CN116935372A - Vehicle fake license judgment method, system, storage medium and terminal equipment - Google Patents
Vehicle fake license judgment method, system, storage medium and terminal equipment Download PDFInfo
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Abstract
The invention relates to a vehicle fake-licensed judging method, a system, a storage medium and a terminal device, which calculate the shortest time spent for storing a vehicle from one collection point to another in advance; then according to the license plate number and the sampling time of each sampling point, sampling points and the passing time which are sequentially passed in a period of time of the license plate number to be inspected are obtained; judging whether the time spent by the license plate number to be inspected from the previous passing point to the later passing point is not less than the shortest time required by the two sampling points; namely judging whether all the time spent by adjacent positions in the running track of the vehicle is not less than a preset time minimum threshold value; if yes, judging that the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the situation that the time spent by the two positions is smaller than the preset shortest time exists, and the situation can not be realized, and the vehicle corresponding to the license plate number to be checked can be judged to be the fake-licensed vehicle.
Description
Technical Field
The invention relates to the technical field of block chains, in particular to a vehicle fake-licensed judging method based on a block chain.
Background
The vehicle license plate refers to the license plate number of other vehicles which are stolen or illegally used. Specifically, when one person uses a number on another person's license plate to travel on a road, a vehicle fake-licensed behavior is constituted. Vehicle decks are often created to evade the penalty of traffic violations or to conduct other violations. Such behavior can lead to serious problems such as road safety hazards, random theft of other assets, etc.
Because motor vehicles and license plates are not regulated, the behavior of the fake license plates has a trend of increasing, and the fake license plates are developed from the use of civil license plates to the use of special license plates, army license plates and warning license plates; the development from refitting and assembling the license plate of the vehicle to the license plate of the abandoned vehicle and robbing the vehicle and then to the re-acquisition of the license plate of the motor vehicle by deception and brining means occurs. Meanwhile, as the number of motor vehicles increases, police field investigation is required for identifying the vehicle fake license, or the vehicles are actively reported by a fake license user, the background is further verified, and the manual investigation cost is further increased.
A blockchain is a chain database linked back and forth by multiple blocks of data that is commonly built and maintained between computing nodes in a distributed peer-to-peer network. Currently, the blockchain technology has fused a plurality of front edge technologies such as a distributed network technology, a consensus algorithm, an intelligent contract technology, a password algorithm and the like, and has the characteristics of non-falsification, privacy security, decentralization, multi-node cooperation and the like. These features make blockchain technology an effective means of solving the vehicle fake-licensed problem.
However, the existing fake-licensed car judgment method based on the blockchain has the defects that the distributed cooperation advantage of the blockchain is not exerted, the judgment rule is complex and not comprehensive enough. How to provide a fake-licensed car auxiliary judging method based on a block chain, simplifying and perfecting judging rules is a technical problem to be solved currently.
Disclosure of Invention
In order to solve the technical problems, the invention provides a vehicle fake-licensed judging method based on a block chain, which comprises the following steps:
s1: in a traffic network, N acquisition points { L }, are deployed 1 ,L 2 ,...,L N }，Calculating the collecting point L of the vehicle from any one i To another acquisition point L j The shortest time T that is required to be spent ij min The method comprises the steps of carrying out a first treatment on the surface of the N acquisition points { L ] 1 ,L 2 ,...,L N Sum of corresponding shortest time T ij min Uploading to a blockchain;
s2: obtain the sampling points { L }, passing through 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Uploading to the blockchain;
s3: obtaining a license plate number to be inspected;
s4: according to { L } passing through each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time which pass through the license plate number to be inspected in turn within a period of time; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is not less than the shortest time T spent between two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the If yes, the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the vehicle corresponding to the license plate number to be checked is a fake-licensed vehicle.
Further, step S2 includes:
s21: collecting all collecting points { L }, in real time 1 ,L 2 ,...,L N Picture data P ik And record the sampling time T ik ；
S22: according to the picture data P of each acquisition point at each moment ik Each acquisition point { L } is identified 1 ,L 2 ,...,L N License plate number C passing each moment ikr And picture P of the vehicle ik Acquisition time T of corresponding vehicle picture ik And license plate number C ikr As a dataset { P ik ,T ik ,C ikr Upload to the blockchain.
