CN117278657A - Data processing method, data transmitting device, computer equipment and medium - Google Patents

Data processing method, data transmitting device, computer equipment and medium Download PDF

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Publication number
CN117278657A
CN117278657A CN202310961685.5A CN202310961685A CN117278657A CN 117278657 A CN117278657 A CN 117278657A CN 202310961685 A CN202310961685 A CN 202310961685A CN 117278657 A CN117278657 A CN 117278657A
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China
Prior art keywords
data
sending
analysis
quality index
message
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CN202310961685.5A
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Chinese (zh)
Inventor
张斯静
龙美元
明瑶
陶登攀
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Chongqing Changan Automobile Co Ltd
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Chongqing Changan Automobile Co Ltd
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Priority to CN202310961685.5A priority Critical patent/CN117278657A/en
Publication of CN117278657A publication Critical patent/CN117278657A/en
Pending legal-status Critical Current

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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L69/00—Network arrangements, protocols or services independent of the application payload and not provided for in the other groups of this subclass
    • H04L69/22—Parsing or analysis of headers
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/10—Protocols in which an application is distributed across nodes in the network
    • H04L67/1097—Protocols in which an application is distributed across nodes in the network for distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/50—Network services
    • H04L67/56—Provisioning of proxy services
    • H04L67/568—Storing data temporarily at an intermediate stage, e.g. caching

Abstract

The invention provides a data processing method, a data sending device, computer equipment and a medium, and relates to the field of data acquisition. The data processing method is applied to the cloud device and comprises the following steps: transmitting a data acquisition instruction to data acquisition equipment; analyzing a first data message sent by data acquisition equipment to obtain first analysis data of the first data message; based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data, performing first edge calculation on the first analysis data, and determining a first quality index of the first analysis data; determining first analysis data with a first quality index within a preset quality index range as temporary storage data; and executing the processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data. By determining the processing strategy of the temporary storage data, the cloud equipment is prevented from storing data with abnormal data quality.

Description

Data processing method, data transmitting device, computer equipment and medium
Technical Field
The present invention relates to the field of data acquisition, and in particular, to a data processing method, a data sending device, a computer device, and a medium.
Background
Along with the rapid development of intelligent control technology, the intelligent control technology is widely applied to the control of intelligent equipment such as automobiles. In general, data acquisition equipment in an automobile can acquire data of a plurality of controllers in the automobile to obtain data such as a vehicle door state, a vehicle lamp state and a vehicle speed. The automobile uploads the acquired data to cloud equipment such as a cloud server and the like so as to realize intelligent control of the automobile through a large amount of data. When abnormal data quality conditions such as abnormal accuracy and abnormal real-time performance exist in the data, the control of the automobile is affected. Data acquisition is usually required for a plurality of controllers of an automobile, and massive data can be acquired in a short time. In addition, the cloud device also needs to store the collected data of a plurality of automobiles at the same time, so that the load of the cloud device when the cloud device stores the data is further increased, and the efficiency of the cloud device for storing the data is low.
However, there is often inaccurate or incomplete data with abnormal data quality in all the data collected. If massive data are verified, all acquired data are stored through the cloud device, data quality verification needs to be manually performed on the data, the data verification efficiency is low, and further data storage delay is caused. In order to ensure the efficiency of data storage, only part of data in all data is usually subjected to quality verification, or all data is directly stored in the cloud device without verifying the data, so that a large amount of data with abnormal data quality is stored in the cloud device.
Disclosure of Invention
One of the purposes of the present invention is to provide a data processing method, so as to solve the problem that a large amount of data with abnormal data quality is stored in a cloud device; the second objective is to provide a data transmission method; a third object is to provide a data processing apparatus; the fourth object is to provide a data transmission device; a fifth object is to provide a computer device; a sixth object is to provide a machine readable storage medium.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
in a first aspect, the present application provides a data processing method, applied to a cloud device, where the data processing method includes:
transmitting a data acquisition instruction to data acquisition equipment;
analyzing a first data message sent by data acquisition equipment to obtain first analysis data of the first data message;
based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data, performing first edge calculation on the first analysis data, and determining a first quality index of the first analysis data;
determining first analysis data with a first quality index within a preset quality index range as temporary storage data;
and executing a processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data, wherein the second analysis data is obtained by analyzing a second data message sent by the data acquisition equipment within a first time period after the first data message is sent, and the processing strategy comprises deleting the temporary storage data and storing the temporary storage data into a data warehouse.
