• Spatial Information Research
• /
• v.14 no.4 s.39
• /
• pp.379-389
• /
• 2006

Map databases for CNS (Car Navigation System) can be accessed quickly and compressed efficiently due to that these are usually recorded as in a PSF (Physical Storage Format). However, it is difficult to create and manage data storage based on a file-system. To solve these problems, DBMS needs to be combined with spatial data management. Therefore, we developed an embedded DBMS with which to store data and conduct quick searches in CNS. Spatial data could be easily managed and accessed using the compression method, Multi-Link, spatial index, and spatial division. In the result, the proposed embedded DBMS searched quickly and stably supported data management. If synchronization is applied in DBMS, it is expected to utilize the advantages of an embedded DBMS.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.8 no.1
• /
• pp.63-74
• /
• 2005

The telematics device, which is a typical embedded system on the transportation or vehicle, requires the embedded spatial DBMS based on RTOS (Real Time Operating System) for processing the huge spatial data in real time. This spatial DBMS can be developed very easily by SQL3 functions of the ORDBMS such as UDT (user-defined type) and UDF (user-defined function). However, developing index suitable for the embedded spatial DBMS is very difficult. This is due to the fact that there is no built-in SQL3 functions to construct spatial indexes. In this study, we compare and analyze both Generalized Search Tree and Relational Indexing methods which are suggested as common ways of developing User-Defined Indexes nowadays. Two implementations of R-Tree based on each method were done and region query performance test results were evaluated for suggesting a suitable indexing method of an embedded spatial DBMS, especially for telematics devices.

• Spatial Information Research
• /
• v.19 no.1
• /
• pp.107-116
• /
• 2011

Due to development of environment of wireless Internet, location based services on the basis of spatial data have been increased such as real time traffic information as well as CNS(Car Navigation System) to provide mobile user with route guidance to the destination. However, the current application adopting the file-based system has limitation of managing and storing the huge amount of spatial data. In order to supplement this challenge, research which is capable of managing large amounts of spatial data based on embedded database system is surely demanded. For this reason, this study aims to suggest the lossless compression technique by using the hybrid approach of BytePacking and Lempel-Ziv which can be applicable in DBMS so as to save a mass spatial data efficiently. We apply the proposed compression technique to actual the Seoul and Inchcon metropolitan area and compared the existing method with suggested one using the same data through analyzing the query processing duration until the reconstruction. As a result of comparison, we have come to the conclusion that suggested technique is far more performance on spatial data demanding high location accuracy than the previous techniques.

• The KIPS Transactions:PartD
• /
• v.15D no.5
• /
• pp.609-620
• /
• 2008

The service handling the map data in the mobile device including navigation, LBS, Telematics, and etc., becomes various. The size of map data which is stored and managed in the mobile device is growing and reaches in several GB. The conventional navigation system has used the read-only PSF (physical storage format) in order to enhance the performance of system by maximum in the mobile device which has limited resources. So though a little part of the map data is changed the whole data must be updated. In general, it takes several ten minutes to write the 2 GB map data to a flash memory of mobile device. Therefore, we have developed the mobile spatial DBMS (database management system) to solve the problem which is that the partial map data couldn't be updated in the conventional navigation system. And we suggest the policy to guarantee the performance of the navigation system which is implemented using the spatial mobile DBMS and verify this by experiment.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2008.06a
• /
• pp.59-66
• /
• 2008

최근 유비쿼터스 컴퓨팅 환경이 발전함에 따라 교통(u-Transport), 복지(u-Care), 문화(u-Fun), 환경(u-Green), 산업(u-Business), 행정(u-Government), 도시(u-City) 뿐만 아니라 사용자의 위치와 다양한 공간 정보를 제공하는 u-GIS가 유비쿼터스 컴퓨팅 환경의 핵심 요소 기술로 대두되고 있다. 이에 본 논문에서는 기존의 PC용 MMDBMS인 HS QLDB를 확장하여 모바일 장치에서 시공간 데이타를 효율적으로 처리 및 관리할 수 있는 내장형 시공간 DBMS를 설계 및 구현하였다. 내장형 시공간 DBMS는 OpenGIS "Simple Features Specification for SQL"에서 명시하는 공간 데이타 타입과 공간 연산자를 확장하여 시공간 데이타 타입과 시공간 연산자를 제공하며, 시공간 데이타 특성들 고려한 산술 연산 코딩 압축 기법을 제공하고, 모바일 저장 장치인 플래쉬 메모리에서 효율적인 시공간 데이타 검색을 위한 시공간 인덱스를 지원한다. 그리고, 내장형 시공간 DBMS와 U-GIS 서버 사이에서 시공간 데이타 수입/수출의 성능 향상을 위한 데이타 캐슁 기능과 DBMS의 안정성을 위한 백업/복구 기능을 지원한다.

