• Convergence Security Journal
• /
• v.23 no.4
• /
• pp.81-92
• /
• 2023

In recent years, the ROK military is promoting Defense Innovation 4.0 with the goal of fostering strong military based on science and technology equipped with artificial intelligence(AI) to prepare for the upcoming population cliff. In particular, at the present time of increased threats of North Korea, the South Korean military is seeking to deal with a decrease in military service resources through the introduction of a Scientific Guard System using advanced technology. TICN which is a core basic communication system to ensure the integrated combat capability of the ROK military is, however, limited to use as a based network for the emerging Scientific Guard System due to the narrow transmission bandwidth with widely spread poor reception area. To deal with this problem, this paper proposes TVWS-based Scientific Guard Systems with TVWS-based wireless network construction technology that has been available for free in Korea since 2017. The TVWS-based Scientific Guard System proposed in this paper, when compared to the existing wired network-based Scientific Guard Systems, has various advantages in terms of minimizing operational gaps, reducing construction costs, and flexibility in installation and operation.

• Korean Security Journal
• /
• no.10
• /
• pp.243-272
• /
• 2005

All measures related to the safety of the casino facilities guarantee safety of facilities that are targets of security guards, protect lives and properties, minimize risks of artificial and natural disaster and crimes. In summary, plan for responding to safety and accidents should be developed not only for the casino facilities but also for the facilities of annexed buildings, and lives and properties of customers and employees. Determine areas in the casino facilities that are prone to accidents and set around-the-clock guard in the areas or maintain surveillance with CCTV and prevent accidents through continuous patrol. These are the most basic and the most important requirements in safety. In addition, casinos which prompt gambling are causing economic and psychological treats to families. To resolve these social issues, casinos have adopted limited entrance system. To support this system, new forms of machine security systems such as video automatic recognition system of fingerprint pattern recognition system should be adopted too. In addition, security guards in casino facilities need to instill themselves with a sense of ownership as well as a strong sense of mission to do the best for customer security and to protect the company assets and employees and manage accidents that could occur without notice. Security guards should do their best to enable manage accidents that could occur without notice. Security guards should do their best to enable tourists who are on the rise due to increase in advanced country-style tourism and leisurely activities to get the utmost satisfaction from the casinos, and as a leader of private security company, establish the foundation for security based on the characteristics of security in Korea.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.2
• /
• pp.149-162
• /
• 2005

This paper suggest a way to detect a specific wanted figure in public places such as subway stations and banks by comparing color face images extracted from the real time CCTV with the face images of designated specific figures. Assuming that the characteristic of the surveillance camera allows the face information in screens to change arbitrarily and to contain information on numerous faces, the accurate detection of the face area was focused. To solve this problem, the normalization work using subsampling with $20{\times}20$ pixels on arbitrary face images, which is based on the Perceptron Neural Network model suggested by R. Rosenblatt, created the effect of recogning the whole face. The optimal linear filter and the histogram shaper technique were employed to minimize the outside interference such as lightings and light. The addition operation of the egg-shaped masks was added to the pre-treatment process to minimize unnecessary work. The images finished with the pre-treatment process were divided into three reception fields and the information on the specific location of eyes, nose, and mouths was determined through the neural network. Furthermore, the precision of results was improved by constructing the three single-set network system with different initial values in a row.

• Journal of Korea Water Resources Association
• /
• v.37 no.3
• /
• pp.195-206
• /
• 2004

One of the main factors which reduces the efficiency of a sewage treatment plant is the Inflow/Infiltration(Ⅰ/Ⅰ) in the sewer First we must calculate the quantity of Ⅰ/Ⅰ via the investigation of each sewer to establish the reduction plan of Ⅰ/Ⅰ. However, in Korea, we apply the results of a surveyed sample to the entire study area to establish the reduction plan of Ⅰ/Ⅰ. This methodology just considers the total Ⅰ/Ⅰ for the entire study area but it does not consider the quantity of Ⅰ/Ⅰ for the individual sewer systems. Therefore, we may need the model to consider the Ⅰ/Ⅰ in the individual sewer systems and we develop the model to calculate the Ⅰ/Ⅰ that happen in urban sewer systems. We estimate the Ⅰ/Ⅰ of individual systems by the developed model and the estimated Ⅰ/Ⅰ are utilized as the basic data for the establishment of Ⅰ/Ⅰ reduction plan. The observed Ⅰ/Ⅰ for the entire study area is distributed into the individual sewer systems according to their defect states. Here, the weights of defect elements are calculated using AHP(Analytic Hierarchy Process) and we perform the uncertainty analysis for considering the errors using MCS(Monte Carlo Simulation).

