CN111674360B - Method for establishing distinguishing sample model in vehicle tracking system based on block chain - Google Patents

Method for establishing distinguishing sample model in vehicle tracking system based on block chain Download PDF

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CN111674360B
CN111674360B CN202010483777.3A CN202010483777A CN111674360B CN 111674360 B CN111674360 B CN 111674360B CN 202010483777 A CN202010483777 A CN 202010483777A CN 111674360 B CN111674360 B CN 111674360B
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information
vehicle
capacitor
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CN111674360A (en
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解本巨
刘国柱
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Qingdao Huize Chuangjian Information New Technology Co ltd
Qingdao University of Science and Technology
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Qingdao University of Science and Technology
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    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/30—Detection related to theft or to other events relevant to anti-theft systems
    • B60R25/33—Detection related to theft or to other events relevant to anti-theft systems of global position, e.g. by providing GPS coordinates
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/20—Means to switch the anti-theft system on or off
    • B60R25/25—Means to switch the anti-theft system on or off using biometry
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/20—Means to switch the anti-theft system on or off
    • B60R25/25—Means to switch the anti-theft system on or off using biometry
    • B60R25/252—Fingerprint recognition
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R25/00—Fittings or systems for preventing or indicating unauthorised use or theft of vehicles
    • B60R25/20—Means to switch the anti-theft system on or off
    • B60R25/25—Means to switch the anti-theft system on or off using biometry
    • B60R25/257—Voice recognition
    • 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
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/30—Authentication, i.e. establishing the identity or authorisation of security principals
    • G06F21/31—User authentication
    • G06F21/32—User authentication using biometric data, e.g. fingerprints, iris scans or voiceprints
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/62—Protecting access to data via a platform, e.g. using keys or access control rules
    • G06F21/6218—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database
    • G06F21/6227—Protecting access to data via a platform, e.g. using keys or access control rules to a system of files or objects, e.g. local or distributed file system or database where protection concerns the structure of data, e.g. records, types, queries
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
    • G06F21/60—Protecting data
    • G06F21/64—Protecting data integrity, e.g. using checksums, certificates or signatures

Abstract

The invention discloses a method for establishing a distinguishing sample model in a vehicle tracking system based on a block chain, which comprises a vehicle positioning module, a vehicle tracking device, a service device and a block chain service platform, wherein the vehicle positioning module is used for positioning a vehicle; the vehicle positioning module, the vehicle tracking device, the service device and the block chain service platform are communicated through GPRS connection; the vehicle positioning module is arranged in the automobile control panel; the vehicle tracking device is connected to the automobile control panel through a data line; in a certain distance range, the vehicle tracking device can directly receive the information transmitted by the vehicle positioning module after passing the authentication and authorization, and perform direct connection tracking; the invention provides a tracking system with a high safety coefficient, and a method for establishing a distinguishing sample model in the block chain-based vehicle tracking system for accurately positioning a vehicle and dynamically knowing the dynamic position of the vehicle in real time.

Description

Method for establishing distinguishing sample model in vehicle tracking system based on block chain
The invention relates to a vehicle tracking system based on GPS positioning identification of a block chain, which is a divisional application of patent with the application number of 201910100093.8
Technical Field
The invention relates to the field of vehicle tracking, in particular to a method for establishing a distinguishing sample model in a vehicle tracking system based on a block chain.
Background
With the rapid development of economy, the social possession of automobiles is rapidly increased, the problem of vehicle management and allocation of each unit is more prominent, and meanwhile, various phenomena such as vehicle hijacking and vehicle stealing which harm social security and influence social stability are increased year by year, and the monitoring of vehicles becomes a problem to be solved urgently. The problem that how to improve the dispatching management capability, recover the stolen vehicle and identify the verification information becomes a problem to be solved is that not only the vehicle needs to be monitored but also the unit needs to perform dynamic control and monitoring on the owned vehicle by an individual.
Disclosure of Invention
The invention provides a tracking system with a high safety coefficient, and a method for establishing a distinguishing sample model in the block chain-based vehicle tracking system for accurately positioning a vehicle and dynamically knowing the dynamic position of the vehicle in real time.
The technical scheme of the invention is as follows:
the method for establishing the distinguishing sample model in the vehicle tracking system based on the block chain comprises a vehicle positioning module, a vehicle tracking device, a service device and a block chain service platform; the vehicle positioning module, the vehicle tracking device, the service device and the block chain service platform are communicated through GPRS connection; the vehicle positioning module is arranged in the automobile control panel; the vehicle tracking device is connected to the automobile control panel through a data line; in a certain distance range, the vehicle tracking device can directly receive the information transmitted by the vehicle positioning module after passing the authentication and authorization, and directly track.
