• Journal of the Korean Society of Environmental Restoration Technology
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• v.26 no.5
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• pp.1-18
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• 2023

The Ecosystem Conservation Levy (formerly known as the Ecosystem Conservation Cooperation Fund) system has been in place for 20 years, and it can be said that it has now entered the settlement stage. Based on an analysis of publicly available project implementation data from 2014 to 2020, we found that: 1) As the number of return projects increases, the targets of restoration technologies are also strengthening, and it is necessary to frame a series of processes from application, creation, and monitoring for some detailed projects to improve the effectiveness and efficiency of utilizing the levy. 2) Most of the implemented projects are applied as micro-ecosystem creation, but there are many cases where the contents of the project can be seen as other project categories. This shows that the purpose of the return project needs to be approached more clearly and suggests that institutional complementation is needed from the project application stage. 3) The detailed technologies applied tend to be gradually expanding, but most of them are technologies that are not differentiated from general development projects. It is urgent to secure a more technical identity, such as a range and list of utilized technologies suitable for the characteristics and purposes of return projects. 4) It is necessary to establish a relevant evaluation system or framework to utilize the monitoring results of restoration projects. 5) There have been few cases of application of single restoration technologies since the beginning, but the content and scope of the complexity tend to expand in recent years. Even if the objectives are not comprehensive and diverse, it can be seen that many parts of the projects are oriented toward convergence, so it is necessary to conduct separate research on this. 6) As for the direction of improvement of the return project, it is possible to consider expanding the restoration and conservation focus to partially accommodate the complexity of the natural environment and human ecology. It seems that the expansion of restoration technologies that consider the role and function of humans in the natural environment should be explored.

• Information Systems Review
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• v.21 no.1
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• pp.113-133
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• 2019

Gentrification, caused by residents who are being forced out due to the rise of rent with vitalization by an excessive increase of city tourists and Touristification, meaning of phenomenon of residents' migration caused by residential area turning into tourist attraction have recently pointed out as a global problem. In Korea, the phenomenon such as environmental pollution, the rise of land value and rent, and the weakening of community culture in Jeju island and Bukchon Hanok Village has appeared as well. This phenomenon has become a serious problem by hindering resident's quality of life. In this circumstance, Smart tourism city has been regarded as a solution of these problems. Hence, this study chose Busan city, which has been designated as a smart city since 2015, and examined the complex impacts of the economic benefits, social costs, environmental substantiality, cultural benefits, and technical effects derived from tourism development on the residents' deteriorated quality of life based on Fuzzy-set Qualitative Analysis (fsQCA). As a result, three patterns of the hindrance to residents' quality of life were derived. If social costs of tourism development are perceived to be large, the residents perceive deteriorated quality of life, even if they recognize essential benefits (technological and economic benefits) (Pattern #1) or secondary benefits (environmental and cultural benefits) (Pattern #2) of tourism development. In addition, some residents were found not to recognize any benefits of tourism development (Pattern #3).

• Journal of Intelligence and Information Systems
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• v.26 no.2
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• pp.131-145
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• 2020

