• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.135-138
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• 2009

G-Sensor is being used for controlling motion of smart-phone and robot. G-Sensor can control motion to several direction, because it is composed of X, Y, and Z axis and also can be used on many mobile-phone by using Wi-Fi communication and RS-232C communication on the Bluetooth module. In this research, we suggest the application that realize and develop visual-vehicle-remote-control-system by using mobile-phone with G-Sensor so that drivers can more easily remote control and manage their vehicle with mobile-phone in real-time visual.

• Journal of the Korea Safety Management & Science
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• v.23 no.4
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• pp.93-104
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• 2021

In this paper, we propose a method for diagnosing overload and working load of collaborative robots through performance analysis of machine learning algorithms. To this end, an experiment was conducted to perform pick & place operation while changing the payload weight of a cooperative robot with a payload capacity of 10 kg. In this experiment, motor torque, position, and speed data generated from the robot controller were collected, and as a result of t-test and f-test, different characteristics were found for each weight based on a payload of 10 kg. In addition, to predict overload and working load from the collected data, machine learning algorithms such as Neural Network, Decision Tree, Random Forest, and Gradient Boosting models were used for experiments. As a result of the experiment, the neural network with more than 99.6% of explanatory power showed the best performance in prediction and classification. The practical contribution of the proposed study is that it suggests a method to collect data required for analysis from the robot without attaching additional sensors to the collaborative robot and the usefulness of a machine learning algorithm for diagnosing robot overload and working load.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.3
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• pp.49-55
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• 2022

The design of a battery package and a BMS module for applications using seawater rechargeable batteries, which are known as next-generation energy storage devices, is proposed herein. Seawater rechargeable batteries, which are currently in the initial stage of research, comprise primarily components such as anode and cathode materials. Their application is challenging owing to their low charge capacity and limited charge/discharge voltage and current. Therefore, we design a method for packaging multiple cells and a BMS module for the safe charging and discharging of seawater rechargeable batteries. In addition, a prototype seawater rechargeable battery package and BMS module are manufactured, and their performances are verified by evaluating the prevention of overcharge, overdischarge, overcurrent, and short circuit during charging and discharging.

• Proceedings of the Korean Society of Computer Information Conference
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• 2023.07a
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• pp.69-71
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• 2023

본 논문은 YOLO 기반 모델의 철도 시스템 내 선로 고정장치 탐지 성능을 비교하고 분석한다. 여기서 철도 시스템은 열차가 주행하기 위한 선로, 침목, 패스너 등의 구성요소를 포함한다. 침목은 지반과 직접적으로 연결되며, 선로를 지반 위에 안정적으로 지지하고 궤간을 정확하게 유지하는 역할을 한다. 또한, 패스너는 선로를 침목에 단단히 고정시키는 역할을 한다. 이러한 선로 고정장치의 부재는 인명 사고로 이어질 수 있어 지속적인 관리와 유지 보수가 필수적이다. 본 논문에서는 철도 시스템의 선로 고정장치 탐지를 위해 YOLO V5 및 V8 딥러닝 모델의 적용 가능성을 실험적으로 접근하며, 두 모델의 탐지 성능을 비교한다. 실험 결과, YOLO V8 및 V5 모델은 모두 뛰어난 성능을 보이는데, 특히 YOLO V8 모델이 더욱 우수한 성능을 보인다. 이로써 YOLO 알고리즘은 선로 고정장치 탐지에 적합하다는 것을 증명한다. 그러나 일부 False Positive Sample이 관측되었음을 확인하고, 이로부터 모델 성능의 개선이 필요하다는 결론을 도출하였다.

• Journal of the Korean Society of Industry Convergence
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• v.27 no.1
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• pp.25-37
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• 2024

The objective of this study was to create intelligent rail robots that are optimized for facility management and implement digital twin systems for smart road tunnel management. An autonomous surveillance system is formed by combining the sensing platform consisting of railing robots, fixed cameras and environmental detection sensors with the digital twin data platform technology for tunnel monitoring and early fire suppression. In order to develop mobile rail robots for fire extinguishing, we also designed and manufactured robots for extinguishing & monitoring and fire extinguishing devices, and then we examined the optimization of all parts. Our next step was to build a digital twin for road tunnel management by developing continuous image display system and implementing 3D modeling. After constructing prototypes, we attempted simulations by configuring abnormal symptom scenarios, such as vehicles fires. This study's proposal proposes high-accuracy risk prediction services that will enable intelligent management of risks in the tunnel with early response at each stage, using the data collected from the intelligent rail robots and digital twin systems.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.343-345
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• 2024

얼굴 연령 분류 기법은 신원 확인 시스템 고도화, 유동 인구 통계 자동화 시스템 구축, 연령 제한 콘텐츠 관리 시스템 고도화 등 다양한 분야에 적용할 수 있는 확장 가능성을 가진다. 넓은 확장 가능성을 가지는 만큼 적용된 시스템의 안정성을 위해서는 얼굴 연령 분류 기법의 높은 정확도는 필수적이다. 따라서, 본 논문에서는 Vision Transformer(ViT) 기반 분류 알고리즘의 얼굴 연령 분류 성능을 비교 분석한다. ViT 기반분류 알고리즘으로는 최근 널리 사용되고 있는 ViT, Swin Transformer(ST), Neighborhood Attention Transformer(NAT) 세 가지로 선정하였으며, ViT의 얼굴 연령 분류 정확도 65.19%의 성능을 확인하였다.

• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.267-268
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• 2024

한국통합 물류협회에 따르면 총 택배 물량은 2020년은 약34억 개, 2021년은 약36억 만 개로 매년 꾸준히 성장하였다. 택배 물류센터에서 택배를 고객에게 전달시키기 위해서는 포장, 검수, 진열, 파지, 상차, 하차 등 많은 공정이 필요하다. 고용 인력의 부족, 인건비 상승, 부상의 위험, 높은 노동의 강도 등의 문제가 발생하였고, 소비자들의 입장에서도 제품 손상 또는 배송 지연 등의 여러 가지 문제를 야기해왔다. 본 논문은 로봇과 자율주행 기술을 활용하여 상품의 분류 및 배송과정을 자동화 하는 '스마트 물류창고 시스템'을 제안한다. 컨베이어 벨트를 이용해 택배물품의 분류를 자동화하고 자율주행 차량을 통해 배송을 하게 되고 DB를 통해 물품을 관리하게 되어 효율적인 운영을 가능하게 하고 경제적 손실을 줄인다. 적외선 센서, 바코드 센서를 이용해 컨베이어 벨트 구동 및 물품의 정보를 알 수 있으며 서보모터로 물품을 분류한다. 또한 입출고 차량이 명령을 통해 물품을 자동으로 입고 및 출고하여 DB에게 물품의 정보를 전송한다. 스마트 물류창고 시스템을 통해 인건비 절감, 오 배송, 물품 파손 등이 사라지게 되고 물류창고 뿐만 아니라 다양한 분야에서 적용 할 수 있을 것이다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.398-407
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• 2021

Firefighters (who are responsible for people's safety) have one of the jobs that are expected to have problems due to aging in the workforce. An increase in the average age of firefighters can lead to serious social problems. The aim of this study is to survey firefighters in Jeollanam-do about their awareness of aging in firefighters, and to propose a plan to prepare them for aging through investigation and analysis of work problems that may occur due to an aging workforce. The survey shows that the higher the age group, the higher the awareness of aging firefighters, and the higher the total work experience and internal/external work experience, the higher the awareness of aging. As a plan to solve various problems that may arise from aging in firefighters, regular operation of physical fitness promotion programs, field work, job rotation, and managerial measures (such as a change of position to an administrative department) are prepared, and drone or robot technology is used. These solutions include the introduction of applied high-tech technologies to firefighting activities, establishment of retirement management policies, and preparation of plans to revitalize the connection to private employment. In order to maximize the applicability of the field, government institutional plans and preparations are essential.

• Journal of the Society of Disaster Information
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• v.19 no.3
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• pp.665-672
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• 2023

Purpose: Underground utility tunnel is facility that is jointly house infrastructure such as electricity, water and gas in city, causing condensation problems due to lack of airflow. This paper aims to prevent electricity leakage fires caused by condensation by detecting whether the control panel door in the underground utility tunnel is open using a deep learning model. Method: YOLO, a deep learning object recognition model, is trained to recognize the opening and closing of the control panel door using video data taken by a robot patrolling the underground utility tunnel. To improve the recognition rate, image augmentation is used. Result: Among the image enhancement techniques, we compared the performance of the YOLO model trained using mosaic with that of the YOLO model without mosaic, and found that the mosaic technique performed better. The mAP for all classes were 0.994, which is high evaluation result. Conclusion: It was able to detect the control panel even when there were lights off or other objects in the underground cavity. This allows you to effectively manage the underground utility tunnel and prevent disasters.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.6
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• pp.193-204
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• 2022

In a smart factory environment in a small and medium-sized enterprise (SME) environment, sensors and actuators operating on actual manufacturing lines, programmable logic controllers (PLCs) to manage them, human-machine interface (HMI) to control and manage such PLCs, and consists of operational technology server to manage PLCs and HMI again. PLC and HMI, which are in charge of control automation, perform direct connection with OT servers, application systems for factory operation, robots for on-site automation, and production facilities, so the development of security technology in a smart factory environment is demanded. However, smart factories in the SME environment are often composed of systems that used to operate in closed environments in the past, so there exist a vulnerable part to security in the current environment where they operate in conjunction with the outside through the Internet. In order to achieve the internalization of smart factory security in this SME environment, it is necessary to establish a process according to the IEC 62443-4-1 Secure Product Development Life cycle at the stage of smart factory SW and HW development. In addition, it is necessary to introduce a suitable development methodology that considers IEC 62443-4-2 Component security requirements and IEC 62443-3 System security requirements. Therefore, this paper proposes an application plan for the IEC 62443 based development security process to provide security internalization to smart factories in an SME environment.