Data detection method, apparatus, device, and medium

Abstract

The application discloses a data detection method, device, equipment and medium, and relates to the field of Internet of Vehicles. The method is executed by a first vehicle and comprises the following steps: obtaining running data of the first vehicle, wherein the running data is used for describing the working state of each component of the first vehicle during driving in a historical time period; wherein, from when the first vehicle enters a working state from a dormant state, a vehicle terminal of the first vehicle collects the running data generated by the first vehicle, and the running data is sent to a supervision platform based on a preset frequency; detecting based on the running data to determine whether the running data meets preset data quality requirements, and obtaining a detection result; and in the case that the running data does not meet the data quality requirements, obtaining a corresponding vehicle adjustment scheme based on the detection result. The running data of the vehicle sent to the supervision platform in the historical time period can be detected to determine whether the running data does not meet the data quality requirements.

Description

TECHNICAL FIELD

[0001] Embodiments of the present application relate to the field of Internet of Vehicles, and in particular to a data detection method, device, equipment and medium. BACKGROUND

[0002] In order to ensure the safety of new energy vehicles on the road, a series of operation specifications are formulated by the relevant regulatory platform. Each new energy vehicle needs to upload vehicle data to a professional regulatory platform at regular intervals, and the professional regulatory platform analyzes the vehicle data to determine whether the vehicle meets the relevant regulations.

[0003] In related technologies, the national regulatory platform will feed back the detection results to the vehicle within the agreed time after unified detection of the vehicle data, help the vehicle to rectify, and improve the quality of the vehicle data.

[0004] However, due to the diversity of vehicle data sources and the complexity of data formats, the collected vehicle data may have missing and low-quality conditions. The regulatory platform cannot give accurate analysis results based on low-quality data, and the regulatory platform has a long detection period. The vehicle cannot adjust itself in time during the waiting period for the detection results. SUMMARY

[0005] Embodiments of the present application provide a data detection method, device, equipment and medium, which can detect the operation data sent by the vehicle to the regulatory platform in the historical time period, determine whether the operation data has a condition that does not meet the data quality requirements, and make corresponding adjustments before the regulatory platform issues the monitoring results, thereby improving the efficiency of obtaining data detection results. The technical solution is as follows:

[0006] On the one hand, a data detection method is provided, which is executed by a first vehicle, and the method comprises:

[0007] Obtaining operation data of the first vehicle, the operation data being used to describe working states of components of the first vehicle during driving in a historical time period, wherein, from the first vehicle entering a working state from a dormant state, a vehicle terminal of the first vehicle collects the operation data generated by the first vehicle, and sends the operation data to a regulatory platform based on a preset frequency, the regulatory platform being used to monitor an operation process of the first vehicle;

[0008] Detecting based on the operation data to determine a condition that the operation data meets a preset data quality requirement, obtaining a detection result, the data quality requirement comprising at least one of a data integrity requirement, a data consistency requirement and a data timeliness requirement;

[0009] In a case where the operation data does not meet the data quality requirement, a corresponding vehicle adjustment scheme is acquired based on the detection result, and the vehicle adjustment scheme is used to guide adjustment of operation data of the first vehicle in a future time period to meet the data quality requirement.

[0010] In another aspect, a data detection device is provided, and the device comprises:

[0011] An acquisition module is configured to acquire operation data of a first vehicle, the operation data being used to describe working states of components of the first vehicle when the first vehicle travels in a historical time period, wherein the operation data generated by the first vehicle is collected by a terminal of the first vehicle from a time when the first vehicle enters a working state from a dormant state, and the operation data is sent to a supervision platform based on a preset frequency, and the supervision platform is used to monitor an operation process of the first vehicle.

[0012] A detection module is configured to perform detection based on the operation data, determine a case where the operation data meets a preset data quality requirement, and obtain a detection result, wherein the data quality requirement comprises at least one of a data integrity requirement, a data consistency requirement, and a data timeliness requirement.

[0013] The acquisition module is further configured to, in a case where the operation data does not meet the data quality requirement, acquire a corresponding vehicle adjustment scheme based on the detection result, and the vehicle adjustment scheme is used to guide adjustment of operation data of the first vehicle in a future time period to meet the data quality requirement.

[0014] In an optional embodiment, the detection module is further configured to perform preprocessing on the operation data to obtain preprocessed data, wherein the preprocessed data meets a preset data format requirement; acquire a first detection task corresponding to the data integrity requirement, a second detection task corresponding to the data consistency requirement, and a third detection task corresponding to the data timeliness requirement; perform first detection on the operation data based on the first detection task to obtain a first detection result; perform second detection on the operation data based on the second detection task to obtain a second detection result; perform third detection on the operation data based on the third detection task to obtain a third detection result; and acquire the detection result of the first vehicle based on the first detection result, the second detection result, and the third detection result.

[0015] In an optional embodiment, the detection module is further configured to acquire a first hash value, the first hash value being a value obtained by performing a hash operation on the operation data when the operation data is collected; perform a hash operation on the transmitted operation data again based on the first detection task to generate a second hash value; and determine, based on a matching condition between the first hash value and the second hash value, whether the operation data meets the data integrity requirement as the first detection result.

[0016] In an optional embodiment, the detection result includes a problem code, the problem code being used to indicate a data quality problem existing in the operation data.

[0017] The acquisition module is further configured to acquire a code correspondence table, the code correspondence table including a correspondence between the problem code and a candidate adjustment scheme; and acquire, based on the problem code in the detection result, the vehicle adjustment scheme corresponding to the problem code from the code correspondence table when the operation data does not meet the data quality requirement.

[0018] In an optional embodiment, the acquisition module is further configured to acquire a first adjustment scheme from the code correspondence table in response to the problem code indicating that a total number of the operation data does not reach a preset total number threshold, wherein the first adjustment scheme is used to guide to increase a daily average use time length of the first vehicle to a first time length threshold.