Furthermore, the vehicle positioning module comprises a GPS positioning instrument, a first information storage module and an information sending module, and the information sending module is electrically connected with the first information storage module and the GPS positioning instrument; the first information storage module records a license plate number, the name of the owner of the vehicle, the color of the vehicle body, the residual amount of fuel and a running path; the information sending module sends the information stored by the real-time GPS positioning and first information storage module;
the vehicle tracking device comprises a power supply module, an information identification module, a second information storage module, a first information transceiving module and a display; the power supply module is electrically connected with the information identification module, the second information storage module, the first information transceiving module and the display and provides power; the information identification module comprises a face identification module, a fingerprint identification module and a voiceprint identification module, the face identification module is arranged above the display screen, the fingerprint identification module is arranged on the left side surface of the vehicle tracking device, and the voiceprint identification module is arranged on two sides of the vehicle tracking device; the second information storage module receives the authentication information through the first information transceiver module, and stores the information after the authentication is passed; the first information transceiver module is connected with the second information storage module; the display comprises a central processing unit and a display screen, the central processing unit is electrically connected with the second information storage module, and the central processing unit processes the content of the second information storage module and displays the content on the display screen;
the service device comprises a display module, a processing module, a storage module, an authentication module and a second information transceiving module; the display module, the storage module, the authentication module, the second information transceiver module and the processing module are electrically connected; the display module adopts a touch screen to input and display related information; the authentication module compares the information needing authentication input by the display module with the encrypted information stored in the block chain service platform; the storage module is used for classifying and storing part of authentication information after passing the authentication, and storing information transmitted and received among the service device, the vehicle positioning module and the vehicle tracking device; the processing module displays the information in the storage module after passing the authentication to the display module;
the block chain service platform is communicated with the service device; recording a license plate number, the name of the current owner of the vehicle, the color of the vehicle body, the registration date of the vehicle, the name of the original owner of the vehicle, the name of a distribution enterprise, an enterprise business license number, the identity card number or business license number of the owner of the vehicle, the contact address of the owner, a maintenance record, a traffic accident record, insurance policy information, registration certificate information and driving certificate information in the block chain; and the block chain service platform calls the information corresponding to the authority content according to the information sent by the service device and transmits the information to the service device.
Furthermore, the vehicle tracking device also comprises an external power supply interface which converts an external vehicle power supply into a power supply for stabilizing the operation of equipment through a constant-current constant-voltage circuit; the constant-current constant-voltage circuit comprises a signal processor, a diode, a resistor, a capacitor, a polar capacitor and a photosensitive element;
the number of the signal processors is two, namely a signal processor U1 and a signal processor U3; the first pin and the second pin of the signal processor U1 are used as negative poles of input, the third pin of the signal processor U1 is connected with one end of a capacitor C5, and the other end of the capacitor C5 is connected with the cathode of a polar capacitor C3 and one end of a capacitor C4 and is connected with the negative pole of the input; the anode of the polar capacitor C3 is connected with one end of the resistor R8, one end of the resistor R5, one end of the resistor R9, the fourth pin of the signal processor U1 and the other end of the capacitor C4;
the resistor R8, the resistor R7 and the resistor R6 are connected in series, and the other end of the resistor R6, one end of the resistor R1, one end of the resistor R2 and one end of the capacitor C1 are used as input anodes; the other end of the resistor R1, one end of the resistor R3 and the other end of the capacitor C1 are connected with the cathode of the diode D1; the resistor R2 is connected with the resistor R3 in series; the anode of the diode D1 is connected with the fifth pin, the sixth pin, the seventh pin and the eighth pin of the signal processor U1; one end of the capacitor C1 and the anode of the diode D1 are connected with two ends of the inductor T1;
the other end of the resistor R5 is connected with the cathode of the diode D3, the anode of the diode D3 is connected with one end of the resistor R4 and the cathode of the diode D2, and the other end of the resistor R4 is connected with the anode of the polar capacitor C2 and one end of the capacitor C11; the cathode of the polar capacitor C2 and the other end of the capacitor C11 are grounded; the anode of the diode D2 and the other end of the capacitor C11 are connected with two ends of the inductor T2;
the resistor R9 is connected with the resistor R10 in series, the other end of the resistor R10 is connected with the fourth pin of the photosensitive element U2, and the third pin of the photosensitive element U2 is a feedback pin; a resistor R12 is connected between the first pin and the second pin of the photosensitive component, one end of a resistor R12 is connected with a resistor R11, the other end of the resistor R11 is connected with VCC high potential, and the other end of the resistor R2 is connected with the anode of a diode D4 and the anode of a diode D5;
the cathode of the diode D4 is connected with one end of the resistor R14, and the other end of the resistor R14 is connected with one end of the resistor R15 and a first pin of the signal processor U3; the other end of the resistor R15 is connected with one end of a capacitor C7, the other end of the capacitor C7 is connected with one end of a resistor R19, one end of a resistor R20 and a second pin of the signal processor U3, the other end of the resistor R19 is connected with a VCC high potential, and the other end of the resistor R20 and a fourth pin of the signal processor U3 are grounded; the third pin of the signal processor U3 is connected with one end of a resistor R16, and the other end of the resistor R16 is connected with VCC high potential;
the cathode of the diode D5 is connected with one end of the resistor R13, the other end of the resistor R13 is connected with one end of the resistor R17 and the seventh pin of the signal processor U3, the other end of the resistor R17 is connected with one end of the capacitor C10, the other end of the capacitor C10 is connected with the sixth pin of the signal processor U3, one end of the resistor R21 and one end of the capacitor C9, and the other end of the resistor R21 and the other end of the capacitor C9 are grounded together; a fifth pin of the signal processor U3 is connected with one end of a resistor R18 and one end of a capacitor C8, the other end of the capacitor C8 is grounded, and the other end of the resistor R18 is connected with a VCC high potential; the eighth pin of the signal processor U3 is connected to one end of the capacitor C6 and the VCC high potential, and the other end of the capacitor C6 is grounded.
