General processing method and system for intelligent connected vehicle data

Abstract

The present invention proposes a universal processing method and system for intelligent connected vehicle data, comprising the following steps: creating a corresponding rule table using a cloud platform data ID as an identifier, collecting vehicle data and uploading it in encrypted form; the cloud platform decrypting the received key vehicle data ciphertext to obtain the key vehicle data and extracting the vehicle data's domain ID; performing ID matching on the vehicle data's domain ID and the cloud platform data ID, and implementing classification and grading operations on the vehicle data based on the ID matching results, classification rules and classification matching rules, and grading rules and grading matching rules; and calculating the matching success rate of the rule table and the alarm status of the monitoring model within a set time period, and dynamically adjusting the rule table. The present invention creates a rule table based on the cloud platform's business needs, enabling the cloud platform to call the rule table to perform corresponding classification, grading, and monitoring processing operations on vehicle data, thereby meeting the different processing requirements of each platform for vehicle data.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent connected vehicles, and in particular to a general processing method and system for intelligent connected vehicle data. Background Art

[0002] The rapid development of intelligent connected vehicles has generated a massive amount of automotive data. The automotive data processing process includes vehicle data collection, transmission, classification and grading, storage, and monitoring. However, due to the different business needs of different cloud platforms for automotive data, the requirements for classification, grading, and monitoring operations on automotive data vary across cloud platforms. Currently, there is no single automotive data processing method that can adapt to the diverse needs of each platform. Summary of the Invention

[0003] The purpose of the present invention is to address the deficiencies of the existing technology and thus propose a universal processing method and system for intelligent connected vehicle data. A rule table applicable to the cloud platform is created according to the business needs of the cloud platform, so that the cloud platform can call the rule table to perform corresponding classification, grading, monitoring and processing operations on the vehicle data to meet the different processing requirements of each platform for vehicle data.

[0004] A first aspect of the present invention provides a general method for processing intelligent connected vehicle data, the method comprising the following steps:

[0005] The cloud platform pre-creates a corresponding rule table using the cloud platform data ID as an identifier, wherein the rule table includes the cloud platform data ID, classification matching rules, classification rules, hierarchical matching rules, and hierarchical rules, wherein the classification rules include classification codes, and the hierarchical rules include hierarchical codes;

[0006] The cloud platform determines a mapping relationship between the cloud platform data ID and the classification code, a mapping relationship between the cloud platform data ID and the classification code, and a mapping relationship between the cloud platform data ID and the domain ID of the vehicle data;

[0007] The vehicle side collects vehicle data based on a multi-sensor fusion approach, encrypts key vehicle data and the vehicle data's domain ID in the vehicle data to obtain key vehicle data ciphertext, and uploads the key vehicle data ciphertext to the cloud platform; wherein the key vehicle data refers to vehicle data to be centrally and deeply processed by the cloud platform;

[0008] After receiving the key vehicle data ciphertext, the cloud platform decrypts the key vehicle data ciphertext based on a preset decryption algorithm to obtain the key vehicle data, and extracts the domain ID of the vehicle data from the obtained key vehicle data;

[0009] The cloud platform traverses the cloud platform data ID in the rule table and performs ID matching between the domain ID of the extracted car data and the cloud platform data ID in the rule table;

[0010] If the ID matches successfully, the rule table is traversed to check whether there is a classification code and a grading code that has a mapping relationship with the corresponding cloud platform data ID;

[0011] If both the classification code and the grading code exist, the decrypted key vehicle data will be stored in the corresponding database together with the queried classification code and grading code;

[0012] If the classification code does not exist and the grading code exists, the classification rules and classification matching rules in the rule table are used to classify and match the decrypted key vehicle data, and the corresponding classification operation is performed according to the classification matching result; and the decrypted key vehicle data and the retrieved grading code are stored in the corresponding database;

[0013] If the classification code exists and the grade code does not exist, the decrypted key vehicle data is stored together with the queried classification code in the corresponding database, and the grade matching rule and grade matching rule in the rule table are used to perform grade matching on the decrypted key vehicle data, and the corresponding grade operation is performed according to the grade matching result;

[0014] If neither the classification code nor the classification code exists, the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key vehicle data, and corresponding classification operations are performed according to the classification matching results; and the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key vehicle data, and corresponding classification operations are performed according to the classification matching results;

[0015] If the ID matching is unsuccessful, the decrypted key vehicle data is assigned a preset default classification code and default grading code, and the decrypted key vehicle data is stored together with the corresponding default classification code and default grading code in the corresponding database;

[0016] The cloud platform performs alarm monitoring on the decrypted key vehicle data based on the monitoring model, and issues an alarm when the classification code corresponding to the key vehicle data matches the alarm level code preset in the rule table;

[0017] The cloud platform counts the matching success rate of the rule table within a set time period, and dynamically adjusts the classification matching rules and / or hierarchical matching rules according to the matching success rate;

[0018] The cloud platform collects statistics on the alarm conditions of the monitoring model and dynamically adjusts the classification codes in the rule table according to the alarm conditions.

[0019] A second aspect of the present invention provides a universal processing system for intelligent connected vehicle data, which includes a vehicle terminal, a cloud platform, and a mobile terminal, wherein the vehicle terminal is connected to the cloud platform via a network, and the cloud platform is connected to the mobile terminal via a network;

[0020] The car end includes a data acquisition module and a data collection module, and the data acquisition module is connected to the data collection module; the cloud platform includes a rule-making module, a data classification and grading module, and an alarm module, and the data classification and grading module is connected to the alarm module, and the rule-making module is connected to the data classification and grading module and the alarm module respectively;

[0021] The data acquisition module is used to collect vehicle data based on a multi-sensor fusion method;

[0022] The data collection module is used to centrally store the collected vehicle data, encrypt key vehicle data and the vehicle data domain ID in the vehicle data to obtain key vehicle data ciphertext, and upload the key vehicle data ciphertext to the cloud platform; wherein the key vehicle data refers to the vehicle data to be centrally processed in depth by the cloud platform;

[0023] The rule formulation module is used to pre-create a corresponding rule table using the cloud platform data ID as an identifier, wherein the rule table includes the cloud platform data ID, classification matching rules, classification rules, hierarchical matching rules, and hierarchical rules, wherein the classification rules include classification codes, and the hierarchical rules include hierarchical codes; the rule formulation module is used to determine the mapping relationship between the cloud platform data ID and the classification code, the mapping relationship between the cloud platform data ID and the hierarchical code, and the mapping relationship between the cloud platform data ID and the domain ID of the vehicle data; the rule formulation module is used to count the matching success rate of the rule table within a set time period, and dynamically adjust the classification matching rules and / or hierarchical matching rules according to the matching success rate; and count the alarm conditions of the monitoring model, and dynamically adjust the hierarchical codes in the rule table according to the alarm conditions;