With reference to the first aspect, in a first possible implementation manner, the data processing method further includes:
and deleting the first analysis data and sending a first sending stop instruction to the data acquisition equipment under the condition that the first quality index is smaller than the lower limit value of the preset quality index range, wherein the first sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within the second duration.
With reference to the first possible implementation manner of the first aspect, in a second possible implementation manner, the data processing method further includes:
acquiring a first number of times of sending a first sending stop instruction in a first preset period, wherein the first preset period is longer than a second duration;
and under the condition that the first time number is larger than a first time number threshold value, sending a first acquisition stop instruction, wherein the first acquisition stop instruction is used for controlling the data acquisition equipment to stop acquiring the data message in a first preset period.
With reference to the first aspect, in a third possible implementation manner, based on the similarity between the second parsed data and the temporary stored data and the second quality index of the second parsed data, executing a processing policy of the temporary stored data includes:
Storing the temporary storage data to a data warehouse under the condition that the similarity of each second analysis data and the temporary storage data is larger than the preset similarity and the number of the second analysis data with the second quality index in the preset quality index range is larger than the preset number;
and deleting the first analysis data and sending a second sending stop instruction to the data acquisition equipment under the condition that the similarity of at least one second analysis data and the temporary storage data is smaller than or equal to the preset similarity and/or the number of the second analysis data with the second quality index within the preset quality index range is smaller than or equal to the preset number, wherein the second sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within a third duration.
With reference to the third possible implementation manner of the first aspect, in a fourth possible implementation manner, the data processing method further includes:
acquiring a second number of times of sending a second sending stop instruction in a second preset period, wherein the second preset period is longer than a third duration;
and sending a second acquisition stop instruction under the condition that the second time is larger than a second time threshold, wherein the second acquisition stop instruction is used for controlling the data acquisition equipment to stop acquiring the data message in a second preset period.
With reference to the first aspect, in a fifth possible implementation manner, the data processing method further includes:
and storing the first analysis data to a data warehouse under the condition that the first quality index is larger than the upper limit value of the preset quality index range.
In a second aspect, the present application provides a data transmission method, applied to a data acquisition device, where the data transmission method includes:
responding to a data acquisition instruction of the cloud device, and acquiring data of all signals in a preset time period to obtain a data message;
filtering the data of invalid signals in the data message according to the bus identification of each signal and the signal effective range;
and sending the data message to cloud equipment.
With reference to the second aspect, in a first possible implementation manner, the data acquisition device includes a communication module, sends a data packet to the cloud device, and includes:
according to the current communication state of the communication module and the data size of the data message, performing second edge calculation on the data message, and determining a first transmission rate of each signal sent to the cloud device by the communication module;
and based on the first transmission rate of each signal, sending the data message to the cloud device through the communication module.
With reference to the first possible implementation manner of the second aspect, in a second possible implementation manner, the data sending method further includes:
according to the current load state and the data size of the data message, performing third edge calculation on the data message, and determining a second transmission rate of each signal sent to the communication module;
the data message is sent to the communication module based on the second transmission rate of each signal.
In a third aspect, the present application provides a data processing apparatus, applied to a cloud device, the data processing apparatus including:
the instruction sending module is used for sending a data acquisition instruction to the data acquisition equipment;
the message analysis module is used for analyzing the first data message sent by the data acquisition equipment to obtain first analysis data of the first data message;
the quality index determining module is used for carrying out first edge calculation on the first analysis data based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data to determine a first quality index of the first analysis data;
the data temporary storage module is used for determining first analysis data with the first quality index within a preset quality index range as temporary storage data;
The processing strategy executing module is used for executing the processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data, wherein the second analysis data is obtained by analyzing the second data message sent by the data acquisition equipment within the first time period after the first data message is sent, and the processing strategy comprises the steps of deleting the temporary storage data and storing the temporary storage data into a data warehouse.
In a fourth aspect, the present application provides a data transmission device, applied to a data acquisition apparatus, the data transmission device including:
the data acquisition module is used for responding to a data acquisition instruction of the cloud device, and acquiring data of all signals in a preset time period to obtain a data message;
the invalid signal filtering module is used for filtering the data of the invalid signals in the data message according to the bus identification and the signal valid range of each signal;
and the message sending module is used for sending the data message to the cloud device.
In a fifth aspect, the present application provides a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, implements a data processing method as in the first aspect, or a data transmission method as in the second aspect.
In a sixth aspect, the present application provides a machine-readable storage medium having stored thereon a computer program which, when executed by a processor, implements a data processing method as in the first aspect, or a data transmission method as in the second aspect.
