• Proceedings of the Korean Society of Computer Information Conference
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• 2024.01a
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• pp.145-146
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• 2024

본 논문에서는 최근 몇 년 동안 스마트시티 인프라 투자가 크게 성장하였으며 글로벌 스마트 쓰레기통 시장은 성장 가능성이 높을 것으로 예상된다. 본 논문에서는 이에 발맞추어 CNN과 MQTT를 활용한 스마트 쓰레기통을 제작하였다. 쓰레기의 종류를 구별하고 해당되는 쓰레기통의 뚜껑을 골라 여는 것은 현대인의 생활에서 비효율을 야기한다. 이러한 문제를 해결하고자 CNN을 통한 효율적인 분류와 MQTT를 통한 통신, 센서들을 활용한 더 나은 쓰레기 수거 방식을 제공한다. 스마트 쓰레기통으로 일상을 더욱 편하고 효율적이게 만드는 데 기여하고자 한다.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.329-341
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• 2020

As COVID-19 pandemic sweeps across the world, more than 45 million confirmed cases and over 1,000,000 deaths have occurred till now, and this situation is expected to continue for some time. In particular, more than half of the infections in European countries such as Italy and Spain occurred in nursing homes, and it is reported that over 4,000 people died in nursing homes for older adults in the United States. Therefore, the issues that need to be addressed after the COVID-19 crisis include finding a fundamental solution to group care and shifting to family-centered care. More specifically, it is expected that there will be ever more lively discussion on establishing and expanding hyper-technology based community care, that is, family-centered care integrated with ICT and other Industry 4.0 technologies. This poses a challenge of how to combine social security and social welfare with Industry 4.0 in concrete ways that go beyond the abstract suggestions made in the past. A case in point is the proposal involving smart welfare cities. Given this background, the present paper examined the concept, scope, and content of non-face-to-face care in the context of previous literature on the function and scope of the social security platform, and the concept and expandability of the smart welfare city. Implementing a smart city to realize the kind of social security and welfare that our society seeks to provide has significant bearing on the implementation of community care or aging in place. One limitation of this paper, however, is that it does not address concrete measures for implementing non-face-to-face care from the policy and legal/institutional perspectives, and further studies are needed to explore such measures in the future. It is expected that the findings of this paper will provide the future course and vision not only for the smart welfare city but also for the social security and welfare system in administrative, practical, and legislative aspects, and ultimately contribute to improving the quality of human life.

• Journal of the Korean Association of Geographic Information Studies
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• v.18 no.2
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• pp.120-134
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• 2015

Under the hypothesis that the form of road network could affect crime occurrence, this study demonstrates to prove them using Space Syntax with real crime data. We calculated integration, control, connection index by means of Space Syntax and analyzed the relationship between the three indexes and the number of crime occurrence on the each road. Next, in order to generalize the analysis results we adopted Multi-Agent Model and simulated several scenarios on the computer virtual space. The results revealed that integration index has the strongest relationship with crime occurrence both in the case of real study area and virtual space simulations. Though this study has several limitations on the extent of virtual space and realistic computer programming of agents' behavior, the results are meaningful to verify the relationship between the form of read network and crime occurrence. Moreover the simulation platform that this study developed has promising possibilities to find realistic solutions on the effective police deployment or facility layout to improve smart safe city development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.10
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• pp.8-15
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• 2018

This article investigates intelligent security integrated platform for real-time crime response and preventive crime prevention. This study analyzed intelligent crime prevention platform elements by analyzing crime prevention system/platform research, intelligent crime prevention research, and case study of municipality integrated operation center crime prevention system. Through this, we developed a practical intelligent security platform, and suggested a linkage with existing municipalities and smart city integrated platform system considering scalability. This enables CCTV monitoring, which is used only for existing post processing, to cope with real-time crime. It is expected that it will be able to solve the incidents in golden-time by grasping the precise position of the complainant not only in the outdoor but also indoors. It is also possible to provide citizen-centered crime-prevention social safety net information sharing service by enhancing citizen participation as well as improving control efficiency. The intelligent security platform has advantages that it is easy to spread the municipality because it is developed considering existing municipal system, smart city integration platform, and linkage and expansion with other security services.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.4
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• pp.45-54
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• 2020

This study investigated basic data on walking characteristics, including walking speed and cognitive-response for the elderly, and based on these, the time of walking signal was calculated. The on-site survey examined the actual pedestrian crossing speed using a stopwatch, and the age was divided into groups of ordinary people and the elderly. Analysis of the data showed that the average walking speed for the general public was 1.29 m/s, while the average walking speed for the elderly was 1.13 m/s, higher than that of the general public. In addition, the lower speed of the 15th percentile was analyzed to 1.01 m/s for the general population and 0.85 m/s for the elderly, showing a lower walking speed than the standard for the general area and 0.8 m/s for the protected area. However, for senior citizens who use walking sticks or wheelchairs, the speed of the lower 15th-percentile is 0.73 m/s, which is lower than the current standard of protected areas, according to the analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.97-105
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• 2020

Recently, for a smart city, there is a demand for a technology for acquiring traffic information using an intelligent road infrastructure and managing it. In the meantime, various technologies such as loop detectors, ultrasonic detectors, and image detectors have been used to analyze road traffic information but these have difficulty in collecting various informations, such as traffic density and length of a queue required for building a traffic information DB for moving vehicles. Therefore, in this paper, assuming a smart city built on the basis of a camera infrastructure such as intelligent CCTV on the road, a solution for calculating the traffic DB of moving vehicles using Vision Tracking of road CCTV cameras is presented. Simulation and verification of basic performance were conducted and solution can be usefully utilized in related fields as a new intelligent traffic DB calculation solution that reflects the environment of road-mounted CCTV cameras and moving vehicles in a variable smart city road environment. It is expected to be there.