[0024] The data classification and grading module has a built-in database, and is used to decrypt the key vehicle data ciphertext based on a preset decryption algorithm after receiving the key vehicle data ciphertext to obtain the key vehicle data; and extract the domain ID of the vehicle data from the obtained key vehicle data;

[0025] The data classification and grading module is further configured to traverse the cloud platform data IDs in the rule table and perform ID matching between the domain IDs of the extracted car data and the cloud platform data IDs in the rule table;

[0026] If the ID matches successfully, the rule table is traversed to check whether there is a classification code and a grading code that has a mapping relationship with the corresponding cloud platform data ID; if both the classification code and the grading code exist, the decrypted key car data is stored together with the queried classification code and grading code in the corresponding database; if the classification code does not exist and the grading code exists, the classification rules and classification matching rules in the rule table are used to classify and match the decrypted key car data, and the corresponding classification operation is performed according to the classification matching result; and the decrypted key car data is stored together with the queried grading code in the corresponding database; if the classification code exists and the grading code does not exist, The decrypted key automobile data is stored together with the queried classification code in the corresponding database, and the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; if the classification code and the classification code do not exist, the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result;

[0027] If the ID matching is unsuccessful, the decrypted key vehicle data is assigned a preset default classification code and default grading code, and the decrypted key vehicle data is stored together with the corresponding default classification code and default grading code in the corresponding database;

[0028] The alarm module is used to perform alarm monitoring on the decrypted key vehicle data based on the monitoring model, and issue an alarm when the classification code corresponding to the key vehicle data matches the alarm level code preset in the rule table;

[0029] The mobile terminal is used for data exchange between the management terminal and / or the vehicle owner terminal and the cloud platform.

[0030] The beneficial effects of the present invention are:

[0031] The present invention takes automobile data as the center and sets up a universal processing method for classifying, grading, and monitoring automobile data. This method is applicable to different cloud platforms, such as automobile manufacturer cloud platforms, service cloud platforms such as Didi, and regulatory agency cloud platforms. Each cloud platform can create its own applicable rule table according to business needs, so that the cloud platform can call the rule table to perform corresponding classification, grading, monitoring and processing operations on automobile data to meet the different processing requirements of each platform for automobile data. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a flow chart of a general method for processing intelligent connected vehicle data according to the present invention;

[0033] Figure 2 Schematic block diagram of a universal processing system for intelligent connected vehicle data according to the present invention;

[0034] Figure 3 This is a flow chart of the ID matching, classification code search and grading code search of the present invention. DETAILED DESCRIPTION

[0035] In order to more clearly understand the above-mentioned objects, features and advantages of the present invention, the present invention is further described in detail below with reference to the accompanying drawings and specific embodiments.

[0036] Example 1

[0037] The following describes a general method for processing intelligent connected vehicle data according to an embodiment of the present invention with reference to the accompanying drawings.

[0038] Figure 1 A flowchart of a general method for processing intelligent connected vehicle data is shown, and the general method for processing intelligent connected vehicle data includes the following steps:

[0039] The cloud platform pre-creates a corresponding rule table using the cloud platform data ID as an identifier, wherein the rule table includes the cloud platform data ID, classification matching rules, classification rules, hierarchical matching rules, and hierarchical rules, wherein the classification rules include classification codes, and the hierarchical rules include hierarchical codes;

[0040] The cloud platform determines a mapping relationship between the cloud platform data ID and the classification code, a mapping relationship between the cloud platform data ID and the classification code, and a mapping relationship between the cloud platform data ID and the domain ID of the vehicle data;

[0041] The vehicle side collects vehicle data based on a multi-sensor fusion approach, encrypts key vehicle data and the vehicle data's domain ID in the vehicle data to obtain key vehicle data ciphertext, and uploads the key vehicle data ciphertext to the cloud platform; wherein the key vehicle data refers to vehicle data to be centrally and deeply processed by the cloud platform;

[0042] As attached Figure 3 As shown, after receiving the key car data ciphertext, the cloud platform decrypts the key car data ciphertext based on a preset decryption algorithm to obtain the key car data, and extracts the domain ID of the car data from the obtained key car data;

[0043] The cloud platform traverses the cloud platform data ID in the rule table and performs ID matching between the domain ID of the extracted car data and the cloud platform data ID in the rule table;

[0044] If the ID matches successfully, it means that there is a cloud platform data ID mapped to the domain ID of the car data in the rule table, then the rule table is traversed to check whether there is a classification code and a grading code that has a mapping relationship with the corresponding cloud platform data ID;

[0045] If both the classification code and the classification code exist, it means that the classification code and classification code mapped to the cloud platform data ID that has successfully matched the ID exist in the rule table, and the decrypted key car data is stored together with the queried classification code and classification code in the corresponding database;

[0046] If the classification code does not exist and the classification code exists, it means that there is no classification code mapped to the cloud platform data ID with successful ID matching in the rule table, but there is a classification code mapped to the cloud platform data ID with successful ID matching. Then, the classification rule and classification matching rule in the rule table are used to classify and match the decrypted key vehicle data, and the corresponding classification operation is performed according to the classification matching result; and the decrypted key vehicle data and the queried classification code are stored in the corresponding database together;

[0047] If the classification code exists but the classification code does not exist, it means that there is a classification code mapped to the cloud platform data ID that has successfully matched the ID in the rule table, but there is no classification code mapped to the cloud platform data ID that has successfully matched the ID. Then, the decrypted key vehicle data and the queried classification code are stored in the corresponding database, and the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key vehicle data, and the corresponding classification operation is performed according to the classification matching result.

[0048] If neither the classification code nor the classification code exists, it means that the classification code and classification code mapped to the cloud platform data ID that has successfully matched the ID do not exist in the rule table, then the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; and the classification rules and classification matching rules in the rule table are used to perform hierarchical matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the hierarchical matching result;

[0049] If the ID matching is unsuccessful, it means that there is no cloud platform data ID mapped to the domain ID of the vehicle data in the rule table, then the decrypted key vehicle data is assigned a preset default classification code and default grading code, and the decrypted key vehicle data is stored together with the corresponding default classification code and default grading code in the corresponding database;

[0050] The cloud platform performs alarm monitoring on the decrypted key vehicle data based on the monitoring model, and issues an alarm when the classification code corresponding to the key vehicle data matches the alarm level code preset in the rule table;

[0051] The cloud platform calculates the matching success rate of the rule table within a set time period, and dynamically adjusts the classification matching rules and / or hierarchical matching rules according to the matching success rate;

[0052] The cloud platform collects statistics on the alarm conditions of the monitoring model and dynamically adjusts the classification codes in the rule table according to the alarm conditions, wherein the alarm conditions include alarm frequency and alarm objects.