The invention has the beneficial effects that:
(1) The cloud device verifies the first analysis data by using the quality index, and determines the first analysis data needing secondary quality verification as temporary storage data. Determining the data quality of the temporary storage data through the second analysis data, and further determining whether to delete the temporary storage data or store the temporary storage data, so that the data with abnormal data quality stored by the cloud device is avoided, the data quality of the cloud device is improved, and the storage resources of the cloud device are saved;
(2) The cloud device deletes or stores the data with the quality index not in the preset index range in real time, and when the temporary storage data is determined to be deleted or stored, the cloud device executes the processing strategy of the temporary storage data after the first time period due to the fact that the second analysis data in the first time period need to be acquired, and then the cloud device stores the data in batches. Compared with the method for directly storing all the data, the method reduces the load of the cloud equipment by storing the data in batches, and improves the efficiency of the cloud equipment for storing the data.
Drawings
The accompanying drawings are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain, without limitation, the embodiments of the invention. In the drawings:
FIG. 1 shows a flow chart of a data processing method provided by an embodiment of the present application;
fig. 2 illustrates an application example diagram of a cloud device provided in an embodiment of the present application;
fig. 3 shows a flowchart of a data transmission method provided in an embodiment of the present application;
fig. 4 shows a schematic structural diagram of a data acquisition device according to an embodiment of the present application;
FIG. 5 is a schematic diagram of a data processing apparatus according to an embodiment of the present application;
fig. 6 shows a schematic structural diagram of a data transmission device according to an embodiment of the present application.
Detailed Description
The following describes the detailed implementation of the embodiments of the present invention with reference to the drawings. It should be understood that the detailed description and specific examples, while indicating and illustrating the invention, are not intended to limit the invention.
The components of the embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations. Thus, the following detailed description of the embodiments of the invention, as presented in the figures, is not intended to limit the scope of the invention, as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be made by a person skilled in the art without making any inventive effort, are intended to be within the scope of the present invention.
The terms "comprises," "comprising," "including," or any other variation thereof, are intended to cover a specific feature, number, step, operation, element, component, or combination of the foregoing, which may be used in various embodiments of the present invention, and are not intended to first exclude the presence of or increase the likelihood of one or more other features, numbers, steps, operations, elements, components, or combinations of the foregoing.
Furthermore, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and should not be construed as indicating or implying relative importance.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which various embodiments of the invention belong. The terms (such as those defined in commonly used dictionaries) will be interpreted as having a meaning that is the same as the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein in connection with the various embodiments of the invention.
Example 1
Referring to fig. 1, fig. 1 shows a flowchart of a data processing method according to an embodiment of the present application.
The data processing method in fig. 1 is applied to the cloud device, and the data processing method in fig. 1 includes:
s110, sending a data acquisition instruction to the data acquisition equipment.
Referring to fig. 2, fig. 2 illustrates an application example diagram of a cloud device provided in an embodiment of the present application.
When the data acquisition device 220 is required to perform data acquisition, the cloud device 210 communicates with the data acquisition device 220 through TSP (Time Shared Protocol, time-sharing routing protocol). The cloud device 210 sends a data acquisition instruction to the data acquisition device 220 to perform data acquisition through the data acquisition device 220.
It should be understood that the type of the data acquisition device 220 is set according to actual requirements, and is not limited herein. For easy understanding, in the embodiment of the present application, the data acquisition device 220 is a data processing device of a vehicle, and the data acquisition device 220 performs data acquisition on signals of various controllers in the vehicle, so as to perform intelligent control on the vehicle through the acquired data. The data obtained by the data acquisition device 220 may be vehicle speed, vehicle door state, vehicle lamp state data, etc. The type of the cloud device 210 is also set according to actual requirements, which is not limited herein.
S120, analyzing the first data message sent by the data acquisition equipment to obtain first analysis data of the first data message.
The data acquisition equipment acquires data of signals of the controllers, and sends acquired data to the cloud equipment in the form of a message. The message is a data unit in the network, and the first data message includes complete data sent by the data acquisition device. The cloud device analyzes the first data message sent by the data acquisition device to obtain first analysis data of the first data message. It should be understood that the data type of the first analysis data is obtained by analyzing according to actual requirements, and may be a name, a bus identifier, a length, a start bit, a timestamp, etc. of each signal, which are not described herein.
S130, based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data, performing first edge calculation on the first analysis data, and determining a first quality index of the first analysis data.