[0019] In an optional embodiment, the acquisition module is further configured to acquire a second adjustment scheme from the code correspondence table in response to the problem code indicating that a proportion of valid data in the operation data does not reach a preset valid proportion threshold, wherein the second adjustment scheme is used to guide to park the first vehicle at a position where a transmission signal quality meets a transmission requirement, and the valid data refers to data in the operation data meeting the data quality requirement.

[0020] In an optional embodiment, before the acquisition module, the apparatus further includes:

[0021] A connection establishment module is configured to establish a communication connection between the vehicle terminal and the supervision platform when the vehicle terminal enters a working state from a sleep state, and send the operation data to the supervision platform at the preset frequency based on the communication connection when the first vehicle generates the operation data.

[0022] The acquisition module is further configured to acquire a target adjustment scheme based on the detection result in a case where the detection result indicates that the proportion of empty data in the operation data reaches a preset empty data proportion threshold, wherein the target adjustment scheme is used to indicate that state information of each component in the first vehicle is acquired before the communication connection between the vehicle terminal and the supervision platform is established, and the communication connection between the vehicle terminal and the supervision platform is established when the state information of each component indicates that each component of the first vehicle enters a working state.

[0023] In another aspect, a computer device is provided, which includes a processor and a memory having stored therein at least one instruction, at least one program, a code set or instruction set, which is loaded and executed by the processor to implement the data detection method according to any one of the above embodiments of the present application.

[0024] In another aspect, a computer readable storage medium is provided, which has stored therein at least one instruction, at least one program, a code set or instruction set, which is loaded and executed by a processor to implement the data detection method according to any one of the above embodiments of the present application.

[0025] In another aspect, a computer program product or computer program is provided, which includes computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium, and the processor executes the computer instructions to cause the computer device to perform the data detection method according to any one of the above embodiments.

[0026] The technical scheme provided by the embodiments of the present application has at least the following beneficial effects:

[0027] The operation data of the first vehicle transmitted to the supervision platform in real time in a historical time period is collected, the supervision platform simulates detection of the operation data, determines whether the operation data meets the data quality requirements, obtains a detection result, and generates a corresponding adjustment scheme according to the detection result, and makes corresponding adjustment to the first vehicle, so that the operation data generated by the first vehicle in a future time period meets the data quality requirements. Since the supervision platform detects the data and issues a detection report in a relatively long cycle, and the detection report cannot indicate the operation data, the problem type and how to guide the first vehicle to make corresponding adjustment in detail, the data detection method provided by the present application can provide a self-detection means for the vehicle and the user, help the user to understand the problems of the operation data of the vehicle in time, improve the efficiency of the vehicle adjustment, and control the operation data generated by the vehicle in the future time period to meet the quality requirements and corresponding specifications. Attached Figure Description

[0028] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0029] Figure 1 This is a schematic diagram of a data detection system provided in an exemplary embodiment of this application;

[0030] Figure 2 This is a flowchart of a data detection method provided in an exemplary embodiment of this application;

[0031] Figure 3 This is a structural block diagram of a data detection apparatus provided in an exemplary embodiment of this application;

[0032] Figure 4 This is a structural block diagram of a data detection apparatus provided in another exemplary embodiment of this application;

[0033] Figure 5 This is a structural block diagram of a computer device provided in an exemplary embodiment of this application. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0035] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0036] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0037] It should be noted that the information and data involved in the present application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data need to comply with relevant laws, regulations and standards of relevant countries and regions.

[0038] It should be understood that although the terms first, second, etc. may be used in this application to describe various information, these information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, a first parameter can also be referred to as a second parameter without departing from the scope of the present application, and similarly, a second parameter can also be referred to as a first parameter. Depending on the context, the word "if" as used herein can be interpreted as "when" or "upon" or "in response to determining".

[0039] First, the terms involved in the embodiments of the present application are briefly introduced:

[0040] T-BOX (Telematics Box, vehicle communication module): used to realize the communication and data exchange between the vehicle and the outside. T-BOX connects with the CAN bus (Controller Area Network, Controller Area Network), LIN bus (Local Interconnect Network, Local Interconnect Network) and other communication interfaces inside the vehicle to obtain various state information of the vehicle, such as engine speed, vehicle speed, oil quantity, battery state, etc. After processing, these data are sent to the cloud server through the cellular network. According to relevant regulations and standards, T-BOX can transmit real-time high-voltage electric related static data, dynamic data and fault status of the vehicle to the designated platform.

[0041] In the present application, the vehicle terminal involved for collecting the running data of the first vehicle and sending to the supervision platform refers to T-BOX. In order to ensure that the first vehicle meets the corresponding specifications during driving, the running data generated by the first vehicle during driving will be sent to the supervision platform by T-BOX based on fixed frequency, and the running data is encapsulated into a message during transmission. The supervision platform will detect the quality of the data uploaded by T-BOX, and feed back an analysis report in the future time period, which indicates the problem type of the running data. The user can adjust the first vehicle based on the report content, so that the running data generated by the first vehicle in the subsequent driving process meets the specifications.

[0042] In the field of new energy vehicles, in order to ensure the safety and driving specifications of vehicles on the road, the running data generated by the vehicle during operation needs to meet the strict requirements of the national supervision platform on data quality.

[0043] The new energy vehicle must enter static data and integrate dynamic data on the designated supervision platform. The static data includes basic parameters and configuration information of the vehicle, such as the vehicle identification code, vehicle model, vehicle brand, etc. The dynamic data refers to the running data generated by the vehicle during driving, such as the real-time vehicle speed, the charging state of the vehicle, the mileage of the vehicle, etc. The supervision platform will regularly dynamically check these running data and provide quality statistics. Users can download the relevant analysis report through the platform, adjust the vehicle parts, make the vehicle driving process comply with the specifications, and make the running data generated in the future time period comply with the quality requirements of the supervision platform.

[0044] In the related art, the supervision platform needs a long period to analyze and evaluate the running data after detection and issue an evaluation report. In this process, the user can only wait for the report to be generated. If there is running data that does not meet the quality requirements during the vehicle operation (i.e., the vehicle has specification problems during driving), the problem cannot be self-detected before the supervision platform issues the report, and the corresponding adjustment cannot be made in time. The vehicle adjustment efficiency is low.