Further, classified storage in the storage module of the service device is carried out by establishing an accurate distinguishing sample model; specifically, the accurate distinguishing sample model is established as follows:
the accurate distinguishing sample model is processed by adopting a plurality of continuous same processing model units, each model unit comprises an input layer, a hidden layer and an output layer, namely the model units form input and output correspondence, and a mapping model is established by the hidden layer; the input layer comprises output values of all nodes of a previous layer of sample model, weights of all nodes of the layer where the node is located and the previous layer, a threshold value of a current node and an activation function, and a specific judgment formula is as follows:
Figure GDA0003058847980000041
xj＝f(Sj)
wherein f is an activation function, an S-shaped function is selected, i and j are nodes of each layer of the sample model, namely the first input values, the second layer is processed, and w isijAs a weight between node i and node j, bjIs the threshold value, x, of node jjAn output value of each node; first time sample model input layer nodeThere is no threshold;
the activation function is specifically as follows:
Figure GDA0003058847980000051
where x is the input, e is a constant, A, B is a constant.
Further, the accurate sample model discrimination further comprises a verification mechanism, namely a reverse transmission process, which repeatedly corrects the weight and the threshold value through comparison between input and final output, and further corrects the weight and the threshold value in the forward modeling processing, so that error identification is reduced to the minimum, and the accurate sample model discrimination is obtained, and the specific processing is as follows:
the reverse transfer process specific handling function E is as follows:
Figure GDA0003058847980000052
wherein d isjFor all results of the output layer, yjThe result after forward modeling processing is shown, w is a weight, b is a threshold value, and n is the number of layers;
the gradient of E (w, b) is proportional to the weight vector correction, so for the jth output node:
Figure GDA0003058847980000053
eta is a variable; according to the activation function, the derivation of the activation function can be known to obtain
Figure GDA0003058847980000054
Thereby aiming at wijHave the advantages that
Figure GDA0003058847980000061
Therein is provided with
Figure GDA0003058847980000062
Also for bjIs provided with
Figure GDA0003058847980000063
So as to obtain the weight between the hidden layer and the output layer and the adjustment amount of the output layer threshold value; and obtaining a weight between nodes of the input layer and the hidden layer and an adjustment quantity of a threshold value of the nodes between the hidden layers, wherein a specific formula is as follows:
Figure GDA0003058847980000064
Figure GDA0003058847980000071
wherein wkiIs the weight between the input layer k node and the hidden layer i node, then
Figure GDA0003058847980000072
According to the formula, based on a gradient descent method, obtaining the weight and the threshold value of the connection node between the hidden layer and the output layer, and the method is completed by the following formula:
Figure GDA0003058847980000073
Figure GDA0003058847980000074
wherein eta1、η2As a variable, represented by the formulaThe weight and the threshold value of the connection between the input layer and the hidden layer can be obtained, and the specific formula is as follows:
Figure GDA0003058847980000075
Figure GDA0003058847980000076
in construction, the number of nodes of an input layer and the number of nodes of an output layer are determined according to actual conditions, but the number of nodes of a hidden layer is uncertain, but the number of nodes of the hidden layer can influence the fitting degree of a network, so that the number of nodes of the hidden layer is determined by adopting the following formula:
Figure GDA0003058847980000077
the number of hidden layer nodes is represented by h, the number of input layer nodes is represented by m, the number of output layer nodes is represented by r, and the number of more accurate hidden layer nodes and more accurate model addition adjusting constants are represented by a.
Compared with the prior art, the invention has the advantages that: according to the invention, the block chain service platform is utilized to guarantee data safety, and the vehicle tracking device directly receives corresponding information of the vehicle to improve the tracking efficiency. Due to the data security of the block chain, real-time data retention is carried out in the tracking process, and the collected evidence is caught by the police and becomes more fair and legal. The invention authorizes the equipment by utilizing the consensus mechanism of the block chain, increases the safety of the whole system and improves the reliability of mutual information sharing.
The vehicle tracking device is generally an automobile with an external power supply, and the voltage and the current of the automobile are unstable, so that in order to prolong the whole service life and improve the new energy of the vehicle tracking device, a constant-current constant-voltage circuit is designed to improve and guarantee the stability of the whole operation, and other module circuits are designed conventionally.
In order to improve the efficiency of information search, the invention establishes an accurate distinguishing sample model, accurately distinguishes information by establishing the model, can quickly and accurately find corresponding vehicle information only by inputting partial characteristic information in the following tracking process of a police, and carries out quick information sharing through a service device so as to greatly improve the processing efficiency.
Drawings
FIG. 1 is a schematic structural diagram of the present invention.
FIG. 2 is a schematic view of a vehicle locating module of the present invention.
Fig. 3 is a schematic diagram of a vehicle tracking device according to the present invention.
Fig. 4 is a schematic diagram of the service device of the present invention.
Fig. 5 is a circuit diagram of the constant current and voltage circuit of the present invention.
FIG. 6 is a block diagram of a process model for accurately distinguishing between sample models according to the present invention.
Detailed Description
The invention is further described with reference to the following figures and detailed description.
As shown in fig. 1 to 6, a method for establishing a differentiated sample model in a blockchain-based vehicle tracking system includes a vehicle positioning module, a vehicle tracking device, a service device, and a blockchain service platform. The vehicle positioning module, the vehicle tracking device, the service device and the block chain service platform are communicated through GPRS connection. The vehicle positioning module is arranged in the automobile control panel. The vehicle tracking device is connected to the automobile control panel through a data line. In a certain distance range, the vehicle tracking device can directly receive the information transmitted by the vehicle positioning module after passing the authentication and authorization, and directly track. The information sent between each module device is encrypted, so that the content of the information cannot be decrypted without holding a corresponding key.