And determining the data integrity rate of the first analysis data according to the data type in the first data message actually received by the cloud end device and the data type required to be acquired by the data acquisition device. And determining the uploading success rate of the first analysis data according to the times of the signal in the first data message sent to the cloud end equipment and the times of the data acquisition equipment actually carrying out data acquisition on the signal. And determining the data consistency rate of the first analysis data according to the number of signals, which are actually collected in the first data message and are consistent with the signals required to be collected, and the number of all the signals actually collected by the data collection equipment. And executing a strategy of first edge calculation on the first analysis data, wherein the strategy of first edge calculation comprises the step of determining a first quality index of the first analysis data based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data. Specifically, the first quality index of the first analysis data may be determined according to the weighted average of the data integrity rate, the upload success rate, and the data consistency rate.
And S140, determining the first analysis data with the first quality index within the preset quality index range as temporary storage data.
After the first quality index of the first analysis data is obtained, whether the first quality index is in a preset quality index range or not is determined. The upper limit value and the lower limit value of the preset quality index range are set according to actual requirements, and are not limited herein. For ease of understanding, in the embodiment of the present application, the upper limit value of the preset quality index range is 70%, and the lower limit value of the preset quality index range is 60%.
And under the condition that the first quality index of the first analysis data is in the preset quality index range, determining that secondary detection is required to be carried out on the accuracy of the first analysis data, and determining the first analysis data as temporary storage data so as to avoid data with abnormal storage quality.
S150, executing a processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data.
When the data acquisition device acquires data, the data acquisition device acquires similar data at intervals and sends the similar data to the cloud device, so that the cloud device can analyze the data message to obtain similar analysis data. Taking the first analysis data as an example of the door state, when the door of the vehicle is kept in the closed state, the cloud device analyzes the data message in a short time, and a large amount of similar analysis data which are used for describing that the door is kept in the closed state are obtained.
The cloud device further sets a value of at least one second data message sent by the received data acquisition device within a first time period after receiving the first data message sent by the data acquisition device, wherein the first time period is set according to actual requirements, and the value is not limited herein. For ease of understanding, the first duration in the examples of the present application is 10 minutes. The cloud device analyzes each second data message to obtain second analysis data of each second data message.
Determining whether the data acquisition equipment transmits a data message similar to the temporary storage data or not based on the similarity between the second analysis data and the temporary storage data; and determining whether the data acquired by the data acquisition device is determined to be temporary stored data a plurality of times based on a second quality index of the second analysis data, and further executing a processing strategy of the temporary stored data, wherein the processing strategy comprises deleting the temporary stored data and storing the temporary stored data to a data warehouse. And verifying the first analysis data by using the quality index, and determining the first analysis data needing secondary quality verification as temporary storage data. The data quality of the temporary storage data is determined through the second analysis data, and whether the temporary storage data is deleted or stored is further determined, so that the data with abnormal data quality stored by the cloud device is avoided, and the data quality of the cloud device is improved. Meanwhile, the data processing method can be applied to any cloud device, the cloud device and the data acquisition device do not need to be newly added with other hardware devices such as bus devices, the cloud device can store data of each data acquisition device, and hardware cost of data acquisition is reduced.
The cloud device deletes or stores the data with the quality index not in the preset index range in real time, and when the temporary storage data is determined to be deleted or stored, the cloud device executes the processing strategy of the temporary storage data after the first time period due to the fact that the second analysis data in the first time period need to be acquired, and then the cloud device stores the data in batches. Compared with the method for directly storing all the data, the method reduces the load of the cloud equipment by storing the data in batches, and improves the efficiency of the cloud equipment for storing the data.
In an embodiment of the present application, the data processing method further includes:
and deleting the first analysis data and sending a first sending stop instruction to the data acquisition equipment under the condition that the first quality index is smaller than the lower limit value of the preset quality index range, wherein the first sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within the second duration.
And under the condition that the first quality index is smaller than the lower limit value of the preset quality index range, namely, the first quality index is smaller than 60%, determining that the first analysis data is low-quality data, namely, the first analysis data cannot accurately describe the actual condition of the vehicle. If the first analysis data is directly stored, not only is the storage resources of the data warehouse wasted, but also control data of the vehicle cannot be generated through the data warehouse, which affects the control of the vehicle. In the embodiment of the application, under the condition that the first quality index is smaller than the lower limit value of the preset quality index range, the first analysis data with low data quality is directly deleted, so that the low-quality data is prevented from being stored in a data warehouse. And simultaneously, sending a first sending stop instruction to the data acquisition equipment, wherein the first sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within a second duration. By deleting the temporary storage data with abnormal data quality, the storage of the quality abnormal data to the data warehouse is avoided. And further data quality of the cloud device. The value of the second duration is set according to the actual requirement, and is not limited herein.