[0045] Moreover, after downloading the report on the supervision platform, the adjustment scheme of the vehicle is analyzed and compared one by one, and the adjustment scheme of the vehicle is manually formulated. This method not only consumes time and effort, but also cannot guarantee the effect of rectification.

[0046] The present application provides a data detection method, which can self-detect the running data of the vehicle during the process of detecting the running data by the supervision platform and generating the analysis report, estimate the possible quality problems of the vehicle running data in advance, and generate the corresponding vehicle adjustment scheme, thereby improving the efficiency of data detection and the execution effect of the vehicle adjustment scheme.

[0047] Secondly, the data detection system involved in the embodiment of the present application is described, and the schematic diagram is shown in Figure 1 The data detection system involves a first vehicle 110 and a server 120, and the first vehicle 110 and the server 120 are connected through a communication network 140. The first vehicle 110 is internally deployed with a vehicle terminal / T-BOX for collecting running data, and the server 120 is deployed with a supervision platform.

[0048] After the first vehicle 110 is woken up from the sleep state, the vehicle terminal, as the component that is woken up first in the vehicle, will immediately establish a communication connection with the supervision platform. During the starting or driving process of the first vehicle 110, the vehicle terminal will collect the running data generated by the first vehicle 110 in real time and encapsulate the running data into a message to be sent to the supervision platform at a fixed frequency. The supervision platform will evaluate the quality of the received running data.

[0049] The data detection method of the scheme is described by taking the first period as an example. The first period is 24 hours. The data uploaded by the first vehicle 110 to the supervision platform in the past 24 hours is stored in the vehicle platform corresponding to the first vehicle 110 (the vehicle platform can be a platform corresponding to the manufacturer of the first vehicle 110, for example, the first vehicle 110 is an A brand vehicle, and the A brand enterprise has a dedicated vehicle platform). When performing data self-detection, the first vehicle 110 downloads all running data sent in the past 24 hours from the vehicle platform.

[0050] The running data is detected to determine whether the running data meets the data quality requirements. The data quality requirements actually refer to the standards for detecting data by the supervision platform, including but not limited to at least one of data integrity requirements, data consistency requirements, data timeliness requirements, and the like.

[0051] The detection of the running data generates a detection result. The detection result is still in the form of a report issued by the supervision platform, for example, in the form of a problem code indicating problems existing in the running data. Each problem code corresponds to a different data quality problem. Based on the detection result, a corresponding vehicle adjustment scheme is obtained. The vehicle adjustment scheme is automatically generated by the vehicle terminal or other terminal / server device connected to the first vehicle 110. The adjustment scheme can help the user to adjust the first vehicle 110 in advance, take measures as much as possible before the analysis report is issued by the supervision platform, improve the quality of the running data generated by the first vehicle 110 in the future time period, and make the driving process of the first vehicle 110 in the future time period more standardized and safe.

[0052] It is worth noting that the above-mentioned server can be a standalone physical server, a server cluster or a distributed system composed of multiple physical servers, a cloud server providing cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, content distribution networks (CDN), and big data and artificial intelligence platforms, and the like basic cloud computing services.

[0053] Among them, cloud technology refers to a hosting technology that unifies a series of resources such as hardware, software, network, etc. in a wide area network or local area network to realize data calculation, storage, processing and sharing. Cloud technology is a general term for network technology, information technology, integration technology, management platform technology, application technology, etc. based on cloud computing business model application, which can form a resource pool, and can be used on demand, flexibly and conveniently. Cloud computing technology will become an important support. The background service of the technical network system needs a large amount of computing and storage resources, such as video websites, picture websites and more portal websites. With the high development and application of the Internet industry, every item in the future may have its own identification mark and needs to be transmitted to the background system for logical processing. Different levels of data will be processed separately, and various industry data will need strong system support, which can only be realized through cloud computing.

[0054] In some embodiments, the above-mentioned server can also be implemented as a node in a blockchain system.

[0055] In combination with the above-mentioned name introduction and application scenario, the data detection method provided by the present application is described. The method can be executed by a server or a vehicle, or jointly executed by a server and a vehicle. In the present application, the method is executed by the first vehicle as an example, as shown in Figure 2 , and Figure 2 is a flowchart of the data detection method provided by an exemplary embodiment of the present application. The method comprises the following steps.

[0056] Step 210, obtaining running data of the first vehicle.

[0057] Among them, the running data is used to describe the working state of each component of the first vehicle during driving in the historical time period.

[0058] For example, the historical time period refers to the time period within 24 hours in the past based on the current time. The current time is 00:00:00 on October 2, 2020, and the historical time period is the time period between 00:00:00 on October 1, 2020 and 00:00:00 on October 2, 2020.

[0059] For example, the running data includes vehicle speed data, vehicle charging state data (vehicle battery remaining capacity), total distance data (mileage) and the like of the first vehicle during driving in the historical time period.

[0060] For example, in a historical time period, the first vehicle is in a driving state in a first time period between 8:00:00 and 8:25:00 and a second time period between 17:00:00 and 17:50:00, then the vehicle speed data contains an average vehicle speed V1 = 40 km / h in the first time period and an average vehicle speed V2 = 25 km / h in the second time period; the vehicle charging state data includes the power corresponding to the start and end timestamps of the first time period and the second time period: the power at 8:00:00 is 100%, the power at 8:25:00 is 95%, the power at 17:00:00 is 94%, and the power at 17:50:00 is 90%; the total distance traveled is 25 / 60*40+50 / 60*25 = 16.67+20.83≈37.5km, that is, the mileage of driving about 37.5km.

[0061] Among them, from the first vehicle entering the working state from the dormant state, the vehicle terminal of the first vehicle collects the running data generated by the first vehicle, and sends the running data to the supervision platform based on a preset frequency.

