本文選題：大數(shù)據(jù) + 數(shù)據(jù)挖掘�。� 參考：《計(jì)算機(jī)工程》2017年05期

【摘要】：針對(duì)現(xiàn)有公安違法取證分析系統(tǒng)存在效率低下、功能單一的問(wèn)題,提出基于云平臺(tái)和大數(shù)據(jù)的違法取證分析系統(tǒng)。利用Mongo DB存儲(chǔ)原始海量的車輛軌跡數(shù)據(jù),采用MapReduce分布式計(jì)算對(duì)軌跡數(shù)據(jù)進(jìn)行挖掘與篩選,通過(guò)大數(shù)據(jù)平臺(tái)上的系統(tǒng)調(diào)度器對(duì)系統(tǒng)各層資源進(jìn)行有效調(diào)度并監(jiān)控系統(tǒng)運(yùn)行狀態(tài)�；�于提取的離散軌跡數(shù)據(jù)對(duì)違反規(guī)定時(shí)間行駛、違法規(guī)定路線行駛、疲勞駕駛3種交通違法行為進(jìn)行取證分析,從而找出違法車輛。實(shí)驗(yàn)結(jié)果表明,當(dāng)車輛軌跡數(shù)據(jù)規(guī)模較大時(shí),該系統(tǒng)仍具有較高的運(yùn)行效率及穩(wěn)定性。
[Abstract]:In view of the problems of low efficiency and single function in the existing public security illegal forensics analysis system, a criminal forensics analysis system based on cloud platform and big data is put forward. Mongo DB is used to store the original massive vehicle trajectory data, MapReduce distributed computing is used to mine and filter the track data, and the system scheduler on big data platform is used to effectively schedule the system resources and monitor the system running state. Based on the collected discrete track data, three kinds of illegal traffic behaviors, such as breaking the prescribed time, illegal route and fatigue driving, are analyzed to find out the illegal vehicles. The experimental results show that the system still has high efficiency and stability when the vehicle track data scale is large.
【作者單位】： 武漢大學(xué)計(jì)算機(jī)學(xué)院;公安部交通管理科學(xué)研究所;武漢大學(xué)國(guó)家衛(wèi)星定位系統(tǒng)工程技術(shù)研究中心;
【基金】：國(guó)家“863”計(jì)劃項(xiàng)目(2013AA12A206) 道路交通安全公安部重點(diǎn)實(shí)驗(yàn)室開(kāi)放課題(2016ZDSYSKFKT04) 中國(guó)工程院重大咨詢項(xiàng)目
【分類號(hào)】：D631.2;TP311.13

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