CN104468787A - Man-vehicle association identification method based on big data - Google Patents
Man-vehicle association identification method based on big data Download PDFInfo
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- CN104468787A CN104468787A CN201410744522.2A CN201410744522A CN104468787A CN 104468787 A CN104468787 A CN 104468787A CN 201410744522 A CN201410744522 A CN 201410744522A CN 104468787 A CN104468787 A CN 104468787A
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- 238000000034 method Methods 0.000 title claims abstract description 19
- 238000007619 statistical method Methods 0.000 claims abstract description 6
- 238000013507 mapping Methods 0.000 claims description 6
- 238000012098 association analyses Methods 0.000 claims description 2
- 238000004458 analytical method Methods 0.000 abstract description 5
- 238000005516 engineering process Methods 0.000 description 4
- 206010039203 Road traffic accident Diseases 0.000 description 2
- SAZUGELZHZOXHB-UHFFFAOYSA-N acecarbromal Chemical compound CCC(Br)(CC)C(=O)NC(=O)NC(C)=O SAZUGELZHZOXHB-UHFFFAOYSA-N 0.000 description 2
- 238000007405 data analysis Methods 0.000 description 2
- 238000010276 construction Methods 0.000 description 1
- 238000007418 data mining Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000011835 investigation Methods 0.000 description 1
- 238000007726 management method Methods 0.000 description 1
- 230000006855 networking Effects 0.000 description 1
- 238000005457 optimization Methods 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/27—Replication, distribution or synchronisation of data between databases or within a distributed database system; Distributed database system architectures therefor
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
- G06F16/284—Relational databases
- G06F16/288—Entity relationship models
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W24/00—Supervisory, monitoring or testing arrangements
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/02—Services making use of location information
- H04W4/029—Location-based management or tracking services
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- General Engineering & Computer Science (AREA)
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- Traffic Control Systems (AREA)
Abstract
The invention provides a man-vehicle association identification method based on big data, which belongs to the field of big data. And the driving track of the target vehicle is extracted through the vehicle passing information of the card ports, and the mobile phone information at the corresponding time of each card port is subjected to statistical analysis. Through acquiring vehicle passing data, wireless MSC data and mobile phone user real name registration data of a traffic gate, intelligent analysis and comparison are carried out, and personnel in a target vehicle in a certain time range are rapidly and intelligently identified.
Description
Technical field
The present invention relates to large data technique, particularly relate to a kind of people's car based on large data association recognition methods.
Background technology
Large data (Big data) are commonly used to a large amount of unstructured data and the semi-structured data that describe company's creation, and these data can overspending time and money when downloading to relevant database for analyzing.Normal and the cloud computing of large data analysis is linked together, because the real-time framework of large data set analysis needs as MapReduce, HBase shares out the work to tens of, hundreds of or even thousands of computers.Large data analysis, compared to traditional data warehouse applications, has the features such as data volume is large, query analysis is complicated.Large data need special technology, effectively to process the data in a large amount of tolerance elapsed time.Be applicable to the technology of large data, comprise MPP (MPP) database, data mining electrical network, distributed file system, distributed data base, cloud computing platform, the Internet and extendible storage system.
Large data can be divided into the fields such as large data technique, large data engineering, large data science and large market demand.It is large data technique and large market demand that current people talk about maximum.Engineering and problem in science are not yet taken seriously.Large data engineering refers to the system engineering of the planning construction operation management of large data; Large data science pays close attention in the development of large data network and operation process the rule and and the relation between nature and social activities thereof that find and verify large data.
Internet of Things, cloud computing, mobile Internet, car networking, mobile phone, panel computer, PC and spread all over the various transducers in each corner of the earth, none is not the mode of Data Source or carrying.
The most crucial value of large data is exactly be to carry out storing and analyzing for mass data.Compared with existing other technologies, the integrated cost of " cheap, rapid, optimization " this three aspect of large data is optimum.
To investigate and collect evidence in traffic accident treatment comprehensive even Problem-Error, and may cause series of problems thus, the identification of road traffic accident vehicle driver is investigated and collected evidence comparatively difficulty.By large data separate in traffic system, technical problem to be solved at present could be become in order to solve the difficult situation of existing investigation.
Summary of the invention
The present invention adopts based on the method for large data processing, can position the personnel in the target vehicle corresponding time period, analyzes and sets up people and associate with car.Relatively-stationary driver in the corresponding time range of designated vehicle is identified.