In an embodiment of the present application, the data processing method further includes:
acquiring a first number of times of sending a first sending stop instruction in a first preset period, wherein the first preset period is longer than a second duration;
and under the condition that the first time number of the sending stop instruction is larger than the first time number threshold value, sending a first acquisition stop instruction, wherein the first acquisition stop instruction is used for controlling the data acquisition equipment to stop acquiring the data message in a first preset period.
The method comprises the steps of obtaining first times of sending a first sending stop instruction in a first preset period to determine whether cloud equipment sends the first stop instruction to data acquisition equipment for multiple times in the first preset period, wherein the first preset period is longer than a second duration. The value of the first preset period is set according to the actual requirement, and is not limited herein. Under the condition that the first time number is larger than the first time number threshold value, determining that the quality index of the analysis data is low in a first preset period for multiple times, and then sending a first stop instruction to the data acquisition equipment for multiple times, wherein the cloud equipment sends the first acquisition stop instruction, the first acquisition stop instruction is used for controlling the data acquisition equipment to stop acquiring data messages in the first preset period, so that the cloud equipment is prevented from receiving a large amount of low-quality data, and the data quality of the cloud equipment is further improved. Meanwhile, the data of a plurality of data acquisition devices can be verified and stored, each data acquisition device is controlled to acquire data and send data, and the flexibility of data acquisition is improved. The value of the first preset number of times is set according to the actual requirement, and is not limited herein.
In an embodiment of the present application, based on a similarity between the second analysis data and the temporary storage data and a second quality index of the second analysis data, a processing policy of the temporary storage data is executed, including:
storing the temporary storage data to a data warehouse under the condition that the similarity of each second analysis data and the temporary storage data is larger than the preset similarity and the number of the second analysis data with the second quality index in the preset quality index range is larger than the preset number;
and deleting the first analysis data and sending a second sending stop instruction to the data acquisition equipment under the condition that the similarity of at least one second analysis data and the temporary storage data is smaller than or equal to the preset similarity and/or the number of the second analysis data with the second quality index within the preset quality index range is smaller than or equal to the preset number, wherein the second sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within a third duration.
Specifically, based on the similarity between the second analysis data and the temporary storage data, determining whether the second analysis data and the first analysis data within the first duration are similar, wherein a value of the preset similarity is set according to actual requirements, and the method is not limited herein. For ease of understanding, the preset similarity in the embodiment of the present application is 90%. And determining whether the quality indexes of the plurality of second analysis data are all in a preset quality index range based on the second quality index of the second analysis data under the condition that whether the second analysis data are similar to the first analysis data or not.
Specifically, when the similarity between each second analysis data and the temporary storage data is greater than the preset similarity, and the number of the second analysis data with the second quality index within the preset quality index range is greater than the preset number, it is determined that the first quality index is within the preset quality index range due to abnormal data quality of the temporary storage data, and only analysis data with the quality index within the preset quality index range can be obtained in a short time. Since the quality indexes of the analysis data acquired in a short time are all in the preset quality index range, the data acquired by the data acquisition equipment are determined to be temporary storage data for many times, and the situation that the temporary storage data has no abnormal data quality is determined, and the temporary storage data is stored in the data warehouse.
And under the condition that the similarity between at least one second analysis data and the temporary storage data is smaller than or equal to the preset similarity, determining that the situation that the data acquisition equipment acquires the error data exists, deleting the first analysis data directly when the data quality of the temporary storage data is abnormal, and sending a second sending stop instruction to the data acquisition equipment, wherein the second sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within a third duration. The value of the third duration is set according to the actual requirement, and is not limited herein. For ease of understanding, the second duration and the third duration are both 0.5 hours in the embodiments of the present application.
Under the condition that the number of the second analysis data with the second quality index within the preset quality index range is smaller than or equal to the preset number, the condition that the quality of the data acquired by the data acquisition equipment is abnormal is determined, and further the analysis data with the data quality index not close to the acquired data quality index is caused to be directly deleted, and a second sending stop instruction is sent to the data acquisition equipment. By deleting the temporary storage data with abnormal data quality, the storage of the quality abnormal data to the data warehouse is avoided. By controlling the data acquisition equipment to stop sending the data message, the cloud equipment is prevented from receiving a large amount of low-quality data, and the data quality of the cloud equipment is further improved.
