• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.24 no.5
• /
• pp.183-188
• /
• 2024

Recently, CCTV cameras have been installed not only in crowded streets but also in less frequently traveled alleyways. This is because CCTV increases the arrest rate. The arrest rate directly affects the crime rate, as potential criminals tend to avoid areas with high arrest rates. Therefore, this paper collects public data on CCTV installation locations, arrest rates, and crime rates in various regions, stores the collected data using the Hadoop big data system, and refines and processes the data using appropriate tools. Subsequently, R programming is employed to analyze and visualize the relationship between the number of CCTV installations and crime rates. By leveraging big data correlation analysis techniques, this study evaluates the effectiveness of CCTV installations.

• Korean Journal of Childcare and Education
• /
• v.13 no.6
• /
• pp.43-67
• /
• 2017

Objective: The purpose of this study was to explore the feasibility to utilize image data recorded and accumulated from CCTV at child care centers. Methods: Literature reviews, consultations and workshops with scholars studying child development, legal professionals, and engineers, focus group interviews with professionals working with young children, and surveys targeting parents, directors and teachers were implemented. Results: It was found the big data from CCTV at child care centers can be used to make policies and implement research as a secondary data set after anonymization. Extracting implicit and useful data from images stored on CCTV is technically feasible. Also, it can be legally guaranteed to analyze the data under the condition of acquiring informed consents. Conclusion/Implications: It was likely to utilize image data from CCTV at child care centers as a secondary data set in order for policy development and scholarly purposes, after overcoming obstacles of the budget for additional infrastructures and consents of information holders.

• The Korean Journal of Franchise Management
• /
• v.15 no.4
• /
• pp.49-67
• /
• 2024

Purpose: This study analyzed the effect of ethical aspects of CCTV surveillance, such as Security, Responsibility, and Privacy, on consumers' perceptions of unmanned stores. Research design, data, and methodology: The data were collected from 270 participants through an online survey, which was conducted over seven days from October 7 to 13, 2024, with the assistance of an online survey company. The constructs were developed with Delphi Method. And the collected data were analyzed using Delphi Method, SPSS 26, and SmartPLS 4. Results: According to the results, CCTV Security positively influenced the intention to use unmanned stores through the mediation of CCTV Responsibility and consumer attitude. Additionally, Privacy Concerns moderated the relationship between Security and Responsibility. Conclusion: The results of the study show that marketing strategies that emphasize the ethical aspects of CCTV surveillance in unmanned store operations have a positive effect on consumer perception and behavior. When Security and Responsibility are strengthened, consumers' attitudes toward Unmanned stores are formed more favorably and their intention to use unmanned stores is enhanced. In addition Privacy Concerns act as an important factor that moderates the relationship between Security and Responsibility. Therefore, marketers can improve the performance of unmanned stores by communicating the ethical aspects of CCTV operation.

• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.23 no.4
• /
• pp.462-469
• /
• 2019

According to the survey of Ministry of the Interior and Safety in Korea, The number of public and private CCTV reached over ten million and is still increasing. Also with improving Image Processing Technology, it is possible to obtain diverse information. Recently, various services using CCTV are being provided. Therefore it is necessary to ensure CCTV image integrity. However there is no system to prove events in film yet. In this paper, we suggest system model that can manage, use and authenticate CCTV. This model allows a CCTV film to be verified by other nearby CCTVs' data. This model ensures film's integrity by using blockchain. And also, It addresses privacy problem in CCTV and file size problem in blockchain by using not large film data but much smaller analyzed data.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2022.05a
• /
• pp.498-500
• /
• 2022

CCTV protects people and assets safely by identifying dangerous situations and responding promptly. However, it is difficult to continuously monitor the increasing number of CCTV images. For this reason, there is a need for a device that continuously monitors CCTV images and notifies when abnormal behavior occurs. Recently, many studies using artificial intelligence models for image data analysis have been conducted. This study simultaneously learns spatial and temporal characteristic information between image data to classify various abnormal behaviors that can be observed in CCTV images. As an artificial intelligence model used for learning, we propose a multi-classification deep learning model that combines an end-to-end 3D convolutional neural network(CNN) and ResNet.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.27 no.2
• /
• pp.19-33
• /
• 2024

