一种面向车辆位置信息的异构数据实时云存储及可视化
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摘要
随着各种机动车数量连年持续不断的增长,如何对其进行实时有效的管理就成为有关部门面临的迫切需要解决的实际问题.利用基于物联网技术所发展起来的车联网方案来解决此类问题成为了一个必然的方向.本文提出一种基于移动终端的异构数据获取并远程实时的云存储及相关数据融合并可视化的系统架构.开发移动终端应用程序用于实时获取文本、图片、视频三种具有不同数据结构特点的异构数据,在远程通信的基础上实现三种数据的分类云存储,并在云存储的基础上实现数据融合等相关应用.测试表明,整个系统工作稳定有效,效率较高,可以满足相关部门对于车辆管理的需求.
With the continuous growth of various types of motor vehicles, how to manage them in real time and effectively has become an urgent problem that the relevant departments urgently need to solve. It is an inevitable direction to solve such problems by using the Internet of Vehicles solution developed based on the Internet of Things technology. This paper proposes a system architecture based on heterogeneous data acquisition and remote real-time cloud storage and related data fusion and visualization based on mobile terminals. Develop mobile terminal application for real-time access to heterogeneous data with different data structure characteristics of text, picture, and video, realize classification cloud storage of three kinds of data on the basis of remote communication, and realize data on the basis of cloud storage fusion and other related applications. Tests show that the whole system works stably and efficiently, and has high efficiency, which can meet the needs of relevant departments for vehicle management.
With the continuous growth of various types of motor vehicles, how to manage them in real time and effectively has become an urgent problem that the relevant departments urgently need to solve. It is an inevitable direction to solve such problems by using the Internet of Vehicles solution developed based on the Internet of Things technology. This paper proposes a system architecture based on heterogeneous data acquisition and remote real-time cloud storage and related data fusion and visualization based on mobile terminals. Develop mobile terminal application for real-time access to heterogeneous data with different data structure characteristics of text, picture, and video, realize classification cloud storage of three kinds of data on the basis of remote communication, and realize data on the basis of cloud storage fusion and other related applications. Tests show that the whole system works stably and efficiently, and has high efficiency, which can meet the needs of relevant departments for vehicle management.
引文
[1] 新华社.2017年底:我国机动车保有量3.10亿辆驾驶人3.85亿人[EB/OL].(2018-01-15).http://www.gov.cn/xinwen/2018-01/15/content_5256832.htm.
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[2] 史毅仁.车联网中数据融合的研究[D].北京:北京交通大学,2017.
[3] 肖楠.车联网环境下车载定位系统设计与实现[D].北京:北京交通大学,2016.
[4] 肖尧.智能交通信息采集与融合技术的应用研究[D].南昌:华东交通大学,2011.
[5] Buyya R,Yeo C S,Venugopal S,et al.Cloud computing and emerging IT platforms:Vision,hype,and reality for delivering computing as the 5th utility [J].Future Generation Computer Systems,2009,25(6):599-616.
[6] 周可,王桦,李春花.云存储技术及其应用[J].中兴通讯技术,2010 (4):24-27.
[7] Wen J R,Zheng S,Lu H.Semi-structured data storage schema selection:US20060053140A1[P].2006-03-09.
[8] Chun B T,Lee S H.A study on intelligent traffic system related with smart city [J].International Journal of Smart Home,2015,9(7):223-230.
[9] 李明伟.“互联网+交通”融合发展的模式及建议[J].信阳师范学院学报(哲学社会科学版),2017(1):61-65.
[10] 庄恩瀚.物联网数据融合研究[D].石家庄:石家庄铁道大学信息科学与技术学院,2014.
[11] 张念慈.基于数据融合的实时数据处理应用研究[D].武汉:武汉理工大学计算机科学与技术学院,2010.
[12] Shin W,Kiyomoto S,Fukushima K,et al.A Formal Model to Analyze the Permission Authorization and Enforcement in the Android Framework [C]// IEEE Second International Conference on Social Computing.IEEE,2010:944-951.
[13] Shvachko K V.HDFS Scalability:The limits to growth[J].login:the magazine of USENIX & SAGE,2010,35(2):6-16.
[14] Ding B,Chao A N.Research on AJAX development based on Struts2 framework [J].Computer Engineering & Design,2009,30(16):3910-3902.
[15] NettiK.Interactive Guided Online/Off-line search using Google API and JSON [J].International Journal of Computer Science Issues (IJCSI),2010,7(5):21-25.