• Smart Media Journal
• /
• v.13 no.7
• /
• pp.9-17
• /
• 2024

Due to the increase in energy consumption, and eco-friendly policies, there is a need for efficient energy consumption in buildings. Anomaly power detection based on deep learning are being used. Because of the difficulty in collecting anomaly data, anomaly detection is performed using reconstruction error with a Recurrent Neural Network(RNN) based autoencoder. However, there are some limitations such as the long time required to fully learn temporal features and its sensitivity to noise in the train data. To overcome these limitations, this paper proposes the TCN-USAD, combined with Temporal Convolution Network(TCN) and UnSupervised Anomaly Detection for multivariate data(USAD). The proposed model using TCN-based autoencoder and the USAD structure, which uses two decoders and adversarial training, to quickly learn temporal features and enable robust anomaly detection. To validate the performance of TCN-USAD, comparative experiments were performed using two building energy datasets. The results showed that the TCN-based autoencoder can perform faster and better reconstruction than RNN-based autoencoder. Furthermore, TCN-USAD achieved 20% improved F1-Score over other anomaly detection models, demonstrating excellent anomaly detection performance.

• Journal of Cadastre & Land InformatiX
• /
• v.52 no.1
• /
• pp.105-118
• /
• 2022

The demand for information related to 3D spatial objects model in metaverse, smart cities, digital twins, autonomous vehicles, urban air mobility will be increased. 3D model construction for spatial objects is possible with various equipments such as satellite-, aerial-, ground platforms and technologies such as modeling, artificial intelligence, image matching. However, it is not easy to quickly detect and convert spatial objects that need updating. In this study, based on spatial information (features) and attributes, using matching elements such as address code, number of floors, building name, and area, the converged building DB and the detected building DB are constructed. Both to support above and to verify the suitability of object selection that needs to be updated, one system prototype was developed. When constructing the converged building DB, the convergence of spatial information and attributes was impossible or failed in some buildings, and the matching rate was low at about 80%. It is believed that this is due to omitting of attributes about many building objects, especially in the pilot test area. This system prototype will support the establishment of an efficient drone shooting plan for the rapid update of 3D spatial objects, thereby preventing duplication and unnecessary construction of spatial objects, thereby greatly contributing to object improvement and cost reduction.

• Journal of Internet Computing and Services
• /
• v.22 no.4
• /
• pp.83-98
• /
• 2021

The purpose of this study to find the factors influencing the fire alarms using IoT firefighting facility management system data of Seoul Fire & Disaster Headquarters, and to present academic implications for establishing an effective prevention system of fire situation. As the number of high and complex buildings increases and former bulidings are advanced, the fire detection facilities that can quickly respond to emergency situations are also increasing. However, if the accuracy of the fire situation is incorrectly detected and the accuracy is lowered, the inconvenience of the residents increases and the reliability decreases. Therefore, it is necessary to improve accuracy of the system through efficient inspection and the internal environment investigation of buildings. The purpose of this study is to find out that false detection may occur due to building characteristics such as usage or time, and to aim of emphasizing the need for efficient system inspection and controlling the internal environment. As a result, it is found that the size(total area) of the building had the greatest effect on the fire alarms, and the fire alarms increased as private buildings, R-type receivers, and a large number of failure or shutoff days. In addition, factors that influencing fire alarms were different depending on the main usage of the building. In terms of time, it was found to follow people's daily patterns during weekdays(9 am to 6 pm), and each peaked around 10 am and 2 pm. This study was claimed that it is necessary to investigate the building environment that caused the fire alarms, along with the system internal inspection. Also, it propose additional recording of building environment data in real-time for follow-up research and system enhancement.

• Spatial Information Research
• /
• v.16 no.4
• /
• pp.479-488
• /
• 2008

This paper performs investigation of the state-of-the-art approaches to building extraction in terms of their sensory input data and methodologies. For the last decades, there have been many types of sensory input data introduced into the mapping science and engineering field, which are considerably diverse in aspects of spatial resolution and data processing. With the cutting-edge technology in this field, accordingly, one of the key issues in GIS is to reconstruct three -dimensional virtual models of the real world to meet the requirements occurring in spatial applications such as urban design, disaster management, and civil works. Thus, this study investigates the strengths and weaknesses of previous approaches to automating building extraction with two categories - building detection and modeling and with sensor types categorized. The findings in this study can be utilized in enhancing automation algorithms and choosing suitable sensors, so that they can be optimized for a specific purpose.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2006.05a
• /
• pp.187-192
• /
• 2006

도시의 과밀화로 인해 건물들은 고층화, 대형화되고 복잡한 형태를 이루고 있어 건물 이용자들에게 2차원의 정보뿐만 아니라 3차원 공간정보의 필요성이 증가하고 있으며 이를 해결하기 위해 3차원 GIS 모델의 활용이 요구되고 있다. 그러나 현재까지 연구되거나 응용되어 온 3차원 모델은 주로 건물 외부형태의 시각화를 위한 것으로 3차원 공간분석에 응용되기에는 한계가 존재해 왔다. 이에 본 연구에서는 3차원 모델을 공간분석에 적용하는 하나의 방안으로서 건물의 내부공간에서 경로탐색을 구현하기 위한 방법을 제시하였다. 이를 위해 건물 내부의 각 실들과 연결통로 및 기타 시설들을 각각 오브젝트로 분리하여 3차원으로 모델링하였다. 2차원 GIS데이터와 3차원 모델에 각각 벡터기반의 네트워크 모델을 생성하고 DB를 이용하여 두 모델을 연동함으로써 3차원 모델에서 네트워크기반의 경로분석과 탐지기능을 가능하게 하였다.