[0062] When the first vehicle is awakened from the dormant state, all components inside the first vehicle will be awakened in turn, and the vehicle terminal is the component that is awakened first. When the vehicle terminal is awakened, it will actively establish a communication connection with the supervision platform. This process can be regarded as the first vehicle logging in with a corresponding account on the supervision platform, and the running data generated by the first vehicle and sent to the supervision platform is recorded in time through the account.

[0063] Among them, the vehicle terminal sends the running data to the supervision platform in the form of a message, so the number of running data actually refers to the number of messages sent by the vehicle terminal to the supervision platform. The data length, data type and data volume contained in each unit message can be arbitrary.

[0064] The supervision platform is used to monitor the running process of the first vehicle, and to detect and evaluate the quality of the received running data to determine whether the first vehicle running process meets the corresponding rules.

[0065] The supervision platform will feed back an analysis report to the first vehicle within a specified time, and the analysis report contains the results of detecting and analyzing the running data. The results indicate the quality problems existing in the running data of the first vehicle in the form of problem codes.

[0066] The user can download the analysis report on the supervision platform, and make corresponding adjustments to the first vehicle based on the content in the report, so that the running data generated by the first vehicle in the subsequent driving process meets the preset data quality requirements, ensuring the safety and standardization of the first vehicle in the driving process.

[0067] The supervision platform has a long cycle for detecting and analyzing the operation data, and therefore, the data detection method is actually used to shorten the cycle of vehicle adjustment, and the data self-detection is performed while the supervision platform uniformly detects the operation data.

[0068] It is worth noting that the first vehicle sends the operation data to the supervision platform after the operation data is generated, and the operation data is not modified before transmission. The operation data is collected by the on-board terminal of the first vehicle for quality self-detection after a period of accumulation. The quality self-detection is used to detect the quality of the accumulated operation data, analyze the problems in the operation data, and timely adjust the vehicle based on the analysis result, so that the operation data generated by the first vehicle in the subsequent operation process and sent to the supervision platform meets the quality requirements as much as possible.

[0069] In step 220, the operation data is detected based on the operation data to determine whether the operation data meets the preset data quality requirements, and a detection result is obtained.

[0070] The data quality requirements include at least one of data integrity requirements, data consistency requirements, and data timeliness requirements.

[0071] Optionally, the operation data is preprocessed to obtain preprocessed data, and the preprocessed data meets the preset data format requirements.

[0072] The data source of the operation data includes not only the data generated by the first vehicle in the driving process in real time, but also the data collected from other channels.

[0073] The operation data collected in step 210 can be collected from multiple channels such as automobile manufacturers, charging infrastructure providers, and related supervision agencies.

[0074] The operation data collected by the automobile manufacturer actually refers to the operation data generated during the driving of the automobile. The operation data is transmitted to the supervision platform in real time and stored in the vehicle platform corresponding to the automobile manufacturer. The operation data collected by the charging infrastructure provider includes charging duration data and charging power data of the vehicle at the charging site. According to the duration and power data, the battery power change of the vehicle can be inferred. The operation data collected by the related supervision agency includes vehicle driving state data collected by the vehicle when passing through the monitoring camera during driving, such as whether to slow down at the turning intersection, whether to slow down and stop at the red and green light intersection, and the like. According to the vehicle driving state data, the vehicle speed change of the vehicle can be inferred.

[0075] For example, the preset data format requirements refer to that the operation data does not include repeated data, noise-rich data, and the like.

[0076] Noise in data refers to unintended, random or interfering changes introduced in the process of data collection, transmission, storage or processing. It includes transmission noise (data may be affected by electromagnetic interference, signal attenuation and other factors during transmission, resulting in data distortion), random noise (random and unpredictable interference in data), etc.

[0077] Optionally, the process of preprocessing the operation data includes cleaning, deduplication, format conversion and other operations on the data to eliminate noise, outliers and duplicate data in the operation data, etc.

[0078] The first detection task corresponding to the data integrity requirement, the second detection task corresponding to the data consistency requirement, and the third detection task corresponding to the data timeliness requirement are obtained.

[0079] Based on the first detection task, the operation data is detected to obtain the first detection result.

[0080] For example, based on the hash operation method (hash function), the operation data is detected, and the hash function is a function of transforming the input (data) of any length into the output (hash value) of fixed length through the hash algorithm, which is used to check the integrity of the data and ensure that the data has not been tampered with during transmission or storage.

[0081] For example, data is transmitted from A end to B end. In order to detect whether the data changes during transmission, hash operation is performed based on the original data before the data is transmitted from A end, and hash value A1 is obtained. Hash value A1 and data are transmitted to B end at the same time, and hash value B1 is obtained by B end based on the received data.

[0082] Compare the matching degree between hash value A1 and hash value B1. If the matching degree meets the preset requirement (for example, hash value A1 = hash value B1), it is considered that the data meets the integrity requirement.

[0083] Optionally, the first hash value is obtained, which is the value obtained by performing hash operation on the operation data when collecting the operation data. Based on the first detection task, the operation data transmitted is re-hashed to generate the second hash value.

[0084] Based on the matching between the first hash value and the second hash value, the compliance of the operation data to the data integrity requirement is determined as the first detection result.

[0085] In some embodiments, the check code can also be used to check the data integrity. The check code is a method for detecting and correcting errors that occur during data transmission. It can detect and possibly correct errors in the data by adding additional information (check code) to the original data. Here, it is not described again.

[0086] performing a second detection on the operation data based on a second detection task to obtain a second detection result.

[0087] For example, by comparing and verifying the operation data collected by different subjects (including but not limited to automobile manufacturers, automobile dealers, charging infrastructure providers and related supervisory agencies), it is checked whether there are contradictions or inconsistencies in the operation data, and the consistency of the data is ensured.

[0088] For example, the operation data indicates that the first vehicle charges once during driving, and it is checked whether the battery state of the first vehicle before and after charging conforms to the power change rule. When the power of the first vehicle after charging is lower than that before charging, the battery state of the first vehicle does not conform to the power change rule.

[0089] performing a third detection on the operation data based on a third detection task to obtain a third detection result.

