• 제목/요약/키워드: vision-based monitoring

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GCP Placement Methods for Improving the Accuracy of Shoreline Extraction in Coastal Video Monitoring

  • Changyul Lee;Kideok Do;Inho Kim;Sungyeol Chang
    • Journal of Ocean Engineering and Technology
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    • v.38 no.4
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    • pp.174-186
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    • 2024
  • In coastal video monitoring, the direct linear transform (DLT) method with ground control points (GCPs) is commonly used for geo-rectification. However, current practices often overlook the impact of GCP quantity, arrangement, and the geographical characteristics of beaches. To address this, we designed scenarios at Chuam Beach to evaluate how factors such as the distance from the camera to GCPs, the number of GCPs, and the height of each point affect the DLT method. Accuracy was assessed by calculating the root mean square error of the distance errors between the actual GCP coordinates and the image coordinates for each setting. This analysis aims to propose an optimal GCP placement method. Our results show that placing GCPs within 200 m of the camera ensures high accuracy with few points, whereas positioning them at strategic heights enhances shoreline extraction. However, since only fixed cameras were used in this study, factors like varying heights, orientations, and resolutions could not be considered. Based on data from a single location, we propose an optimal method for GCP placement that takes into account distance, number, and height using the DLT method.

Target-free vision-based approach for vibration measurement and damage identification of truss bridges

  • Dong Tan;Zhenghao Ding;Jun Li;Hong Hao
    • Smart Structures and Systems
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    • v.31 no.4
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    • pp.421-436
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    • 2023
  • This paper presents a vibration displacement measurement and damage identification method for a space truss structure from its vibration videos. Features from Accelerated Segment Test (FAST) algorithm is combined with adaptive threshold strategy to detect the feature points of high quality within the Region of Interest (ROI), around each node of the truss structure. Then these points are tracked by Kanade-Lucas-Tomasi (KLT) algorithm along the video frame sequences to obtain the vibration displacement time histories. For some cases with the image plane not parallel to the truss structural plane, the scale factors cannot be applied directly. Therefore, these videos are processed with homography transformation. After scale factor adaptation, tracking results are expressed in physical units and compared with ground truth data. The main operational frequencies and the corresponding mode shapes are identified by using Subspace Stochastic Identification (SSI) from the obtained vibration displacement responses and compared with ground truth data. Structural damages are quantified by elemental stiffness reductions. A Bayesian inference-based objective function is constructed based on natural frequencies to identify the damage by model updating. The Success-History based Adaptive Differential Evolution with Linear Population Size Reduction (L-SHADE) is applied to minimise the objective function by tuning the damage parameter of each element. The locations and severities of damage in each case are then identified. The accuracy and effectiveness are verified by comparison of the identified results with the ground truth data.

Deep learning of sweep signal for damage detection on the surface of concrete

  • Gao Shanga;Jun Chen
    • Computers and Concrete
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    • v.32 no.5
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    • pp.475-486
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    • 2023
  • Nondestructive evaluation (NDE) is an important task of civil engineering structure monitoring and inspection, but minor damage such as small cracks in local structure is difficult to observe. If cracks continued expansion may cause partial or even overall damage to the structure. Therefore, monitoring and detecting the structure in the early stage of crack propagation is important. The crack detection technology based on machine vision has been widely studied, but there are still some problems such as bad recognition effect for small cracks. In this paper, we proposed a deep learning method based on sweep signals to evaluate concrete surface crack with a width less than 1 mm. Two convolutional neural networks (CNNs) are used to analyze the one-dimensional (1D) frequency sweep signal and the two-dimensional (2D) time-frequency image, respectively, and the probability value of average damage (ADPV) is proposed to evaluate the minor damage of structural. Finally, we use the standard deviation of energy ratio change (ERVSD) and infrared thermography (IRT) to compare with ADPV to verify the effectiveness of the method proposed in this paper. The experiment results show that the method proposed in this paper can effectively predict whether the concrete surface is damaged and the severity of damage.