In line with the trend of industrial innovation, IoT technology utilized in a variety of fields is emerging as a key element in creation of new business models and the provision of user-friendly services through the combination of big data. The accumulated data from devices with the Internet-of-Things (IoT) is being used in many ways to build a convenience-based smart system as it can provide customized intelligent systems through user environment and pattern analysis. Recently, it has been applied to innovation in the public domain and has been using it for smart city and smart transportation, such as solving traffic and crime problems using CCTV. In particular, it is necessary to comprehensively consider the easiness of securing real-time service data and the stability of security when planning underground services or establishing movement amount control information system to enhance citizens' or commuters' convenience in circumstances with the congestion of public transportation such as subways, urban railways, etc. However, previous studies that utilize image data have limitations in reducing the performance of object detection under private issue and abnormal conditions. The IoT device-based sensor data used in this study is free from private issue because it does not require identification for individuals, and can be effectively utilized to build intelligent public services for unspecified people. Especially, sensor data stored by the IoT device need not be identified to an individual, and can be effectively utilized for constructing intelligent public services for many and unspecified people as data free form private issue. We utilize the IoT-based infrared sensor devices for an intelligent pedestrian tracking system in metro service which many people use on a daily basis and temperature data measured by sensors are therein transmitted in real time. The experimental environment for collecting data detected in real time from sensors was established for the equally-spaced midpoints of 4×4 upper parts in the ceiling of subway entrances where the actual movement amount of passengers is high, and it measured the temperature change for objects entering and leaving the detection spots. The measured data have gone through a preprocessing in which the reference values for 16 different areas are set and the difference values between the temperatures in 16 distinct areas and their reference values per unit of time are calculated. This corresponds to the methodology that maximizes movement within the detection area. In addition, the size of the data was increased by 10 times in order to more sensitively reflect the difference in temperature by area. For example, if the temperature data collected from the sensor at a given time were 28.5℃, the data analysis was conducted by changing the value to 285. As above, the data collected from sensors have the characteristics of time series data and image data with 4×4 resolution. Reflecting the characteristics of the measured, preprocessed data, we finally propose a hybrid algorithm that combines CNN in superior performance for image classification and LSTM, especially suitable for analyzing time series data, as referred to CNN-LSTM (Convolutional Neural Network-Long Short Term Memory). In the study, the CNN-LSTM algorithm is used to predict the number of passing persons in one of 4×4 detection areas. We verified the validation of the proposed model by taking performance comparison with other artificial intelligence algorithms such as Multi-Layer Perceptron (MLP), Long Short Term Memory (LSTM) and RNN-LSTM (Recurrent Neural Network-Long Short Term Memory). As a result of the experiment, proposed CNN-LSTM hybrid model compared to MLP, LSTM and RNN-LSTM has the best predictive performance. By utilizing the proposed devices and models, it is expected various metro services will be provided with no illegal issue about the personal information such as real-time monitoring of public transport facilities and emergency situation response services on the basis of congestion. However, the data have been collected by selecting one side of the entrances as the subject of analysis, and the data collected for a short period of time have been applied to the prediction. There exists the limitation that the verification of application in other environments needs to be carried out. In the future, it is expected that more reliability will be provided for the proposed model if experimental data is sufficiently collected in various environments or if learning data is further configured by measuring data in other sensors.

• Journal of the Korean Society of Systems Engineering
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• v.15 no.2
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• pp.98-107
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• 2019

The defense system development process is a process of developing various systems that perform functions in various functional areas such as battlefield awareness, command control, force application, and logistical support. In other words, the defense system development process is a process of developing many systems simultaneously in various functional areas. Various systems developed through this process should be interoperable so that they can be integrated and operated in a joint warfighting environment. To successfully implement this, the US Department of Defense uses the Joint Capability Integrated Development System(JCIDS) for the defense system development, and within this JCIDS processes the Capability Based Assessment(CBA) methodology as its core technology. This CBA methodology transforms the mission activity requirements to functional capability requirements logically and transforms the functional capability requirements to system requirements logically also. Smart City is a city that improves the convenience and quality of life of the citizen by integrates various systems that perform various functions of the city and smarties various functional systems with smart services by using IT technology. In other words, defense system development and smart city development have a common feature of the process of developing many systems simultaneously in various functional areas. In order to address the problem of having to develop many systems simultaneously in each functional area, it is important to logically transform the various mission scenarios into functions and logically transform the functions into systems. Therefore, a joint capability integrated development system and its core methodology, Capability Based Assessment(CBA), can be applied to smart city development. This paper proposes a method for performing a smart city concept design method using the capability based evaluation (CBA) method.

• Informatization Policy
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• v.24 no.2
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• pp.3-19
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• 2017

This article examines the issues around the coming age of artificial intelligence and the 4th industrial revolution. First, this articles addresses the changes we will encounter with the advance of innovative technologies. Changes in future jobs, education, travel and other lifestyle issues are discussed and responses of a few countries(governments) regarding preparations for such future changes are illustrated. To sum up, three dimensions - sustainable technology development, legal and policy-related establishments, and consensus building among the public - are identified as areas to focus on for the future. Particularly, it is advised that the Korean government apply and utilize new technologies to solve public issues and problems, particularly the newly-emerging "urban renewal" and "smart city" issues.

