• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2014년도 추계 학술논문 발표대회
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• pp.88-89
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• 2014

A vector-photo is a photography which contain image and 5W1H information. Objects pictured and an image in a vector-photo can be linked by 5W1H information in the vector-photo. This study discuss a positioning module to link between vector-photos and 3D BIM model. The module developed in this study can be utilized in a system that can link the vector-photos with objects in BIM model.

• 전기학회논문지
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• 제66권7호
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• pp.1092-1099
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• 2017

This paper proposes a novel way of vehicle detection and classification based on image features. There are two main processes in the proposed system, which are database construction and vehicle classification processes. In the database construction, there is a tight censorship for choosing appropriate images of the training set under the rigorous standard. These images are trained using Haar features for vehicle detection and histogram of oriented gradients extraction for vehicle classification based on the support vector machine. Additionally, in the vehicle detection and classification processes, the region of interest is reset using a number plate to reduce complexity. In the experimental results, the proposed system had the accuracy of 0.9776 and the $F_1$ score of 0.9327 for vehicle classification.

• 드라이브 ㆍ 컨트롤
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• 제19권3호
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• pp.16-22
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• 2022

Crushers are equipment that crush natural stones, to produce aggregates used at construction sites. As the crusher proceeds, the inner liner becomes worn, causing the size of the aggregate produced to gradually increase. The vision sensor-based aggregate analysis system analyzes the size and distribution of aggregates in production, in real time through image analysis. This study developed an algorithm that can segmentate aggregates in images in real time. using image preprocessing technology combining various filters and morphology techniques, and aggregate region characteristics such as convex hull and concave hull. We applied the developed algorithm to fine aggregate, intermediate aggregate, and thick aggregate images to verify their performance.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2022년도 봄 학술논문 발표대회
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• pp.73-74
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• 2022

Concrete structures occupy the largest proportion of modern infrastructure, and concrete structures often have cracking problems. Existing concrete crack diagnosis methods have limitations in crack evaluation because they rely on expert visual inspection. Therefore, in this study, we design a deep learning model that detects, visualizes, and outputs cracks on the surface of RC structures based on image data by using a CNN (Convolution Neural Networks) model that can process two- and three-dimensional data such as video and image data. do. An experimental study was conducted on an algorithm to automatically detect concrete cracks and visualize them using a CNN model. For the three deep learning models used for algorithm learning in this study, the concrete crack prediction accuracy satisfies 90%, and in particular, the 'InceptionV3'-based CNN model showed the highest accuracy. In the case of the crack detection visualization model, it showed high crack detection prediction accuracy of more than 95% on average for data with crack width of 0.2 mm or more.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.411-412
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• 2023

The purpose of this research and development is to develop a structure module that improves the efficiency and constructability of the layout structure as well as the design development of rainwater permeable storage tank blocks using inorganic binders and aggregates with the aim of reducing greenhouse gas (CO₂) with eco-friendly materials. In addition, for the efficient response to flooding of the developed permeable storage structure, we present a technical solution for combining drone mapping technology and flood monitoring technology that can analyze topographical factors in detail.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2023년도 봄 학술논문 발표대회
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• pp.331-332
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• 2023

With the aging of buildings, the number and importance of regular inspections of buildings are increasing. The current safety inspection goes through a procedure in which a skilled technician visits an old building, visually checks it, takes a photo, and finally organizes and judges it at the office. For this, field personnel and analysis and review personnel are required. Since the inspection procedure includes taking pictures, a huge amount of data has been accumulated from the time digital photos were used to the present. When a model that can check cracks outside a building is developed using these data, manpower and time required can be greatly reduced. Therefore, this study aims to create a model for classifying cracks that occur outside the building through the artificial intelligence method. The created model can be used as a basic model for determining cracks only by external photography in the future, and furthermore, it can be used as basic data for calculating the size and width of cracks.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2015년도 춘계 학술논문 발표대회
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• pp.17-18
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• 2015

In manufacturing industry, image scanning technique has made enormous progress in past decades. 3D models have been also very important to continuously monitor the related spatial information for freeform buildings. The process of shape making of 3D scanning is as follows: mesh surface segmentation, NURBS surface generation, and parametric solid model generation. We will review the process and applying process. Especially in the construction industry, 3D data collection by laser scanning has become an high quality 3D models. Therefore, in this research, we have an effort to review construction of reverse design process for freeform envelope using 3D scanning. The technology enables many 3D shape engineering and design parameterization of reverse engineering in the construction site.

• 한국건축시공학회:학술대회논문집
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• 한국건축시공학회 2014년도 추계 학술논문 발표대회
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• pp.100-101
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• 2014

The generation of 3D models for freeform buildings is an important task while continuous monitoring of the related spatial information at different time phases. Realistic models of freeform building have to provide high geometric accuracy and detail at an effective data size.(Al-kheder, S. 2008) The efficiency of this image-based technique has been increased considerably by the development of digital technologies. Furthermore, 3D data collection based on laser scanning has become an high quality 3D models for construction site. Therefore, in this research, we have an effort to review construction methods to make freeform envelope of building using 3D scanning technology.

• 국제초고층학회논문집
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• 제9권4호
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• pp.335-342
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• 2020

This article comes up with a new method which is based on the visual characteristic of the objects and machine learning technology to achieve semi-automated recognition of the personnel, machine & materials of the construction sites. Balancing the real-time performance and accuracy, using Faster RCNN (Faster Region-based Convolutional Neural Networks) with transfer learning method appears to be a rational choice. After fine-tuning an ImageNet pre-trained Faster RCNN and testing with it, the result shows that the precision ratio (mAP) has so far reached 67.62%, while the recall ratio (AR) has reached 56.23%. In other word, this recognizing method has achieved rational performance. Further inference with the video of the construction of Huoshenshan Hospital also indicates preliminary success.

• 드라이브 ㆍ 컨트롤
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• 제17권4호
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• pp.8-14
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• 2020

Intelligent devices using ICT technology have been introduced in the field of construction machinery to improve productivity and stability. Among the intelligent devices, Machine Guidance is a device that provides real-time posture, location, and work range to drivers by installing various sensors, controllers, and satellite navigation systems on construction machines. Conversely, the efficiency of equipment that requires location information, such as machine guidance, will be greatly reduced in buildings, and tunnels in the GPS blind spots. Thus, the other high-precision positioning technologies are required in the GPS blind spot zone. In this study, we will develop a relative position measurement system that provides precise location information such as construction machinery and robots in a local area where the GPS reception is difficult. A relative position measurement system tracks a marker in the form of a sphere installed on a vehicle by using the image base tracking technology, and measures the distance and direction information to the marker to calculate a position.