The vehicle positioning module comprises a GPS locator, a first information storage module and an information sending module, and the information sending module is electrically connected with the first information storage module and the GPS locator. The first information storage module records license plate number, name of the owner of the vehicle, color of the vehicle body, residual fuel amount and driving path. And the information sending module sends the real-time GPS positioning and the information stored by the first information storage module. The information sent by the terminal is encrypted, so that the content of the information cannot be decrypted without holding a corresponding key. Because the device is simple and low in cost, the device can be installed on each trolley, and new automobiles on the market are self-contained.
The vehicle tracking device comprises a power supply module, an information identification module, a second information storage module, a first information transceiving module and a display. The power module is electrically connected with the information identification module, the second information storage module, the first information transceiving module and the display and provides power. The information identification module comprises a face identification module, a fingerprint identification module and a voiceprint identification module, the face identification module is arranged above the display screen, the fingerprint identification module is arranged on the left side face of the vehicle tracking device, and the voiceprint identification module is arranged on two sides of the vehicle tracking device. The second information storage module receives the authentication information through the first information transceiver module, and stores the information after the authentication is passed. The first information receiving and sending module is connected with the second information storage module. The display comprises a central processing unit and a display screen, the central processing unit is electrically connected with the second information storage module, and the central processing unit processes the content of the second information storage module and then displays the content on the display screen.
The operating principle of the system is that the service device mainly sends the authorization verification information to the vehicle tracking device, and the vehicle tracking device stores the information in the second information storage module. Only when the authorized person passes the verification of the fingerprint identification module, the face identification module and the voiceprint identification module, the authorized person can be authorized successfully, and the equipment is started. And displaying the data information on a display from the block chain service platform according to the information which can be seen by the obtained authorized person. In actual operation, for example, the police catches up, the police authorizes a plurality of devices, authorizers are different, but authorization information is the same, and at the moment, as long as a master commander confirms authorization, users corresponding to the devices pass information verification, other secret information of the vehicle to be tracked can be directly sent to the vehicle tracking device through a common recognition mechanism, excessive data are not needed to be repeatedly operated and processed, redundant operation is greatly reduced, and information sharing is improved. The use information of the vehicle tracking device can be stored and sent to the block chain service platform, because the pass time is used as a storage chain, the modification is difficult, and the modification is successful only when more than half of the node storage information is required to be modified, so that the accuracy of data recording is guaranteed from the aspect of visitation, once an illegal action occurs in the execution process of a police, the data can be completely recorded, and the legality of evidence is guaranteed.
After authorization, the vehicle tracking device can directly receive information transmitted by the vehicle positioning module within a certain distance range to perform direct tracking. Therefore, the high-efficiency communication of information is facilitated, and the tracking effect is greatly improved.
The vehicle tracking device further comprises an external power interface, so that the vehicle tracking device can operate for a long time. The external power supply interface converts an external automobile power supply into a power supply for stabilizing the operation of equipment through a constant-current constant-voltage circuit. The constant-current constant-voltage circuit comprises a signal processor, a diode, a resistor, a capacitor, a polar capacitor and a photosensitive element. The specific circuit is shown in fig. 5.
There are two signal processors, signal processor U1 and signal processor U3. The first pin and the second pin of the signal processor U1 are used as negative poles of the input, the third pin of the signal processor U1 is connected with one end of a capacitor C5, and the other end of the capacitor C5 is connected with the cathode of a polar capacitor C3 and one end of a capacitor C4, and is connected with the negative pole of the input. The anode of the polar capacitor C3 is connected to one end of the resistor R8, one end of the resistor R5, one end of the resistor R9, the fourth pin of the signal processor U1, and the other end of the capacitor C4.
The resistor R8, the resistor R7 and the resistor R6 are connected in series, and the other end of the resistor R6, one end of the resistor R1, one end of the resistor R2 and one end of the capacitor C1 are used as input anodes. The other end of the resistor R1, one end of the resistor R3, and the other end of the capacitor C1 are connected to the cathode of the diode D1. Resistor R2 is connected in series with resistor R3. An anode of the diode D1 is connected to the fifth, sixth, seventh, and eighth pins of the signal processor U1. One end of the capacitor C1 and the anode of the diode D1 are connected to both ends of the inductor T1.
The other end of the resistor R5 is connected to the cathode of the diode D3, the anode of the diode D3 is connected to one end of the resistor R4 and the cathode of the diode D2, and the other end of the resistor R4 is connected to the anode of the polar capacitor C2 and one end of the capacitor C11. The cathode of the polar capacitor C2 and the other end of the capacitor C11 are grounded. The anode of the diode D2 and the other end of the capacitor C11 are connected to both ends of the inductor T2.
The resistor R9 is connected in series with the resistor R10, the other end of the resistor R10 is connected with the fourth pin of the photosensitive element U2, and the third pin of the photosensitive element U2 is a feedback pin. A resistor R12 is connected between the first pin and the second pin of the photosensitive component, one end of a resistor R12 is connected with a resistor R11, the other end of the resistor R11 is connected with VCC high potential, and the other end of the resistor R2 is connected with the anode of a diode D4 and the anode of a diode D5.