In an embodiment of the present application, the data processing method further includes:
acquiring a second number of times of sending a second sending stop instruction in a second preset period, wherein the second preset period is longer than a third duration;
and sending a second acquisition stop instruction under the condition that the second time is larger than a second time threshold, wherein the second acquisition stop instruction is used for controlling the data acquisition equipment to stop acquiring the data message in a second preset period.
And acquiring a second number of times of sending a second sending stop instruction in a second preset period to determine whether the cloud device sends the second stop instruction to the data acquisition device for multiple times in the second preset period, wherein the second preset period is longer than a third duration. The value of the second preset period is set according to the actual requirement, and is not limited herein. For ease of understanding, in the embodiments of the present application, the first preset period and the second preset period are both 24 hours. Under the condition that the second times are larger than a second times threshold, determining that the quality index of the analysis data is abnormal in a second preset period for a plurality of times, and then sending a second stop instruction to the data acquisition equipment for a plurality of times, wherein the cloud equipment sends the second acquisition stop instruction, the second acquisition stop instruction is used for controlling the data acquisition equipment to stop acquiring data messages in the second preset period, so that the cloud equipment is prevented from receiving a large amount of low-quality data, and the data quality of the cloud equipment is further improved. Meanwhile, the data of a plurality of data acquisition devices can be verified and stored, each data acquisition device is controlled to acquire data and send data, and the flexibility of data acquisition is improved. The value of the second preset number is set according to the actual requirement, and is not limited herein. For ease of understanding, in the embodiment of the present application, the first preset number of times is 3 times, and the second preset number of times is 5 times.
In an embodiment of the present application, the data processing method further includes:
and storing the first analysis data to a data warehouse under the condition that the first quality index is larger than the upper limit value of the preset quality index range.
And under the condition that the first quality level is larger than the upper limit value of the preset quality index range, determining that the first analysis data is data with high data quality, and storing the first analysis data with high data quality into a data warehouse.
It should be understood that, in the case that the first quality index is greater than the lower limit value of the preset quality index range, the quality level of the first analysis data may be determined according to the first quality index. Specifically, in the case where the first quality index is greater than 60% and less than or equal to 70%, that is, in the case where the first quality index is within the preset quality index range, the quality level of the first analysis data is determined as the fourth quality level. In the case where the first quality index is greater than 70% and less than or equal to 80%, the quality level of the first analysis data is determined as a third quality level. In the case where the first quality index is greater than 80% and less than or equal to 90%, the quality level of the first analysis data is determined as the second quality level. And determining the quality level of the first analysis data as a first quality level under the condition that the first quality index is more than 90%.
And according to the quality grade of the first analysis data, quickly determining whether the first analysis data is high-quality data. Meanwhile, in the case where the quality level of the first analysis data is the fourth quality level, the first analysis data is determined as temporary storage data. And executing the processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data.
The application provides a data processing method, which is applied to cloud equipment, and comprises the following steps: transmitting a data acquisition instruction to data acquisition equipment; analyzing a first data message sent by data acquisition equipment to obtain first analysis data of the first data message; based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data, performing first edge calculation on the first analysis data, and determining a first quality index of the first analysis data; determining first analysis data with a first quality index within a preset quality index range as temporary storage data; and executing the processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data. The cloud device verifies the first analysis data by using the quality index, and determines the first analysis data needing secondary quality verification as temporary storage data. The data quality of the temporary storage data is determined through the second analysis data, and then whether the temporary storage data is deleted or stored is determined, so that the data with abnormal data quality stored by the cloud device is avoided, the data quality of the cloud device is improved, and the storage resources of the cloud device are saved. The cloud device deletes or stores the data with the quality index not in the preset index range in real time, and when the temporary storage data is determined to be deleted or stored, the cloud device executes the processing strategy of the temporary storage data after the first time period due to the fact that the second analysis data in the first time period need to be acquired, and then the cloud device stores the data in batches. Compared with the method for directly storing all the data, the method reduces the load of the cloud equipment by storing the data in batches, and improves the efficiency of the cloud equipment for storing the data.
Example 2
Referring to fig. 3, fig. 3 shows a flowchart of a data transmission method provided in an embodiment of the present application.
The data transmission method in fig. 3 is applied to a data acquisition device, and the data transmission method in fig. 3 includes:
s310, responding to a data acquisition instruction of the cloud device, and acquiring data of all signals within a preset time period to obtain a data message.