[0090] For example, a time threshold for updating the operation data is set, and it is checked whether the operation data is updated in time to ensure the timeliness and real-time of the operation data.

[0091] For example, the preset time threshold is 10 seconds, that is, the operation data is collected every 10 seconds, and the collected operation data is used as the updated data. The operation data collection time is arranged in chronological order, and it is checked whether the time interval between the adjacent two collected operation data exceeds the preset time threshold. If it exceeds, it does not conform to the timeliness.

[0092] Based on the first detection result, the second detection result and the third detection result, a detection result of the first vehicle is obtained. According to the detection result of the first vehicle, a data quality evaluation report is generated to provide a reliable data basis for policy making, market analysis and decision support.

[0093] In some embodiments, in addition to the above three detection tasks, data security detection is also needed when detecting the quality of the operation data, such as using encryption technology, data desensitization, access control and other technologies to ensure the security and privacy of the operation data.

[0094] Step 230, in the case that the operation data does not conform to the data quality requirement, a corresponding vehicle adjustment scheme is obtained based on the detection result.

[0095] The vehicle adjustment scheme is used to guide the adjustment of the operation data of the first vehicle in the future time period to conform to the data quality requirement.

[0096] Optionally, the detection result comprises a problem code, the problem code being used to indicate that the running data has a data quality problem. The problem code is an encoding used by the supervision platform to define the type of problem existing in the running data after detecting the running data. The problem code has multiple numerical values, each value corresponding to a different data quality problem. The problem code can guide the user to the general direction of adjusting the first vehicle.

[0097] For example, refer to Table 1 below, which lists several common problem codes and the corresponding problem descriptions.

[0098] Table 1

[0099] Code Description 148 Real time data time is more than 30 seconds away from server time 134 Login message time is more than 30 seconds away from server time 1 Odometer is empty or invalid 27 Drive motor list is empty or invalid 61 Charge status is empty or invalid 72 Vehicle status is empty or error 7 Speed is empty or invalid value

[0100] When the problem code is 148, it means that the time when the first vehicle generates the running data and the time when the supervision platform receives the running data differ by more than 30 seconds, and there is a data delay.

[0101] When the problem code is 134, it means that the time when the running data is reported to the supervision platform and the time when the supervision platform receives the running data differ by more than 30 seconds, and there is a data delay.

[0102] When the problem code is 1, it means that the running data received by the supervision platform shows that the mileage of the first vehicle is empty or invalid (exceeding the actual vehicle allowed mileage range, for example, 1000 km in 1 hour, etc.).

[0103] When the problem code is 27, it means that the running data received by the supervision platform shows that the driving motor state of the first vehicle is empty or invalid.

[0104] When the problem code is 61, it means that the running data received by the supervision platform shows that the charging state of the first vehicle is empty or invalid (exceeding the actual charging state allowed range, for example, negative value, etc.).

[0105] When the problem code is 72, it means that the running data received by the supervision platform shows that the vehicle state of the first vehicle is empty or invalid (not consistent with the actual situation, for example, the vehicle speed of the first vehicle is not 0, the vehicle state shows static, etc.).

[0106] When the problem code is 7, it means that the running data received by the supervision platform shows that the vehicle speed of the first vehicle is empty or invalid (exceeding the actual vehicle allowed speed range, for example, the upper limit of the vehicle speed is 100 km / h, the displayed vehicle speed is 120 km / h, etc.).

[0107] Optionally, an encoding reference table is acquired, the encoding reference table comprising a correspondence between a problem code and a candidate adjustment scheme; and in a case where the operation data does not meet the data quality requirement, the corresponding vehicle adjustment scheme is acquired from the encoding reference table based on the problem code in the detection result.

[0108] For example, in response to the problem code indicating that the total number of operation data does not reach a preset total number threshold, a first adjustment scheme is acquired from the encoding reference table, wherein the first adjustment scheme is used to guide to increase the daily average use time length of the first vehicle to a first time length threshold.

[0109] For example, the total number threshold is 500, and the detection requirement of the supervision platform is as follows: the total number of operation data (the total number of messages sent by the vehicle terminal) uploaded by the public operation vehicle to the supervision platform in a period of one week needs to reach 500 or more; and the total number of operation data (the total number of messages sent by the vehicle terminal) uploaded by the private vehicle to the supervision platform in two charging cycles needs to reach 500 or more; otherwise, it is considered that the total number of operation data does not reach the preset total number threshold.

[0110] The first adjustment scheme is as follows: the first time length threshold is 1 hour, and the daily average use time length of the first vehicle is increased, which requires the first vehicle to travel more than 1 hour per day.

[0111] For example, in response to the problem code indicating that the proportion of valid data in the operation data does not reach a preset valid proportion threshold, a second adjustment scheme is acquired from the encoding reference table, wherein the second adjustment scheme is used to guide the first vehicle to be parked at a position where the transmission signal quality meets the transmission requirement, and the valid data refers to the data in the operation data meeting the data quality requirement.

[0112] For example, the preset valid proportion threshold is 80%, and the valid data is considered unqualified when the proportion of the valid data in the total data is less than 80%. Alternatively, the error data is considered unqualified when the proportion of the error data in the total data is more than 3%.

[0113] The valid data proportion calculation formula is as follows:

[0114] (1) valid proportion = (valid data number) / (total operation data number) %;

[0115] (2) total operation data number = (valid data + error data + invalid data + re-sent historical operation data + data with a display time and service difference exceeding a preset threshold) number;

[0116] (3) invalid data number = (data of the first vehicle logging in and logging out the supervision platform + T-BOX heartbeat signal message) number.

[0117] The second adjustment scheme is as follows: the first vehicle is controlled to stop at a place with a good network signal to reduce the number of retransmission operation data.

[0118] In some embodiments, the problem code is used to indicate that the time of uploading the message (operation data) after the vehicle terminal logs in the supervision platform does not correspond, for example, when the supervision platform checks the qualified and complete sending time of the operation data, the GPS (Global Positioning System) time is used as the reference. If the time error of the data sent by the vehicle terminal is less than 10 seconds, it is considered qualified, and if it exceeds 10 seconds, it is considered unqualified.