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
• /
• 2009.04a
• /
• pp.273-274
• /
• 2009

도로네트워크 데이터는 교통 정보, 경로 안내서비스 등 실시간 정보제공을 위해 차량 항법용 데이터에서 가장 핵심적인 영역에 해당하며 효율적인 관리와 유지가 필수적이다. 기존 파일 기반 시스템인 미디어 포맷(KIWI, GDF 등)에서는 콤팩트한 데이터 구성으로 읽기 위주의 빠른 매체 접근 등에 좋은 이점이 있지만, 최근 모바일 시스템 환경에 DBMS를 활용한 위치 기반 서비스(LBS)에 대한 관심이 증가 하고 있다. 이에 본 연구에서는 임베디드 DBMS를 이용하여 네트워크의 계층성을 지원하는 데이터 모델과 이를 활용한 탐색 알고리듬을 설계하고 프로토타입 시스템을 구현하였다. 특히 대규모 도로망의 원거리 탐색을 대상으로 메모리 구성과 탐색 시간 측면에서 일반 영역 탐색방법과 계층 탐색방법의 검색 결과를 비교하여 계층 탐색 방법의 효율성을 검증하였다.

• The Journal of the Institute of Internet, Broadcasting and Communication
• /
• v.11 no.1
• /
• pp.109-113
• /
• 2011

Recently, according to the development of ubiquitous computing, the u-GIS which not only used in u-Transport, u-Care, u-Fun, u-Green, u-Business, u-Government, and u-City but also used to provides various spatial information such as the location of user is being the core technology of the ubiquitous computing environment. In this paper, we implemented an mobile spatio-temporal Query Processing Systems for handling the Spatio-Temporal Data in mobile equipment.The mobile spatio-temporal Query Processing Systems provides the spatio-temporal data type and the spatio-temporal operator that is expanded by the spatial data type and the spatial operator from OepenGIS "Simple Feature Specification for SQL". It supports arithmetic coding compression techniques that is considered with a spatio-temporal data specific character. It also provides the function of data cashing for improving the importation and exportation of the spatio-temporal data between a embedded spatio-temporal DBMS and u-GIS server.

• The KIPS Transactions:PartB
• /
• v.13B no.5 s.108
• /
• pp.561-568
• /
• 2006

WPS(Wearable Personal Station) for next generation PC can define as a core terminal of 'Ubiquitous Computing' that include information processing and network function and overcome spatial limitation in acquisition of new information. As a way to acquire significant dynamic gesture data of user from haptic devices, traditional gesture recognizer based on desktop-PC using wire communication module has several restrictions such as conditionality on space, complexity between transmission mediums(cable elements), limitation of motion and incommodiousness on use. Accordingly, in this paper, in order to overcome these problems, we implement hand gesture recognition system using fuzzy algorithm and neural network for Post PC(the embedded-ubiquitous environment using blue-tooth module and WPS). Also, we propose most efficient and reasonable hand gesture recognition interface for Post PC through evaluation and analysis of performance about each gesture recognition system. The proposed gesture recognition system consists of three modules: 1) gesture input module that processes motion of dynamic hand to input data 2) Relational Database Management System(hereafter, RDBMS) module to segment significant gestures from input data and 3) 2 each different recognition modulo: fuzzy max-min and neural network recognition module to recognize significant gesture of continuous / dynamic gestures. Experimental result shows the average recognition rate of 98.8% in fuzzy min-nin module and 96.7% in neural network recognition module about significantly dynamic gestures.