For ease of understanding, the data acquisition device 220 in embodiments of the present application is a data processing device of a vehicle. Typically the vehicle comprises a plurality of controllers and the data acquisition device comprises a micro control unit (Micro Controller Unit, MCU) for data acquisition of signals from the controllers. Specifically, the data acquisition device responds to a data acquisition instruction of the cloud device, performs data acquisition on signals of all controllers in a preset time period, and forms data of a plurality of signals into a data message so as to store the data of each signal to the cloud device.
S320, filtering the data of invalid signals in the data message according to the bus identification and the signal effective range of each signal.
And determining whether the data message comprises the data of the invalid signal according to the bus identification of each signal. In case there is no matching preset bus identification for the bus identification (Controller Area Network Identity Document, caid) of the current signal, the current signal is determined as an invalid signal. And under the condition that the bus identification of the current signal has the matched preset bus identification, determining the current signal as a valid signal. And determining whether the data message comprises the data of the invalid signal according to the valid range of each signal. And determining the current signal as an invalid signal in the case that the valid signal range of the current signal is smaller than the preset signal range threshold. And determining the current signal as the effective signal under the condition that the effective signal range of the current signal is larger than or equal to a preset signal range threshold value. And determining invalid signals according to the bus identification of each signal and the signal valid range, filtering the data of the invalid signals in the data message, and retaining the data of the valid signals.
S330, the data message is sent to the cloud device.
The data acquisition equipment sends the data message with the valid signal reserved to the cloud equipment so as to store the signal data of each controller through the cloud equipment. For ease of understanding, in the embodiments of the present application, the data collection device sends the data packet to the cloud device through TLV (Ttype Length Value, tag length content) protocol. By filtering the data of the invalid signals in the data message in advance, the data quality of the data stored in the cloud device can be effectively improved. Meanwhile, the number of data stored in the cloud device is reduced, the load of the cloud device is reduced, and the data storage efficiency of the cloud device is improved.
In the embodiment of the application, the data acquisition device includes a communication module, sends the data message to the cloud device, and includes:
according to the current communication state of the communication module and the data size of the data message, performing second edge calculation on the data message, and determining a first transmission rate of each signal sent to the cloud device by the communication module;
and based on the first transmission rate of each signal, sending the data message to the cloud device through the communication module.
Referring to fig. 4, fig. 4 is a schematic structural diagram of a data acquisition device according to an embodiment of the present application.
The micro control unit 420 is configured to perform data collection on signals of each controller 410 to obtain data messages, where the number of controllers 410 is set according to actual requirements, and is not limited herein. For ease of understanding, only one controller 410 is shown. The micro control unit 420 cannot directly send the data message to the cloud device, and needs to forward the data message to the communication module 430, and then send the data message to the cloud device through the communication module 430, where the type of the communication module 430 is set according to the actual requirement, and may be a 4G (Fourth Generation Communications System, fourth-generation mobile communication system) module, and the like, which is not limited herein.
When the communication module 430 needs to forward the data packet to the cloud device, the second edge calculation policy is executed. The second edge calculation policy is to determine the first transmission rate of each signal sent to the cloud device by the communication module 430 according to the current communication state of the communication module 430 and the data size of the data packet, where the current communication state of the communication data includes parameters such as the network transmission rate and the network load of the communication module 430, which are not described herein.
For ease of understanding, the micro control unit 420 in the embodiment of the present application performs data acquisition on the signal a, the signal B, and the signal C. In the case that the first transmission rate of the signal a is determined to be greater than the first transmission rate of the signal B, and the first transmission rate of the signal B is determined to be greater than the first transmission rate of the signal C, based on the first transmission rate of each signal, according to the data of the signal a, the data of the signal B, and the arrangement sequence of the data of the signal C, the data message is sent to the cloud device through the communication module 430. Based on the first transmission rate of each signal, the data message is sent to the cloud end device, so that the data uploading efficiency of the data acquisition device 400 is improved, and the data uploading time extension caused by the conditions of delay and the like of the data message is avoided.
In an embodiment of the present application, the data sending method further includes:
according to the current load state and the data size of the data message, performing third edge calculation on the data message, and determining a second transmission rate of each signal sent to the communication module;
the data message is sent to the communication module based on the second transmission rate of each signal.
