• Journal of the Korea Society of Computer and Information
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• v.27 no.12
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• pp.141-149
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• 2022

In this paper, we propose a design of CCTV enlcosure record management system based on blockchain. Since CCTV video records are transferred to the control center through enclosure, it is very important to manage the enclosure to prevent modulation and damage of the video records. Recently, a smart enclosure monitoring system with real-time remote monitoring and opening and closing state management functions is used to manage CCTV enclosures, but there is a limitation to securing the safety of CCTV video records. The proposed system detect modulated record and recover the record through hash value comparison by distributed stored record in the blockchain. In addition, the integrity verification API is provided to ensure the integrity of enclosure record received by the management server. In order to verify the effectiveness of the system, the integrity verification accuracy and elapsed time were measured through experiments. As a result, the integrity of enclosure record (accuracy: 100%) was confirmed, and it was confirmed that the elapsed time for verification (average: 73 ms) did not affect monitoring.

• Journal of Multimedia Information System
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• v.7 no.3
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• pp.205-214
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• 2020

Crime has become one of the major problems in modern society. Even though visual surveillances through closed-circuit television (CCTV) is extensively used for solving crime, the number of crimes has not decreased. This is because there is insufficient workforce for performing 24-hour surveillance. In addition, CCTV surveillance by humans is not efficient for detecting dangerous situations owing to accuracy issues. In this paper, we propose the autonomous detection of dangerous situations in CCTV scenes using a deep learning model with relational inference. The main feature of the proposed method is that it can simultaneously perform object detection and relational inference to determine the danger of the situations captured by CCTV. This enables us to efficiently classify dangerous situations by inferring the relationship between detected objects (i.e., distance and position). Experimental results demonstrate that the proposed method outperforms existing methods in terms of the accuracy of image classification and the false alarm rate even when object detection accuracy is low.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.12
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• pp.546-554
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• 2019

Typically, closed-circuit television (CCTV) monitoring is mainly used for post-processes (i.e. to provide evidence after an incident has occurred), but by using a streaming video feed, machine-based learning, and advanced image recognition techniques, current technology can be extended to respond to crimes or reports of missing persons in real time. The multi-CCTV cooperation technique developed in this study is a program model that delivers similarity information about a suspect (or moving object) extracted via CCTV at one location and sent to a monitoring agent to track the selected suspect or object when he, she, or it moves out of range to another CCTV camera. To improve the operating efficiency of local government CCTV control centers, we describe here the partial automation of a CCTV control system that currently relies upon monitoring by human agents. We envisage an integrated crime prevention service, which incorporates the cooperative CCTV network suggested in this study and that can easily be experienced by citizens in ways such as determining a precise individual location in real time and providing a crime prevention service linked to smartphones and/or crime prevention/safety information.

• Journal of Advanced Navigation Technology
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• v.16 no.4
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• pp.697-702
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• 2012

With an elevator supply and demand increases, It has been enlarged various requirements for the safety of the elevator. Elevator safety requirements can be the ability to respond to emergencies quickly. Recently, QR code was attached to all elevator for the elevator safety and it is established by law for the Elevator rescue work. And also the elevator system is seeking to utilize more secure elevator with mandatory installation of CCTV and direct call devices. However, CCTV and direct call service is operating on an individual method and it has not been proposed integrated model. In this paper, we propose the safety elevator integration model with CCTV, direct call service and remote control based on smart phone. Using the proposed model, we can be improved the efficiency of maintenance and ability of prompt action in the event of a disaster.

• Journal of the Korea Society of Computer and Information
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• v.28 no.1
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• pp.65-70
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• 2023

In this paper, we propose a CCTV storage space securing model using YOLO v3. CCTV is installed and operated in various parts of society for disasters, disasters and safety such as crime prevention, fire prevention, and monitoring, and the number of CCTV is increasing and the quality of the video quality is improving. Due to this, as the number and size of image files increase, it is difficult to cope with the existing storage space. In order to solve this problem, we propose a model that detects specific objects in CCTV images using YOLO v3 library and deletes unnecessary frames by saving only the corresponding frames, thereby securing storage space by reducing the size of the image file, and thereby Periodic images can be stored and managed. After applying the proposed model, it was confirmed that the average image file size was reduced by 94.9%, and it was confirmed that the storage period was increased by about 20 times compared to before the application of the proposed model.