CCTV for crime prevention is expanding; however, due to the absence of guidelines for determining installation locations, CCTV is being installed in locations unrelated to areas with frequent crime occurrences. In this study, we developed a CCTV Priority Installation Index and applied it in a case study area. The index consists of crime vulnerability and surveillance vulnerability indexes, calculated using machine learning algorithms to predict crime incident counts per grid and the proportion of unmonitored area per grid. We tested the index in a pilot area and found that utilizing the Viewshed function in CCTV visibility analysis resolved the problem of overestimating surveillance area. Furthermore, applying the index to determine CCTV installation locations effectively improved surveillance coverage. Therefore, the CCTV Priority Installation Index can be utilized as an effective decision-making tool for establishing smart and safe cities.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.20 no.5
• /
• pp.195-205
• /
• 2020

Recently, after the 4th industrial revolution era has arrived, technological advances started to develop and these changes have led to widespread use of data. Big data is often used for the safety of citizens, including the administration, safety and security of the country. In order to enhance the efficiency of maintaining such security, it is necessary to understand the installation status of CCTVs. By comparing the installation rate of CCTVs and crime rate in the area, we should analyze and improve the status of CCTV installation status, and crime rate in each area in order to increase the efficiency of security. Therefore, in this paper, big data analytic system based on public data is developed to collect data related to crime rate such as CCTV, female population, entertainment center, etc. and to reduce crime rate through efficient management and installation of CCTV.

• Journal of Digital Convergence
• /
• v.15 no.5
• /
• pp.61-69
• /
• 2017

This study aims to investigate the public big data standard analysis model developed by Ministry of the Interior and examine its accuracy and reliability of prediction. To do this, big data standard analysis index were calculated to apply them to the real world case of CCTV monitoring system prior installation in K city. The result of this case study revealed that the areas to be installed CCTV consisted with the area where residences requested and complained to install CCTV monitoring systems, which indicated that the result of big data standard analysis model provided accurate and reliable outcomes. The result of this study suggested implications on effective exploitation of big data analysis.

• Journal of Digital Contents Society
• /
• v.14 no.4
• /
• pp.447-454
• /
• 2013

As the surveillance CCTVs are increasing every year, big data image processing for the CCTV image data has become a hot issue. In this paper, we propose a Hadoop-based big data image processing technique to recognize a vehicle number from a large amount of automatic number plate images taken from CCTVs. We also implement the vehicle route tracking system that displays the moving path of the searched vehicle on Google Maps with the related information together. In order to evaluate the performance we compare and analysis the vehicle number recognition time for a lot of CCTV image data in Hadoop and the single PC environment.

• Journal of Information Processing Systems
• /
• v.19 no.6
• /
• pp.767-777
• /
• 2023

In modern society, user privacy is emerging as an important issue as closed-circuit television (CCTV) systems increase rapidly in various public and private spaces. If CCTV cameras monitor sensitive areas or personal spaces, they can infringe on personal privacy. Someone's behavior patterns, sensitive information, residence, etc. can be exposed, and if the image data collected from CCTV is not properly protected, there can be a risk of data leakage by hackers or illegal accessors. This paper presents an innovative approach to "machine learning based reversible chaotic masking method for user privacy protection in CCTV environment." The proposed method was developed to protect an individual's identity within CCTV images while maintaining the usefulness of the data for surveillance and analysis purposes. This method utilizes a two-step process for user privacy. First, machine learning models are trained to accurately detect and locate human subjects within the CCTV frame. This model is designed to identify individuals accurately and robustly by leveraging state-of-the-art object detection techniques. When an individual is detected, reversible chaos masking technology is applied. This masking technique uses chaos maps to create complex patterns to hide individual facial features and identifiable characteristics. Above all, the generated mask can be reversibly applied and removed, allowing authorized users to access the original unmasking image.