• Journal of Energy Engineering
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• v.29 no.3
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• pp.86-90
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• 2020

This paper examines a blockchain network-based transaction system using location proofing in power direct transactions between networked energy clouds, energy communities, and prosumer machines participating in smart cities. It utilizes location-based blockchain network technology, which enables long-distance travel with recharging by power purchases during autonomous movements, autonomous electric vehicles that can purchase and sell electricity, and solar street lights that can be produced and sold in fixed form. In addition, it is possible to provide optimum power transaction matching and settlement reliability between machines without human intervention in power transactions between electric chargers. It also introduces a business-to-object business model between autonomous machines that exist in multiple and different spaces and through energy clouds that are expected to be scattered with various transaction prices, policies, and incentives.

• The Journal of the Korea Contents Association
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• v.12 no.3
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• pp.9-16
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• 2012

The research of vehicle license plate recognition has been widely studied for the smart city project. The license plate recognition can be hard due to the geometric distortion and the image quality degradation in case of capturing the driving car image at CCTV without trigger signal on the road. In this paper, the high performance vehicle license plate recognition system using edge-based segment image is introduced which is robust in the geometric distortion and the image quality degradation according to non-trigger signal. The experimental results of the proposed real time license plate recognition algorithm which is implemented at the CCTV on the road show that the plate detection rate was 97.5% and the overall character recognition rate of the detected plates was 99.3% in a day average 1,535 vehicles for a week operation.

• The Journal of the Korea Contents Association
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• v.20 no.9
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• pp.439-447
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• 2020

Public data refers to all data or information created by public institutions, and public information that leads to communication and cooperation among all people. Public data is an important method to lead the next generation of new industries such as artificial intelligence and smart cities, Korea is continuously ranked high in the international evaluation related to public data. However, despite the continuous efforts, the use of public data or industrial influence is insufficient. Quality issues are continuously discussed in the use of public data, but the criteria for quantitatively evaluating data are insufficient. This paper reviews indicators for public data quality evaluation and performs quantitative evaluation on selected public data. In particular, the quality of open standard data constructed and opened based on public data management guidelines is examined to determine whether government guidelines are appropriate. The data quality assessment includes the metadata and data values of open standard data, and is reviewed based on completeness and accuracy indicators. Based on the data analysis results, this paper proposes policy and technical measures for quality improvement.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.1
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• pp.73-81
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• 2012

This study ultimately aims to suggest directions for development of U-City Competitiveness Index through thorough analyses of U-City competitiveness concepts and previous research in U-City-related index. In an attempt to reach the aforementioned goals, the concept of U-City competitiveness is presented based on existing publications on informatization age, future city, and U-City. Next, insights on the development of U-City Competitiveness Index are provided via analysis of research on indices regarding U-City and future city. Finally, the process of developing UCity Competitiveness Index and cautionary comments for each developmental step has been provided. Based on the research results, U-City competitiveness refers to the ability to respond to demands of residents in a timely manner as well as to manage U-City, ICT, U-City infrastructure, and U-City services that maximizes the efficiency of urban space management. In order for proper assessment of these criteria, development of assessment tools, selection of indices, standardization, allocation of weight per index, and construction of assessment framework are required.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.10
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• pp.77-83
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• 2020

The technologies of 3D spatial information, such as Smart City and Digital Twins, are developing rapidly for managing land and solving urban problems scientifically. In this construction of 3D spatial information, an object using aerial photo images is built as a digital DB. Realistically, the task of extracting a texturing image, which is an actual image of the object wall, and attaching an image to the object wall are important. On the other hand, occluded areas occur in the texturing image. In this study, the ResNet algorithm in deep learning technologies was tested to solve these problems. A dataset was constructed, and the street tree was detected using the ResNet algorithm. The ability of the ResNet algorithm to detect the street tree was dependent on the brightness of the image. The ResNet algorithm can detect the street tree in an image with side and inclination angles.