• Journal of Korean Society for Geospatial Information Science
• /
• v.11 no.2 s.25
• /
• pp.61-66
• /
• 2003

The change detection using the satellite imagery and airphotos has been carried out in the application of terrain mapping, environment, forestry, facility detection, etc. The low-spatial resolution data such as Landsat, NOAA satellite images is generally used for automatic change detection, while on the other hand the high-spatial resolution data is used for change detection by image interpretation. The research to integrate automatic method with manual change detection through the high-spatial resolution satellite image is performed. but the problem such as shadow, building 'lean' due to perspective geometry and precision geocorrection was found. In this paper we performed change detection using the IKONOS satellite images, and present the concerning problem.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.18 no.1
• /
• pp.51-57
• /
• 2000

With the emergence of laser mapping systems, higher resolution DTM of urban area can be acquired and can be used to generate precise orthoimage. But, when the conventional orthoimage generation methods are applied to the area containing features with height difference such as cliffs, bridges, banks. elevated highways and buildings, they cause problems such as occlusion and double mapping. Therefore, this study proposes a new algorithm by modifying and refining conventional orthoimage generation methods. With this algorithm, areas which have occlusion are detected from the base image using camera orientation parameters and DTM. Also, detected areas are restored using alternative images which does not have occlusion in that area. This study can be distinguished from the other studies in the aspects that the proposed algorithm in this paper doesn't need information on building and that uses DTM data and orientation parameters.

• Proceedings of the KAIS Fall Conference
• /
• 2008.05a
• /
• pp.98-100
• /
• 2008

최근 무선통신 기술의 발달과 편리성으로 무선 랜의 활용 증가하고 있다. 이와 더불어 무선 랜의 보안 위협과 취약성에 대하여 이슈화 되고 있다. 따라서 IEEE에서는 802.11 표준안을 제정하고 무선 랜의 보안 취약점을 보완하기 위해 802.11i등 새로운 표준들을 제정하고 있지만, 아직까지 해결되지 않은 보안 위협들이 존재한다. 본 논문에서는 액세스 포인트의 비콘 프레임을 이용하여 건물 내 액세스 포인트의 보안 상태 와 비인가 액세스 포인트를 탐지하는 시스템과 RSSI, 삼각측량범 및 칼만필터 알고리즘을 사용한 위치탐지 알고리즘을 제안하고, 기존 탐지 알고리즘과 제안 알고리즘의 결과 비교로 성능을 평가하였다.

• Proceedings of the Korean Society of Computer Information Conference
• /
• 2021.07a
• /
• pp.653-654
• /
• 2021

본 논문에서는 문화재 손상 검출을 위한 직선 검출 기법을 제안한다. 이 기법은 문화재 건물의 볼록함, 즉 배부름 현상을 검출하기 위하여 원본 이미지의 직선과 윤곽을 탐지하여 두 선을 비교한다. 배부름 현상이 나타난 문화재의 경우 곡선이 볼록하게 검출되기 때문에 직선과 비교했을 때 일치하지 않는다. 직선 탐지 기법과 윤곽 탐지 기법은 컴퓨터 비전을 기반으로 이루어져 있으며, 이 선들은 이미지의 엣지를 이용하여 검출한다. 배부름 현상은 문화재의 전체 부분 중 일부분에 발생하기 때문에 직선과 윤곽을 비교했을 때 차이를 드러내므로 우수한 성능을 보인다.

• Korean Journal of Remote Sensing
• /
• v.27 no.2
• /
• pp.75-87
• /
• 2011

This paper presents a method for region-based building extraction from high resolution satellite images(HRSI) using integrated information of spectral and color invariant features without user intervention such as selecting training data sets. The purpose of this study is also to evaluate the effectiveness of the proposed method by applying to IKONOS and QuickBird images. Firstly, the image is segmented by the MSRG method. The vegetation and shadow regions are automatically detected and masked to facilitate the building extraction. Secondly, the region merging is performed for the masked image, which the integrated information of the spectral and color invariant features is used. Finally, the building regions are extracted using the shape feature for the merged regions. The boundaries of the extracted buildings are simplified using the generalization techniques to improve the completeness of the building extraction. The experimental results showed more than 80% accuracy for two study areas and the visually satisfactory results obtained. In conclusion, the proposed method has shown great potential for the building extraction from HRSI.