A vehicle overloading blacklist management system and method

Abstract

The present invention provides an overloading vehicle blacklist management system and method, belonging to the field of consortium blockchain technology. The overloading vehicle blacklist management system includes an acquisition module, a verification module, an analysis module, an update module, and an encryption module. The acquisition module is used to obtain the initial overloading data of passing vehicles and verify the unique identifier; the verification module is used to verify the network path according to the unique identifier to obtain trusted overloading data; the analysis module is used to analyze the overlimit level according to the trusted overloading data and mark the corresponding degree identifier; the update module is used to access the historical records of the dynamic blacklist library to redefine the bad behavior level and obtain a configuration instruction code or an update instruction code; by introducing a risk assessment mechanism, the overlimit level of passing vehicles is evaluated for the management part to make corresponding penalties, and the overlimit data is integrated to formulate corresponding management policies.

Description

Technical Field

[0001] The present invention belongs to the technical field of overloading blacklist management. Specifically, it relates to a management system and method for the overloading vehicle blacklist. Background Art

[0002] In recent years, overloading has become the "number one killer" of road traffic safety. Many major traffic accidents in China are related to vehicle overloading. Overloading not only easily induces traffic accidents, but also easily damages traffic infrastructure such as roads and bridges, and will also cause certain damage to the market economic order.

[0003] At present, some drivers still remain incorrigible after multiple overloading penalties. However, relying solely on relevant management personnel to manage overloading has limited effects in terms of manpower and material resources. Therefore, a management system for establishing a long-term mechanism for overloading control is needed. Summary of the Invention

[0004] The embodiments of the present invention provide a management system and method for the overloading vehicle blacklist, aiming to solve the problem of relying solely on manual management of overloading.

[0005] In view of the above problems, the technical solution proposed by the present invention is:

[0006] In a first aspect, a management system for the overloading vehicle blacklist is applied to include a smart terminal, including:

[0007] A dynamic blacklist library, which is used to store and update blacklist information;

[0008] An acquisition module, which is used to obtain the initial overloading data of passing vehicles and verify the unique identifier;

[0009] A verification module, which is used to verify the network path according to the unique identifier to obtain reliable overloading data;

[0010] An analysis module, which is used to analyze the overloading level according to the reliable overloading data and mark the corresponding degree identifier;

[0011] An update module, which is used to access the historical records of the dynamic blacklist library to redefine the bad behavior level and obtain a configuration instruction code or an update instruction code;

[0012] An encryption module, which is used to encrypt the configuration instruction code or the update instruction code to obtain a reliable data packet.

[0013] As a preferred technical solution of the present invention, the acquisition module includes:

[0014] An acquisition unit, which is used to acquire the initial overloading data of the passing vehicle through the intelligent terminal;

[0015] A first extraction unit, which is used to extract the unique identification information from the initial overloading data;

[0016] A verification unit, which is used to verify the authenticity of the unique identification information; wherein, the unique identification information includes device information, device location information, network path and transmission time.

[0017] As a preferred technical solution of the present invention, the verification module includes:

[0018] A determination unit, which is used to determine the occurrence location information according to the network path;

[0019] A calculation unit, which is used to calculate the distance information between the occurrence location information and the device location information;

[0020] A judgment unit, which is used to judge whether the distance information exceeds a preset distance threshold; wherein, if the distance information does not exceed the preset distance threshold, the initial overloading data is determined as reliable overloading data.

[0021] As a preferred technical solution of the present invention, the analysis module includes:

[0022] A second extraction unit, which is used to extract the front-end overloading data of the passing vehicle from the reliable overloading data; wherein, the front-end overloading data includes video images and overloading data;

[0023] An analysis unit, which is used to analyze the overrun level of the passing vehicle according to the overloading data;

[0024] An identification unit, which is used to label a degree identifier for the reliable overloading data according to the overrun level.

[0025] As a preferred technical solution of the present invention, the overrun level includes three levels: low risk, medium risk and high risk, and the degree identifier includes three colors: yellow, purple and red, and corresponds to the three levels of low risk, medium risk and high risk.