The cathode of the diode D4 is connected to one end of the resistor R14, and the other end of the resistor R14 is connected to one end of the resistor R15 and the first pin of the signal processor U3. The other end of the resistor R15 is connected with one end of a capacitor C7, the other end of the capacitor C7 is connected with one end of a resistor R19, one end of a resistor R20 and a second pin of the signal processor U3, the other end of the resistor R19 is connected with VCC high potential, and the other end of the resistor R20 and a fourth pin of the signal processor U3 are grounded together. The third pin of the signal processor U3 is connected to one end of a resistor R16, and the other end of the resistor R16 is connected to VCC high potential.
The cathode of the diode D5 is connected to one end of the resistor R13, the other end of the resistor R13 is connected to one end of the resistor R17 and the seventh pin of the signal processor U3, the other end of the resistor R17 is connected to one end of the capacitor C10, the other end of the capacitor C10 is connected to the sixth pin of the signal processor U3, one end of the resistor R21 and one end of the capacitor C9, and the other end of the resistor R21 and the other end of the capacitor C9 are grounded together. The fifth pin of the signal processor U3 is connected to one end of a resistor R18 and one end of a capacitor C8, the other end of the capacitor C8 is grounded, and the other end of the resistor R18 is connected to a VCC high potential. The eighth pin of the signal processor U3 is connected to one end of the capacitor C6 and the VCC high potential, and the other end of the capacitor C6 is grounded.
The input voltage of the commercial vehicle is basically 12V to 24V, and the maximum output current can reach 15 amperes or even 20 amperes. A common output voltage commonly used in the market is 5V, and an output current is about 1A-4A, which is still very unstable, and it is difficult to realize long-term stable use of the vehicle tracking device. After the constant-current constant-voltage circuit is adopted, the output voltage is still 5V, and the output current is controlled to be 1.7A to 2.2A. Facilitating long-term use of the device in this environment.
The service device comprises a display module, a processing module, a storage module, an authentication module and a second information transceiving module. The display module, the storage module, the authentication module, the second information transceiver module and the processing module are electrically connected. The display module adopts a touch screen to input related information and display the information. The authentication module compares the information needing authentication input by the display module with the encrypted information stored in the block chain service platform. The storage module classifies and stores part of authentication information after passing the authentication, and stores information transmitted and received between the service device and the vehicle positioning module and between the service device and the vehicle tracking device. And the processing module displays the information in the storage module after the authentication is passed to the display module.
The service device inputs accurate information through the authentication module by the actual obligee to start tracking through authentication, transmission data of first authentication are many, but after authentication, the actual obligee can be directly authorized through a consensus mechanism, and a lot of information does not need to be provided repeatedly, so that redundancy is reduced, concurrency is increased, and processing efficiency and information sharing are improved. The service device can receive the information of the vehicle positioning module and the vehicle tracking device and display the information for real-time monitoring of actual authorized persons, so that the police can conveniently conduct overall command and decide whether to increase hands or not according to the command of police officers.
The block chain service platform is communicated with the service device. The block chain records the license plate number, the name of the current owner of the vehicle, the color of the vehicle body, the registration date of the vehicle, the name of the original owner of the vehicle, the name of a distribution enterprise, the number of an enterprise business license, the number of the identity card or the number of the business license of the owner of the vehicle, the contact address of the owner, the maintenance record, the record of the traffic accident, the information of the insurance policy, the information of the registration card and the information of the driving card. And the block chain service platform calls the information corresponding to the authority content according to the information sent by the service device and transmits the information to the service device.
Preferably, the classified storage in the storage module of the service device is performed by establishing a precise distinguishing sample model. If the Mazda A6 vehicle information and photos in the data are used as the input of the sample model, the automobile is firstly output when the data enter the sample model for the first time, then the sample model is processed for the second time, the automobile is output as the Mazda, the red Mazda is output for the third time, the damage degree is output for the fourth time, the tire state … … is output for the fifth time, and finally the specific details of classified storage, the actual color, the vehicle condition, the form path and the like of the Mazda A6 are obtained, so that the refined storage of the accurate information is established. Therefore, all information of the unique corresponding actual vehicle can be efficiently obtained by inputting part of vehicle characteristic information after the police authorizes the vehicle.
Specifically, the accurate distinguishing sample model is established as follows:
the accurate distinguishing sample model is processed by adopting a plurality of continuous same processing model units, each model unit comprises an input layer, a hidden layer and an output layer, namely the model units form input and output correspondence, and a mapping model is established by the hidden layer. The input layer comprises output values of all nodes of a previous layer of sample model, weights of all nodes of the layer where the node is located and the previous layer, a threshold value of a current node and an activation function, and a specific judgment formula is as follows:
Figure GDA0003058847980000131
xj＝f(Sj)
wherein f is an activation function, an S-shaped function is selected, i and j are nodes of each layer of the sample model, namely the first input values, the second layer is processed, and w isijAs a weight between node i and node j, bjIs the threshold value, x, of node jjThe output value of each node. The first time the sample model input layer node has no threshold.
The activation function is specifically as follows:
Figure GDA0003058847980000141
where x is the input, e is a constant, A, B is a constant.