By obtaining the car data excessively of traffic block port, wireless MSC data, cellphone subscriber's real name registration data of operator, carries out intellectual analysis comparison, fast the personnel identified in the car of target carriage within the scope of certain hour of intelligence.The method is made up of 4 parts: the mapping of positional information and data encasement in (1) MSC.(2) according to bayonet socket data, the driving trace of target vehicle at the appointed time in scope is depicted.(3) according to the driving trace of target carriage, statistical analysis is carried out to the MSC cellphone information of each bayonet socket corresponding time.Draw to there is the potential cell-phone number associated with target vehicle.(4) by cellphone subscriber's real name registration data, people is associated with vehicle.
The present invention mainly comprises following process:
(1) preparation of data:
By the real-time write HBase database of car information of crossing of bayonet socket, comprise information of vehicles, spend the car time, bayonet socket numbering etc., wherein rowkey is the number-plate number+mistake car time.MSC information is carried out mapping and preliminary treatment, enters HBase storehouse.Wherein comprise the msisdn of mobile phone, imei, imsi, dest_lac, dest_ci, the time, zone name etc., rowkey is the bayonet socket ID+ time.The ID of bayonet socket maps according to dest_lac and dest_ci, is this bayonet socket ID by the base station maps near bayonet socket.
(2) acquisition of target vehicle driving trace:
The license plate number inputted by user and corresponding time period, in HBase, carry out scan according to rowkey, the driving trace that target vehicle is complete within a period of time can be drawn.Mainly comprise the bayonet socket that vehicle once occurred, and the corresponding time.
(3) association analysis of vehicle and cellphone information:
According to the bayonet socket that target vehicle once occurred, and the time that correspondence occurs at bayonet socket, search the cellphone information near this bayonet socket before and after the corresponding time within a few minutes, obtain the mobile phone list occurred.These phone numbers of statistical analysis number of times that base station occurs near corresponding bayonet socket.The potential relevance of the cell-phone number that occurrence number is higher is stronger.
(4) foundation of people's car association:
According to the real name register information of cellphone subscriber, can cellphone subscriber be obtained, thus establish people's incidence relation corresponding with vehicle.
By obtaining the car data excessively of traffic block port, wireless MSC data, cellphone subscriber's real name registration data of operator, carries out intellectual analysis comparison, fast the personnel identified in the car of target carriage within the scope of certain hour of intelligence.
Accompanying drawing explanation
Fig. 1 is that cellphone information maps schematic diagram.
Fig. 2 is raw-data map.
Embodiment
First to process and the preparation of mobile phone position information in MSC, thus be convenient to be associated with bayonet socket.And cross car information by bayonet socket, extract the driving trace of target carriage, and statistical analysis is carried out to the cellphone information in each bayonet socket corresponding time.
More detailed elaboration is carried out to content of the present invention below:
(1) bayonet socket is crossed in car information write HBase database.Initial data is as accompanying drawing 2;
(2) cellphone information is write in HBase database, map according to dest_lac and dest_ci of different operator base stations and neighbouring bayonet socket.By the base station association around bayonet socket to this bayonet socket ID.Bayonet socket ID such as corresponding to dest_lac:54021 dest_ci:33281 base station is 3701126116.By the bayonet socket ID after mapping together stored in HBase.As accompanying drawing 1;
(3) trace information of the corresponding time period of query aim vehicle.Such as search license plate number be Shandong A12345 at 2013-11-29, the driving trace of 8 o'clock to 10 o'clock, can return 4 results (be 3701126151,3701126190 respectively through ID, the bayonet socket of 3701126235,3701126116).The corresponding time through bayonet socket is respectively: 08:20:00,08:23:00,08:35:00,09:13:00;
(4) search through each bayonet socket time before and after a period of time in cellphone information.Such as in the base station that bayonet socket ID is near 3701126151, search the data in mobile phone within two minutes before and after 08:20:00;
(5) number of times that cell-phone number occurs in each bayonet socket of track of vehicle is added up.
Claims (5)
1., based on people's car association recognition methods of large data, it is characterized in that, the method is made up of 4 parts:
(1) mapping of positional information and data encasement in MSC;
(2) according to bayonet socket data, the driving trace of target vehicle at the appointed time in scope is depicted;
(3) according to the driving trace of target carriage, statistical analysis is carried out to the MSC cellphone information of each bayonet socket corresponding time; Draw to there is the potential cell-phone number associated with target vehicle;
(4) by cellphone subscriber's real name registration data, people is associated with vehicle.