[0026] As a preferred technical solution of the present invention, the update module includes:

[0027] A comparison unit, which is used to access the dynamic blacklist library to retrieve whether the passing vehicle has a historical record; wherein, if the passing vehicle has no historical record, a configuration instruction code is generated, and if the passing vehicle has a historical record, the next step is executed;

[0028] An update unit, and the definition unit is configured to redefine the bad behavior level of the passing vehicle according to a preset rule and generate an update instruction code; wherein, the bad levels are 1, 2, and 3 levels respectively.

[0029] As a preferred technical solution of the present invention, the preset rule is: the low risk does not exceed 30 times, the medium risk does not exceed 10 times, and the high risk does not exceed 5 times.

[0030] As a preferred technical solution of the present invention, the encryption module includes:

[0031] A first generation unit, and the generation unit is configured to generate a unique trusted ciphertext for the configuration instruction code or the update instruction code;

[0032] A splitting unit, and the splitting unit is configured to split the unique trusted ciphertext into N sequence segments;

[0033] A second generation unit, and the second generation unit is configured to generate a mask for each of the sequence segments to obtain a trusted data packet.

[0034] In a second aspect, an overloading vehicle blacklist management method provided by an embodiment of the present invention includes the following steps:

[0035] S1, obtaining the initial overloading data of the passing vehicle and verifying the unique identifier;

[0036] S2, verifying the network path according to the unique identifier to obtain trusted overloading data;

[0037] S3, analyzing the overlimit level according to the trusted overloading data and marking the corresponding degree identifier;

[0038] S4, accessing the historical records of the dynamic blacklist library to redefine the bad behavior level and obtaining a configuration instruction code or an update instruction code;

[0039] S5, encrypting the configuration instruction code or the update instruction code to obtain a trusted data packet.

[0040] The beneficial effects of the above technical solutions provided by the embodiments of the present invention at least include:

[0041] (1) By screening the network path twice, the authenticity of the network path is effectively ensured, thereby ensuring the accuracy of the initial overloading data and preventing false initial overloading data from occurring.

[0042] (2) By introducing a risk assessment mechanism, the overlimit level of passing vehicles is evaluated for the management part to make corresponding penalties, and the overlimit data is integrated to formulate corresponding management policies.

[0043] The above description is only an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the specific embodiments of the present invention are hereinafter specifically exemplified. Brief Description of the Drawings

[0044] Figure 1 It is a schematic structural diagram of an overloading vehicle blacklist management system disclosed by the present invention;

[0045] Figure 2 It is a flowchart of a method for managing the blacklist of overloading vehicles disclosed by the present invention.

[0046] Description of the reference numerals: 100, dynamic blacklist library; 200, obtaining module; 210, obtaining unit; 220, first extraction unit; 230, verification unit; 300, verification module; 310, determination unit; 320, calculation unit; 330, judgment unit; 400, analysis module; 410, second extraction unit; 420, analysis unit; 430, identification unit; 500, update module; 510, comparison unit; 520, update unit; 600, encryption module; 610, first generation unit; 620, splitting unit; 630, second generation unit. Detailed Embodiments

[0047] In order to make the purposes, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0048] Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0049] It should be noted that: like reference numerals and letters denote like items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0050] Embodiment 1

[0051] Referring to the attached Figure 1As shown in the figure, the present invention provides a technical solution: a management system for the blacklist of overloading vehicles, including an intelligent terminal, a dynamic blacklist library 100, an acquisition module 200, a verification module 300, an analysis module 400, an update module 500, and an encryption module 600;

[0052] Among them, the intelligent terminal includes a hard disk video recorder and a floor electronic scale.

[0053] The dynamic blacklist library 100 is used to store and update blacklist information;

[0054] The acquisition module 200 is used to obtain the initial overloading data of the passing vehicle and verify the unique identifier;

[0055] The verification module 300 is used to verify the network path according to the unique identifier to obtain reliable overloading data;

[0056] The analysis module 400 is used to analyze the overlimit level according to the reliable overloading data and mark the corresponding degree identifier;

[0057] The update module 500 is used to access the historical records of the dynamic blacklist library 100 to redefine the bad behavior level and obtain a configuration instruction code or an update instruction code;

[0058] The encryption module 600 is used to encrypt the configuration instruction code or the update instruction code to obtain a reliable data packet.

