• Journal of Korean Association for Spatial Structures
• /
• v.23 no.3
• /
• pp.95-103
• /
• 2023

With the increasing number of aging buildings across Korea, emerging maintenance technologies have surged. One such technology is the non-contact detection of concrete cracks via thermal images. This study aims to develop a technique that can accurately predict the depth of a crack by analyzing the temperature difference between the crack part and the normal part in the thermal image of the concrete. The research obtained temperature data through thermal imaging experiments and constructed a big data set including outdoor variables such as air temperature, illumination, and humidity that can influence temperature differences. Based on the collected data, the team designed an algorithm for learning and predicting the crack depth using machine learning. Initially, standardized crack specimens were used in experiments, and the big data was updated by specimens similar to actual cracks. Finally, a crack depth prediction technology was implemented using five regression analysis algorithms for approximately 24,000 data points. To confirm the practicality of the development technique, crack simulators with various shapes were added to the study.

• Journal of the Ergonomics Society of Korea
• /
• v.31 no.1
• /
• pp.261-269
• /
• 2012

Objective: The aim of this study is to develop an analysis method to extract plausible types of errors when using a smart mobile in nuclear power plants. Background: Smart mobiles such as a smart-phone and a tablet computer(smart-pad) are to be introduced to the various industries. Nuclear power plant like APR1400 already adopted many up-to-date digital devices within its main control room. With this trend, various types of smart mobiles will be inevitably introduced to the nuclear field in the near future. However nuclear power plants(NPPs) should be managed considering a big risk as a result of the trend not only economically but also socially compared to the other industrial systems. It is formally required to make sure to reasonably prevent the all hazards due to the introduction of new technologies and devices before the application to the specific tasks in nuclear power plants. Method: We define interaction segments(IS) as a main architect of interaction description, and enumerate all plausible error segments(ES) for a part of design evaluation of digital devices. Results: We identify various types of interaction errors which are coped with reasonably by interaction design using smart mobiles. Conclusion: According to the application result of the proposed method, we conclude that the proposed method can be utilized to specify the requirements to the human error hazards in digital devices, and to conduct a human factors review during the design of digital devices. Application: The proposed method can be applied to predict the human errors of the tasks related to the digital devices; therefore we can ensure the safety to apply the digital devices to be introduced to NPPs.

• Journal of Drive and Control
• /
• v.19 no.1
• /
• pp.1-7
• /
• 2022

Recently, a re-painting robot was developed to semi-automatically conduct blasting work in bridge spaces to improve work productivity and worker safety. In this study, a vision sensor-based monitoring module was developed to automatically move the re-painting robot along the path. The monitoring module provides direction information to the robot by analyzing the boundary between the painting surface and the metal surface. To stably measure images in unstable environments, various techniques for improving image visibility were applied in this study. Then, the driving performance was verified in a similar environment.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.7
• /
• pp.474-484
• /
• 2019

In this age, where the social environment is changing rapidly and unpredictably, interest in safety from crime is increasing in Korean society. As the desire to live a life free from the fear of crime increases, interest in the construction of safe cities is also rising nationwide. To meet the national demand, the Korean government is promoting a project to link public disaster safety systems by involving municipalities, 112, 119, and other emergency services and institutions through the Smart City Integrated Platform in order to construct a smart safety net. This study investigates the linking of theSmart City Integrated Platform and theIntelligent Security Project. The results are as follows. 1. The linkage's objective is clear. 2. The system sector can provide information to accident-related organizations. 3. The scenario area can be expanded to a crime-prevention sector, and a long-term urban information integration infrastructure can be created. 4. Product testing is enabled by a smart city road map and through continuous consultation with relevant organizations. 5. Project diffusion to other local governments can be promoted with the continued addition of commercial products.

• Journal of the Korean Institute of Gas
• /
• v.23 no.5
• /
• pp.15-23
• /
• 2019

42.5% of domestic gas accident due to human factors, and 38% occurred in residential area. Also gas accident caused by deterioration / malfunction increased more than 2 times for last 1 year. In this study we developed IoT based gas safety platform service for Home-gas safety, which secured 99.32% of data transmit accuracy, monitoring and remote control through LPWA bidirectional communication.