Development of a LonRF Intelligent Device-based Ubiquitous Home Network Testbed (LonRF 지능형 디바이스 기반의 유비쿼터스 홈네트워크 테스트베드 개발)

  • 이병복;박애순;김대식;노광현
    • Journal of Institute of Control, Robotics and Systems
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    • v.10 no.6
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    • pp.566-573
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    • 2004
  • This paper describes the ubiquitous home network (uHome-net) testbed and LonRF intelligent devices based on LonWorks technology. These devices consist of Neuron Chip, RF transceiver, sensor, and other peripheral components. Using LonRF devices, a home control network can be simplified and most devices can be operated on LonWorks control network. Also, Indoor Positioning System (IPS) that can serve various location based services was implemented in uHome-net. Smart Badge of IPS, that is a special LonRF device, can measure the 3D location of objects in the indoor environment. In the uHome-net testbed, remote control service, cooking help service, wireless remote metering service, baby monitoring service and security & fire prevention service were realized. This research shows the vision of the ubiquitous home network that will be emerged in the near future.

Online Monitoring System based notifications on Mobile devices with Kinect V2 (키넥트와 모바일 장치 알림 기반 온라인 모니터링 시스템)

  • Niyonsaba, Eric;Jang, Jong-Wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.20 no.6
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    • pp.1183-1188
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    • 2016
  • Kinect sensor version 2 is a kind of camera released by Microsoft as a computer vision and a natural user interface for game consoles like Xbox one. It allows acquiring color images, depth images, audio input and skeletal data with a high frame rate. In this paper, using depth image, we present a surveillance system of a certain area within Kinect's field of view. With computer vision library(Emgu CV), if an object is detected in the target area, it is tracked and kinect camera takes RGB image to send it in database server. Therefore, a mobile application on android platform was developed in order to notify the user that Kinect has sensed strange motion in the target region and display the RGB image of the scene. User gets the notification in real-time to react in the best way in the case of valuable things in monitored area or other cases related to a reserved zone.

Network vision of disaster prevention management for seashore reclaimed u-City (해안매립 신도시의 재해 예방관리 네트워크 비젼)

  • Ahn, Sang-Ro
    • Proceedings of the Korean Geotechical Society Conference
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    • 2009.09a
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    • pp.117-129
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    • 2009
  • This paper studied the safety management network system of infrastructure which constructed smart sensors, closed-circuit television(CCTV) and monitoring system. This safety management of infrastructure applied to bridge, cut slop and tunnel, embankment etc. The system applied to technologies of standardization guidelines, data acquirement technologies, data analysis and judgment technologies, system integration setup technology, and IT technologies. It was constructed safety management network system of various infrastructure to improve efficient management and operation for many infrastructure. Integrated safety management network system of infrastructure consisted of the real-time structural health monitoring system of each infrastructure, integrated control center, measured data transmission using i of tet web-based, collecting data using sf ver, early alarm system which the dangerous event of infrastructure occurred. Integrated control center consisted of conference room, control room to manage and analysis the data, server room to present the measured data and to collect the raw data. Early alarm system proposed realization of warning and response within 5 minute or less through development of sensor-based progress report and propagation automation system using the media such as MMS, VMS, EMS, FMS, SMS and web services of report and propagation. Based on this, the most effective u-Infrastructure Safety Management System is expected to be stably established at a less cost, thus making people's life more comfortable. Information obtained from such systems could be useful for maintenance or structural safety evaluation of existing structures, rapid evaluation of conditions of damaged structures after an earthquake, estimation of residual life of structures, repair and retrofitting of structures, maintenance, management or rehabilitation of historical structures.