[0053] It should be noted that the car uploads the encrypted key car data to the cloud platform in real-time, scheduled, and engine-off modes. The car data uploaded to the cloud platform carries vehicle information, personnel information, and decryption-related information, including owner information, identity information, and key information.

[0054] When encrypting and transmitting vehicle data, the vehicle side uses a certificate management system and a key management system to encrypt the vehicle data, such as using a CA system and a KMS key management system to encrypt the vehicle data; the cloud platform verifies the credibility of the received vehicle data by determining whether the vehicle information carried by the vehicle data falls within a pre-set vehicle trusted list, and / or whether the personnel information carried by the vehicle data falls within a pre-set personnel trusted list. If it falls within the pre-set vehicle trusted list and / or the pre-set personnel trusted list, the key vehicle data ciphertext that has successfully verified the credibility is decrypted based on a preset decryption algorithm.

[0055] The general processing method for intelligent connected vehicle data in this embodiment is centered on vehicle data and provides a general processing method for automatically and quickly classifying, grading, and monitoring vehicle data. The method is applicable to different cloud platforms such as service cloud platforms and regulatory agency cloud platforms. Service cloud platforms include automobile manufacturer cloud platforms, Didi, etc. Each cloud platform can expand the rule table based on its own business needs using the cloud platform data ID as an identifier to obtain a rule table that matches the business needs of each cloud platform, thereby enabling the cloud platform to call the rule table to perform corresponding classification, grading, monitoring, and processing operations on the vehicle data to automatically meet the different processing needs of each platform for vehicle data.

[0056] like Figure 1 As shown, in some embodiments, the domain ID of the car data is logically transformed to form the cloud platform data ID; wherein the logical transformation includes encryption, etc.;

[0057] It should be noted that since the cloud platform data ID is based on the architecture of the vehicle side, it uses the domain ID of the vehicle data as the initial identifier and is formed after logical transformation. Therefore, there is a mapping relationship between the cloud platform data ID and the domain ID of the vehicle data, which can be used as the basis for the classification and grading of vehicle data. In addition, using the cloud platform data ID as the identifier of the rule table in the cloud platform can also prevent the cloud platform from leaking the domain ID of the vehicle side.

[0058] Furthermore, the cloud platform uses the cloud platform data ID as an identifier in advance, and when creating a corresponding rule table, executes:

[0059] Using the cloud platform data ID as an identifier, set the classification rules and classification matching rules in the rule table. The classification rules include general classification rules, custom classification rules, and unclassified rules. The classification matching rules include classification regular matching rules, classification head and tail matching rules, classification middle matching rules, and classification fuzzy matching rules.

[0060] Using the cloud platform data ID as an identifier, set the hierarchical rules and hierarchical matching rules in the rule table. The hierarchical rules include default hierarchical rules and custom hierarchical rules. The hierarchical matching rules include hierarchical regular matching rules, hierarchical head-tail matching rules, hierarchical middle matching rules, and hierarchical fuzzy matching rules.

[0061] The cloud platform data ID is used as an identifier and the alarm level code in the monitoring model is set according to the classification code; wherein the specific value of the alarm level code is set according to business needs, with reference to relevant standards, and after training with big data.

[0062] It can be understood that the classification matching rules are pre-set in the rule table according to business needs, and are used to realize the matching operation between automobile data and classification rules; the hierarchical matching rules are pre-set in the rule table according to business needs, and are used to realize the matching operation between automobile data and hierarchical rules.

[0063] Among them, the classified regular matching rule and the hierarchical regular matching rule are both configured to use regular expressions for rule matching, the classified head-to-tail matching rule and the hierarchical head-to-tail matching rule are both configured as head-to-tail matching algorithms, the classified middle matching rule and the hierarchical middle matching rule are both configured as middle data matching algorithms, and the classified fuzzy matching rule and the hierarchical fuzzy matching rule are both configured as fuzzy data matching algorithms; the specific classified matching rules and hierarchical matching rules are not repeated here.

[0064] It should be noted that the general classification rules in the classification rules are pre-set in the rule table based on the general rules of the Internet of Vehicles industry; for example, the general classification rules are set according to the "Technical Requirements for Data Security of Internet of Vehicles Information Services" (YD / T3751-2020) and the "Requirements for the Protection of Personal Information of Users of Internet of Vehicles Information Services" (YD / T3746-2020);

[0065] The custom classification rules in the classification rules are pre-set in the rule table of each cloud platform according to business needs. If it is not a general rule of the Internet of Vehicles industry (classification strategy that does not recognize general classification rules), the car data can be directly customized for classification; if it is a general rule of the Internet of Vehicles industry (classification strategy that recognizes general classification rules), it is further classified based on the general classification rules to achieve further refinement and customization of classification, thereby meeting the personalized classification needs of the Internet of Vehicles industry;

[0066] The non-classification rule in the classification rule is applicable to automobile data that cannot be classified and is only used as scattered data;

[0067] When classifying automobile data, the data parameters are the lowest level of classification. For example, the data parameters such as engine speed and driving speed are used as the lowest level of classification.

[0068] The default classification rules in the classification rules are pre-set in the rule table based on the general rules of the Internet of Vehicles industry. For example, the default classification rules are set according to the "Technical Requirements for Data Security of Internet of Vehicles Information Services" (YD / T3751-2020) and the "Requirements for the Protection of Personal Information of Users of Internet of Vehicles Information Services" (YD / T3746-2020);

[0069] The custom classification rules in the classification rules are pre-set in the rule table based on business needs. The custom classification rules can classify the sensitivity levels of automobile data according to business needs; for example, automobile data can be divided into general data, important publicly available data, important non-public data, and sensitive data. The classification strategy is implemented by adaptively combining the default classification rules and the custom classification rules in a similar manner to the classification strategy, so as to achieve further refinement and customization of the classification, thereby meeting the personalized classification demands of the Internet of Vehicles industry.