Establishing the accurate differentiated sample model also includes a verification mechanism, namely a reverse transfer process, in order to verify the final accuracy. The weight and the threshold are repeatedly corrected through comparison between input and final output, so that the weight and the threshold in forward modeling processing are corrected, error identification is reduced to the minimum, and an accurate distinguishing sample model is obtained, and the specific processing is as follows:
the reverse transfer process specific handling function E is as follows:
Figure GDA0003058847980000142
wherein d isjFor all results of the output layer, yjAnd w is a weight, b is a threshold value and n is the number of layers. And continuously comparing and adjusting the weight value and the threshold value of the sample model to reduce the relative error gradient, so that the correction is carried out according to a gradient reduction method.
The gradient of E (w, b) is proportional to the weight vector correction, so for the jth output node:
Figure GDA0003058847980000143
eta is a variable. According to the activation function, the derivation of the activation function can be known to obtain
Figure GDA0003058847980000144
Thereby aiming at wijHave the advantages that
Figure GDA0003058847980000145
Figure GDA0003058847980000151
Therein is provided with
Figure GDA0003058847980000152
Also for bjIs provided with
Figure GDA0003058847980000153
So as to obtain the weight value between the hidden layer and the output layer and the adjustment quantity of the output layer threshold value. However, the weights between the nodes of the input layer and the hidden layer and the adjustment amount of the threshold of the nodes between the hidden layers need to be obtained, and the specific formula is as follows:
Figure GDA0003058847980000154
Figure GDA0003058847980000161
wherein wkiIs the weight between the input layer k node and the hidden layer i node, then
Figure GDA0003058847980000162
According to the formula, based on a gradient descent method, obtaining the weight and the threshold value of the connection node between the hidden layer and the output layer, and the method is completed by the following formula:
Figure GDA0003058847980000163
Figure GDA0003058847980000164
wherein eta1、η2The weight and the threshold value of the connection between the input layer and the hidden layer can be obtained by the above formula as a variable, and the specific formula is as follows:
Figure GDA0003058847980000165
Figure GDA0003058847980000166
in construction, the number of nodes of an input layer and the number of nodes of an output layer are determined according to actual conditions, but the number of nodes of a hidden layer is uncertain, but the number of nodes of the hidden layer can influence the fitting degree of a network, so that the number of nodes of the hidden layer is determined by adopting the following formula:
Figure GDA0003058847980000167
the number of hidden layer nodes is represented by h, the number of input layer nodes is represented by m, the number of output layer nodes is represented by r, and the number of more accurate hidden layer nodes and more accurate model addition adjusting constants are represented by a.
The foregoing is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and decorations can be made without departing from the spirit of the present invention, and these modifications and decorations should also be regarded as being within the scope of the present invention.

Claims (3)

1. The method for establishing the distinguishing sample model in the vehicle tracking system based on the block chain is characterized by comprising a vehicle positioning module, a vehicle tracking device, a service device and a block chain service platform; the vehicle positioning module, the vehicle tracking device, the service device and the block chain service platform are communicated through GPRS connection; the vehicle positioning module is arranged in the automobile control panel; the vehicle tracking device is connected to the automobile control panel through a data line; in a certain distance range, the vehicle tracking device can directly receive the information transmitted by the vehicle positioning module after passing the authentication and authorization, and perform direct connection tracking;
classified storage in a storage module of the service device is carried out by establishing an accurate distinguishing sample model; specifically, the accurate distinguishing sample model is established as follows:
the accurate distinguishing sample model is processed by adopting a plurality of continuous same processing model units, each model unit comprises an input layer, a hidden layer and an output layer, namely the model units form input and output correspondence, and a mapping model is established by the hidden layer; the input layer comprises output values of all nodes of a previous layer of sample model, weights of all nodes of the layer where the node is located and the previous layer, a threshold value of a current node and an activation function, and a specific judgment formula is as follows:
Figure FDA0003058847970000011
xj＝f(Sj)
wherein f is an activation function, an S-shaped function is selected, i and j are nodes of each layer of the sample model, namely the first input values, the second layer is processed, and w isijAs a weight between node i and node j, bjIs the threshold value, x, of node jjAn output value of each node; the first time sample model input layer node has no threshold value;
the activation function is specifically as follows:
Figure FDA0003058847970000012
where x is an input, e is a constant, A, B is a constant;
the vehicle positioning module comprises a GPS positioning instrument, a first information storage module and an information sending module, and the information sending module is electrically connected with the first information storage module and the GPS positioning instrument; the first information storage module records a license plate number, the name of the owner of the vehicle, the color of the vehicle body, the residual amount of fuel and a running path; the information sending module sends the information stored by the real-time GPS positioning and first information storage module;
the vehicle tracking device comprises an external power interface which converts an external automobile power supply into a power supply for stabilizing the operation of equipment through a constant-current constant-voltage circuit; the constant-current constant-voltage circuit comprises a signal processor, a diode, a resistor, a capacitor, a polar capacitor and a photosensitive element;
