• International conference on construction engineering and project management
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• 2020.12a
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• pp.485-492
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• 2020

Information on the energy consumption of buildings that can be obtained through conventional methods is limited. Therefore, this study aims to develop a model that can support decision making about building facility management through digital transformation technologies. Through the IoT sensor, the building's energy data and indoor air quality data are collected, and the monitored data is visualized through the ELK Stack and produced as a dashboard. In addition, the target building is photographed with a 360-degree camera and maps using a tool to create a 360-degree tour. Using such digital transformation technologies, users of buildings can obtain various information in real time without visiting buildings directly. This can lead to changes in actions or actions for building management, supporting facility management decisions, and consequently reducing building energy consumption.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.129-136
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• 2008

There is a tremendous need for an effective indoor facility management since the building are tend to be built taller and bigger due to latest technology. Also, information that is continuously used and transferred during the design and construction phase is emerging due to 3D object-oriented CAD. Therefore, a system that will use such information for facility management should be developed. In this study, we have defined a process that will automatically create an spatial network model and also verified the usability by establishing an sample model. As a result, an effective spatial network has been generated and an evacuation path finder was found efficiently.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.7
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• pp.647-654
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• 2016

Indoor localization based on visible-light communication using the received signal strength intensity (RSSI) has been widely studied because of its high accuracy compared with other wireless localization methods. However, because the RSSI can vary according to the inclination and azimuth of the receiver, a large error can occur, even at the same position. In this paper, we propose a visible-light communication-based 3-D indoor positioning algorithm using the Gauss-Newton technique in order to reduce the errors caused by the change in the inclination of the receiver. The proposed system reduces the amount of computations by selecting the initial position of the receiver through the linear least-squares method (LSM), which is applied to the RSSIs, and improves the position accuracy by applying the Gauss-Newton technique to the 3-D nonlinear model that contains the RSSIs acquired by the changes in the azimuth and inclination of the receiver. In order to verify the validity of the proposed algorithm in an indoor space with dimensions of $6{\times}6{\times}3m$ where 16 LED lights are installed, we compare and analyze the errors of the conventional linear LSM-based trilateration technique and the proposed algorithm according to the changes in the inclination and azimuth of the receiver. The experimental results show that the location accuracy of the proposed algorithm is improved by 82.5% compared to the conventional LSM-based trilateration technique.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.210-214
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• 2008

It is actually impossible to model and store all objects which exist in real home environment into robot's database in advance. To resolve this problem, this paper proposes new object modeling method that can be available for robot self-modeling, which is capable of estimating whole model's shape from partial surface data using Generic Model. And this whole produce is conducted to cylindrical objects like cup, bottles and cans which can be easily found at indoor environment. The detailed process is firstly we obtain cylinder's initial principle axis using points coordinates and normal vectors from object's surface after we separate cylindrical object from 3D image. This 3D image is obtained from 3D sensor. And second, we compensate errors in the principle axis repeatedly. Then finally, we do modeling whole cylindrical object using cross sectional principal axis and its radius To show the feasibility of the algorithm, We implemented it and evaluated its accuracy.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.12
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• pp.509-516
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• 2022

Accurate pose prediction of objects in 3D space is an important visual recognition technique widely used in many applications such as scene understanding in both indoor and outdoor environments, robotic object manipulation, autonomous driving, and augmented reality. Most previous works for object pose estimation have the limitation that they require an exact 3D CAD model for each object. Unlike such previous works, this paper proposes a novel neural network model that can predict the poses of unknown objects based on only their RGB color images without the corresponding 3D CAD models. The proposed model can obtain depth maps required for unknown object pose prediction by using an adaptive depth estimator, AdaBins,. In this paper, we evaluate the usefulness and the performance of the proposed model through experiments using benchmark datasets.