Further, the license plate number to be checked is the license plate number collected in the step S2 or the license plate number registered in the license plate tube.
Further, the method further comprises the following steps: distributing the license plate numbers to be checked to a plurality of fake-licensed car judging nodes according to a task distribution algorithm, and uploading the acquired license plate numbers and task distribution conditions to a block chain;
further, the task allocation algorithm specifically comprises the following steps:
average distribution;
or, according to the node calculation force distribution, the higher the calculation force is, the more license plates to be inspected are distributed;
or, distributing the credit value obtained by calculation according to the node attribute, wherein the higher the credit value is, the more license plates to be inspected are distributed;
or, according to the calculated load distribution of the nodes, the higher the load is, the less license plates to be inspected are distributed.
In another aspect, a blockchain-based vehicle fake-licensed determination system is configured to perform any of the above-described vehicle fake-licensed determination methods; the system comprises:
a data storage module for storing N acquisition points { L ] 1 ,L 2 ,...,L N -and the vehicle from any one of the collection points L i To another acquisition point L j The shortest time T that is required to be spent ij min ；
A data acquisition module for acquiring the data of each sampling point { L } 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Uploading to the blockchain;
the task acquisition module is used for acquiring the license plate number to be inspected; preferably, the method further comprises the step of distributing the license plate number to be inspected to a plurality of judging modules, namely the fake-licensed car judging nodes.
A judging module for judging the { L } passing through each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time of the license plate numbers to be inspected in sequence; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is less than the shortest time T required by the two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the If yes, the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the vehicle corresponding to the license plate number to be checked is a fake-licensed vehicle.
Further, the license plate identification system further comprises a manual confirmation module which is used for inquiring the running track and the owner information of the vehicle according to the suspected license plate number, manually judging whether the license plate number is sleeved, and uploading the judgment result to the block chain.
Further, the system also comprises a block chain certification module which is used for storing and verifying the information generated by each module and providing data query service for each module.
In another aspect, the present invention also provides a computer storage medium storing executable program code; the executable program code is configured to execute any of the vehicle fake-licensed determination methods described above.
In another aspect, a terminal device includes a memory and a processor; the memory stores program code executable by the processor; the program code is used in any of the above-described vehicle fake-licensed determination methods.
The invention provides a vehicle fake-licensed judging method, a system, a storage medium and a terminal device, which pre-calculate and store a vehicle from a collection point L i To another acquisition point L j The shortest time T that is required to be spent ij min The method comprises the steps of carrying out a first treatment on the surface of the Then according to { L } passing each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time which pass through the license plate number to be inspected in turn within a period of time; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is not less than the shortest time T spent by the two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the Namely judging whether all the time spent by adjacent positions in the running track of the vehicle is not less than a preset time minimum threshold value; if yes, judging that the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the time spent by the existence of two positions is less than the preset minimum time T ij min The situation that the license plate number to be checked corresponds to the vehicle is not realized, and the license plate number to be checked can be judged to be the fake license plate vehicle. The method comprises the following steps: on the one hand, a fake-licensed car auxiliary judging method is provided, which can identify whether the number of the license plate has suspicion of fake licensed or not only by judging whether the time of the adjacent position in the running track of the vehicle is less than the preset shortest time, and other comparison judgment is not needed, so that judgment is carried outThe method has the advantages that the rule is comprehensive, the rule is concise, the calculated amount is small, compared with the prior art, the fake-licensed vehicle with similar appearance can be avoided, compared with the prior art, the calculated amount can be reduced, and the judging efficiency can be improved; on the other hand: the distributed cooperation characteristics of the distributed block chains of the block chains are fully developed, the characteristics of tamper resistance and the like are achieved, and the precision and accuracy of the fake-licensed vehicle judgment can be further improved. Preferably, a calculation task allocation method is provided, wherein a rationality task for judging a vehicle driving path is allocated to a plurality of blockchain nodes for calculation, so that the calculation pressure of a central calculation node is reduced, and the efficiency of judging the fake-licensed vehicle is improved.