the number of the signal processors is two, namely a signal processor U1 and a signal processor U3; the first pin and the second pin of the signal processor U1 are used as negative poles of input, the third pin of the signal processor U1 is connected with one end of a capacitor C5, and the other end of the capacitor C5 is connected with the cathode of a polar capacitor C3 and one end of a capacitor C4 and is connected with the negative pole of the input; the anode of the polar capacitor C3 is connected with one end of the resistor R8, one end of the resistor R5, one end of the resistor R9, the fourth pin of the signal processor U1 and the other end of the capacitor C4;
the resistor R8, the resistor R7 and the resistor R6 are connected in series, and the other end of the resistor R6, one end of the resistor R1, one end of the resistor R2 and one end of the capacitor C1 are used as input anodes; the other end of the resistor R1, one end of the resistor R3 and the other end of the capacitor C1 are connected with the cathode of the diode D1; the resistor R2 is connected with the resistor R3 in series; the anode of the diode D1 is connected with the fifth pin, the sixth pin, the seventh pin and the eighth pin of the signal processor U1; one end of the capacitor C1 and the anode of the diode D1 are connected with two ends of the inductor T1;
the other end of the resistor R5 is connected with the cathode of the diode D3, the anode of the diode D3 is connected with one end of the resistor R4 and the cathode of the diode D2, and the other end of the resistor R4 is connected with the anode of the polar capacitor C2 and one end of the capacitor C11; the cathode of the polar capacitor C2 and the other end of the capacitor C11 are grounded; the anode of the diode D2 and the other end of the capacitor C11 are connected with two ends of the inductor T2;
the resistor R9 is connected with the resistor R10 in series, the other end of the resistor R10 is connected with the fourth pin of the photosensitive element U2, and the third pin of the photosensitive element U2 is a feedback pin; a resistor R12 is connected between the first pin and the second pin of the photosensitive component, one end of a resistor R12 is connected with a resistor R11, the other end of the resistor R11 is connected with VCC high potential, and the other end of the resistor R2 is connected with the anode of a diode D4 and the anode of a diode D5;
the cathode of the diode D4 is connected with one end of the resistor R14, and the other end of the resistor R14 is connected with one end of the resistor R15 and a first pin of the signal processor U3; the other end of the resistor R15 is connected with one end of a capacitor C7, the other end of the capacitor C7 is connected with one end of a resistor R19, one end of a resistor R20 and a second pin of the signal processor U3, the other end of the resistor R19 is connected with a VCC high potential, and the other end of the resistor R20 and a fourth pin of the signal processor U3 are grounded; the third pin of the signal processor U3 is connected with one end of a resistor R16, and the other end of the resistor R16 is connected with VCC high potential;
the cathode of the diode D5 is connected with one end of the resistor R13, the other end of the resistor R13 is connected with one end of the resistor R17 and the seventh pin of the signal processor U3, the other end of the resistor R17 is connected with one end of the capacitor C10, the other end of the capacitor C10 is connected with the sixth pin of the signal processor U3, one end of the resistor R21 and one end of the capacitor C9, and the other end of the resistor R21 and the other end of the capacitor C9 are grounded together; a fifth pin of the signal processor U3 is connected with one end of a resistor R18 and one end of a capacitor C8, the other end of the capacitor C8 is grounded, and the other end of the resistor R18 is connected with a VCC high potential; the eighth pin of the signal processor U3 is connected to one end of the capacitor C6 and the VCC high potential, and the other end of the capacitor C6 is grounded.
2. The method for creating a differentiated sample model in a blockchain-based vehicle tracking system according to claim 1, wherein the accurate differentiated sample model further includes a verification mechanism, i.e. a reverse transmission process, which repeatedly corrects the weight and the threshold by comparing the input with the final output, and further corrects the weight and the threshold in the forward modeling process, so that the error recognition is minimized, and the accurate differentiated sample model is obtained by the following specific processes:
the reverse transfer process specific handling function E is as follows:
Figure FDA0003058847970000031
wherein d isjFor all results of the output layer, yjThe result after forward modeling processing is shown, w is a weight, b is a threshold value, and n is the number of layers;
the gradient of E (w, b) is proportional to the weight vector correction, so for the jth output node:
Figure FDA0003058847970000041
eta is a variable; according to the activation function, the derivation of the activation function can be known to obtain
Figure FDA0003058847970000042
Thereby aiming at wijHave the advantages that
Figure FDA0003058847970000043
Therein is provided with
Figure FDA0003058847970000044
Also for bjIs provided with
Figure FDA0003058847970000045
So as to obtain the weight between the hidden layer and the output layer and the adjustment amount of the output layer threshold value; and obtaining a weight between nodes of the input layer and the hidden layer and an adjustment quantity of a threshold value of the nodes between the hidden layers, wherein a specific formula is as follows:
Figure FDA0003058847970000051
wherein wkiIs the weight between the input layer k node and the hidden layer i node, then
Figure FDA0003058847970000052
According to the formula, based on a gradient descent method, obtaining the weight and the threshold value of the connection node between the hidden layer and the output layer, and the method is completed by the following formula:
Figure FDA0003058847970000053
Figure FDA0003058847970000054
wherein eta1、η2The weight and the threshold value of the connection between the input layer and the hidden layer can be obtained by the above formula as a variable, and the specific formula is as follows:
Figure FDA0003058847970000061
Figure FDA0003058847970000062
in construction, the number of nodes of an input layer and the number of nodes of an output layer are determined according to actual conditions, but the number of nodes of a hidden layer is uncertain, but the number of nodes of the hidden layer can influence the fitting degree of a network, so that the number of nodes of the hidden layer is determined by adopting the following formula:
Figure FDA0003058847970000063
the number of hidden layer nodes is represented by h, the number of input layer nodes is represented by m, the number of output layer nodes is represented by r, and the number of more accurate hidden layer nodes and more accurate model addition adjusting constants are represented by a.