[0070] The Internet of Vehicles industry refers to all related industries involved in automobile data classification and grading technology, including but not limited to the automobile manufacturing industry, automobile sales industry, automobile rental industry, shared travel industry, and automobile software service industry.

[0071] When creating the corresponding rule table using the cloud platform data ID as an identifier, the mapping relationship between the cloud platform data ID and the classification rule is determined. The classification rule corresponding to the cloud platform data ID is pre-configured based on the cloud platform type, etc. Therefore, when the classification code does not exist, the classification rule mapped to the cloud platform data ID can be quickly found based on the cloud platform data ID.

[0072] When creating the corresponding rule table using the cloud platform data ID as an identifier, the mapping relationship between the cloud platform data ID and the grading rules is also determined. The grading rules corresponding to the cloud platform data ID are pre-configured based on the cloud platform type, etc.; therefore, when the grading code does not exist, the grading rules mapped to the cloud platform data ID can be quickly found based on the cloud platform data ID.

[0073] It should be noted that the cloud platform uses the cloud platform data ID as an identifier to create a corresponding rule table, which serves as a basis for the cloud platform to call the rule table to classify, grade, and alarm monitor the vehicle data after decrypting the vehicle data.

[0074] Example 2

[0075] It should be noted that, during the initialization phase, a mapping relationship is pre-established between the cloud platform data ID and the classification code, a mapping relationship is pre-established between the cloud platform data ID and the classification code, and a mapping relationship is pre-established between the domain ID of the vehicle data and the cloud platform data ID. The above mapping relationships include but are not limited to one-to-one relationships;

[0076] Subsequently, as the type of automobile data increases, new domain IDs of automobile data will appear, so there may be situations where ID matching fails; accordingly, the cloud platform data ID corresponding to the domain ID of the new automobile data is added to the rule table, but the corresponding classification code and / or grading code is not assigned to the cloud platform data ID in a timely manner.

[0077] It can be understood that there is a mapping relationship between the cloud platform data ID and the classification code, and a mapping relationship between the cloud platform data ID and the grading code; the cloud platform data ID, classification code and grading code are all pre-configured in the initialization stage, so during classification matching and grading matching, the cloud platform can quickly and accurately assign corresponding classification codes and grading codes to the automobile data based on the mapping relationship, thereby realizing the classification and grading operations of the automobile data.

[0078] If the ID match is successful but the corresponding classification code cannot be found, the cloud platform matches the vehicle data with the classification rules in the rule table according to the classification matching rules in the rule table, and performs the classification operation corresponding to the matching result to meet the cloud platform's classification processing of diverse vehicle data;

[0079] Therefore, based on Example 1, this example provides a specific implementation of another general method for processing data of intelligent connected vehicles.

[0080] like Figure 1 As shown, in some embodiments, the cloud platform uses the classification rules and classification matching rules in the rule table to perform classification matching on the decrypted key automobile data, and when performing corresponding classification operations according to the classification matching results, performs:

[0081] Based on the ID matching result, the classification matching rules in the rule table are screened to select a target classification matching rule from the classification matching rules; wherein the target classification matching rule refers to a specific matching rule in the classification matching rules that is associated with the ID matching result;

[0082] The classification rules in the rule table are obtained, and the decrypted key automobile data is classified and matched with the classification rules according to each target classification matching rule.

[0083] In order to improve the efficiency of classification matching, the cloud platform screens the specific matching rules in the classification matching rules based on the ID matching results, and screens out the specific matching rules associated with the data type corresponding to the ID matching results, thereby effectively reducing the amount of matching calculations.

[0084] It should be noted that there is an association between the target classification matching rule and the classification code in the classification rule, so the cloud platform can choose, based on the classification matching result, to assign the key vehicle data a classification code preset in the classification rule or a preset default classification code;

[0085] Specifically, when the cloud platform classifies and matches the decrypted key automobile data with the classification rules according to each target classification matching rule, it executes:

[0086] The cloud platform performs parallel matching on the decrypted key automobile data according to each target classification matching rule and the classification rule, and obtains classification matching results obtained by matching according to each target classification matching rule;

[0087] Performing an OR operation on the classification matching results to obtain a classification OR operation result;

[0088] If the result of the classification OR operation is true, indicating that the vehicle data matches the corresponding classification rule correctly, the decrypted key vehicle data is assigned a corresponding classification code (the classification code associated with the corresponding classification rule), and the decrypted key vehicle data and the corresponding classification code are stored in the corresponding database;

[0089] If the classification OR operation result is false, indicating that the car data does not match the classification rule correctly, the decrypted key car data is assigned a preset default classification code, and the decrypted key car data and the corresponding default classification code are stored in the corresponding database.

[0090] It should be noted that, if the ID match is successful but the corresponding classification code cannot be found, the cloud platform will match the vehicle data with the classification rules in the rule table according to the classification matching rules in the rule table, and perform the corresponding classification operation based on the matching results, so as to realize the classification processing of diversified vehicle data by the cloud platform;

[0091] like Figure 1 As shown, in some embodiments, the cloud platform uses the hierarchical rules and hierarchical matching rules in the rule table to perform hierarchical matching on the decrypted key automobile data, and when performing corresponding hierarchical operations according to the hierarchical matching results, performs:

[0092] Based on the ID matching result, the hierarchical matching rules in the rule table are screened to select a target hierarchical matching rule in the hierarchical matching rules; the target hierarchical matching rule refers to a specific matching rule in the hierarchical matching rules associated with the ID matching result;

[0093] Obtaining the hierarchical rules in the rule table, and performing parallel matching on the decrypted key vehicle data and the hierarchical rules according to each target hierarchical matching rule, to obtain hierarchical matching results corresponding to each target hierarchical matching rule;

[0094] Perform an OR operation on the hierarchical matching results corresponding to each target hierarchical matching rule to obtain a hierarchical OR operation result;

[0095] If the result of the classification OR operation is true, indicating that the vehicle data matches the classification rule correctly, the decrypted key vehicle data is assigned a corresponding classification code (the classification code associated with the corresponding classification rule), and the decrypted key vehicle data and the corresponding classification code are stored in the corresponding database;

[0096] If the result of the classification OR operation is false, indicating that the car data does not match the classification rules correctly, the decrypted key car data is assigned a preset default classification code, and the decrypted key car data and the corresponding default classification code are stored in the corresponding database.

