• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.168-170
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• 2022

The government enacted and promulgated the 'Severe Accident Punishment Act' in January 2021, and is enforcing the law for workplaces with 50 or more full-time workers. However, the number of industrial accident accidents in 2021 increased by 10.7% compared to the same period of the previous year, and chemical gas Safety accidents due to leaks and explosions also occur frequently. Therefore, in high-risk industrial sites, comprehensive Safety measures are urgently needed. In this study, BLE Mesh networking in industrial sites with poor communication environment apply technology. The complex sensor AIoT device recognizes a dangerous situation as a gas sensing value, voice, and motion value, and transmits it to the server. The server monitors the risk situation in real time through information value analysis and judgment through artificial intelligence LSTM algorithm and CNN algorithm for AIoT transmission information. Through this study, through the development of AIoT devices capable of gas sensing, voice and motion recognition, and AI-applied safety management systems, It will contribute to the expansion of the social safety net by expanding its application.

• The Journal of Korea Robotics Society
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• v.18 no.4
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• pp.385-391
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• 2023

In the elderly population, sarcopenia occurs due to physical aging, leading to movement restrictions and loss of function. This results in dependence on daily activities and limitations in participation, ultimately decreasing the overall quality of life. In this study, we propose an algorithm designed to enable patients with sarcopenia to perform sit-to-stand and stand-to-sit movements seamlessly in their daily lives. The algorithm incorporates a wearable robot for muscle support and includes algorithms for standing and seated muscle strength support. To validate the algorithm's performance, EMG sensors were attached to the Rectus Femoris and Biceps Femoris muscles. The participants underwent two scenarios: one without wearing the device and one with the device providing muscle strength support, performing sit-to-stand and stand-to-sit motions for one minute in each case. The results showed a 16% increase in the EMG peak value of the Rectus Femoris muscle during standing motion (p=0.009). On the right side, there was a roughly 20% decrease (p=0.018) during standing and a 21% decrease (p=0.014) during sitting motion. In the future, we aim to gather additional data to further refine the algorithm. Our goal is to develop an optimal muscle strength support algorithm based on this data, making it applicable for real-life use by patients with sarcopenia.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.2
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• pp.67-72
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• 2022

Recently, various intelligent application services using artificial intelligence are being actively developed. In particular, research on artificial intelligence-based real-time prediction services is being actively conducted in the manufacturing industry, and the demand for artificial intelligence services that can detect and predict fire and odors is very high. However, most of the existing detection and prediction systems do not predict the occurrence of fires and odors, but rather provide detection services after occurrence. This is because AI-based prediction service technology is not applied in existing systems. In addition, fire prediction, odor detection and odor level prediction services are services with ultra-low delay characteristics. Therefore, in order to provide ultra-low-latency prediction service, edge computing technology is combined with artificial intelligence models, so that faster inference results can be applied to the field faster than the cloud is being developed. Therefore, in this paper, we propose an LSTM algorithm-based learning model that can be used for fire prediction and odor detection/prediction, which are most required in the manufacturing industry. In addition, the proposed learning model is designed to be implemented in edge devices, and it is proposed to receive real-time sensor data from the IoT terminal and apply this data to the inference model to predict fire and odor conditions in real time. The proposed model evaluated the prediction accuracy of the learning model through three performance indicators, and the evaluation result showed an average performance of over 90%.

• Journal of Internet of Things and Convergence
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• v.10 no.2
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• pp.69-75
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• 2024

This paper proposes an IoT-based indoor autonomous driving system that applies SLAM (Simultaneous Localization And Mapping) and Navigation techniques in a ROS (Robot Operating System) environment based on TurtleBot3. The proposed autonomous driving system can be applied to indoor autonomous wheelchairs and robots. In this study, the operation was verified by applying it to an indoor self-driving wheelchair. The proposed autonomous driving system provides two functions. First, indoor environment information is collected and stored, which allows the wheelchair to recognize obstacles. By performing navigation using the map created through this, the rider can move to the desired location through autonomous driving of the wheelchair. Second, it provides the ability to track and move a specific logo through image recognition using OpenCV. Through this, information services can be received from guides wearing uniforms with the organization's unique logo. The proposed system is expected to provide convenience to passengers by improving mobility, safety, and usability over existing wheelchairs.