Drawings
FIG. 1 is a flow chart of one embodiment of a blockchain-based vehicle fake-licensed determination method of the present invention;
FIG. 2 is a schematic block-chain based vehicle fake-licensed determination system of one embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and fully with reference to the accompanying drawings, in which it is evident that the embodiments described are only some, but not all embodiments of the invention. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
It should be noted that, in the embodiment of the present invention, directional indications such as up, down, left, right, front, and rear … … are referred to, and the directional indications are merely used to explain the relative positional relationship, movement conditions, and the like between the components in a specific posture, and if the specific posture is changed, the directional indications are correspondingly changed. In addition, if there are descriptions of "first, second", "S1, S2", "step one, step two", etc. in the embodiments of the present invention, the descriptions are only for descriptive purposes, and are not to be construed as indicating or implying relative importance or implying that the number of technical features indicated or indicating the execution sequence of the method, etc. it will be understood by those skilled in the art that all matters in the technical concept of the present invention are included in the scope of this invention without departing from the gist of the present invention.
As shown in fig. 1, the present invention provides a vehicle fake-licensed determination method based on a blockchain, including:
s1: in a traffic network, N acquisition points { L }, are deployed 1 ,L 2 ,...,L N Calculating the vehicle from any one collecting point L i To another acquisition point L j The shortest time T that is required to be spent ij min The method comprises the steps of carrying out a first treatment on the surface of the N acquisition points { L ] 1 ,L 2 ,...,L N Sum of corresponding shortest time T ij min Uploading to a blockchain;
specifically, the N acquisition points { L } are optionally but not limited to deployed in the traffic network according to a monitoring system of the traffic network 1 ,L 2 ,...,L N Determining a data acquisition point L according to the distance of each acquisition point, road conditions (such as road type, traffic flow and the like, particularly, expressways have better vehicle conditions, run quickly, small roads have poor vehicle conditions and slow running, small traffic flow has fast running, large traffic flow and even traffic jam have slow running) and the like i To another data acquisition point L j The shortest time T that is required to be spent ij min And storing the above information { L }, via the traffic network data storage node 1 ,L 2 ,...,L N Sum T ij min To the blockchain, preferably, but not limited to, dynamically updated at time intervals, etc.
S2: obtain the sampling points { L }, passing through 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Uploading to the blockchain;
preferably, the method comprises the following steps:
s21: collecting all collecting points { L }, in real time 1 ,L 2 ,...,L N Picture data P ik And record the sampling time T ik I.e. the elapsed time of the vehicle;
in particular, the selection ofBut not limited to, using monitoring equipment in existing traffic networks where N sampling points { L } are deployed 1 ,L 2 ,...,L N Collecting photos or videos of all collecting points, and identifying vehicle pictures at all moments of all collecting points through the photos or videos, such as a vehicle picture P at the kth moment of the ith collecting point ik And record and collect the vehicle picture P ik Acquisition time T of (1) ik ；
S22: according to the picture data P of each acquisition point at each moment ik Each acquisition point { L } is identified 1 ,L 2 ,...,L N License plate number C passing each moment ikr And picture P of the vehicle ik Acquisition time T of corresponding vehicle picture ik And license plate number C ikr As a dataset { P ik ,T ik ,C ikr Uploading to the blockchain;
specifically, C ikr Optionally but not limited to a license plate number corresponding to a vehicle, when picture P ik When there are a plurality of vehicles, i.e. corresponding to the same P ik ,T ik With a plurality of C ik1 、C ik2 … … and is uploaded to the blockchain as a total dataset or datasets.
S3: obtaining a license plate number to be inspected; specifically, the license plate number to be inspected is extracted from the identified license plate numbers optionally but not limited to; or randomly acquiring all or part of registered license plates in a license plate house in a certain area at one time to be the license plate number to be inspected or acquiring the registered license plates in turn according to ascending order or descending order to be the license plate number to be inspected;
preferably, step S3, further optionally but not limited to, includes: s3': distributing the acquired license plate numbers to a plurality of fake-licensed car judging nodes according to a task distribution algorithm, and uploading the acquired license plate numbers and task distribution conditions to a block chain;
specifically, the task allocation nodes are optionally, but not limited to, deployed in the blockchain to complete the above-mentioned work, so as to improve the efficiency and accuracy of the fake-licensed vehicle judgment.
