• Spatial Information Research
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• v.23 no.1
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• pp.49-57
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• 2015

Due to high density of population and progress of high building construction technologies, the number of high buildings has been increasing. Several information services have been provided to figure out complex indoor structures of building such as indoor navigations and indoor map services. The most fundamental information for these services are indoor network information. Indoor network in building provides topological connectivity between spaces unlike geometric information of buildings. In order to make indoor network information, we have to edit network manually or derive network properties based on the geometric data of buildings. This process is not easy for complex buildings. In this paper, we suggest a method to generate indoor network automatically based on crowdsourcing. From the collected individual trajectories, we derive indoor network information with crowdsourcing. We validate our method with a sample set of trajectory data and the result shows that our method is practical if the indoor positioning technology is reasonably accurate.

• Spatial Information Research
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• v.23 no.3
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• pp.113-122
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• 2015

Recently, according to developing advanced construction technologies, buildings has been enlarged such as high-rise buildings or complex buildings associated with underground facilities. The number of indoor activity population has increased very quickly. Because of that, technical requirements for Indoor location based service (Indoor LBS) also have been increased. Although indoor networks have to be constructed for efficient LBSs in indoor space based on OGC IndoorGML, it is not suitable for large and complex space to apply the simple network structure to constructing indoor navigation networks. The indoor navigation network has to be constructed according to logical, physical, and functional constraints for indoor space. In order to do that, subspacing methods are required to partition large and complex indoor space into proper size of subspace. In this paper, we proposed the basic requirements of subspacing in indoor space for creating efficient indoor network, as well the work process of subspacing in indoor space.

• Spatial Information Research
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• v.21 no.2
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• pp.1-9
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• 2013

Recently many researches have focused on indoor navigation system. An optimal indoor navigation method can help people to find a path in large and complex buildings easily. However, some indoor navigation algorithms only calculate approximate routes based on spatial topology analysis, while others only use indoor road networks. However, both of them use only one of the spatial topology or network information. In this paper, we present a navigation method based on topology analysis and room internal networks for indoor navigation path. FT-Indoornavi (Flexible Topology Analysis Indoornavi) calculate internal routes based on spatial topology and internal path networks to support length-dependent and running-time optimal routing, which adapt to complex indoor environment and can achieve a better performance in comparison of Elastic algorithm and iNav.

• Spatial Information Research
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• v.23 no.3
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• pp.1-10
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• 2015

Due to recent improvement of various sensor technologies, indoor positioning becomes available. However, Indoor positioning technologies by Wi-Fi radio map and acceleration sensor and digital campus still have a certain level of errors and a number of researches have been done to increase the positioning accuracy of the indoor positioning. If we could provide a room level accuracy, indoor location based services with current indoor positioning methods such as Wi-Fi radio map and acceleration sensors would be possible. In this paper, we propose an indoor map matching method to provide a room level accuracy based on hidden markov model.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.1463-1466
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• 2005

상황인지로부터 알아 낼수 있는 여러가지 정보들 중에 하나가 위치정보이다. 위치인지는 어떠한 대상의 위치를 알아내는 것으로서 가장 대표적인 위치인지 시스템으로는 GPS 가 있다. 그러나 GPS 는 건물 내부에서 사용될 수 없는 단점을 지니고 있다. 이를 극복하기 위해 본 논문은 센서 네트워크 기반의 저전력 실내 위치인지 시스템 설계에 대해 기술한다. 구현된 실내 위치인지 시스템은 센서 네트워크 기반으로 설계되었다. 하드웨어 플랫폼은 모트를 기반으로 하고 있으며 운영체제는 Tiny OS 를 사용한다. 거리측정 방식은 RF 신호와 초음파 신호 사이의 시간차를 이용하고 위치측정은 삼각측량법을 이용하였다. 초음파를 이용한 다른 위치인지 시스템에 비해 저전력으로 동작한다는 점이 특징이며 위치추적이 정확하고 속도가 빠른 장점을 지니고 있다. 현재까지의 실내 위치인지 시스템은 몇가지 극복해야할 문제점들이 남아있지만 지속적인 연구를 통해 문제점들을 해결하면 홈 시큐리티나 오토메이션, 헬스케어 등과 연동하여 실내 환경에서 인간의 삶의 질 향상에 기여 할 수 있을 것이다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.6B
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• pp.888-894
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• 2010

For the indoor positioning, wireless fingerprinting is most favorable because fingerprinting is most accurate among the technique for wireless network based indoor positioning which does not require any special equipments dedicated for positioning. The deployment of a fingerprinting method consists of off-line phase and on-line phase and more efficient and accurate methods have been studied. This paper proposes a bayesian algorithm for wireless fingerprinting and indoor location determination using fuzzy clustering with bayesian learning as a statistical learning theory.