[0097] It should be noted that, based on the impact of automobile data leakage, the classification operation uses the classification code as an identifier to determine the danger level and corresponding usage permissions; for example, automobile data with a danger level of 1 is granted internal public data and can be accessed by system operators; automobile data with a danger level of 2 can only be made public to some personnel, that is, the automobile data needs to be configured with personnel access rights, and only configured personnel can view it; automobile data with a danger level of 3 has limited personnel access rights; automobile data with a danger level of 4 is accessible by default to the data owner and administrator, and no one else can access it; automobile data with a danger level of 5 is accessible only to administrators and reviewers;

[0098] After defining the danger level and corresponding usage permissions, the vehicle data is stored according to the corresponding storage strategy. For example, unstructured data such as images, voice, and fingerprints are encrypted and stored in isolation on designated servers. String data with a danger level exceeding level 3 is encrypted, while string data below level 3 is stored unencrypted.

[0099] And the car data is shared according to the sharing strategy; for example, core and highly sensitive car data is not shared and can only be viewed by core personnel; conditional sharing is implemented for moderately sensitive car data, and sharing is supported through internal approval and authorization; and free sharing is implemented for shared information.

[0100] Example 3

[0101] It should be noted that, in Example 2, the grading operation uses the grading code as an identifier to formulate the danger level and the corresponding usage rights according to the influence after the automobile data is leaked. Therefore, after determining the grading code corresponding to the key automobile data, the danger level corresponding to the grading code can be determined; in order to realize the alarm monitoring of key automobile data, the cloud platform presets the corresponding alarm level code according to the danger level; therefore, based on the above embodiment, this embodiment provides a specific implementation method of another general processing method for intelligent connected vehicle data.

[0102] like Figure 1 As shown, in some embodiments, the cloud platform counts the matching success rate of the rule table within a set time period, and dynamically adjusts the classification matching rules and / or hierarchical matching rules according to the matching success rate, and executes:

[0103] The cloud platform counts the matching success rate of each classification matching rule within a set time period;

[0104] If the matching success rate of each classification matching rule within the set time period is greater than the preset matching rate, no adjustment will be made to all classification matching rules;

[0105] If there is a classification matching rule with a matching success rate lower than the preset matching rate within the set time period, and the classification matching rule does not fall within the range of key classification matching rules, the corresponding classification matching rule is deleted;

[0106] If the matching success rate of all classification matching rules within the set time period is lower than the preset matching rate, a "classification abnormality" prompt message will be sent to the management end through the cloud platform, reminding the management staff to manually adjust the classification matching rules to improve the effective matching rate;

[0107] Count the default category matching frequency within the set time period. If the default category matching frequency is too high (the default category matches many times within the set time period, i.e., the frequency is high), it indicates that the category matching rules are not set properly. In this case, manually adjust the category matching rules in the rule table to improve the effective matching rate; and

[0108] The cloud platform counts the matching success rate of each hierarchical matching rule within a set time period;

[0109] If the matching success rate of each hierarchical matching rule within the set time period is greater than the preset matching rate, no adjustment will be made to all hierarchical matching rules;

[0110] If there is a hierarchical matching rule with a matching success rate lower than the preset matching rate within the set time period, and the hierarchical matching rule does not fall within the range of key hierarchical matching rules, the corresponding hierarchical matching rule is deleted;

[0111] If the matching success rate of all classification matching rules within the set time period is lower than the preset matching rate, a "classification abnormality" prompt message will be sent to the management end through the cloud platform to remind the management to manually adjust the classification matching rules;

[0112] Count the default hierarchical matching frequency within the set time period. If the default hierarchical matching frequency is too high, it means that the hierarchical matching rules are not set properly. Manually adjust the hierarchical matching rules in the rule table to improve the effective matching rate.

[0113] It should be noted that the set time period is pre-set according to the business needs of the cloud platform, for example, the set time period is 30 days; the preset matching rate of the classification matching rule and the preset matching rate of the hierarchical matching rule are also pre-set according to the business needs of the cloud platform, for example, the preset matching rate is 50%;

[0114] The phrase "not belonging to the scope of key classification matching rules" means that deleting such classification matching rules will not affect the classification matching results; the phrase "not belonging to the scope of key hierarchical matching rules" means that deleting such hierarchical matching rules will not affect the hierarchical matching results;

[0115] Deleting classification matching rules whose matching success rate within the set time period is lower than the preset matching rate and which do not fall within the scope of key classification matching rules, and deleting hierarchical matching rules whose matching success rate within the set time period is lower than the preset matching rate and which do not fall within the scope of key hierarchical matching rules, are both aimed at reducing system matching resource usage and improving system utilization.

[0116] Therefore, the cloud platform counts the matching success rate of the rule table within the set time period, and adjusts the classification matching rules and / or hierarchical matching rules in the rule table according to the matching success rate, forming a feedback mechanism for classification operations and hierarchical operations to achieve automatic adjustment of the rule table, reduce human intervention, and improve the security of automobile data classification and grading operations.

[0117] like Figure 1 As shown, in some embodiments, when the cloud platform performs alarm monitoring on the decrypted key automobile data based on the monitoring model, it executes:

[0118] The alarm level codes preset in the monitoring model include general information level codes, important information level codes, sensitive alarm level codes and abnormal alarm level codes;

[0119] Determine whether the classification code corresponding to the key vehicle data matches the alarm level code preset in the monitoring model,

[0120] When it is detected that the classification code corresponding to the decrypted key vehicle data matches the sensitive warning level code, the decrypted key vehicle data is determined to be sensitive information, and the cloud platform sends a reminder message to the management terminal; and

[0121] When the classification code corresponding to the decrypted key vehicle data matches the abnormality warning level code, the decrypted key vehicle data is determined to be abnormal information, and an alarm message is sent to the vehicle owner via SMS.

[0122] It can be understood that the cloud platform uses the monitoring model to actively monitor the vehicle data in real time and handle abnormal alarms, notifying the corresponding personnel when the vehicle data becomes abnormal and / or sensitive so that the corresponding personnel can take timely measures to eliminate safety hazards and prevent the situation from further deteriorating. At the same time, it also enables the cloud platform to monitor and process vehicle data.

[0123] It should be noted that the cloud platform collects statistics and analyzes sensitive files in stored vehicle data in real time, and monitors abnormal status of vehicle data in real time. When a mapping relationship is detected between the classification code corresponding to the vehicle data and the sensitive warning level code, the vehicle data is determined to be sensitive information, such as criminal information or minors. The cloud platform sends a reminder to the management personnel, prompting them to take timely measures to eliminate safety hazards.