More preferably, the specific allocation manner is selected but not limited to:
1. average distribution;
2. distributing according to the node calculation force, wherein the higher the calculation force is, the more license plates to be inspected are distributed;
3. distributing the credit values obtained by calculation according to the node attributes, wherein the higher the credit values are, the more license plates to be inspected are distributed;
4. and according to the calculated load distribution of the nodes, the higher the load is, the less license plates to be inspected are distributed.
S4: according to { L } passing through each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time which pass through the license plate number to be inspected in turn within a period of time; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is not less than the shortest time T spent between two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the If yes, the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the vehicle corresponding to the license plate number to be checked is a fake-licensed vehicle. It should be noted that, since the vehicle corresponding to the license plate number to be inspected may pass through a plurality of sampling points within the period of time, when determining, if only one adjacent time is less than the shortest time required by two sampling points, the "no" is considered to be true, and the vehicle corresponding to the license plate number to be inspected is a fake-licensed vehicle.
In this embodiment, a blockchain-based vehicle fake-licensed determination method of the present invention is presented that pre-calculates the stored vehicle from one collection point L i To another acquisition point L j The shortest time T that is required to be spent ij min The method comprises the steps of carrying out a first treatment on the surface of the Then according to { L } passing each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time which pass through the license plate number to be inspected in turn within a period of time; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is not less than the shortest time T spent by the two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the Namely judging whether all the time spent by adjacent positions in the running track of the vehicle is not less than a preset time minimum threshold value; if yes, judgeDetermining the vehicle corresponding to the license plate number to be checked as a non-fake license plate vehicle; if not, the time spent by the existence of two positions is less than the preset minimum time T ij min The situation that the license plate number to be checked corresponds to the vehicle is not realized, and the license plate number to be checked can be judged to be the fake license plate vehicle. The method comprises the following steps: on one hand, the auxiliary fake-licensed car judging method is provided, which only needs to judge whether the time of the adjacent positions in the running track of the car is less than the preset shortest time, and can identify whether the license plate number has the suspicion of the fake licensed or not, other comparison judgment is not needed, the judging rule is comprehensive, the rule is concise, the calculated amount is small, compared with the prior art, the fake-licensed car with similar appearance can be avoided, compared with the prior art, the calculated amount can be reduced, and the judging efficiency is improved; on the other hand: the distributed cooperation characteristics of the distributed block chains of the block chains are fully developed, the characteristics of tamper resistance and the like are achieved, and the precision and accuracy of the fake-licensed vehicle judgment can be further improved. Preferably, a calculation task allocation method is provided, wherein a rationality task for judging a vehicle driving path is allocated to a plurality of blockchain nodes for calculation, so that the calculation pressure of a central calculation node is reduced, and the efficiency of judging the fake-licensed vehicle is improved.
On the other hand, as shown in fig. 2, the present invention further provides a vehicle fake-licensed determination system based on a blockchain, including:
a data storage module for storing N acquisition points { L ] 1 ,L 2 ,...,L N -and the vehicle from any one of the collection points L i To another acquisition point L j The shortest time T that is required to be spent ij min ；
A data acquisition module for acquiring the data of each sampling point { L } 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Uploading to the blockchain;
the task acquisition module is used for acquiring the license plate number to be inspected; preferably, the method further comprises the step of distributing the license plate number to be inspected to a plurality of judging modules, namely the fake-licensed car judging nodes.
A judging module for judging the { L } passing through each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time of the license plate numbers to be inspected in sequence; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is less than the shortest time T required by the two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the If yes, the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the vehicle corresponding to the license plate number to be checked is a fake-licensed vehicle.