3. The method for creating the differentiated sample model in the blockchain-based vehicle tracking system according to claim 1, wherein the vehicle positioning module comprises a GPS locator, a first information storage module and an information sending module, and the information sending module is electrically connected with the first information storage module and the GPS locator; the first information storage module records a license plate number, the name of the owner of the vehicle, the color of the vehicle body, the residual amount of fuel and a running path; the information sending module sends the information stored by the real-time GPS positioning and first information storage module;
the vehicle tracking device comprises a power supply module, an information identification module, a second information storage module, a first information transceiving module and a display; the power supply module is electrically connected with the information identification module, the second information storage module, the first information transceiving module and the display and provides power; the information identification module comprises a face identification module, a fingerprint identification module and a voiceprint identification module, the face identification module is arranged above the display screen, the fingerprint identification module is arranged on the left side surface of the vehicle tracking device, and the voiceprint identification module is arranged on two sides of the vehicle tracking device; the second information storage module receives the authentication information through the first information transceiver module, and stores the information after the authentication is passed; the first information transceiver module is connected with the second information storage module; the display comprises a central processing unit and a display screen, the central processing unit is electrically connected with the second information storage module, and the central processing unit processes the content of the second information storage module and displays the content on the display screen;
the service device comprises a display module, a processing module, a storage module, an authentication module and a second information transceiving module; the display module, the storage module, the authentication module, the second information transceiver module and the processing module are electrically connected; the display module adopts a touch screen to input and display related information; the authentication module compares the information needing authentication input by the display module with the encrypted information stored in the block chain service platform; the storage module is used for classifying and storing part of authentication information after passing the authentication, and storing information transmitted and received among the service device, the vehicle positioning module and the vehicle tracking device; the processing module displays the information in the storage module after passing the authentication to the display module;
the block chain service platform is communicated with the service device; recording a license plate number, the name of the current owner of the vehicle, the color of the vehicle body, the registration date of the vehicle, the name of the original owner of the vehicle, the name of a distribution enterprise, an enterprise business license number, the identity card number or business license number of the owner of the vehicle, the contact address of the owner, a maintenance record, a traffic accident record, insurance policy information, registration certificate information and driving certificate information in the block chain; and the block chain service platform calls the information corresponding to the authority content according to the information sent by the service device and transmits the information to the service device.
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Family Cites Families (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US8359243B2 (en) * 2009-05-12 2013-01-22 Ford Motor Company System and method for electronically scheduling a vehicle order
CN101806905A (en) * 2010-02-22 2010-08-18 中国农业大学 Navigation positioning method and device for agricultural machines
KR101140025B1 (en) * 2010-12-14 2012-05-02 김기태 Method and system for detecting overload and unlawful measurement of vehicle
US9365188B1 (en) * 2011-04-22 2016-06-14 Angel A. Penilla Methods and systems for using cloud services to assign e-keys to access vehicles
CN102539098B (en) * 2011-12-15 2014-01-22 东南大学 Bridge dynamic load testing method based on neural network technology
CN103020657A (en) * 2012-12-28 2013-04-03 沈阳聚德视频技术有限公司 License plate Chinese character recognition method
EP3410369A1 (en) * 2013-06-19 2018-12-05 United States Postal Service System and method for providing real-time tracking of items in a distribution network
CN104851280B (en) * 2014-02-13 2017-03-29 中国移动通信集团公司 A kind of vehicle travel control method, device, system and relevant device
US10402792B2 (en) * 2015-08-13 2019-09-03 The Toronto-Dominion Bank Systems and method for tracking enterprise events using hybrid public-private blockchain ledgers
CN106023195B (en) * 2016-05-18 2019-03-01 河南师范大学 BP neural network image partition method and device based on self-adapted genetic algorithm
CN106080512A (en) * 2016-07-01 2016-11-09 李红彪 A kind of sensor-based intelligent vehicle-carried alarm processing method
CN106114453B (en) * 2016-07-13 2018-09-21 广汽本田汽车有限公司 A kind of distribution high safety automotive theft proof system
CN106709474A (en) * 2017-01-23 2017-05-24 无锡职业技术学院 Handwritten telephone number identification, verification and information sending system
CN107122937A (en) * 2017-04-27 2017-09-01 电子科技大学 A kind of freight logistics application process based on block chain
WO2018222412A1 (en) * 2017-05-31 2018-12-06 Walmart Apollo, Llc Systems and methods to enable robotic node participation in peer-to-peer commercial transactions
US10380812B2 (en) * 2017-06-23 2019-08-13 International Business Machines Corporation Vehicle transaction validation
CN107323417A (en) * 2017-07-26 2017-11-07 青岛科技大学 A kind of multifunctional vehicle mounted assistant based on BLE
CN107808659A (en) * 2017-12-02 2018-03-16 宫文峰 Intelligent sound signal type recognition system device
CN108099846A (en) * 2017-12-21 2018-06-01 北京智帮帮科技有限公司 A kind of accidental enciphering physical message block chain anti-counterfeiting system
CN108470266A (en) * 2018-04-01 2018-08-31 南京交通职业技术学院 Product tracking system based on block chain
CN108597128A (en) * 2018-05-04 2018-09-28 济南浪潮高新科技投资发展有限公司 Urban network joins Car sharing system and method
CN108846269A (en) * 2018-06-04 2018-11-20 黑龙江大学 One kind is towards manifold identity identifying method and identification authentication system
CN109191049B (en) * 2018-09-06 2021-01-01 辽宁工业大学 Logistics transportation supervision system and method based on cloud computing
CN109284988B (en) * 2018-12-24 2019-03-15 上海市浦东新区城市运行综合管理中心 Data analysis system and method

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