[0059] Furthermore, the acquisition module 200 includes:

[0060] An acquisition unit 210, which is used to obtain the initial overloading data of the passing vehicle through the intelligent terminal;

[0061] A first extraction unit 220, which is used to extract the unique identifier information from the initial overloading data;

[0062] A verification unit 230, which is used to verify the authenticity of the unique identifier information; among them, the unique identifier information includes device information, device location information, network path, and transmission time.

[0063] Specifically, the acquisition unit 210 obtains the initial overloading data from the hard disk video recorder and the floor electronic scale; during the process of verifying the unique identifier information, the verification of the network path during the transmission process is mainly carried out to judge whether there is a suspicious path, so as to screen the suspicious path.

[0064] Furthermore, the verification module 300 includes:

[0065] Determination unit 310, which is configured to determine the occurrence location information according to the network path;

[0066] Calculation unit 320, which is configured to calculate the distance information between the occurrence location information and the device location information;

[0067] Judgment unit 330, which is configured to judge whether the distance information exceeds a preset distance threshold; wherein, if the distance information does not exceed the preset distance threshold, the initial over-limit data is determined as reliable over-limit data.

[0068] Specifically, considering the possibility of a fake network path, therefore, it is necessary to first find the actual occurrence location information of the network path. After calculating the distance between the occurrence location information and the device location information, the authenticity of the network path can be ensured, thereby guaranteeing the accuracy of the initial over-limit data and preventing the appearance of false initial over-limit data.

[0069] Furthermore, the analysis module 400 includes:

[0070] Second extraction unit 410, which is configured to extract the front-end over-limit data of the passing vehicle in the reliable over-limit data; wherein, the front-end over-limit data includes video images and over-load data;

[0071] Analysis unit 420, which is configured to analyze the over-limit level of the passing vehicle according to the over-load data;

[0072] Identification unit 43, which is configured to label a degree identifier for the reliable over-limit data according to the over-limit level.

[0073] In a preferred embodiment of the present invention, the over-limit level includes three levels: low risk, medium risk, and high risk, and the degree identifier includes three colors: yellow, purple, and red, and corresponds to the three levels of low risk, medium risk, and high risk.

[0074] Specifically, according to the different load limits of each vehicle, each risk level has a different risk threshold range. For example, the load limit of a mini truck does not exceed 1800 kg. Then, the low-risk range is from 1800 kg to 2200 kg, the medium-risk range is from 2200 kg to 2400 kg, and the high-risk range is above 2400 kg.

[0075] Therefore, by introducing a risk assessment mechanism, the over-limit level of passing vehicles is evaluated for the management department to make corresponding penalties, and the over-limit data is integrated to formulate corresponding management policies.

[0076] Furthermore, the update module 500 includes:

[0077] A comparison unit 510, where the comparison unit 510 is used to access the dynamic blacklist library 100 to retrieve whether the passing vehicle has a historical record; wherein, if the passing vehicle has no historical record, a configuration instruction code is generated, and if the passing vehicle has a historical record, the next step is executed;

[0078] An update unit 520, where the definition unit is used to redefine the bad behavior level of the passing vehicle according to a preset rule and generate an update instruction code.

[0079] In a preferred embodiment of the present invention, the preset rule is: the low risk does not exceed 30 times, the medium risk does not exceed 10 times, and the high risk does not exceed 5 times.

[0080] Specifically, through the retrieval of the dynamic blacklist library 100, for passing vehicles without historical records, they can be created in the dynamic blacklist; for passing vehicles with historical records, the bad behavior levels of the passing vehicles are evaluated according to the preset rules; among them, the bad levels are 1, 2, and 3 levels respectively. Level 1 means 3 low risks occur, level 2 means 1 low risk or 1 medium risk occurs, and level 3 means 1 high risk occurs.

