City Geospatial Dashboard: IoT and Big Data Analytics for Geospatial Solutions Provider in Disaster Management

被引:20
|
作者
Lwin, Ko Ko [1 ]
Sekimoto, Yoshihide [1 ]
Takeuchi, Wataru [2 ]
Zettsu, Koji [3 ]
机构
[1] Univ Tokyo, Inst Ind Sci, Human Ctr Urban Informat, Tokyo 1538505, Japan
[2] Univ Tokyo, Inst Ind Sci, Remote Sensing Environm & Disaster, Tokyo 1538505, Japan
[3] NICT Natl Inst Informat & Commun Technol, Big Data Analyt Lab, Tokyo, Japan
基金
日本科学技术振兴机构;
关键词
geospatial dashboard; IoT; big data analytics; geovisualisation; disaster management;
D O I
10.1109/ict-dm47966.2019.9032921
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Geospatial information generated from satellites, drones, and big data (mobile CDR (call details record), GPS trajectory data, wireless sensor network, and IoT (Internet of Things)) are important to all processes in disaster management such as disaster mitigation, preparedness, response, and mitigation. The emergence of a global navigation system and wireless communication technology changed the way we live and how we collect geospatial data in the field. For example, a large amount of geospatial data streams from the data repository as a base map in the field, and many IoT devices can collect and transmit geospatial data to IoT cloud server or centralised geodatabases. Moreover, collection, sharing and visualisation of all collected geospatial data is a crucial task for effective disaster planning and mitigation. Proper information needs to reach appropriate disaster management teams in minimal time to reduce loss of life and property. In this paper, we discuss establishment of a City Geospatial Dashboard, which can collect, share and visualise geospatial data collected from satellites, IoT devices, and other big data. We also explain geovisualisation of big data analytical results such as near-real-time rainfall profiler, hourly grid population, link population and flow direction estimated from mobile CDR, and hourly link speed computed from bus/taxi GPS trajectory data in order to improve spatial thinking and planning processes in disaster management by providing a set of spatial analysis tools known as geovisualisation.
引用
收藏
页数:4
相关论文
共 50 条
  • [1] GEOSPATIAL DATA, ANALYTICS, AND CUSTOM SOLUTIONS
    O'Connor, James
    Smith, Mike
    GIM INTERNATIONAL-THE WORLDWIDE MAGAZINE FOR GEOMATICS, 2016, 30 (10): : 36 - 37
  • [2] GEOSPATIAL DATA, ANALYTICS, AND CUSTOM SOLUTIONS
    Leonov, Andrey
    Anikushkin, Mikhail
    Buynov, Andrey
    GIM INTERNATIONAL-THE WORLDWIDE MAGAZINE FOR GEOMATICS, 2016, 30 (09): : 22 - 23
  • [3] Geospatial Big Data Analytics Engine for Spark
    Wang, Shaohua
    Zhong, Yang
    Lu, Hao
    Wang, Erqi
    Yun, Weiying
    Cai, Wenwen
    BIGSPATIAL 2017: PROCEEDINGS OF THE 6TH ACM SIGSPATIAL INTERNATIONAL WORKSHOP ON ANALYTICS FOR BIG GEOSPATIAL DATA (BIGSPATIAL-2017), 2017, : 42 - 45
  • [4] Geospatial Digital Dashboard for Exploratory Visual Analytics
    Sjoebergh, Jonas
    Tanaka, Yuzuru
    INFORMATION SEARCH, INTEGRATION, AND PERSONALIZATION, 2014, 421 : 3 - 17
  • [5] FogGIS: Fog Computing for Geospatial Big Data Analytics
    Barik, Rabindra K.
    Dubey, Harishchandra
    Samaddar, Arun B.
    Gupta, Rajan D.
    Ray, Prakash K.
    2016 IEEE UTTAR PRADESH SECTION INTERNATIONAL CONFERENCE ON ELECTRICAL, COMPUTER AND ELECTRONICS ENGINEERING (UPCON), 2016, : 613 - 618
  • [6] Efficient Geospatial Analytics on Time Series Big Data
    Al Jawameh, Isam Mashhour
    Bellavista, Paolo
    Corradi, Antonio
    Foschini, Luca
    Montanan, Rebecca
    IEEE INTERNATIONAL CONFERENCE ON COMMUNICATIONS (ICC 2022), 2022, : 3002 - 3008
  • [7] Geospatial Big Data or Big Geospatial Data: A Bibliometric Review
    Ndu, Chidinma Godsgood
    Shoko, Moreblessings
    SOUTH AFRICAN JOURNAL OF GEOMATICS, 2024, 13 (01): : 158 - 171
  • [8] Comparative Analysis of SpatialHadoop and GeoSpark for Geospatial Big Data Analytics
    Lenka, Rakesh K.
    Barik, Rabindra K.
    Gupta, Noopur
    Ali, Syed Mohd
    Rath, Amiya
    Dubey, Harishchandra
    PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING AND INFORMATICS (IC3I), 2016, : 484 - 488
  • [9] Cloud GIS Model for Coastal Geospatial Big Data Analytics
    Barik, K.K.
    Mishra, Vivek
    Mohanty, J.R.
    Debbarma, Mrinal K.
    Barik, R.K.
    Studies in Big Data, 2022, 114 : 1 - 11
  • [10] Evaluation of Data Management Systems for Geospatial Big Data
    Amirian, Pouria
    Basiri, Anahid
    Winstanley, Adam
    COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2014, PT V, 2014, 8583 : 678 - +