• Title/Summary/Keyword: 인공지능CCTV

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Design of Video Pre-processing Algorithm for High-speed Processing of Maritime Object Detection System and Deep Learning based Integrated System (해상 객체 검출 고속 처리를 위한 영상 전처리 알고리즘 설계와 딥러닝 기반의 통합 시스템)

  • Song, Hyun-hak;Lee, Hyo-chan;Lee, Sung-ju;Jeon, Ho-seok;Im, Tae-ho
    • Journal of Internet Computing and Services
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    • v.21 no.4
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    • pp.117-126
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    • 2020
  • A maritime object detection system is an intelligent assistance system to maritime autonomous surface ship(MASS). It detects automatically floating debris, which has a clash risk with objects in the surrounding water and used to be checked by a captain with a naked eye, at a similar level of accuracy to the human check method. It is used to detect objects around a ship. In the past, they were detected with information gathered from radars or sonar devices. With the development of artificial intelligence technology, intelligent CCTV installed in a ship are used to detect various types of floating debris on the course of sailing. If the speed of processing video data slows down due to the various requirements and complexity of MASS, however, there is no guarantee for safety as well as smooth service support. Trying to solve this issue, this study conducted research on the minimization of computation volumes for video data and the increased speed of data processing to detect maritime objects. Unlike previous studies that used the Hough transform algorithm to find the horizon and secure the areas of interest for the concerned objects, the present study proposed a new method of optimizing a binarization algorithm and finding areas whose locations were similar to actual objects in order to improve the speed. A maritime object detection system was materialized based on deep learning CNN to demonstrate the usefulness of the proposed method and assess the performance of the algorithm. The proposed algorithm performed at a speed that was 4 times faster than the old method while keeping the detection accuracy of the old method.

Effective machine learning-based haze removal technique using haze-related features (안개관련 특징을 이용한 효과적인 머신러닝 기반 안개제거 기법)

  • Lee, Ju-Hee;Kang, Bong-Soon
    • Journal of IKEEE
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    • v.25 no.1
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    • pp.83-87
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    • 2021
  • In harsh environments such as fog or fine dust, the cameras' detection ability for object recognition may significantly decrease. In order to accurately obtain important information even in bad weather, fog removal algorithms are necessarily required. Research has been conducted in various ways, such as computer vision/data-based fog removal technology. In those techniques, estimating the amount of fog through the input image's depth information is an important procedure. In this paper, a linear model is presented under the assumption that the image dark channel dictionary, saturation ∗ value, and sharpness characteristics are linearly related to depth information. The proposed method of haze removal through a linear model shows the superiority of algorithm performance in quantitative numerical evaluation.

Design of an Visitor Identification system for the Front Door of an Apartment using Deep learning (딥러닝 기반 이용한 공동주택현관문의 출입자 식별 시스템 설계)

  • Lee, Min-Hye;Mun, Hyung-Jin
    • Journal of the Korea Convergence Society
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    • v.13 no.4
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    • pp.45-51
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    • 2022
  • Fear of contact exists due to the prevention of the spread of infectious diseases such as COVID-19. When using the common entrance door of an apartment, access is possible only if the resident enters a password or obtains the resident's permission. There is the inconvenience of having to manually enter the number and password for the common entrance door to enter. Also, contactless entry is required due to COVID-19. Due to the development of ICT, users can be easily identified through the development of face recognition and voice recognition technology. The proposed method detects a visitor's face through a CCTV or camera attached to the common entrance door, recognizes the face, and identifies it as a registered resident. Then, based on the registered information of the resident, it is possible to operate without contact by interworking with the elevator on the server. In particular, if face recognition fails with a hat or mask, the visitor is identified by voice or additional authentication of the visitor is performed based on the voice message. It is possible to block the spread of contagiousness without leaving any contactless function and fingerprint information when entering and exiting the front door of an apartment house, and without the inconvenience of access.

Estimation of Incident Detection Time on Expressways Based on Market Penetration Rate of Connected Vehicles (커넥티드 차량 보급률 기반 고속도로 돌발상황 검지시간 추정)

  • Sanggi Nam;Younshik Chung;Hoekyoung Kim;Wonggil Kim
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.38-50
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    • 2023
  • Recent advances in artificial intelligence (AI) technology have enabled the integration of AI technology into image sensors, such as Closed-Circuit Television (CCTV), to detect specific traffic incidents. However, most incident detection methods have been carried out using fixed equipment. Therefore, there have been limitations to incident detection for all roadways. Nevertheless, the development of mobile image collection and analysis technology, such as image sensors and edge-computing, is spreading. The purpose of this study is to estimate the reducing effect of the incident detection time according to the introduction level of mobile image collection and analysis equipment (or connected vehicles). To carry out this purpose, we utilized data on the number of incidents collected by the Suwon branch of the Gyeongbu expressway in 2021. The analysis results showed that if the market penetration rate (MPR) of connected vehicles is 4% or higher for two-lane expressway and 3% or higher for three-lane expressways, the incident detection time was less than one minute. Furthermore, if the MPR is 0.4% or higher for two-lane expressways and 0.2% or higher for three-lane expressways, the incident detection time decreased compared to the average incident detection time announced by the Korea Expressway Corporation for both two-lane and three-lane expressways.