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Automated Training Database Development through Image Web Crawling for Construction Site Monitoring (건설현장 영상 분석을 위한 웹 크롤링 기반 학습 데이터베이스 구축 자동화)

  • Hwang, Jeongbin;Kim, Jinwoo;Chi, Seokho;Seo, JoonOh
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.39 no.6
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    • pp.887-892
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    • 2019
  • Many researchers have developed a series of vision-based technologies to monitor construction sites automatically. To achieve high performance of vision-based technologies, it is essential to build a large amount and high quality of training image database (DB). To do that, researchers usually visit construction sites, install cameras at the jobsites, and collect images for training DB. However, such human and site-dependent approach requires a huge amount of time and costs, and it would be difficult to represent a range of characteristics of different construction sites and resources. To address these problems, this paper proposes a framework that automatically constructs a training image DB using web crawling techniques. For the validation, the authors conducted two different experiments with the automatically generated DB: construction work type classification and equipment classification. The results showed that the method could successfully build the training image DB for the two classification problems, and the findings of this study can be used to reduce the time and efforts for developing a vision-based technology on construction sites.

A Study of the Shaft Power Measuring System Using Cameras (카메라를 이용한 축계 비틀림 계측 장치 개발)

  • Jeong, Jeong-Soon;Kim, Young-Bok;Choi, Myung-Soo
    • Journal of Ocean Engineering and Technology
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    • v.24 no.4
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    • pp.72-77
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    • 2010
  • This paper presents a method for measuring the shaft power of a marine main engine. Usually, in traditional systems for measuring shaft power, a strain gauge is used even though it has several disadvantages. First, it is difficult to set up the strain gauge on the shaft and acquire the correct signal for analysis. Second, it is very expensive and complicated. For these reasons, we investigated alternative approaches for measuring shaft power and proposed a new method that uses a vision-based measurement system. For this study, templates for image processing and CCD cameras were installed at the both ends of the shaft. Then, in order for the cameras to capture the images synchronously, we used a trigger mark and a optical sensor. The position of each template between the first and the second camera images were compared to calculate the torsion angle. The proposed measurement system can be installed more easily than traditional measurement systems and is suitable for any shaft because it does not contact the shaft. With this approach, it is possible to measure the shaft power while a ship is operating.

A study on the creation of mission performance data using search drone images (수색용 드론 이미지를 활용한 임무수행 데이터 생성에 관한 연구)

  • Lee, Sang-Beom;Lim, Jin-Taek
    • Journal of the Institute of Convergence Signal Processing
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    • v.22 no.4
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    • pp.179-184
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    • 2021
  • Along with the development of the fourth industry, the public sector has increasingly paid more attention to search using drones and real-time monitoring, for various goals. The drones are used and researched to complete a variety of searching and monitoring missions, including search for missing persons, security, coastal patrol and monitoring, speed enforcement, highway and urban traffic monitoring, fire and wildfire monitoring, monitoring of illegal fishing in reservoirs and protest rally monitoring. Police stations, fire departments and military authorities, however, concentrate on the hardware part, so there are little research on efficient communication systems for the real-time monitoring of data collected from high-performance resolution and infrared thermal imagining cameras, and analysis programs suitable for special missions. In order to increase the efficiency of drones with the searching mission, this paper, therefore, attempts to propose an image analysis technique to increase the precision of search by producing image data suitable for searching missions, based on images obtained from drones and provide the foundation for improving relevant policies and establishing proper platforms, based on actual field cases and experiments.

Design and Implementation of Real time Monitoring System based on Web camera for safe agricultural product management (안전한 농산물 관리를 위한 웹 카메라 기반의 실시간 모니터링 시스템의 설계 및 구현)

  • Kim Tak-Chen;Ryu Kwang-Hee;Jung Hoe-Kyung
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.10 no.8
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    • pp.1366-1372
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    • 2006
  • After the import liberalization of agricultural products, The Imported agricultural products rapidly increased market share of domestic agricultural products. But Imported agricultural products include various agricultural chemicals and food additives. In order to improve competitiveness in domestic markets of farmhouses and to secure food safety, the farmers needs to introduce Systematic support and various system. In this paper, established system that use Monitoring technology, to inform production information and management information about agricultural products to consumer by real time. Therefore unused analog camera such as CCTV(Closed-Circuit Television) for real time Monitoring. This system Used web camera that offer picture quality that is good than CCTV at place that consists network without distinction in the place. An advantage of real time Monitoring system designed multi-vision interface showing multi images on single screen and, for the purpose of the improvement in efficiency, the functions of saving images and of scheduling the time to save the images.