[0119] For example, the time of sending the operation data by the vehicle terminal is displayed as 10:00:20 on the vehicle terminal side, and the time of receiving the operation data by the supervision platform is displayed as 10:00:15 on the supervision platform side, which is earlier than the sending time, indicating that there is an error, and the timing method on the vehicle terminal needs to be adjusted to eliminate the time error.

[0120] For example, the first vehicle mainly uses the GPS time as the reference and transmits data in an environment with a strong network signal, or improves the hardware of the vehicle terminal (T-BOX) to improve the timing accuracy, or realizes secondary time adjustment through software program design. The first vehicle is powered on twice after leaving the warehouse to reduce the risk of time overage.

[0121] In some embodiments, the problem code indicates that the message content is incorrect, that is, there is part of the content error in the operation data. Among them, the supervision platform mainly detects each piece of information in the operation data, including but not limited to, the mileage information, the vehicle speed information, the charging state information, the battery state information, the motor list information and the temperature sensor list information of the first vehicle.

[0122] Before obtaining the operation data of the first vehicle for data detection, when the vehicle terminal enters the working state from the sleep state, the communication connection between the vehicle terminal and the supervision platform is established. When the first vehicle generates operation data, the operation data is sent to the supervision platform at a preset frequency based on the communication connection.

[0123] Optionally, in the case where the detection result indicates that the proportion of empty data in the operation data reaches a preset empty data proportion threshold, a target adjustment scheme is obtained based on the detection result, wherein the target adjustment scheme is used to indicate that the state information of each component in the first vehicle is obtained before the communication connection between the vehicle terminal and the supervision platform is established, and when the state information of each component indicates that each component of the first vehicle enters the working state, the communication connection between the vehicle terminal and the supervision platform is established.

[0124] T-BOX as the core of the whole signal reporting, in a period of time after the first vehicle is turned off, the whole vehicle enters a deep sleep state, if there is a message on the CAN network at this time, or is remotely awakened. T-BOX as the component that is preferentially awakened, other network nodes at this time are still in a sleep state, T-BOX cannot receive the message at that time, and can only send empty data and invalid values to the monitoring platform.

[0125] The target adjustment scheme is as follows: the network message (operation data) is classified and processed. The authentication between T-BOX and the monitoring platform is strongly checked. When T-BOX is just awakened, the data of other network nodes is abnormal, at this time, T-BOX does not perform login handshake verification with the platform, and after all the first vehicle internal components are awakened, the login to the monitoring platform is attempted. On the other hand, each node on the network can be required to strictly control the data quality to avoid irrelevant messages from being uploaded. At the same time, T-BOX can perform related memory processing on the related buried point data, and when an error signal or an empty signal is obtained, the previously stored signal is used as a default value.

[0126] In summary, the data detection method provided by the application collects operation data of the first vehicle sent to the monitoring platform in a historical time period, simulates detection of the monitoring platform on the operation data, determines whether the operation data meets the data quality requirement, obtains a detection result, and generates a corresponding adjustment scheme according to the detection result, and adjusts the first vehicle accordingly, so that the operation data generated by the first vehicle in a future time period meets the data quality requirement. Since the monitoring platform detects the data and issues a detection report in a relatively long period, and the detection report cannot indicate the operation data, the problem type and how to guide the first vehicle to make corresponding adjustment in detail, the data detection method provided by the application can provide a self-detection means for the vehicle and the user, help the user to understand the problems of the operation data of the vehicle in time, improve the efficiency of the vehicle adjustment, and control the operation data generated by the vehicle in the future time period to meet the quality requirement and the corresponding specification.

[0127] Figure 3 is a structural block diagram of a data detection device provided by an exemplary embodiment of the application, as Figure 3 shown, the device includes the following parts.

[0128] The acquisition module 310 is configured to acquire operation data of the first vehicle, and the operation data is used to describe working states of components of the first vehicle when the first vehicle drives in a historical time period. From when the first vehicle enters a working state from a sleep state, the vehicle terminal of the first vehicle collects the operation data generated by the first vehicle, and sends the operation data to a monitoring platform based on a preset frequency. The monitoring platform is used to monitor an operation process of the first vehicle.

[0129] The detection module 320 is configured to perform detection based on the operation data, determine a case where the operation data meets preset data quality requirements, and obtain a detection result, the data quality requirements including at least one of data integrity requirements, data consistency requirements, and data timeliness requirements.

[0130] The acquisition module 310 is further configured to acquire, in a case where the operation data does not meet the data quality requirements, a corresponding vehicle adjustment scheme based on the detection result, the vehicle adjustment scheme being used to guide adjustment of the operation data of the first vehicle in a future time period to meet the data quality requirements.

[0131] In an optional embodiment, the detection module 320 is further configured to perform preprocessing on the operation data to obtain preprocessed data, the preprocessed data meeting preset data format requirements; acquire a first detection task corresponding to the data integrity requirements, a second detection task corresponding to the data consistency requirements, and a third detection task corresponding to the data timeliness requirements; perform first detection on the operation data based on the first detection task to obtain a first detection result; perform second detection on the operation data based on the second detection task to obtain a second detection result; perform third detection on the operation data based on the third detection task to obtain the third detection result; and acquire the detection result of the first vehicle based on the first detection result, the second detection result, and the third detection result.

[0132] In an optional embodiment, the detection module 320 is further configured to acquire a first hash value, the first hash value being a value obtained by performing hash operation on the operation data when the operation data is collected; perform hash operation again on the operation data that has been transmitted to generate a second hash value based on the first detection task; and determine, based on a matching condition between the first hash value and the second hash value, a meeting condition of the operation data to the data integrity requirements as the first detection result.

[0133] In an optional embodiment, the detection result includes a problem code, the problem code being used to indicate a data quality problem existing in the operation data.

[0134] The acquisition module 310 is further configured to acquire a code correspondence table, the code correspondence table including a corresponding relationship between the problem code and a candidate adjustment scheme; and acquire, in a case where the operation data does not meet the data quality requirements, the corresponding vehicle adjustment scheme from the code correspondence table based on the problem code in the detection result.