• Journal of the Semiconductor & Display Technology
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• v.17 no.1
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• pp.62-65
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• 2018

In the era of the 4th Industrial Revolution, IoT products of various and specialized fields are being developed and produced. Especially, the generation of the artificial intelligence, robotic technology Multilayer substrates and packaging technologies in the notebook, mobile device, display and semiconductor component industries are demanding the need for flexible materials along with miniaturization and thinning. To do this, this work use FCCL (Flexible Copper Clad Laminate), which is a flexible printed circuit board (PCB), to implement FPCB (Flexible PCB), COF (Chip on Film) Use is known to be essential. In this paper, I propose a transfer device which prevents the occurrence of scratches by analyzing the mechanism of wrinkle and scratch mechanism during the transfer process of thin film material in which the thickness increases while continuously moving in air or solution.

• Convergence Security Journal
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• v.21 no.1
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• pp.63-72
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• 2021

The hospital biomedical engineering team is responsible for establishing and regulating the Medical Device Management Program (MEMP) to ensure that medical devices are safe and reliable. As technology advances, medical devices such as artificial intelligence and precision medicine are developing into a form that allows connection between objects anytime, anywhere, and as various technologies converge, internal and external security threats continue to increase. In this paper, we present a study of the Medical Device Management Program (Secure-MEMP) method, considering that the security threat of medical devices continues to increase due to advances in technology.

• Electronics and Telecommunications Trends
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• v.37 no.1
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• pp.32-41
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• 2022

With the development of computing technology, the convergence of ICT with existing traditional industries is being attempted. In particular, with the recent advent of 5G, connectivity with numerous AuT (autonomous Things) in the real world as well as simple mobile terminals has increased. As more devices are deployed in the real world, the need for technology for devices to learn and act autonomously to communicate with humans has begun to emerge. This article introduces "Device to the Edge," a new computing paradigm that enables various devices in smart spaces (e.g., factories, metaverse, shipyards, and city centers) to perform ultra-reliable, low-latency and high-speed processing regardless of the limitations of capability and performance. The proposed technology, referred to as EdgeCPS, can link devices to augmented virtual resources of edge servers to support complex artificial intelligence tasks and ultra-proximity services from low-specification/low-resource devices to high-performance devices.

• Membrane and Water Treatment
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• v.13 no.5
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• pp.219-225
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• 2022

5th Assessment Report of the Intergovernmental Panel on Climate Change Weather (AR5) predicts that recent severe hydrological events will affect the quality of water and increase water pollution. To analyze changes in water quality due to future climate change, input data (precipitation, average temperature, relative humidity, average wind speed, and solar radiation) were compiled into a representative concentration curve (RC), defined using 8.5. AR5 and future use are calculated based on land use. Semi-distributed emission model Calculate emissions for each target period. Meteorological factors affecting water quality (precipitation, temperature, and flow) were input into a multiple linear regression (MLR) model and an artificial neural network (ANN) to analyze the data. Extensive experimental studies of flow properties have been carried out. In addition, an Acoustic Doppler Velocity (ADV) device was used to monitor the flow of a large open channel connection in a wastewater treatment plant in Ho Chi Minh City. Observations were made along different streams at different locations and at different depths. Analysis of measurement data shows average speed profile, aspect ratio, vertical position Measure, and ratio the vertical to bottom distance for maximum speed and water depth. This result indicates that the transport effect of the compound was considered when preparing the hazard analysis.

• Journal of Information Technology Applications and Management
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• v.16 no.3
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• pp.29-43
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• 2009

The advancement of emerging technologies can create more national value, and this motivates many nations to invest their resources in the emerging technologies. However, due to limited financial and human resources, even a wealthy nation cannot afford to randomly invest its resource in all profitable technologies. Therefore, cautious appraisal and prioritization of the competitive technologies should be conducted first, and then concentrated investment should be done for only the selected technologies. In this study, we propose a quantitative criterion for prioritizing the targeted electronic device technologies. The prioritization scheme devised in this study consists of a growth layer, a profitability layer, a vitality layer, and an influence layer. The proposed model forecasts the most promising technologies by applying the revised version of the Analytic Hierarchy Process (AHP). We performed empirical experiments on 12 emerging electronic device technologies to analyze the practical applicability of our study. The experimental data was obtained from 70 experts in high-tech industry as a part of the 2004 Prioritization and Selection project that was carried out in South Korea. As a result, the proposed scheme was able to present the most promising areas for investment in the field of electronic device technology.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.33 no.6
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• pp.351-358
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• 2020

This paper presents a tuned mass damper (TMD) utilizing a parametric design technique to reduce the dynamic responses to seismic loads of retractable large spatial structures. An artificial intelligence algorithm was developed to automatically search for the installation position of the damping device. This enables confirming the dynamic response of the structure in real time while finding the optimum position for the damping device. Further, the optimum mass of the damping device is determined from among several alternatives, and a design that can be effectively applied to both open and closed conditions of the roof is obtained.