• Journal of the Korean housing association
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• v.17 no.5
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• pp.47-54
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• 2006

This study aims to evaluate the sound insulation performance of Korean traditional paper(Hanji) windows as a material of environmental friendly building. Six types of traditional windows with 4 types of traditional window positions, were installed in l/2.5 scale model house. And then according to KS F 2235, comparative sound level differences between outdoor and indoor were measured. The main results are as follows; 1) TL(Transmission Loss) of Korean traditional paper windows, which cover one eighth of total balcony window, are ranged from 15 to 19 dB(A) in the living room and from 8 to 11 dB(A) in the balcony space. 2) TL of Korean traditional paper windows, which cover one fourth of total balcony window, are ranged from 10 to 19 dB(A) in the living room and from 8 to 10 dB(A) in the balcony space. 3) TL of Korean traditional windows with one side-one layer paper is ranged from 10 to 21 dB(A) and two side-one layer paper is 15 to 23 dB(A) and two side-two layer paper is 19 to 23 dB(A) respectively.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2007.11a
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• pp.840-843
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• 2007

There is a tremendous need for an effective indoor facility management since the building are tend to be built taller and bigger due to latest technology, Also, information that is continuously used and transferred during the design and construction phase is emerging due to 3D object-oriented CAD. Therefore, a system that will use such information for facility management should be developed. In this study, we present the methodology for definition the process that generates the Space Network Model automatically and examine the effective value of it.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.32 no.6
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• pp.637-650
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• 2014

Geospatial research on emergency response in multi-level micro-spatial environments (e.g., multi-story buildings) that aims at understanding and analyzing human movements at the micro level has increased considerably since 9/11. Past research has shown that reducing the time rescuers needed to reach a disaster site within a building (e.g., a particular room) can have a significant impact on evacuation and rescue outcomes in this kind of disaster situations. With the purpose developing emergency response systems that are capable of using complex real-time geospatial information to generate fast-changing scenarios, this study develops a Spatiotemporal Optimal Route Algorithm (SORA) for guiding rescuers to move quickly from various entrances of a building to the disaster site (room) within the building. It identifies the optimal route and building evacuation bottlenecks within the network in real-time emergency situations. It is integrated with a Ubiquitous Sensor Network (USN) based tracking system in order to monitor dynamic geospatial entities, including the dynamic capacities and flow rates of hallways per time period. Because of the limited scope of this study, the simulated data were used to implement the SORA and evaluate its effectiveness for performing 3D topological analysis. The study shows that capabilities to take into account detailed dynamic geospatial data about emergency situations, including changes in evacuation status over time, are essential for emergency response systems.

• Journal of the Korean Association of Geographic Information Studies
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• v.21 no.4
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• pp.132-144
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• 2018

3D Geo-spatial information models have been widely used in the field of Civil Engineering, Medical, Computer Graphics, Urban Management and many other. Especially, in surveying and geo-spatial field, the demand for high quality 3D geospatial information and indoor spatial information is so highly increasing. However, it is so difficult to provide a low-cost and high efficiency service to the field which demand the highest quality of 3D model, because pre-constructed spatial data are composed of different formats and storage structures according to the application purpose of each institutes. In fact, the techniques to construct a high applicable 3D geo-spatial model is very expensive to collect and analyze geo-spatial data, but most demanders of 3D geo-spatial model never want to pay the high-cost to that. This study, therefore, suggest the effective way to construct 3D geo-spatial model with low-cost of construction. In general, the effective way to reduce the cost of constructing 3D geo-spatial model as presented in previous studies is to combine the raw data obtained from point cloud observatory and UAV imagery, however this method has some limitation of usage from difficulties to approve the use of raw data because of those have been managed separately by various institutes. To solve this problem, we developed the linking & management system for unifying a high-Resolution raw geo-spatial data based on the point cloud DB and apply this system to extract the basic database from 3D geo-spatial mode for the road database registration. As a result of this study, it can be provided six contents of main entries for road registration by applying the developed system based on the point cloud DB.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.3
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• pp.384-390
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• 2020

The reverberation effect on the sound when producing movies or VR contents is a very important factor in the realism and liveliness. The reverberation time depending the space is recommended in a standard called RT60(Reverberation Time 60 dB). In this paper, we propose a scene recognition technique for automatic reverberation editing. To this end, we devised a classification model that independently trains color images and predicted depth images in the same model. Indoor scene classification is limited only by training color information because of the similarity of internal structure. Deep learning based depth information extraction technology is used to use spatial depth information. Based on RT60, 10 scene classes were constructed and model training and evaluation were conducted. Finally, the proposed SCR + DNet (Scene Classification for Reverb + Depth Net) classifier achieves higher performance than conventional CNN classifiers with 92.4% accuracy.