• The Journal of the Korea institute of electronic communication sciences
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• v.13 no.6
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• pp.1275-1280
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• 2018

We made a smartphone interlocking location tracking streetlight and remote display device to compensate the defect of real time identifiable CCTV streetlights and child safety notification applications. It controls brightness of LED by detecting the surrounding brightness and objects with ultrasonic sensor and illuminance senor. The CCTV receives the location of smartphone by Bluetooth and takes the target of the location. It realizes a wireless transmission system that the video is upload to the tablet PC via WiFi.

• Journal of the Korea Convergence Society
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• v.8 no.3
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• pp.15-22
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• 2017

People generally believe that disaster forecast and warning systems and response systems are well established in the age of cutting edge technology. As a matter of fact, reliable systems to respond to disasters are not properly equipped, as we witnessed the Sewol ferry disaster in 2014. The existing forecast and warning systems are based on sensor information with low efficiency, and image information is only operated by monitoring staff manually. In addition, the interconnection between a warning system and a response system in order to decide how to cope with the recognized disaster is very insufficient. This paper introduces the CCTV based disaster recognition and real time crisis response system composed of the CCTV image recognition engine and the crisis response technique. This system has brought the possibility to overcome the limitations of existing sensor based forecast and warning systems, and to resolve the problems in the absence of monitoring staff when responding to crisis.

• Journal of Advanced Marine Engineering and Technology
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• v.37 no.8
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• pp.918-931
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• 2013

The conventional object tracking techniques using PTZ camera detects object movements by analyzing acquired image. However, this technique requires expensive hardware devices to perform a complex image processing. And it is occasionally hard to detect object movements, if an acquired image is low quality or image acquisition is impossible. In this paper, we proposes a smart security CCTV system applying to wireless sensor network technique based on IEEE 802.15.4 standard to overcome the problems of conventional object tracking technique, which enables to track suspicious objects by detecting object movements and GPS data in sensor node. This system enables an efficient control of PTZ camera to observe a wide area, decreasing image processing complexity. Also, wireless sensor network is implemented using mesh networks to increase the efficiency of installing sensor node.

• Journal of Korean Tunnelling and Underground Space Association
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• v.24 no.3
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• pp.247-262
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• 2022

In domestic tunnels, it is mandatory to install CCTVs in tunnels longer than 200 m which are also recommended by installation of a CCTV-based automatic accident detection system. In general, the CCTVs in the tunnel are installed at a low height as well as near by the moving vehicles due to the spatial limitation of tunnel structure, so a severe perspective effect takes place in the distance of installed CCTV and moving vehicles. Because of this effect, conventional CCTV-based accident detection systems in tunnel are known in general to be very hard to achieve the performance in detection of unexpected accidents such as stop or reversely moving vehicles, person on the road and fires, especially far from 100 m. Therefore, in this study, the region of interest is set up and a new concept of inverse perspective transformation technique is introduced. Since moving vehicles in the transformed image is enlarged proportionally to the distance from CCTV, it is possible to achieve consistency in object detection and identification of actual speed of moving vehicles in distance. To show this aspect, two datasets in the same conditions are composed with the original and the transformed images of CCTV in tunnel, respectively. A comparison of variation of appearance speed and size of moving vehicles in distance are made. Then, the performances of the object detection in distance are compared with respect to the both trained deep-learning models. As a result, the model case with the transformed images are able to achieve consistent performance in object and accident detections in distance even by 200 m.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2023.05a
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• pp.251-252
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• 2023

As technology improves with the 4th industrial revolution, smart construction is becoming a key part of safety management in the architecture and civil engineering. By using object detection technology with CCTV data, construction sites can be managed efficiently. In this study, super resolution technology based on deep learning is proposed to improve the accuracy of object detection in construction sites. As the resolution of a train set data and test set data get higher, the accuracy of object detection model gets better. Therefore, according to the scale of construction sites, different object detection models can be considered.