• Journal of the Korean Association of Geographic Information Studies
• /
• v.24 no.1
• /
• pp.54-67
• /
• 2021

At present, CPTED projects are showing an effect such as reducing the anxiety of residents from crimes and improving the criminal environment about crimes through crime prevention. However, most of the CPTED programs have been implemented mainly to improve the physical environment without verifying systematically and empirically on the relationship between the program and improving the quality of life of residents and satisfaction level of residents etc. Accordingly, the objective of this study is to grope for a plan to apply CPTED to urban regeneration for improvement in the safety and life quality of residents using AHP and Visualizing The Mental Map. For this, We selected four case areas in Busan and then analyzed the dead zones of CPTED programs by visualizing the mental maps and heat maps of residents for case districts. As a result of evaluating the priority of CPTED program, installation of CCTVs and streetlights for prevention of crimes was found to be the most important elements. Result of analyzing mental map, the existing crime prevention facilities and CPTED programs were found to have resolved most of physical disorder. However, it showed that, for psychological factors which the residents feel such as social disorder, a number of dead zones exist.

• Smart Media Journal
• /
• v.13 no.2
• /
• pp.68-84
• /
• 2024

This paper describes the development of a system and algorithms for high-quality welfare services by recognizing behavior development indicators (activity, sociability, danger) in children aged 0 to 2 years old using action recognition technology. Action recognition targeted 11 behaviors from lying down in 0-year-olds to jumping in 2-year-olds, using data directly obtained from actual videos provided for research purposes by three nurseries in the Gwangju and Jeonnam regions. A dataset of 1,867 actions from 425 clip videos was built for these 11 behaviors, achieving an average recognition accuracy of 97.4%. Additionally, for real-world application, the Edge Video Analyzer (EVA), a behavior analysis device, was developed and implemented with a region-specific random frame selection-based PoseC3D algorithm, capable of recognizing actions in real-time for up to 30 people in four-channel videos. The developed system was installed in three nurseries, tested by ten childcare teachers over a month, and evaluated through surveys, resulting in a perceived accuracy of 91 points and a service satisfaction score of 94 points.

• Journal of Intelligence and Information Systems
• /
• v.26 no.2
• /
• pp.131-145
• /
• 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 Digital Convergence
• /
• v.10 no.10
• /
• pp.333-338
• /
• 2012

Human resource management is bringing the various changes with the IT technology. In particular, if HRM is non-scientific method such as group management, physical plant, working hours constraints, personal contacts, etc, the current enterprise human resources management(e-HRM) appeared in the individual dimension management, virtual workspace (for example: smart work center, home work, etc.), working time flexibility and elasticity, computer-based statistical data and the scientific method of analysis and management has been a big difference in the sense. Therefore, depending on changes in the environment, companies have introduced a variety of techniques as RFID card, fingerprint time & attendance systems in order to build more efficient and strategic human resource management system. In this paper, time and attendance, access control management system was developed using multi camera for 2D and 3D face recognition technology-based for efficient enterprise human resource management. We had an issue with existing 2D-style face-recognition technology for lighting and the attitude, and got more than 90% recognition rate against the poor readability. In addition, 3D face recognition has computational complexities, so we could improve hybrid video recognition and the speed using 3D and 2D in parallel.

• KIPS Transactions on Computer and Communication Systems
• /
• v.5 no.10
• /
• pp.347-352
• /
• 2016

Recently, IoT technology has been applied in various field. In particular, the technology focuses on analysing large amount of data that has been gathered from the environmental sensors, to provide valuable information. This technique has been actively researched in the agro-industrial sector. Many researches are underway in the monitoring and control for growth crop environment in agro-industrial. Normally, the average weather data is provided by the manual agro-control method but the value may differ due to the different region's weather and environment that may cause problem in the disease and insect-pest prevention. In order to develop a suitable integrated system for fruit tree, all the necessary information is obtained from the Jeollanam-do province, which has the high production rate in the Korea. In this paper, we propose an integrated support platform for the growing crops, to minimize the damage caused due to the weather disaster through image analysis, forecasting models, by using the micro-climate weather information collection and CCTV. The fruit tree damage caused by the weather disaster are controlled by utilizing various IoT technology by maintaining the growth environment, which helps in the disease and insect-pest prevention and also helps farmers to improve the expected production.

• Journal of Korean Society of Transportation
• /
• v.20 no.3
• /
• pp.17-30
• /
• 2002

Incident duration prediction is one of the most important steps of the overall incident management process. An accurate and reliable estimate of the incident duration can be the main difference between an effective incident management operation and an unacceptable one since, without the knowledge of such time durations, traffic impact can not be estimated or calculated. This research presents several multiple linear regression models for incident duration prediction using data consisting of 384 incident cases. The main source of various incident cases was the Traffic Incident Reports filled out by the Motorist Assistant Units of the Korea Highway Corporation. The models were proposed separately according to the time of day(daytime vs. nighttime) and the fatality/injury incurred (fatality/injury vs. property damage only). Two models using an integrated dataset, one with an intercept and the other without it, were also calibrated and proposed for the generality of model application. Some findings are as follows ; ?Variables such as vehicle turnover, load spills, the number of heavy vehicles involved and the number of blocked lanes were found to significantly affect incident duration times. ?Models, however, tend to overestimate the duration times when a dummy variable, load spill, is used. It was simply because several of load spill incidents had excessively long clearance times. The precision was improved when load spills were further categorized into "small spills" and "large spills" based on the size of vehicles involved. ?Variables such as the number of vehicles involved and the number of blocked lanes found not significant when a regression model was calibrated with an intercept. whereas excluding the intercept from the model structure signifies those variables in a statistical sense.