Real-time Analysis and Visualization for Big Data of Energy Consumption

被引:0
|
作者
Li, Jiaxue [1 ,2 ]
Song, Wei [1 ]
Fong, Simon [2 ]
机构
[1] North China Univ Technol, Dept Digital Media Technol, Beijing, Peoples R China
[2] Univ Macau, Dept Comp & Informat Sci, Taipa, Macau, Peoples R China
关键词
big data; energy consumption; K-Means; DirectX; CUDA;
D O I
10.1145/3178212.3178229
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
This paper proposes a research on real-time analysis and visualization for big data of energy consumption. In this research, we access real-time energy consumption data from cloud storage by a Transmission Control Protocol/Internet Protocol (TCP/IP). In order to optimize K-Means clustering algorithm, we implement CUDA C programming to finish data-intensive calculation in the Graphic Processing Unit (GPU), which enhances the efficiency of analysis for big data of energy consumption. Meanwhile, to realize data visualization, we draw the data mining results in a multidimensional plane utilizing DirectX, which is a standard graphics API. We also render the original energy consumption data directly in the form of four-dimensional geometry with the plane together, so as to obtain more useful information intuitively.
引用
收藏
页码:13 / 16
页数:4
相关论文
共 50 条
  • [1] Platform for real-time data analysis and visualization based on Big Data methods
    Ferreira, Gabriel
    Alves, Paulo
    de Almeida, Simone
    [J]. PROCEEDINGS OF 2021 16TH IBERIAN CONFERENCE ON INFORMATION SYSTEMS AND TECHNOLOGIES (CISTI'2021), 2021,
  • [2] Real-Time Data ETL Framework for Big Real-Time Data Analysis
    Li, Xiaofang
    Mao, Yingchi
    [J]. 2015 IEEE INTERNATIONAL CONFERENCE ON INFORMATION AND AUTOMATION, 2015, : 1289 - 1294
  • [3] A Progressive Real-time Visualization Method for Earthquake Big Data
    Shan, Weifeng
    Li, Jianqiao
    Teng, Yuntian
    Chen, Huiling
    Li, Zhiyang
    Wang, Maofa
    [J]. Journal of Computers (Taiwan), 2022, 33 (01) : 87 - 100
  • [4] Real-time private consumption prediction using big data
    Shin, Seung Jun
    Seo, Beomseok
    [J]. KOREAN JOURNAL OF APPLIED STATISTICS, 2024, 37 (01) : 13 - 38
  • [5] VisMillion: A novel interactive visualization technique for real-time big data
    Pires, Goncalo
    Mendes, Daniel
    Goncalves, Daniel
    [J]. PROCEEDINGS OF THE 2019 INTERNATIONAL CONFERENCE ON GRAPHICS AND INTERACTION (ICGI 2019), 2019, : 86 - 93
  • [6] Real-Time Analysis and Visualization of Pathogen Sequence Data
    Neher, Richard A.
    Bedford, Trevor
    [J]. JOURNAL OF CLINICAL MICROBIOLOGY, 2018, 56 (11)
  • [7] Real-Time Big Data Analysis Architecture and Application
    Sharma, Nandani
    Agarwal, Manisha
    [J]. DATA SCIENCE AND BIG DATA ANALYTICS, 2019, 16 : 313 - 320
  • [8] Real-time Big Data Technologies of Energy Internet Platform
    Wang Guilan
    Zhou Guoliang
    Zhao Hongshan
    Liu Hongyang
    [J]. 2016 IEEE INTERNATIONAL CONFERENCE ON POWER SYSTEM TECHNOLOGY (POWERCON), 2016,
  • [9] Data pipeline for real-time energy consumption data management and prediction
    Im, Jeonghwan
    Lee, Jaekyu
    Lee, Somin
    Kwon, Hyuk-Yoon
    [J]. FRONTIERS IN BIG DATA, 2024, 7
  • [10] Real-time analysis and management of big time-series data
    Biem, A.
    Feng, H.
    Riabov, A. V.
    Turaga, D. S.
    [J]. IBM JOURNAL OF RESEARCH AND DEVELOPMENT, 2013, 57 (3-4)