[0081] That is to say, if a certain passing vehicle has 3 low risks, the bad behavior level of the passing vehicle is adjusted to level 2; if one more occurrence is added on the basis of level 2, the bad behavior level of the passing vehicle is adjusted to level 3; if 1 medium risk or high risk occurs respectively, it is directly determined as level 2 or level 3.

[0082] Furthermore, the encryption module 600 includes:

[0083] A first generation unit 610, where the generation unit is used to generate a unique trusted ciphertext for the configuration instruction code or the update instruction code;

[0084] A splitting unit 620, where the splitting unit 620 is used to split the unique trusted ciphertext into N sequence segments;

[0085] A second generation unit 630, where the second generation unit 630 is used to generate a mask for each of the sequence segments to obtain a trusted data packet.

[0086] Specifically, before transmission, after encrypting the configuration instruction code or the update instruction code, it can prevent data tampering, thereby ensuring the authenticity of the instruction.

[0087] Embodiment 2

[0088] The embodiment of the present invention also discloses a management method for the blacklist of overweight vehicles, as shown in the attached Figure 2 shown, including the following steps:

[0089] S1. Obtain the initial overloading control data of the passing vehicle and verify the unique identifier;

[0090] S2. Check the network path according to the unique identifier to obtain reliable overloading control data;

[0091] S3. Analyze the over-limit level based on the reliable overloading control data and mark the corresponding degree identifier;

[0092] S4. Access the historical records of the dynamic blacklist library 100 to redefine the bad behavior level and obtain a configuration instruction code or an update instruction code;

[0093] S5. Encrypt the configuration instruction code or the update instruction code to obtain a reliable data packet.

[0094] It should be understood that the specific order or hierarchy of steps in the disclosed process is an example of an exemplary method. Based on design preferences, it should be understood that the specific order or hierarchy of steps in the process can be rearranged without departing from the scope of the present disclosure. The appended method claims present the elements of the various steps in an exemplary order and are not intended to be limited to the specific order or hierarchy recited.

[0095] In the above detailed description, various features are combined in a single embodiment to simplify the present disclosure. This disclosure method should not be construed as reflecting an intention that the embodiments of the claimed subject matter require more features than are expressly recited in each claim. On the contrary, as reflected in the appended claims, the present invention lies in a state less than all the features of the disclosed single embodiment. Therefore, the appended claims are hereby expressly incorporated into the detailed description, where each claim stands alone as a separate preferred embodiment of the present invention.

[0096] Those skilled in the art should also understand that the various illustrative logical blocks, modules, circuits, and algorithm steps described in conjunction with the embodiments herein can be implemented as electronic hardware, computer software, or a combination thereof. To clearly illustrate the interchangeability of hardware and software, the above description of various illustrative components, blocks, modules, circuits, and steps has been generally described in terms of their functionality. Whether such functionality is implemented as hardware or software depends on the particular application and the design constraints imposed on the overall system. Skilled artisans can implement the described functionality in a flexible manner for each particular application, but such implementation decisions should not be construed as departing from the scope of the present disclosure.

[0097] The steps of the methods or algorithms described in connection with the embodiments of this specification may be embodied directly as hardware, software modules executed by a processor, or a combination thereof. The software modules may be located in a RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium well known in the art. An exemplary storage medium is connected to the processor so that the processor can read information from, and write information to, the storage medium. Of course, the storage medium may also be an integral part of the processor. The processor and the storage medium may be located in an ASIC. The ASIC may be located in a user terminal. Of course, the processor and the storage medium may also exist as discrete components in a user terminal.

[0098] For a software implementation, the techniques described in this application may be implemented using modules (e.g., procedures, functions, etc.) that perform the functions described in this application. These software codes may be stored in a memory unit and executed by a processor. The memory unit may be implemented within the processor or outside the processor, and in the latter case, it is communicatively coupled to the processor by various means, which are well known in the art.