[0124] When a mapping relationship is detected between the classification code corresponding to the monitored vehicle data and the abnormal alarm level code, the vehicle data is determined to be abnormal information. For example, vehicle speeding, abnormal tire pressure, and high coolant temperature are abnormal conditions. An alert message is sent to the vehicle owner via SMS so that timely disposal measures can be taken;

[0125] In addition, when a car malfunctions or has software problems, managers use OTA (Over-the-Air Technology) to eliminate safety hazards.

[0126] like Figure 1 As shown, in some embodiments, when the cloud platform collects statistics on the alarm status of the monitoring model and dynamically adjusts the classification code in the rule table according to the alarm status, the following is executed:

[0127] The alarm conditions of the pre-configured monitoring model include the alarm frequency and the alarm object, wherein the alarm object is the vehicle data that generates the alarm;

[0128] The cloud platform counts the alarm frequency of the monitoring model, and if the counted alarm frequency exceeds the preset frequency, the corresponding classification code in the rule table is reduced by one level;

[0129] The cloud platform statistically monitors the alarm objects of the model. If the proportion of the alarm objects of the same category and / or the same level counted exceeds a preset ratio, the corresponding classification code in the rule table is reduced by one level.

[0130] The preset frequency can be set manually, for example, the preset frequency is 5 times / 24h, and the preset ratio can also be set manually, for example, the preset ratio is 50%.

[0131] It should be noted that when the cloud platform lowers the corresponding classification code in the rule table by one level, it executes: each time the cloud platform counts that the alarm frequency exceeds the preset frequency and / or the proportion of alarm objects of the same category and / or the same level exceeds the preset proportion, the current classification code is modified to a classification code of a lower level, so that the classification code only changes by one level, step by step.

[0132] It should be noted that the cloud platform pre-sets the alarm level code, monitors and alarms the vehicle data, and dynamically adjusts the classification code in the rule table according to the alarm situation, forming a feedback mechanism for monitoring operations to achieve automatic updates of the rule table, reduce human intervention, and improve the security of vehicle data monitoring operations.

[0133] Example 4

[0134] Based on the above embodiment, this embodiment provides a specific implementation of a general processing system for intelligent connected vehicle data;

[0135] like Figure 2As shown, the universal processing system for intelligent connected vehicle data includes a vehicle side, a cloud platform and a mobile terminal. The vehicle side is connected to the cloud platform via a network, and the cloud platform is connected to the mobile terminal via a network.

[0136] The car end includes a data acquisition module and a data collection module, and the data acquisition module is connected to the data collection module; the cloud platform includes a rule-making module, a data classification and grading module, and an alarm module, and the data classification and grading module is connected to the alarm module, and the rule-making module is connected to the data classification and grading module and the alarm module respectively;

[0137] The data acquisition module is used to collect vehicle data based on a multi-sensor fusion method;

[0138] The data collection module is used to centrally store the collected vehicle data, encrypt key vehicle data and the vehicle data's domain ID in the vehicle data to obtain key vehicle data ciphertext, and upload the key vehicle data ciphertext to the cloud platform. The key vehicle data refers to vehicle data to be centrally processed (including classification, grading, and alarm monitoring) by the cloud platform.

[0139] The rule formulation module is used to pre-create a corresponding rule table using the cloud platform data ID as an identifier, wherein the rule table includes the cloud platform data ID, classification matching rules, classification rules, hierarchical matching rules, and hierarchical rules, wherein the classification rules include classification codes, and the hierarchical rules include hierarchical codes; the rule formulation module is used to determine the mapping relationship between the cloud platform data ID and the classification code, the mapping relationship between the cloud platform data ID and the hierarchical code, and the mapping relationship between the cloud platform data ID and the domain ID of the vehicle data; the rule formulation module is used to calculate the matching success rate of the rule table within a set time period, and dynamically adjust the classification matching rules and / or hierarchical matching rules according to the matching success rate; and to calculate the alarm status of the monitoring model and dynamically adjust the hierarchical code in the rule table according to the alarm status;

[0140] The data classification and grading module has a built-in database, and is used to decrypt the key vehicle data ciphertext based on a preset decryption algorithm after receiving the key vehicle data ciphertext to obtain the key vehicle data; and extract the domain ID of the vehicle data from the obtained key vehicle data;

[0141] The data classification and grading module is further configured to traverse the cloud platform data IDs in the rule table and perform ID matching between the domain IDs of the extracted car data and the cloud platform data IDs in the rule table;

[0142] If the ID matches successfully, the rule table is traversed to check whether there is a classification code and a grading code that has a mapping relationship with the corresponding cloud platform data ID; if both the classification code and the grading code exist, the decrypted key car data is stored together with the queried classification code and grading code in the corresponding database; if the classification code does not exist and the grading code exists, the classification rules and classification matching rules in the rule table are used to classify and match the decrypted key car data, and the corresponding classification operation is performed according to the classification matching result; and the decrypted key car data is stored together with the queried grading code in the corresponding database; if the classification code exists and the grading code does not exist, The decrypted key automobile data is stored together with the queried classification code in the corresponding database, and the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; if the classification code and the classification code do not exist, the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result;

[0143] If the ID matching is unsuccessful, the decrypted key vehicle data is assigned a preset default classification code and default grading code, and the decrypted key vehicle data is stored together with the corresponding default classification code and default grading code in the corresponding database;

[0144] The alarm module is used to perform alarm monitoring on the decrypted key vehicle data based on the monitoring model, and issue an alarm when the classification code corresponding to the key vehicle data matches the alarm level code preset in the rule table;

[0145] The mobile terminal is used for data exchange between the management terminal and / or the vehicle owner terminal and the cloud platform.

[0146] Among them, the multi-sensor fusion method adopts the fusion of cameras, millimeter-wave radars, lidars, ultrasonic radars, etc.; the automobile data includes basic attribute data, vehicle industrial control data, environmental perception data, vehicle control data, application service data and user personal information, etc.

[0147] It can be understood that in this embodiment, the automobile data is centrally stored in the data collection module, and the automobile data to be transmitted to the cloud platform for processing is encrypted and uploaded to the cloud platform; the cloud platform can be one of different cloud platforms such as the automobile manufacturer's cloud platform, the service cloud platform such as Didi, and the regulatory agency's cloud platform. Each cloud platform can create a rule table according to its own business needs;

[0148] It should be noted that the steps of classifying and grading the automobile data by the data classification and grading module are specifically divided into two situations: one is to classify and grade the automobile data at the same time; the other is to classify the automobile data first and then grade the automobile data;

[0149] The set time period is set according to the business needs of the cloud platform, for example, the set time period is 30 days;

[0150] The alarm condition includes the alarm frequency and the alarm object.