2. method according to claim 1, is characterized in that,
The mapping of positional information and data encasement in MSC:
By the real-time write HBase database of car information of crossing of bayonet socket, comprise information of vehicles, spend the car time, bayonet socket numbering etc., wherein rowkey is the number-plate number+mistake car time; MSC information is carried out mapping and preliminary treatment, enters HBase storehouse; Wherein comprise the msisdn of mobile phone, imei, imsi, dest_lac, dest_ci, the time, zone name, rowkey is the bayonet socket ID+ time; The ID of bayonet socket maps according to dest_lac and dest_ci, is this bayonet socket ID by the base station maps near bayonet socket.
3. method according to claim 1, is characterized in that,
The acquisition of target vehicle driving trace:
The license plate number inputted by user and corresponding time period, in HBase, carry out scan according to rowkey, the driving trace that target vehicle is complete within a period of time can be drawn.
4. method according to claim 1, is characterized in that,
The association analysis of vehicle and cellphone information:
According to the bayonet socket that target vehicle once occurred, and the time that correspondence occurs at bayonet socket, search the cellphone information near this bayonet socket before and after the corresponding time within a few minutes, obtain the mobile phone list occurred; These phone numbers of statistical analysis number of times that base station occurs near corresponding bayonet socket; The potential relevance of the cell-phone number that occurrence number is higher is stronger.
5. method according to claim 1, is characterized in that,
The foundation of people's car association:
According to the real name register information of cellphone subscriber, can cellphone subscriber be obtained, thus establish people's incidence relation corresponding with vehicle.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104965908A (en) * | 2015-06-30 | 2015-10-07 | 北京奇艺世纪科技有限公司 | Position range determining method and apparatus |
| CN105282703A (en) * | 2015-09-29 | 2016-01-27 | 北京万集科技股份有限公司 | Method and system for connecting vehicle with in-vehicle mobile terminal |
| CN105357496A (en) * | 2015-12-09 | 2016-02-24 | 武汉大学 | Multisource big data fused video monitoring pedestrian identity identification method |
| CN106303962A (en) * | 2016-08-17 | 2017-01-04 | 公安部道路交通安全研究中心 | A kind of method and system realizing people's car information association |
| CN106611167A (en) * | 2016-12-28 | 2017-05-03 | 山东合天智汇信息技术有限公司 | Tracking method and system |
| CN106855979A (en) * | 2015-12-08 | 2017-06-16 | 亿阳信通股份有限公司 | Data correlation System and method for |
| CN107067730A (en) * | 2017-02-24 | 2017-08-18 | 江苏智通交通科技有限公司 | Net based on the tollgate devices about inconsistent monitoring method of car people car |
| CN107480246A (en) * | 2017-08-10 | 2017-12-15 | 北京中航安通科技有限公司 | A kind of recognition methods of associate people and device |
| CN107610465A (en) * | 2017-09-22 | 2018-01-19 | 杭州玳数科技有限公司 | A kind of traffic monitoring data matching method, system and storage device |
| CN107645709A (en) * | 2017-09-28 | 2018-01-30 | 浙江大华技术股份有限公司 | A kind of method and device for determining personal information |
| CN107862264A (en) * | 2017-10-27 | 2018-03-30 | 武汉烽火众智数字技术有限责任公司 | A kind of vehicle secondary identifying system and its method for serving data analytical center |
| CN108074301A (en) * | 2016-11-15 | 2018-05-25 | 方正国际软件(北京)有限公司 | A kind of system of real name method and device of transportation card |
| CN108573605A (en) * | 2017-03-13 | 2018-09-25 | 北京万集科技股份有限公司 | A kind of vehicle termination matching process and device |
| CN108848460A (en) * | 2018-05-31 | 2018-11-20 | 重庆市城投金卡信息产业股份有限公司 | People's vehicle correlating method based on RFID and GPS data |
| CN109033451A (en) * | 2018-08-21 | 2018-12-18 | 北京深瞐科技有限公司 | People's vehicle dynamic file analysis method and device |
| CN109635857A (en) * | 2018-11-29 | 2019-04-16 | 东软集团股份有限公司 | People's wheel paths method for monitoring and analyzing, device, equipment and storage medium |
| CN109634946A (en) * | 2018-12-06 | 2019-04-16 | 南京森根科技发展有限公司 | A kind of track intelligent Matching association analysis algorithm model excavated based on big data |