• Journal of Cadastre & Land InformatiX
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• v.50 no.1
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• pp.163-180
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• 2020

In this study, to build a spatial information infrastructure, which is a component of a smart city, a 3D digital twin model in the downtown area was built based on the latest spatial information acquisition technology, the drone. Several analysis models were implemented by utilizing. While the data processing time and quality of the three types of drone photogrammetry software are different, the accuracy of the construction model is ± 0.04 in the N direction and ± 0.03m in the E direction. In the m and Z directions, ± 0.02m was found to be less than 0.1m, which is defined as the allowable range of surveying performance and inspection performance for the boundary point in the area where the registration of the boundary point registration is executed. 1: 500 to 1 of the aerial survey work regulation: The standard deviation, which is the error limit of the photographic reference point of the 600 scale, appeared within 0.14 cm, and it was found that the error limit of the large scale specified in the cadastral and aerial survey was satisfied. In addition, in order to increase the usability of smart city realization using a drone-based 3D urban digital twin model, the model built in this study was used to implement Prospect right analysis, landscape analysis, Right of light analysis, patrol route analysis, and fire suppression simulation training. Compared to the existing aerial photographic survey method, it was judged that the accuracy of the naked eye reading point is more accurate (about 10cm) than the existing aerial photographic survey, and it is possible to reduce the construction cost compared to the existing aerial photographic survey at a construction area of about 30㎢ or less.

• Journal of Korea Water Resources Association
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• v.54 no.12
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• pp.1233-1242
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• 2021

In this study, a model was developed to determine whether flooding occurred using image data, which is unstructured data. CNN-based VGG16 and VGG19 were used to develop the flood classification model. In order to develop a model, images of flooded and non-flooded images were collected using web crawling method. Since the data collected using the web crawling method contains noise data, data irrelevant to this study was primarily deleted, and secondly, the image size was changed to 224×224 for model application. In addition, image augmentation was performed by changing the angle of the image for diversity of image. Finally, learning was performed using 2,500 images of flooding and 2,500 images of non-flooding. As a result of model evaluation, the average classification performance of the model was found to be 97%. In the future, if the model developed through the results of this study is mounted on the CCTV control center system, it is judged that the respons against flood damage can be done quickly.

• Journal of Korean Society of Water and Wastewater
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• v.33 no.1
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• pp.9-16
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• 2019

The algal blooms in stagnant streams and lakes have caused many problems. Excessive algae leads to disturbance of ecosystem and overload of water treatment processes. Therefore, phosphorus(P), source of algal blooms, should be controlled. In this study, a filtration trench has been developed to convert dissolved phosphorus into hydroxyapatite(HAP) so that it could be crystallized on the surface of 'phosphorus removal granular material'; and residual particulate phosphorus could be removed by additional precipitation and filtration. The front and rear parts of filtration trench consisted of 'phosphorus removal granular material contact bed' and 'limestone filtration bed', respectively. As a result of the column test using phosphorus removal granular material and limestone serially, $PO_4-P$ was removed more than 90% when EBCT(empty bed contact time) of the contact bed was over 20 minutes; and T-P represented 60% of removal efficiency when total EBCT was over 1.5 hours. The results of column tests to figure out the sedimentation characteristics showed that more than 90% of particulate phosphorus could be removed within 24 hours. It was necessary to optimize the filtration part in order to increase removal efficiency of T-P additionally. Also, it was confirmed through the simulation of Visual MINTEQ that most of particulate phosphorus in the column tests is the form of HAP. Based on the results of the study, it could be suggested that the design parameters are over 0.5 hour of EBCT for phosphorus removal granular material contact bed and over 1.5 hours of EBCT for limestone filtration bed.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.695-706
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• 2022

Medium and high-resolution optical satellites have proven their effectiveness in detecting wildfire areas. However, smoke plumes generated by wildfire scatter visible light incidents on the surface, thereby interrupting accurate monitoring of the area where wildfire occurs. Therefore, a technology to extract smoke in advance is required. Deep learning technology is expected to improve the accuracy of smoke extraction, but the lack of training datasets limits the application. However, for clouds, which have a similar property of scattering visible light, a large amount of training datasets has been accumulated. The purpose of this study is to develop a smoke extraction technique using deep learning, and the limits due to the lack of datasets were overcome by using a cloud dataset on transfer learning. To check the effectiveness of transfer learning, a small-scale smoke extraction training set was made, and the smoke extraction performance was compared before and after applying transfer learning using a public cloud dataset. As a result, not only the performance in the visible light wavelength band was enhanced but also in the near infrared (NIR) and short-wave infrared (SWIR). Through the results of this study, it is expected that the lack of datasets, which is a critical limit for using deep learning on smoke extraction, can be solved, and therefore, through the advancement of smoke extraction technology, it will be possible to present an advantage in monitoring wildfires.