[0151] The universal processing system for intelligent connected vehicle data in an embodiment of the present invention mainly uses a rule-making module to create a corresponding rule table with the cloud platform data ID as an identifier, so that different cloud platforms can create rule tables suitable for themselves according to their own business needs, and uses a data classification and grading module and an alarm module to retrieve the rule table with the corresponding cloud platform data ID as an identifier with the domain ID of the vehicle data, and classifies, grades, and monitors the vehicle data according to the rule table to realize a universal processing method suitable for classification, grading, and monitoring operations of vehicle data on various cloud platforms, so as to meet the different processing requirements of each platform for vehicle data.

[0152] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to preferred embodiments, ordinary technicians in the field should understand that the specific implementation methods of the present invention can still be modified or some technical features can be replaced by equivalents without departing from the spirit of the technical solutions of the present invention. They should all be included in the scope of the technical solutions claimed for protection by the present invention.

Claims

1. A general method for processing intelligent connected vehicle data, characterized in that: The following steps are involved: The cloud platform pre-creates a corresponding rule table using the cloud platform data ID as an identifier, wherein the rule table includes the cloud platform data ID, classification matching rules, classification rules, hierarchical matching rules, and hierarchical rules, wherein the classification rules include classification codes, and the hierarchical rules include hierarchical codes; The cloud platform determines a mapping relationship between the cloud platform data ID and the classification code, a mapping relationship between the cloud platform data ID and the classification code, and a mapping relationship between the cloud platform data ID and the domain ID of the vehicle data; The vehicle side collects vehicle data based on a multi-sensor fusion approach, encrypts key vehicle data and the vehicle data's domain ID in the vehicle data to obtain key vehicle data ciphertext, and uploads the key vehicle data ciphertext to the cloud platform; wherein the key vehicle data refers to vehicle data to be centrally and deeply processed by the cloud platform; After receiving the key vehicle data ciphertext, the cloud platform decrypts the key vehicle data ciphertext based on a preset decryption algorithm to obtain the key vehicle data, and extracts the domain ID of the vehicle data from the obtained key vehicle data; The cloud platform traverses the cloud platform data ID in the rule table and performs ID matching between the domain ID of the extracted car data and the cloud platform data ID in the rule table; If the ID matches successfully, the rule table is traversed to check whether there is a classification code and a grading code that has a mapping relationship with the corresponding cloud platform data ID; If both the classification code and the grading code exist, the decrypted key vehicle data will be stored in the corresponding database together with the queried classification code and grading code; If the classification code does not exist and the grading code exists, the classification rules and classification matching rules in the rule table are used to classify and match the decrypted key vehicle data, and the corresponding classification operation is performed according to the classification matching result; and the decrypted key vehicle data and the retrieved grading code are stored in the corresponding database; If the classification code exists and the grade code does not exist, the decrypted key vehicle data is stored together with the queried classification code in the corresponding database, and the grade matching rule and grade matching rule in the rule table are used to perform grade matching on the decrypted key vehicle data, and the corresponding grade operation is performed according to the grade matching result; If neither the classification code nor the classification code exists, the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key vehicle data, and corresponding classification operations are performed according to the classification matching results; and the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key vehicle data, and corresponding classification operations are performed according to the classification matching results; If the ID matching is unsuccessful, the decrypted key vehicle data is assigned a preset default classification code and default grading code, and the decrypted key vehicle data is stored together with the corresponding default classification code and default grading code in the corresponding database; The cloud platform performs alarm monitoring on the decrypted key vehicle data based on the monitoring model, and issues an alarm when the classification code corresponding to the key vehicle data matches the alarm level code preset in the rule table; The cloud platform counts the matching success rate of the rule table within a set time period, and dynamically adjusts the classification matching rules and / or hierarchical matching rules according to the matching success rate; The cloud platform collects statistics on the alarm conditions of the monitoring model and dynamically adjusts the classification codes in the rule table according to the alarm conditions.

2. The universal processing method for intelligent connected vehicle data according to claim 1, characterized in that: The domain ID of the automobile data is logically transformed to form the cloud platform data ID; wherein the logical transformation includes encryption.

3. The universal processing method for intelligent connected vehicle data according to claim 2, characterized in that: The cloud platform uses the cloud platform data ID as an identifier in advance. When creating the corresponding rule table, the following is executed: Using the cloud platform data ID as an identifier, set the classification rules and classification matching rules in the rule table. The classification rules include general classification rules, custom classification rules, and unclassified rules. The classification matching rules include classification regular matching rules, classification head and tail matching rules, classification middle matching rules, and classification fuzzy matching rules. Using the cloud platform data ID as an identifier, set the hierarchical rules and hierarchical matching rules in the rule table. The hierarchical rules include default hierarchical rules and custom hierarchical rules. The hierarchical matching rules include hierarchical regular matching rules, hierarchical head-tail matching rules, hierarchical middle matching rules, and hierarchical fuzzy matching rules. The cloud platform data ID is used as an identifier and the alarm level code in the monitoring model is set according to the classification code.

4. The universal processing method for intelligent connected vehicle data according to claim 3, characterized in that: The cloud platform uses the classification rules and classification matching rules in the rule table to classify and match the decrypted key automobile data. When performing corresponding classification operations based on the classification matching results, the following operations are executed: Based on the ID matching result, the classification matching rules in the rule table are screened to select the target classification matching rule in the classification matching rules; The classification rules in the rule table are obtained, and the decrypted key automobile data is classified and matched with the classification rules according to each target classification matching rule.

5. The universal processing method for intelligent connected vehicle data according to claim 4, characterized in that: When the cloud platform classifies and matches the decrypted key automobile data with the classification rules according to each target classification matching rule, it executes: Obtaining classification matching results obtained by matching according to each target classification matching rule respectively, performing an OR operation on the classification matching results to obtain a classification OR operation result; If the classification OR operation result is true, the decrypted key vehicle data is assigned a corresponding classification code, and the decrypted key vehicle data and the corresponding classification code are stored in a corresponding database; If the result of the classification OR operation is false, a preset default classification code is assigned to the decrypted key automobile data, and the decrypted key automobile data and the corresponding default classification code are stored in a corresponding database.