Abnormal Behavior Pattern Identifications of One-person Households using Audio, Vision, and Dust Sensors (음성, 영상, 먼지 센서를 활용한 1인 가구 이상 행동 패턴 탐지)

  • Kim, Si-won;Ahn, Jun-ho
    • Journal of Internet Computing and Services
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    • v.20 no.6
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    • pp.95-103
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    • 2019
  • The number of one person households has grown steadily over the recent past and the population of lonely and unnoticed death are also observed. The phenomenon of one person households has been occurred. In the dark side of society, the remarkable number of lonely and unnoticed death are reported among different age-groups. We propose an unusual event detection method which may give a remarkable solution to reduce the number of the death rete for people dying alone and remaining undiscovered for a long period of time. The unusual event detection method we suggested to identify abnormal user behavior in their lives using vision pattern, audio pattern, and dust pattern algorithms. Individually proposed pattern algorithms have disadvantages of not being able to detect when they leave the coverage area. We utilized a fusion method to improve the accuracy performance of each pattern algorithm and evaluated the technique with multiple user behavior patterns in indoor areas.

IoT industrial site safety management system incorporating AI (AI를 접목한 IoT 기반 산업현장 안전관리 시스템)

  • Lee, Seul;Jo, So-Young;Yeo, Seung-Yeon;Lee, Hee-Soo;Kim, Sung-Wook
    • Proceedings of the Korea Information Processing Society Conference
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    • 2022.05a
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    • pp.118-121
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    • 2022
  • 국내 산업재해 사고 사망자의 상당수가 건설업에서 발생하고 있다. 건설 현장에는 굴삭기, 크레인과 같은 중장비가 많고 높은 곳에서 작업하는 경우가 흔해 위험 요소에 노출될 가능성이 높다. 물리적 사고 외에도 작업 중 발생하는 미세먼지에는 여러 유해 인자가 존재하여 건설근로자들에게 호흡기질환과 같은 직업병을 유발한다. 정부에서는 산업현장 안전 관리의 중요성이 증가함에 따라 각종 산업재해로부터 근로자를 보호하기 위한 법안을 마련하였다. 따라서 건설 현장의 경우 산업재해를 방지하기 위해서 위험요소를 사전에 인지하고 즉각 대응할 수 있는 기술이 필요하다. 본 연구에서는 인공지능(AI)과 사물인터넷(IoT)을 통한 자동화 기술을 활용하여 24시간 안전 관리 시스템을 제안한다. 제안하는 IoT 기반 통합안전 관리 시스템은 AI를 적용한 CCTV를 통해 산업 현장을 모니터링하고, 다수의 IoT 센서가 측정한 수치를 근로자 및 관리자가 실시간으로 확인할 수 있게 하여 산업 현장 내 안전사고를 예방한다. 구체적으로 어플리케이션을 통해 미세먼지 농도, 가스 농도, 온도, 습도, 안전모 착용 여부 등을 모니터링할 수 있다. 모니터링 중에 유해물질의 농도가 일정 수치를 넘기거나 안전모를 착용하지 않은 근로자가 발견될 경우 근로자 및 관리자에게 경고 알림을 발송한다. 유해물질 농도는 IoT 센서를 통해 측정하며 안전모 착용 여부는 카메라 센서에 딥러닝 모델을 적용하여 인식하였다. 본 연구에서 제시한 통합안전관리시스템을 통해 건설현장을 비롯한 산업현장의 산업재해 감소와 근로자 안전 증진에 기여할 수 있을 것으로 기대한다.

A Study on Establishing Scientific Guard Systems based on TVWS (TVWS 기반 과학화경계시스템 구축방안 연구)

  • Kyuyong Shin;Yuseok Kim;Seungwon Baik
    • Convergence Security Journal
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    • v.23 no.4
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    • pp.81-92
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    • 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.

A Study on the Concept and User Perception of Smart Park - Focused on the IoT See Park Users in Daegu City - (스마트공원 개념 정립 및 공원 이용자 인식에 관한 연구 - 대구 IoT See 시범사업 공원 이용자를 대상으로 -)

  • Lee, Hyung-Sook;Min, Byoung-Wook;Yang, Tae-Jin;Eum, Jeong-Hee;Kim, Kwon;Lee, Ju-Yong
    • Journal of the Korean Institute of Landscape Architecture
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    • v.47 no.5
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    • pp.41-48
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    • 2019
  • Our daily lives are changing at a rapid pace and the concept of smart city is spreading, as the information communication technologies apply to various fields. However, efforts to prepare for changes in society due to technological evolution are insufficient in the field of landscape architecture. The purposes of this study are to explore the concept of smart parks, to investigate how smart technology has been applied to parks, and to identify the users' perception and satisfaction on smart park services. To this end, we conducted literature review, focus group interviews with experts, and a questionnaire survey with 180 users of the IoT See pilot smart park in Daegu. Smart parks can, as a result, be defined as sustainable parks that improve users' experience in parks and solve social and environmental problems faced by utilizing various high technology. Smart technologies introduced at the park so far have been mostly focused on safety and environmental areas, including AI CCTV, smart street lamp, and fine dust warning devices. The results of survey showed that not many users were aware of the smart services the park provided due to the lack of public communication as well as the nature of maintenance-oriented smart services. The survey also found that AR services for the education of historic parks were the least utilized, while solar power benches and WiFi service were most preferred by the park users. In conclusion, smart technologies need to be integrated with diverse park contents more centered user needs, providing services to enhance safety and environmental management in order to develop user-oriented smart parks.