Preferably, the blockchain-based vehicle fake-licensed determination system of the present invention may also optionally, but not be limited to, include:
and a manual confirmation module: the module is responsible for confirming whether the license plate number with the suspicion of the jacketed plate is truly jacketed, inquiring the running track of the vehicle and the owner information according to the license plate number with the suspicion of the jacketed plate, further judging whether the license plate number is jacketed manually, and uploading the judging result to a block chain.
Or/and, a blockchain certification module: the module is responsible for storing and verifying the information generated by the modules and providing data query services for the modules.
For further explanation of the above blockchain-based vehicle license plate determination method and system, it is assumed that a license plate number of a vehicle is "xiana·12345", and an example flow of determining whether the license plate number is suspected of being licensed is as follows:
the preparation stage: traffic network data storage node acquisition { L } 1 ,L 2 ,...,L N Sum T ij And uploaded to the blockchain; the license plate number "xiang a.12345" is registered to the license plate house;
and a data acquisition stage: each acquisition node acquires data { P } ik ,T ik ,C ikr Uploading to the blockchain;
task allocation stage: the license plate number 'Xiang A.12345' is acquired by a task allocation node and allocated to a certain fake-licensed car judgment node P;
judging stage of fake-licensed car: the fake-licensed vehicle judging node inquires the block chain about the acquisition point and time of the passing license plate number of Xiang A.12345 in a given time interval, if soIf the number of the polled data acquisition points is smaller than 2, directly judging that Hunan A.12345 is not sleeved, otherwise, taking time sequence as a sequence, assuming that vehicles of Hunan A.12345 pass through 4 data acquisition points in sequence: { P 11 ,T 11 ,C 111 }、{P 21 ,T 21 ,C 211 }、{P 31 ,T 31 ,C 311 }、{P 41 ,T 41 ,C 411 -a }; then the fake-licensed vehicle judging and calculating node inquires the blockchain of the shortest time T for the vehicle to pass through the adjacent data acquisition point ijmin The method comprises the steps of carrying out a first treatment on the surface of the Then sequentially judging (T 21 -T 11 )≥T 12min 、(T 31 -T 21 )≥T 23min 、(T 41 -T 31 )≥T 34min If the license plate number is not established, judging that the license plate number is suspected of being covered by the license plate number 'XiangA.12345', otherwise, judging that the license plate number is not covered by the license plate number 'XiangA.12345'; and finally, the fake-licensed car judging and calculating node uploads the judging result to the block chain.
In another aspect, the present invention also provides a computer storage medium storing executable program code; the executable program code is configured to perform any of the blockchain-based vehicle fake-licensed determination methods described above.
In another aspect, the present invention further provides a terminal device, including a memory and a processor; the memory stores program code executable by the processor; the program code is for performing any of the blockchain-based vehicle fake-licensed determination methods described above.
For example, the program code may be partitioned into one or more modules/units that are stored in the memory and executed by the processor to perform the present invention. The one or more modules/units may be a series of computer program instruction segments capable of performing the specified functions, which instruction segments describe the execution of the program code in the terminal device.
The terminal equipment can be computing equipment such as a desktop computer, a notebook computer, a palm computer, a cloud server and the like. The terminal device may include, but is not limited to, a processor, a memory. Those skilled in the art will appreciate that the terminal devices may also include input-output devices, network access devices, buses, and the like.
The processor may be a central processing unit (Central Processing Unit, CPU), but may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage may be an internal storage unit of the terminal device, such as a hard disk or a memory. The memory may also be an external storage device of the terminal device, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device. Further, the memory may also include both an internal storage unit of the terminal device and an external storage device. The memory is used for storing the program codes and other programs and data required by the terminal equipment. The memory may also be used to temporarily store data that has been output or is to be output.
The above-mentioned vehicle fake-license determining system based on the blockchain, the computer storage medium and the terminal device are created based on the above-mentioned vehicle fake-license determining method based on the blockchain, and the technical effects and the advantages thereof are not repeated herein, and each technical feature of the above-mentioned embodiment may be arbitrarily combined, so that the description is concise, and all possible combinations of each technical feature in the above-mentioned embodiment are not described, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope described in the present specification.
