• Journal of the Society of Disaster Information
• /
• v.12 no.2
• /
• pp.130-135
• /
• 2016

In this paper, the trend of evacuation path providing or guidance systems for safety on disaster situation is analyzed. For trend analysis, 31 papers of domestic and international, 29 patents of domestic, and the finished 9 national funded projects, which have been performed for recent 15 years are analysed. As the results of analysis, the previous researches were performed in the view of the guidance systems, but there is no study that can be used for peoples in dangerous situation until now. Also it has technical limitations in using indoor positioning technology for peoples. In this paper, therefore, we propose to use the indoor positioning technology for developing a novel evacuation guidance system for peoples in dangerous situation. It can be utilized to develop a novel evacuation guidance system which is considered indoor disaster situations.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2009.10a
• /
• pp.742-745
• /
• 2009

This paper proposed indoor location recognition method based on RSSI (received signal strength indication) using the LVQ (Learning Vector Quantization) network. The LVQ inputs are the RSSI values measured by the fixed reference nodes and the output are the spatial sections. In order to verify the effectiveness of the proposed method, we performed experiments, and then compared to the conventional triangularity measurement method.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.21 no.4
• /
• pp.442-448
• /
• 2011

There are many research results about a self-localization technique of mobile robot. In this paper we present a self-localization technique based on the features of ceiling vision using a fisheye lens. The features obtained by SIFT(Scale Invariant Feature Transform) can be used to be matched between the previous image and the current image and then its optimal function is derived. The fisheye lens causes some distortion on its images naturally. So it must be calibrated by some algorithm. We here propose some methods for calibration of distorted images and design of a geometric fitness model. The proposed method is applied to laboratory and aile environment. We show its feasibility at some indoor environment.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.41 no.11
• /
• pp.1490-1501
• /
• 2016

In this paper, we propose an image-based indoor localization system using parallel distributed computing. In order to reduce computation time for indoor localization, an scale invariant feature transform (SIFT) algorithm is performed in parallel by using Apache Spark. Toward this goal, we propose a novel image processing interface of Apache Spark. The experimental results show that the speed of the proposed system is about 3.6 times better than that of the conventional system.

• 한국HCI학회:학술대회논문집
• /
• 2007.02a
• /
• pp.50-57
• /
• 2007

사용자가 현재 위치해 있는 장소를 알아내는 것은 상황인식 분야에서 활발히 연구되고 있는 분야중 하나로, 이를 위해서 사용자의 몸에 다양한 센서를 장착하고 그 센서로부터 추출되는 데이터를 분석하여 사용자의 위치를 인식하는 연구가 많이 이루어져왔다. 본 논문에서는, 사용자의 몸에 장착된 카메라로부터 얻어진 영상을 이용하여 사용자의 현재 장소를 인식하는 장소 인식 시스템을 제안한다. 기존의 방법론들에 비해서 높은 성능을 보이기 위해서 본 논문에서는 두 가지 방법을 제안하였다. 먼저 한 방향만의 영상으로는 인식이 어려운 장소에서도 좋은 인식 성능을 보일 수 있도록 하기 위해, 여러 대의 카메라를 동시에 사용하여 여러 방향의 영상을 얻어내는 방법을 제안하였다. 또한 이전 시간의 장소 인식 결과로부터 현재 시간의 장소를 추론하는 데에 있어서, 각 장소들에 대해 알고 있는 사전지식을 보다 많이 적용할 수 있는 인식 모델을 제안하였다. 실제 대학 실내 환경에서의 실험을 통하여, 제안한 방법을 이용한 장소 인식기법이 좋은 성능을 보임을 확인할 수 있었다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.17 no.6
• /
• pp.105-111
• /
• 2017

In this paper, the analysis results are shown about several weights of Weighted K-Nearest Neighbor method, Recently, it is employed for the indoor positioning technologies using WiFi fingerprint which has been actively studied. In spite of the simplest feature, the W-KNN method shows comparable performance to another methods using WiFi fingerprint technology. So W-KNN method has employed in the existing indoor positioning system. It shows positioning error performance according to data preprocessing and weight factor, and the analysis on the weight is very important. In this paper, based on the real measured WiFi fingerprint data, the estimation error is analyzed and the performances are compared, for the case of data processing methods, of the weight of average, variance, and distance, and of the averaging several position of number K. These results could be practically useful to construct the real indoor positioning system.