• Proceedings of the Korean Information Science Society Conference
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• 2010.06d
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• pp.222-225
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• 2010

최근 무선 인터넷 기술의 발달과 보급으로 인해 실생활에서도 쉽게 무선 네트워크를 이용한 통신을 할 수 있게 되었다. 무선 네트워크를 이용한 통신을 위해선 통신 망을 유지해 주는 AP(Access Point)가 필수적이다. 이러한 AP를 활용한 AP의 신호 세기를 이용하는 실내 위치 측위 기술은 위치 기반 서비스의 발달과 함께 주목 받고 있다. 본 논문에서는 실내 위치 측위에 많이 사용되는 삼각측량법을 개선하기 위해 다수의 무선 네트워크 인터페이스를 사용한다. 최근에는 하나의 디바이스에 여러 개의 무선 인터페이스가 장착되는 것이 보편화 되었는데 이러한 여러 개의 인터페이스를 활용하여 실내 위치 측위 값을 보정하였다. 실험 결과, 2개의 모듈을 사용할 때의 결과가 1개의 모듈을 사용했을 때 보다 평균 4.9% 좋은 성능을 보였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.31-38
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• 2011

In this paper, we propose an autonomous Indoor lighting control system in which indoor lighting devices are autonomously controlled such that electricity bills are minimized in our daily life. Our focus is to utilize Passive Infrared (PIR) sensors to detect the presence of human being indoor and automatically to control indoor lighting electric devices. A control algorithm is also devised to control the whole system. We justify the proposed system by demonstrating specific applications in our everyday life. Cost survey and experimental results also demonstrate the efficiency of the proposed system in real life.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2005.11a
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• pp.195-198
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• 2005

최근 실내 환경에서 영상 정보를 사용하여 로봇이 서비스를 제공하기 위한 연구가 활발하다. 과거 영상 처리 접근 방법은 산업 환경과 같은 예측 가능한 환경을 바탕으로 미리 정의된 기하학적 모델을 통해 상황을 인식하였기에, 이를 실내 환경과 같은 가변적인 환경에 적용할 시 성능이 저하된다. 이에 지식을 기반으로 불확실성을 해결하여 정확도를 향상 시킴으로써 영상 인식 성능을 높이기 위한 다양한 연구가 진행되어 왔다. 본 논문에서는 실내에서 활동하는 서비스 로봇의 물체인식 성능을 향상시키기 위해, 대상 물체가 다른 물체에 의해서 가려져 있는 경우 대상 물체의 존재 여부를 추론하기 위한 베이지안 네트워크 모델링 방법을 제안한다. 제안하는 방법은 작은 단위로 설계된 베이지안 네트워크들을 상황에 따라 결합하여 추론 모델이 구성되게 하였고 물체간의 관계를 효과적으로 표현하고 초기 확률 값을 단일하게 유지하기 위해 제안된 확률 값 설정 방법을 사용하였다. 실험은 물체 관계를 추론하는 모듈의 성능을 검증하기 위해 수행되었는데, 5가지 장소에서 82.8$\%$의 정확도를 보여주었다.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.5
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• pp.205-212
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• 2019

Scene graph is a kind of knowledge graph that represents both objects and their relationships found in a image. This paper proposes a 3D scene graph generation model for three-dimensional indoor environments. An 3D scene graph includes not only object types, their positions and attributes, but also three-dimensional spatial relationships between them, An 3D scene graph can be viewed as a prior knowledge base describing the given environment within that the agent will be deployed later. Therefore, 3D scene graphs can be used in many useful applications, such as visual question answering (VQA) and service robots. This proposed 3D scene graph generation model consists of four sub-networks: object detection network (ObjNet), attribute prediction network (AttNet), transfer network (TransNet), relationship prediction network (RelNet). Conducting several experiments with 3D simulated indoor environments provided by AI2-THOR, we confirmed that the proposed model shows high performance.