[0135] In an optional embodiment, the obtaining module 310 is further configured to, in response to the problem code indicating that the total number of the running data does not reach a preset total number threshold, obtain a first adjustment scheme from the coding correspondence table, where the first adjustment scheme is used to guide to increase the daily average use time length of the first vehicle to a first time length threshold.

[0136] In an optional embodiment, the obtaining module 310 is further configured to, in response to the problem code indicating that the proportion of valid data in the running data does not reach a preset valid proportion threshold, obtain a second adjustment scheme from the coding correspondence table, where the second adjustment scheme is used to guide to park the first vehicle at a position where the transmission signal quality meets the transmission requirement, and the valid data refers to data in the running data that meets the data quality requirement.

[0137] In an optional embodiment, the obtaining module 310 is further configured to, before the foregoing, Figure 4 The apparatus further includes:

[0138] The connection establishing module 330 is configured to, when the vehicle-mounted terminal enters a working state from a sleep state, establish a communication connection between the vehicle-mounted terminal and the supervision platform, and based on the communication connection, send the running data to the supervision platform at the preset frequency when the first vehicle generates the running data.

[0139] The obtaining module 310 is further configured to, in a case where the detection result indicates that the proportion of empty data in the running data reaches a preset empty data proportion threshold, obtain a target adjustment scheme based on the detection result, where the target adjustment scheme is used to indicate to obtain state information of each component in the first vehicle before the communication connection between the vehicle-mounted terminal and the supervision platform is established, and when the state information of each component indicates that each component of the first vehicle enters a working state, establish the communication connection between the vehicle-mounted terminal and the supervision platform.

[0140] In summary, the data detection device provided in the application collects running data of the first vehicle sent to the supervision platform in a historical time period, simulates detection of the running data by the supervision platform, determines whether the running data meets the data quality requirements, obtains a detection result, and generates a corresponding adjustment scheme according to the detection result to make corresponding adjustment to the first vehicle, so that the running data generated by the first vehicle in a future time period meets the data quality requirements. Since the supervision platform has a long cycle for detecting data and issuing a detection report, and the detection report cannot indicate the running data, the problem type and how to guide the first vehicle to make corresponding adjustment in detail, the data detection method provided in the application can provide a self-detection means for the vehicle and the user, help the user to know the problems existing in the running data of the vehicle in time, improve the efficiency of vehicle adjustment, and control the running data generated by the vehicle in the future time period to meet the quality requirements and corresponding specifications.

[0141] It should be noted that the data detection device provided in the above embodiments is only exemplified by the division of the above functional modules, and in actual application, the above functions can be completed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to complete all or part of the above described functions. In addition, the data detection device and the data detection method provided in the above embodiments belong to the same concept, and the specific implementation process is described in the method embodiments, which will not be repeated here.

[0142] Figure 5 The structural block diagram of the computer device 500 provided in an example embodiment of the application is shown. The computer device 500 can be a smart phone, a tablet computer, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV) player, a notebook computer or a desktop computer. The computer device 500 can also be referred to as a user device, a portable terminal, a laptop terminal, a desktop terminal and other names.

[0143] Generally, the computer device 500 includes a processor 501 and a memory 502.

[0144] The processor 501 can include one or more processing cores, such as a 4-core processor, an 8-core processor, and the like. The processor 501 can be implemented in at least one of a hardware form of a DSP (Digital Signal Processing), an FPGA (Field-Programmable Gate Array), a PLA (Programmable Logic Array). The processor 501 can also include a main processor and a coprocessor, the main processor being a processor for processing data in an awake state, also known as a CPU (Central Processing Unit), and the coprocessor being a low-power processor for processing data in a standby state. In some embodiments, the processor 501 can be integrated with a GPU (Graphics Processing Unit) that is responsible for rendering and drawing the content required to be displayed by the display screen. In some embodiments, the processor 501 can also include an AI (Artificial Intelligence) processor for processing machine learning-related computing operations.

[0145] The memory 502 can include one or more computer-readable storage media that can be non-transitory. The memory 502 can also include a high-speed random access memory, and a nonvolatile memory such as one or more disk storage devices, flash storage devices. In some embodiments, the non-transitory computer-readable storage medium in the memory 502 is used to store at least one instruction for being executed by the processor 501 to implement the data detection method provided by the method embodiment of the present application.

[0146] In some embodiments, the computer device 500 further includes some other components 503, and the type and number of the other components 503 can be selected based on the functional needs of the computer device 500. Those skilled in the art can understand that the structure shown in the figure does not constitute a limitation on the computer device 500, and can include more or fewer components than shown, or combine certain components, or use different component arrangements. Figure 5 The structure shown in the figure does not constitute a limitation on the computer device 500, and can include more or fewer components than shown, or combine certain components, or use different component arrangements.

[0147] Optionally, the computer readable storage medium can include a read only memory (ROM), a random access memory (RAM), a solid state disk (SSD), an optical disk, or the like. The random access memory can include a resistance random access memory (ReRAM) and a dynamic random access memory (DRAM). The above-mentioned application embodiment numbers are only for description, and do not represent the advantages and disadvantages of the embodiments.

[0148] The embodiments of the present application further provide a computer device, which comprises a processor and a memory. The memory stores at least one instruction, at least one program, a code set or an instruction set. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by the processor to implement the data detection method according to any one of the above-mentioned embodiments of the present application.

[0149] The embodiments of the present application further provide a computer readable storage medium, which stores at least one instruction, at least one program, a code set or an instruction set. The at least one instruction, the at least one program, the code set or the instruction set is loaded and executed by a processor to implement the data detection method according to any one of the above-mentioned embodiments of the present application.

[0150] The embodiments of the present application further provide a computer program product or a computer program, which comprises computer instructions stored in a computer readable storage medium. A processor of a computer device reads the computer instructions from the computer readable storage medium. The processor executes the computer instructions, so that the computer device executes the data detection method according to any one of the above-mentioned embodiments.