• Tunnel and Underground Space
• /
• v.34 no.3
• /
• pp.208-217
• /
• 2024

There is so much research effort for developing and implementing deep learning-based surveillance systems to manage health and safety issues in construction sites. Especially, the development of deep learning-based object detection in various environmental changes has been progressing because those affect decreasing searching performance of the model. Among the various environmental variables, the accuracy of the object detection model is significantly dropped under low illuminance, and consistent object detection accuracy cannot be secured even the model is trained using low-light images. Accordingly, there is a need of low-light enhancement to keep the performance under low illuminance. Therefore, this paper conducts a comparative study of various deep learning-based low-light image enhancement models (GLADNet, KinD, LLFlow, Zero-DCE) using the acquired construction site image data. The low-light enhanced image was visually verified, and it was quantitatively analyzed by adopting image quality evaluation metrics such as PSNR, SSIM, Delta-E. As a result of the experiment, the low-light image enhancement performance of GLADNet showed excellent results in quantitative and qualitative evaluation, and it was analyzed to be suitable as a low-light image enhancement model. If the low-light image enhancement technique is applied as an image preprocessing to the deep learning-based object detection model in the future, it is expected to secure consistent object detection performance in a low-light environment.

• Journal of Korea Multimedia Society
• /
• v.16 no.2
• /
• pp.180-189
• /
• 2013

The SMART Highway project combines road construction with advanced technology and vehicle telecommunications. Its expected outcome is a world-leading intelligent road that is green, fast, and comfortable. A vehicular ad-hoc network(VANET) is the core technology of the SMART Highway, whose transport operation is based on road vehicles. The VANET is a next-generation networking technology that enables wireless communication between vehicles or between vehicles and a road side unit(RSU). In the VANET system, a vehicle accident is likely to cause a serious disaster. Therefore, some information on safety is essential to serve as the key exchange protocol for communication between vehicles. However, the key exchange scheme of the general network proposed for a fast-moving communication environment is unsuitable for vehicles. In this paper, communication between multiple vehicles more efficient and secure key exchange at the vehicle certification by signcryption is proposed.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.10a
• /
• pp.161-163
• /
• 2021

This urban centralization is expected to develop rapidly, with 75% of the population living in the city by 2035. Large cities are becoming unsustainable due to side effects such as environmental pollution, severe traffic jams, excessive energy depletion, and destruction of the natural ecosystem. In addition, the happiness index of citizens of large cities is also falling because of high crime rates and safety accidents, the work-life imbalance caused by inequality and polarization, and overly competitive education. To solve this problem, Smart City, an IT-based future city model, was born. The Korean government is also actively attempting to improve urban competitiveness and promote sustainable development through efficient construction and operation of smart cities as a national focus project. To support the effort, we review the basic directions and strategies of Sejong City's Smart City service infrastructure based on the comprehensive national land plan, Smart City plan, and Smart City strategy plan.

• Journal of Drive and Control
• /
• v.18 no.1
• /
• pp.9-16
• /
• 2021

Overloaded vehicles increase the maintenance cost of road structures, and they are a major factor in causing damage to the roads and bridges. In addition, overloaded vehicles compromise the braking capability of the vehicle; thus, threatening the safety of the driver. In order to prevent overloading of vehicles, the government is cracking down on the roads by using a device that measures the weight of vehicles. But this process is inconvenient because the place where the equipment is installed is far away from where the cargo is loaded. Due to the limitations of these fixed weighing devices, there is a growing need for technology that can monitor vehicle weight distribution and overload conditions in real time. In this work, we develop an onboard scale that can measure the load (weight) of trucks in real time. The onboard scale consists of high sensors, a signal processing unit, and a display, and it measures the load using height-displacement of the vehicle's leaf spring suspension.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.197-199
• /
• 2021

High speed railway system is progressed to SRN(Smart Railway Network) having entirely automation function beyond each componet automations. It is necessity to use mobile communication technology of LTE-R(Long Term Evolution - Railway) and 5G-R(5th Generation - Railway) and information technology of convergence based on AI, Big Data, Deep Learning to construct this smart railway networks. In this paper, a communication structure is suggested for SRN. This suggested communication structure for SRN is composed to include safety operation of high speed train, railway system management and customer services, and also have complexing function of these each functions. Results of this study can be used for SRN construction and opeation, and development of railway communication standards.