The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. The vehicle fake-licensed judging method based on the block chain is characterized by comprising the following steps of:
s1: in a traffic network, N acquisition points { L }, are deployed 1 ,L 2 ,...,L N Calculating the vehicle from any one collecting point L i To another acquisition point L j The shortest time T that is required to be spent ij min The method comprises the steps of carrying out a first treatment on the surface of the N acquisition points { L ] 1 ,L 2 ,...,L N Sum of corresponding shortest time T ij min Uploading to a blockchain;
s2: obtain the sampling points { L }, passing through 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Uploading to the blockchain;
s3: obtaining a license plate number to be inspected;
s4: according to { L } passing through each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time which pass through the license plate number to be inspected in turn within a period of time; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is not less than the shortest time T spent between two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the If yes, the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the vehicle corresponding to the license plate number to be checked is a fake-licensed vehicle.
2. The vehicle fake-licensed determination method according to claim 1, characterized by step S2, comprising:
s21: collecting all collecting points { L }, in real time 1 ,L 2 ,...,L N Picture data P ik And record the sampling time T ik ；
S22: according to the picture data of each acquisition point at each momentP ik Each acquisition point { L } is identified 1 ,L 2 ,...,L N License plate number C passing each moment ikr And picture P of the vehicle ik Acquisition time T of corresponding vehicle picture ik And license plate number C ikr As a dataset { P ik ,T ik ,C ikr Upload to the blockchain.
3. The method according to claim 1, wherein the license plate number to be inspected is a license plate number registered for the license plate number or the license plate tube collected in step S2.
4. The vehicle fake-licensed determination method according to claim 1, further comprising: and distributing the license plate numbers to be checked to a plurality of fake-licensed car judging nodes according to a task distribution algorithm, and uploading the acquired license plate numbers and task distribution conditions to a block chain.
5. The vehicle fake-licensed determination method according to claim 4, wherein the task allocation algorithm specifically includes:
average distribution;
or, according to the node calculation force distribution, the higher the calculation force is, the more license plates to be inspected are distributed;
or, distributing the credit value obtained by calculation according to the node attribute, wherein the higher the credit value is, the more license plates to be inspected are distributed;
or, according to the calculated load distribution of the nodes, the higher the load is, the less license plates to be inspected are distributed.
6. A blockchain-based vehicle fake-licensed determination system for performing the vehicle fake-licensed determination method of any one of claims 1-5; the system comprises:
a data storage module for storing N acquisition points { L ] 1 ,L 2 ,...,L N -and the vehicle from any one of the collection points L i To another acquisition point L j The shortest time T that is required to be spent ij min ；
A data acquisition module for acquiring the data of each sampling point { L } 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Uploading to the blockchain;
the task acquisition module is used for acquiring the license plate number to be inspected; preferably, the method further comprises the step of distributing the license plate number to be inspected to a plurality of judging modules, namely the fake-licensed car judging nodes.
A judging module for judging the { L } passing through each sampling point 1 ,L 2 ,...,L N License plate number C ikr Sampling time T ik Acquiring sampling points and elapsed time of the license plate numbers to be inspected in sequence; judging whether the time spent from the previous passing point to the later passing point of the license plate number to be checked is less than the shortest time T required by the two sampling points ij min The method comprises the steps of carrying out a first treatment on the surface of the If yes, the vehicle corresponding to the license plate number to be checked is a non-fake license plate vehicle; if not, the vehicle corresponding to the license plate number to be checked is a fake-licensed vehicle.
7. The vehicle fake-license determining system according to claim 6, further comprising a manual confirmation module for inquiring the traveling track of the vehicle and the owner information according to the suspected license plate number, manually determining whether the license plate number is fake-licensed, and uploading the determination result to the blockchain.
8. The vehicle fake-licensed determination system of claim 7, further comprising a blockchain certification module for storing and verifying information generated by each module and providing data query services for each module.
9. A computer storage medium having executable program code stored therein; the executable program code for performing the vehicle fake-licensed determination method of any one of claims 1-5.
10. A terminal device comprising a memory and a processor; the memory stores program code executable by the processor; the program code is for executing the vehicle fake-licensed determination method of any one of claims 1-5.
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