[0151] Those skilled in the art can understand that all or part of the steps of the above-mentioned embodiments can be completed by hardware, or by a program instructing related hardware to complete, and the program can be stored in a computer readable storage medium. The above-mentioned storage medium can be a read only memory, a magnetic disk or an optical disk.

[0152] The above-mentioned is only the optional embodiments of the present application, and does not limit the present application. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A data detection method characterized by, The method is performed by a first vehicle, and comprises: obtaining operation data of the first vehicle, the operation data being used to describe working states of components of the first vehicle when the first vehicle travels in a historical time period, wherein the operation data generated by the first vehicle is collected by a terminal of the first vehicle from when the first vehicle enters a working state from a dormant state, and the operation data is sent to a supervision platform based on a preset frequency, the supervision platform being used to monitor an operation process of the first vehicle; based on the operation data, detecting to determine a case where the operation data meets preset data quality requirements, and obtaining a detection result, the data quality requirements including at least one of a data integrity requirement, a data consistency requirement, and a data timeliness requirement; in a case where the operation data does not meet the data quality requirements, obtaining a corresponding vehicle adjustment scheme based on the detection result, the vehicle adjustment scheme being used to guide adjustment of the operation data of the first vehicle in a future time period to meet the data quality requirements; wherein the detection result contains a problem code, the problem code being used to indicate a data quality problem existing in the operation data; an encoding correspondence table is obtained, the encoding correspondence table containing a correspondence between the problem code and a candidate adjustment scheme; in the case where the operation data does not meet the data quality requirements, the corresponding vehicle adjustment scheme is obtained from the encoding correspondence table based on the problem code in the detection result.

2. The method of claim 1, wherein, The method comprises: preprocessing the operation data to obtain preprocessed data, the preprocessed data meeting a preset data format requirement; obtaining a first detection task corresponding to the data integrity requirement, a second detection task corresponding to the data consistency requirement, and a third detection task corresponding to the data timeliness requirement; based on the first detection task, performing first detection on the operation data to obtain a first detection result; based on the second detection task, performing second detection on the operation data to obtain a second detection result; based on the third detection task, performing third detection on the operation data to obtain a third detection result; based on the first detection result, the second detection result, and the third detection result, obtaining the detection result of the first vehicle.

3. The method of claim 2, wherein, The method comprises: obtaining a first hash value, the first hash value being a value obtained by performing a hash operation on the operation data when the operation data is collected; based on the first detection task, generating a second hash value by performing a hash operation on the transmitted operation data again; based on a matching condition between the first hash value and the second hash value, determining a meeting condition of the operation data to the data integrity requirement as the first detection result.

4. The method of claim 1, wherein, The vehicle adjustment scheme based on the detection result in the case that the operation data does not meet the data quality requirement comprises: In response to the problem code indicating that the total number of the operation data does not reach a preset total number threshold, a first adjustment scheme is acquired from the code correspondence table, and the first adjustment scheme is used to guide to increase the daily average use time length of the first vehicle to a first time length threshold.

5. The method of claim 1, wherein, The vehicle adjustment scheme based on the detection result in the case that the operation data does not meet the data quality requirement comprises: In response to the problem code indicating that the proportion of valid data in the operation data does not reach a preset valid proportion threshold, a second adjustment scheme is acquired from the code correspondence table, and the second adjustment scheme is used to guide to park the first vehicle at a position where the transmission signal quality meets the transmission requirement, and the valid data refers to data in the operation data meeting the data quality requirement.

6. The method according to any one of claims 1 to 5, characterized in that, Before the operation data of the first vehicle is acquired, the method further comprises: When the vehicle-mounted terminal enters a working state from a sleep state, a communication connection between the vehicle-mounted terminal and the supervision platform is established; When the operation data of the first vehicle is generated, the operation data is sent to the supervision platform at the preset frequency based on the communication connection; The vehicle adjustment scheme based on the detection result in the case that the operation data does not meet the data quality requirement comprises: In the case that the detection result indicates that the proportion of empty data in the operation data reaches a preset empty data proportion threshold, a target adjustment scheme is acquired based on the detection result, and the target adjustment scheme is used to indicate that, before the communication connection between the vehicle-mounted terminal and the supervision platform is established, state information of each component in the first vehicle is acquired, and when the state information of each component indicates that each component of the first vehicle enters a working state, the communication connection between the vehicle-mounted terminal and the supervision platform is established.

7. A data detection device characterized by comprising: The device comprises: An acquisition module is configured to acquire operation data of a first vehicle, the operation data being used to describe working states of each component of the first vehicle when the first vehicle drives in a historical time period, wherein, from when the first vehicle enters a working state from a sleep state, a vehicle-mounted terminal of the first vehicle collects the operation data generated by the first vehicle, and the operation data is sent to a supervision platform based on a preset frequency, and the supervision platform is used to monitor an operation process of the first vehicle; A detection module is configured to detect based on the operation data, determine a case that the operation data meets a preset data quality requirement, and obtain a detection result, and the data quality requirement comprises at least one of a data integrity requirement, a data consistency requirement and a data timeliness requirement. The acquisition module is further configured to acquire a corresponding vehicle adjustment scheme based on the detection result in a case where the operation data does not meet the data quality requirement, the vehicle adjustment scheme being used to guide adjustment of the operation data of the first vehicle in a future time period to meet the data quality requirement; the detection result contains a problem code, the problem code being used to indicate a data quality problem existing in the operation data; an encoding correspondence table is acquired, the encoding correspondence table containing a correspondence between the problem code and a candidate adjustment scheme; and the corresponding vehicle adjustment scheme is acquired from the encoding correspondence table based on the problem code in the detection result in a case where the operation data does not meet the data quality requirement.

8. A computer device, comprising: The computer device comprises a processor and a memory, and the memory stores at least one program, which is loaded and executed by the processor to implement the data detection method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that, The storage medium stores at least one program, which is loaded and executed by the processor to implement the data detection method according to any one of claims 1 to 6.

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