| CN109671189A (en) * | 2018-10-30 | 2019-04-23 | 南京杰迈视讯科技有限公司 | A kind of smart exit-entrance system based on face and vehicle linked character |
| CN110312201A (en) * | 2018-03-22 | 2019-10-08 | 宝鸡市公安局交通警察支队 | People's vehicle correlating method and system based on communication network and vehicle information acquisition system |
| CN110517500A (en) * | 2018-05-21 | 2019-11-29 | 上海大唐移动通信设备有限公司 | A kind of people's vehicle association process method and device |
| CN110611886A (en) * | 2019-08-01 | 2019-12-24 | 北京北大千方科技有限公司 | Vehicle-mounted mobile phone information acquisition method and device, electronic equipment and medium |
| CN111159254A (en) * | 2019-12-30 | 2020-05-15 | 武汉长江通信产业集团股份有限公司 | Big data processing-based vehicle and person association method |
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008276362A (en) * | 2007-04-26 | 2008-11-13 | Hitachi Ltd | Information distribution system and information distribution method based on position information |
| CN103237201A (en) * | 2013-04-28 | 2013-08-07 | 江苏物联网研究发展中心 | Case video studying and judging method based on social annotation |
| CN103325245A (en) * | 2013-06-25 | 2013-09-25 | 中国科学院信息工程研究所 | Method for predicting space-time traveling track of blacklisted vehicle |
| CN103366573A (en) * | 2013-07-10 | 2013-10-23 | 中兴智能交通（无锡）有限公司 | Vehicle running information tracking method and system based on cloud computing |
| CN104035954A (en) * | 2014-03-18 | 2014-09-10 | 杭州电子科技大学 | Hadoop-based recognition method for fake-licensed car |
-
2014
- 2014-12-09 CN CN201410744522.2A patent/CN104468787A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2008276362A (en) * | 2007-04-26 | 2008-11-13 | Hitachi Ltd | Information distribution system and information distribution method based on position information |
| CN103237201A (en) * | 2013-04-28 | 2013-08-07 | 江苏物联网研究发展中心 | Case video studying and judging method based on social annotation |
| CN103325245A (en) * | 2013-06-25 | 2013-09-25 | 中国科学院信息工程研究所 | Method for predicting space-time traveling track of blacklisted vehicle |
| CN103366573A (en) * | 2013-07-10 | 2013-10-23 | 中兴智能交通（无锡）有限公司 | Vehicle running information tracking method and system based on cloud computing |
| CN104035954A (en) * | 2014-03-18 | 2014-09-10 | 杭州电子科技大学 | Hadoop-based recognition method for fake-licensed car |
Non-Patent Citations (1)
| Title |
|---|
| 庄华，于金虎: "车辆轨迹侦查", 《政法学刊》 * |
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| CN109634946B (en) * | 2018-12-06 | 2020-08-18 | 南京森根科技股份有限公司 | Intelligent track matching correlation analysis method based on big data mining |
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| CN111177487A (en) * | 2019-12-19 | 2020-05-19 | 北京明略软件系统有限公司 | Incidence relation determining method and device, electronic equipment and storage medium |
| CN111159254A (en) * | 2019-12-30 | 2020-05-15 | 武汉长江通信产业集团股份有限公司 | Big data processing-based vehicle and person association method |
| CN111199644A (en) * | 2020-01-06 | 2020-05-26 | 山东合天智汇信息技术有限公司 | Method and system for automatically fitting people and vehicles |
| CN111881379A (en) * | 2020-09-27 | 2020-11-03 | 武汉中科通达高新技术股份有限公司 | Traffic management data processing method and device |
| WO2022062289A1 (en) * | 2020-09-27 | 2022-03-31 | 武汉中科通达高新技术股份有限公司 | Traffic management data processing method and apparatus |
| CN113487865A (en) * | 2021-07-02 | 2021-10-08 | 江西锦路科技开发有限公司 | System and method for acquiring information of vehicles running on highway |
| CN113487865B (en) * | 2021-07-02 | 2022-07-22 | 江西锦路科技开发有限公司 | System and method for acquiring information of vehicles running on highway |
| CN113821734A (en) * | 2021-08-16 | 2021-12-21 | 北京中交兴路信息科技有限公司 | Method, device, equipment and medium for identifying double drivers based on track data |
| CN113821734B (en) * | 2021-08-16 | 2024-03-19 | 北京中交兴路信息科技有限公司 | Method, device, equipment and medium for identifying double drivers based on track data |
| CN113870574A (en) * | 2021-09-17 | 2021-12-31 | 南京熊猫电子股份有限公司 | System and method for automatically detecting passenger car illegal passenger carrying early warning |
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