• Journal of Advanced Marine Engineering and Technology
• /
• v.37 no.2
• /
• pp.220-226
• /
• 2013

Recently, with the rapid development of factory automation and logistics system, a few workers were able to manage the broad workplace such as large vessels and warehouse. To estimate the exact location of these workers in the conventional wireless indoor localization systems, three or more fixed nodes are generally used to recognize the location of a mobile node consisting of a single node. However, these methods are inefficient in terms of node deployment because the broad workplace requires a lot of fixed nodes compared to workers(mobile nodes). Therefore, to efficiently deploy fixed nodes in these environments that need a few workers, this paper presents a novel estimation algorithm which can reduce the number of fixed nodes by efficiently recognizing the relative coordinates of two fixed nodes through a mobile node composed of three nodes. Also, to minimize the distance errors between mobile node and fixed node, rounding estimation(RE) technique is proposed. Experimental results show that the error rate of localization is improved, by using proposed RE technique, 90.9% compared to conventional trilateration in the free space. In addition, despite the number of fixed nodes can be reduced by up to 50% in the indoor free space, the proposed estimation algorithm recognizes precise location which has average error of 0.15m.

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.04a
• /
• pp.92-94
• /
• 2016

시간이 지날수록 건물의 이용은 잦아지고, 건물 안에서 화재 발생가능성이 높아지는 반면 안전하고 신속한 대처는 미흡한 상태이다. 이 문제점을 인식하여 본 논문에서는 화재 대피 시스템을 모든 사람이 대부분 소지하고 있는 스마트폰에 연동시켜 개발 시스템을 구축한다. 화재와 같은 비상상황인지 및 대피상황 분석을 위한 위치인식 서버 시스템을 비콘 관리, 사용자 관리, 비상구 관리 시스템으로 나누어 구축한다. 개발 시스템은 BLE 핑거프린팅 방식을 이용하여 현재 위치파악과 건물 안의 혼잡도, 화재로 인한 폐쇄구역을 표시하여 가장 빠른 길로 안내 하는 기능을 포함한다.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.8 no.6
• /
• pp.121-130
• /
• 2009

In this paper, Gaussian probability distribution model based multi-sensor data fusion algorithm is proposed for a vehicular location awareness system. Conventional vehicular location awareness systems are operated by GPS (Global Positioning System). However, the conventional system is not working in the indoor of building or urban area where the receiver is difficult to receive the signal from satellites. A method which is combined GPS and UWB (Ultra Wide-Band) has developed to improve this problem. However, vehicular is difficult to receive seamless location information since the measurement systems by both GPS and UWB convert the vehicle's movement information separately at each sensor. In this paper, normalized probability distribution model based Hybrid UWB/GPS is proposed by utilizing GPS location data and UWB sensor data. Therefore the proposed system provides information with seamless and location flexible properties. The proposed system tested by Ubisense and Asen GPS in the $12m{\times}8m$ outdoor environments. As a result, the proposed system has improved performance for accurateness and connection ability between devices to support various CNS (Car Navigation System).

• Proceedings of the Korea Information Processing Society Conference
• /
• 2016.10a
• /
• pp.837-838
• /
• 2016

최근 IoT 기술의 발전과 함께 스마트홈 기술의 발달과 Drone을 사용하는 사용자가 꾸준히 늘어나고 있는 추세이다. 스마트홈 시스템의 보안카메라는 정해진 구역을 모니터링 할 수 밖에 없다는 단점을 가지고 있다. 이러한 한계를 극복하고자, 본 논문에서는 사용자가 입력한 목적지로 실내에 미리 배치된 Drone이 이동하여 해당 목적지를 비춰줄 수 있도록 실내 보안카메라 기술을 Drone으로 대체할 수 있는 방법을 제안한다. 목적지를 인식하기 위해 실내에 위치한 Drone과 목적지의 위치값을 알아야 한다. 실내에선 GPS 좌표값을 알 수 없기 때문에 BLE Beacon이 발생시키는 신호를 이용하여 상호간의 통신을 통해 위치, 거리를 계산하도록 한다. 이러한 방식을 적용시킨다면 매번 모니터링이 필요한 구역에 새로 보안카메라를 설치하거나 배선공사하는 불편함 없이 하나의 Drone 하드웨어를 이용한 전방위 모니터링이 가능해 질 것으로 기대한다.