weight filter algorithm. The resulting image is calculated by convolving the transformed center weight with the pixel value inside the filtering mask.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.23 no.1
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• pp.112-122
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• 2024

Recently, as unmanned aerial vehicle technology such as drones has developed, there are many environmental, social and economic benefits, but if there is malicious intent against important national facilities such as airports, public institutions, power plants, and the military, it can seriously affect national safety and people's lives. It can cause damage. To respond to these drone threats, attempts are being made to introduce detection equipment such as RF scanners. In particular, power transmission towers installed in substations, power plants, and Korea's power system can affect detection performance if the transmission tower is located in the RF scanner detection path. In the experiment, a commercial drone was used to measure the signal intensity emitted from the drone and confirm the attenuation rate. The average and maximum attenuation rates showed similar trends in the 2.4 GHz and 5.8 GHz bands, and were also affected by the density of the structure.

• Journal of the Korea Society of Computer and Information
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• v.29 no.1
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• pp.11-19
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• 2024

Multi-agent systems can be utilized in various real-world cooperative environments such as battlefield engagements and unmanned transport vehicles. In the context of battlefield engagements, where dense reward design faces challenges due to limited domain knowledge, it is crucial to consider situations that are learned through explicit sparse rewards. This paper explores the collaborative potential among allied agents in a battlefield scenario. Utilizing the Multi-Robot Warehouse Environment(RWARE) as a sparse reward environment, we define analogous problems and establish evaluation criteria. Constructing a learning environment with the QMIX algorithm from the reinforcement learning library Ray RLlib, we enhance the Agent Network of QMIX and integrate Random Network Distillation(RND). This enables the extraction of patterns and temporal features from partial observations of agents, confirming the potential for improving the acquisition of sparse reward experiences through intrinsic rewards.

• Journal of The Korean Institute of Defense Technology
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• v.5 no.2
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• pp.10-16
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• 2023

This study establishes the operation concept of the 4th industrial revolution defense technology and communication facility-based 5G MUM-T system, and diagnoses our current situation, focusing on the case of US government technology policy, which is a leading country in 5G MUM-T system and operation. And to advance the operation of the 5G MUM-T system, reflect combat robots and drones in the detailed classification of weapon systems, early introduction of low-orbit 5G satellite communication, expansion of the use of 5G specialized networks and wholesale provision for demonstration and verification, establishment of a defense AI governance system, Suggests the necessity of a 3-class method for radiological weapon systems. For future research, it is important to respond to the technological evolution of 6G MUM-T and 6G NTN and compare and analyze each country's policy cases, such as China, Germany, the United Kingdom, and Japan.