A Storage Method for Large Scale Moving Objects Based on PostGIS

被引:0
|
作者
Sheng, Kai [1 ]
Li, Zefang [1 ]
Zhou, Dechao [1 ]
机构
[1] Naval Univ Engn, Coll Elect Engn, Wuhan 430033, Peoples R China
关键词
Moving objects; Trajectory data; Storage model; PostGIS;
D O I
10.1007/978-3-319-38789-5_69
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Storing and managing the large scale moving objects data is one of the research hotspots and difficulties in data mining, trajectory analyzing, location-based services and many other applications. To solve these problems, firstly we design the trajectory point representing model, the trajectory representing model, the moving object data storage model and their relationships based on object-oriented ideology; then we construct a moving objects database using in PostGIS according to the presented models; finally we test the effectiveness of the moving object database with real data. The experimental results show that using the method presented in this paper to store large scale moving objects data can reduce the storage space obviously, meanwhile, it can increase the spatial and temporal querying efficiency effectively.
引用
收藏
页码:623 / 632
页数:10
相关论文
共 50 条
  • [1] A CELLULAR AUTOMATA MODEL OF LARGE-SCALE MOVING-OBJECTS
    CHOPARD, B
    JOURNAL OF PHYSICS A-MATHEMATICAL AND GENERAL, 1990, 23 (10): : 1671 - 1687
  • [2] Algorithm of search and track of static and moving large-scale objects
    Kalyaev, Anatoly
    Khisamutdinov, Maxim
    4TH ANNUAL INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND APPLICATIONS (ITA 2017), 2017, 12
  • [3] Parallel SECONDO: A Practical System for Large-Scale Processing of Moving Objects
    Lu, Jiamin
    Gueting, Ralf Hartmut
    2014 IEEE 30TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), 2014, : 1190 - 1193
  • [4] Discovering Collective Converging Groups of Large Scale Moving Objects in Road Networks
    Jia, Jinping
    Hu, Ying
    Zhao, Bin
    Ji, Genlin
    Liu, Richen
    DATABASE SYSTEMS FOR ADVANCED APPLICATIONS (DASFAA 2021), PT II, 2021, 12682 : 307 - 324
  • [5] Moving objects detection method based on chromaticity distortion
    Yu, Jing
    Duan, Juan
    Su, Kaina
    Jisuanji Gongcheng/Computer Engineering, 2006, 32 (06): : 218 - 220
  • [6] A recognition method for moving objects based on contour features
    Du, Yuren
    Jiangsu Daxue Xuebao (Ziran Kexue Ban) / Journal of Jiangsu University (Natural Science Edition), 2009, 30 (05): : 514 - 517
  • [7] A Trajectory and Orientation Reconstruction Method for Moving Objects Based on a Moving Monocular Camera
    Zhou, Jian
    Shang, Yang
    Zhang, Xiaohu
    Yu, Wenxian
    SENSORS, 2015, 15 (03) : 5666 - 5686
  • [8] Reflectance Transformation Imaging Method for Large-scale Objects
    Kim, Yong Hwi
    Choi, Junho
    Lee, Yong Yi
    Ahmed, Bilal
    Lee, Kwan H.
    2016 13TH INTERNATIONAL CONFERENCE ON COMPUTER GRAPHICS, IMAGING AND VISUALIZATION (CGIV), 2016, : 84 - 87
  • [9] Likelihood-based method for detecting faint moving objects
    Miura, N
    Itagaki, K
    Baba, N
    ASTRONOMICAL JOURNAL, 2005, 130 (03): : 1278 - 1285
  • [10] Improved Moving Objects Detection Method Based on Codebook Model
    Liu Liwei
    Li Hongwei
    Yu Shuo
    PROCEEDINGS 2013 INTERNATIONAL CONFERENCE ON MECHATRONIC SCIENCES, ELECTRIC ENGINEERING AND COMPUTER (MEC), 2013, : 1351 - 1354