6. The universal processing method for intelligent connected vehicle data according to claim 4, characterized in that: The cloud platform uses the hierarchical rules and hierarchical matching rules in the rule table to perform hierarchical matching on the decrypted key automobile data, and when performing corresponding hierarchical operations according to the hierarchical matching results, executes: Based on the ID matching result, the hierarchical matching rules in the rule table are screened to select a target hierarchical matching rule from the hierarchical matching rules; Obtaining the hierarchical rules in the rule table, and matching the decrypted key vehicle data with the hierarchical rules according to each target hierarchical matching rule, to obtain hierarchical matching results corresponding to each target hierarchical matching rule; Performing an OR operation on the hierarchical matching results to obtain a hierarchical OR operation result; If the result of the classification OR operation is true, the decrypted key vehicle data is assigned a corresponding classification code, and the decrypted key vehicle data and the corresponding classification code are stored in a corresponding database; If the result of the classification OR operation is false, a preset default classification code is assigned to the decrypted key vehicle data, and the decrypted key vehicle data and the corresponding default classification code are stored in a corresponding database.

7. The universal method for processing intelligent connected vehicle data according to claim 5 or 6, characterized in that: The cloud platform collects statistics on the matching success rate of the rule table within a set time period and dynamically adjusts the classification matching rules and / or the hierarchical matching rules according to the matching success rate, performing: The cloud platform counts the matching success rate of each classification matching rule within a set time period, and if there is a classification matching rule with a matching success rate lower than a preset matching rate within the set time period, and the classification matching rule does not fall within the range of key classification matching rules, the corresponding classification matching rule is deleted; and The cloud platform counts the matching success rate of each hierarchical matching rule within a set time period. If there is a hierarchical matching rule with a matching success rate lower than a preset matching rate within the set time period, and the hierarchical matching rule does not fall within the range of key hierarchical matching rules, the corresponding hierarchical matching rule is deleted.

8. The universal processing method for intelligent connected vehicle data according to claim 3, characterized in that: When the cloud platform performs alarm monitoring on the decrypted key vehicle data based on the monitoring model, it executes: The alarm level codes preset in the monitoring model include sensitive alarm level codes and abnormal alarm level codes; When it is detected that the classification code corresponding to the decrypted key vehicle data matches the sensitive warning level code, the decrypted key vehicle data is determined to be sensitive information, and the cloud platform sends a reminder message to the management terminal; as well as When the classification code corresponding to the decrypted key vehicle data matches the abnormality warning level code, the decrypted key vehicle data is determined to be abnormal information, and an alarm message is sent to the vehicle owner via SMS.

9. The universal processing method for intelligent connected vehicle data according to claim 8, characterized in that: When the cloud platform collects statistics on the alarm status of the monitoring model and dynamically adjusts the classification code in the rule table according to the alarm status, the following steps are executed: The alarm conditions of the pre-configured monitoring model include the alarm frequency and the alarm object, wherein the alarm object is the vehicle data that generates the alarm; The cloud platform counts the alarm frequency of the monitoring model, and if the alarm frequency exceeds a preset frequency, the corresponding classification code in the rule table is reduced by one level; The cloud platform counts the alarm objects of the monitoring model, and if the proportion of the alarm objects of the same category and / or the same level exceeds a preset ratio, the corresponding classification code in the rule table is reduced by one level.

10. A universal processing system for intelligent connected vehicle data, characterized in that: It includes a car terminal, a cloud platform and a mobile terminal, wherein the car terminal is connected to the cloud platform via a network, and the cloud platform is connected to the mobile terminal via a network; The car end includes a data acquisition module and a data collection module, and the data acquisition module is connected to the data collection module; the cloud platform includes a rule-making module, a data classification and grading module, and an alarm module, and the data classification and grading module is connected to the alarm module, and the rule-making module is connected to the data classification and grading module and the alarm module respectively; The data acquisition module is used to collect vehicle data based on a multi-sensor fusion method; The data collection module is used to centrally store the collected vehicle data, encrypt key vehicle data and the vehicle data domain ID in the vehicle data to obtain key vehicle data ciphertext, and upload the key vehicle data ciphertext to the cloud platform; wherein the key vehicle data refers to the vehicle data to be centrally processed in depth by the cloud platform; The rule formulation module is used to pre-create a corresponding rule table using the cloud platform data ID as an identifier, wherein the rule table includes the cloud platform data ID, classification matching rules, classification rules, hierarchical matching rules, and hierarchical rules, wherein the classification rules include classification codes, and the hierarchical rules include hierarchical codes; the rule formulation module is used to determine the mapping relationship between the cloud platform data ID and the classification code, the mapping relationship between the cloud platform data ID and the hierarchical code, and the mapping relationship between the cloud platform data ID and the domain ID of the vehicle data; the rule formulation module is used to count the matching success rate of the rule table within a set time period, and dynamically adjust the classification matching rules and / or hierarchical matching rules according to the matching success rate; and count the alarm conditions of the monitoring model, and dynamically adjust the hierarchical codes in the rule table according to the alarm conditions; The data classification and grading module has a built-in database, and is used to decrypt the key vehicle data ciphertext based on a preset decryption algorithm after receiving the key vehicle data ciphertext to obtain the key vehicle data; and extract the domain ID of the vehicle data from the obtained key vehicle data; The data classification and grading module is further configured to traverse the cloud platform data IDs in the rule table and perform ID matching between the domain IDs of the extracted car data and the cloud platform data IDs in the rule table; If the ID matches successfully, the rule table is traversed to check whether there is a classification code and a grading code that has a mapping relationship with the corresponding cloud platform data ID; if both the classification code and the grading code exist, the decrypted key car data is stored together with the queried classification code and grading code in the corresponding database; if the classification code does not exist and the grading code exists, the classification rules and classification matching rules in the rule table are used to classify and match the decrypted key car data, and the corresponding classification operation is performed according to the classification matching result; and the decrypted key car data is stored together with the queried grading code in the corresponding database; if the classification code exists and the grading code does not exist, The decrypted key automobile data is stored together with the queried classification code in the corresponding database, and the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; if the classification code and the classification code do not exist, the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; the classification rules and classification matching rules in the rule table are used to perform classification matching on the decrypted key automobile data, and the corresponding classification operation is performed according to the classification matching result; If the ID matching is unsuccessful, the decrypted key vehicle data is assigned a preset default classification code and default grading code, and the decrypted key vehicle data is stored together with the corresponding default classification code and default grading code in the corresponding database; The alarm module is used to perform alarm monitoring on the decrypted key vehicle data based on the monitoring model, and issue an alarm when the classification code corresponding to the key vehicle data matches the alarm level code preset in the rule table; The mobile terminal is used for data exchange between the management terminal and / or the vehicle owner terminal and the cloud platform.

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