[0099] The above description includes examples of one or more embodiments. Of course, it is not possible to describe all possible combinations of components or methods for the purpose of describing the above embodiments, but those of ordinary skill in the art should recognize that the various embodiments can be further combined and arranged. Accordingly, the embodiments described herein are intended to cover all such changes, modifications, and variations that fall within the scope of the appended claims. In addition, with respect to the term "comprising" used in the specification or claims, this term is encompassed in a manner similar to the term "including" as interpreted when "including" is used as a transitional word in a claim. In addition, any use of the term "or" in the claims or the specification is intended to mean "non-exclusive or".

Claims

1. A blacklist management system for overloading control vehicles, which is applied to include intelligent terminals, characterized in that, Including: A dynamic blacklist library for storing and updating blacklist information; An acquisition module for acquiring initial overloading control data of passing vehicles and verifying unique identifiers; The acquisition module includes: An acquisition unit for acquiring the initial overloading control data of the passing vehicle through the intelligent terminal; A first extraction unit for extracting unique identifier information from the initial overloading control data; A verification unit for verifying the authenticity of the unique identifier information; wherein, the unique identifier information includes device information, device location information, network path, and transmission time; A verification module for verifying the network path according to the unique identifier to obtain reliable overloading control data; The verification module includes: A determination unit for determining occurrence location information according to the network path; A calculation unit for calculating the distance information between the occurrence location information and the device location information; A judgment unit for judging whether the distance information exceeds a preset distance threshold; wherein, if the distance information does not exceed the preset distance threshold, the initial overloading control data is determined as reliable overloading control data; An analysis module for analyzing the overloading level according to the reliable overloading control data and marking corresponding degree identifiers; An update module for accessing the historical records of the dynamic blacklist library to redefine the bad behavior level and obtain a configuration instruction code or an update instruction code; An encryption module for encrypting the configuration instruction code or the update instruction code to obtain a reliable data packet.

2. The overloading vehicle blacklist management system according to claim 1, characterized in that, The analysis module includes: A second extraction unit for extracting the front-end overloading control data of the passing vehicle from the reliable overloading control data; wherein, the front-end overloading control data includes video images and overloading data; An analysis unit for analyzing the overloading level of the passing vehicle according to the overloading data; An identification unit for marking a degree identifier for the reliable overloading control data according to the overloading level.

3. The vehicle overloading blacklist management system according to claim 2, wherein, The overloading levels include three levels: low risk, medium risk, and high risk, and the degree identifiers include three colors: yellow, purple, and red, and correspond to the three levels of low risk, medium risk, and high risk respectively.

4. The blacklist management system for over-limit vehicles according to claim 1, characterized in that, The update module includes: A comparison unit for accessing the dynamic blacklist library to retrieve whether the passing vehicle has a historical record; wherein, if the passing vehicle has no historical record, a configuration instruction code is generated, and if the passing vehicle has a historical record, the next step is executed; An update unit for redefining the bad behavior level of the passing vehicle according to preset rules and generating an update instruction code; wherein, the bad levels are 1, 2, and 3 levels respectively.

5. The blacklist management system for overloading control vehicles according to claim 4, characterized in that The preset rules are: level 1 is for 3 occurrences of low risk, level 2 is for 1 occurrence of low risk or 1 occurrence of medium risk, and level 3 is for 1 occurrence of high risk.

6. The over-limit vehicle blacklist management system according to claim 4, wherein, The encryption module includes: The first generation unit is used to generate a unique trusted ciphertext for the configuration instruction code or the update instruction code; The splitting unit is used to split the unique trusted ciphertext into N sequence segments; The second generation unit is used to generate a mask for each of the sequence segments to obtain a trusted data packet.

7. A method for managing the blacklist of overweight vehicles, which is applied to the blacklist management system of overweight vehicles according to any one of claims 1 to 6, and is characterized in that, It includes the following steps: S1. Obtain the initial overloading control data of the passing vehicle and verify the unique identifier; S2. Check the network path according to the unique identifier to obtain trusted overloading control data; S3. Analyze the over-limit level according to the trusted overloading control data and mark the corresponding degree identifier; S4. Access the historical records of the dynamic blacklist library to redefine the bad behavior level and obtain a configuration instruction code or an update instruction code; S5. Encrypt the configuration instruction code or the update instruction code to obtain a trusted data packet.

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