And when the micro control unit needs to forward the data message to the communication module, executing a third edge calculation strategy. The third edge calculation strategy is to determine a second transmission rate of each signal sent to the communication module according to the load state of the micro control unit and the data size of the data message. And under the condition that the second transmission rate of the signal C is determined to be greater than the second transmission rate of the signal A and the second transmission rate of the signal A is determined to be greater than the second transmission rate of the signal B, based on the second transmission rate of each signal, sending the data message to the communication module according to the arrangement sequence of the data of the signal C, the data of the signal A and the data of the signal B. And the data message is sent to the communication module based on the second transmission rate of each signal, so that the data uploading efficiency of the data acquisition equipment is improved, and the data uploading time extension caused by the conditions of delay and the like of the data message is avoided.
Example 3
Referring to fig. 5, fig. 5 is a schematic structural diagram of a data processing apparatus according to an embodiment of the present application. The data processing apparatus 500 in fig. 5 is applied to a cloud device, and the data processing apparatus 500 in fig. 5 includes:
the instruction sending module 510 is configured to send a data acquisition instruction to a data acquisition device;
the message parsing module 520 is configured to parse the first data message sent by the data acquisition device to obtain first parsed data of the first data message;
the quality index determining module 530 is configured to perform first edge calculation on the first analysis data based on the data integrity rate, the upload success rate, and the data consistency rate of the first analysis data, and determine a first quality index of the first analysis data;
a data temporary storage module 540, configured to determine, as temporary storage data, first analysis data whose first quality index is within a preset quality index range;
and a processing policy executing module 550, configured to execute a processing policy of the temporary storage data based on a similarity between the second analysis data and the temporary storage data and a second quality index of the second analysis data, where the second analysis data is obtained by analyzing a second data packet sent by the data acquisition device within a first duration after the first data packet is sent, and the processing policy includes deleting the temporary storage data and storing the temporary storage data in the data warehouse.
In an embodiment of the present application, the data processing apparatus 500 further includes:
the first sending stopping module is used for deleting the first analysis data and sending a first sending stopping instruction to the data acquisition equipment under the condition that the first quality index is smaller than the lower limit value of the preset quality index range, wherein the first sending stopping instruction is used for controlling the data acquisition equipment to stop sending the data message within the second duration.
In an embodiment of the present application, the data processing apparatus 500 further includes:
the first time number acquisition module is used for acquiring a first time number of sending a first sending stop instruction in a first preset period, wherein the first preset period is longer than a second time length;
the first acquisition stopping module is used for sending a first acquisition stopping instruction under the condition that the first time number is larger than a first time number threshold value, wherein the first acquisition stopping instruction is used for controlling the data acquisition equipment to stop acquiring the data message in a first preset period.
In an embodiment of the present application, the processing policy enforcement module 550 includes:
the data storage word sub-module is used for storing the temporary storage data to the data warehouse under the condition that the similarity between each second analysis data and the temporary storage data is larger than the preset similarity and the number of the second analysis data with the second quality index in the preset quality index range is larger than the preset number;
The second sending stopping module is used for deleting the first analysis data and sending a second sending stopping instruction to the data acquisition equipment when the similarity between at least one piece of second analysis data and the temporary storage data is smaller than or equal to the preset similarity and/or the number of the second analysis data with the second quality index within the preset quality index range is smaller than or equal to the preset number, wherein the second sending stopping instruction is used for controlling the data acquisition equipment to stop sending the data message within a third duration.
In an embodiment of the present application, the data processing apparatus 500 further includes:
the second time acquisition module is used for acquiring a second time for transmitting a second transmission stop instruction in a second preset period, wherein the second preset period is longer than a third duration;
the second acquisition stopping module is used for sending a second acquisition stopping instruction under the condition that the second time is larger than a second time threshold, wherein the second acquisition stopping instruction is used for controlling the data acquisition equipment to stop acquiring the data message in a second preset period.
In an embodiment of the present application, the data processing apparatus 500 further includes:
and the analysis data storage module is used for storing the first analysis data to the data warehouse under the condition that the first quality index is larger than the upper limit value of the preset quality index range.
The data processing apparatus 500 is configured to perform the corresponding steps in the above-described data processing method, and specific implementation of each function is not described herein. Furthermore, the alternative example in embodiment 1 is also applicable to the data processing apparatus 500 of embodiment 3.
Example 4
Referring to fig. 6, fig. 6 shows a schematic structural diagram of a data transmitting apparatus according to an embodiment of the present application. The data transmission apparatus 600 in fig. 6 is applied to a data acquisition device, and the data transmission apparatus 600 in fig. 6 includes:
the data acquisition module 610 is configured to respond to a data acquisition instruction of the cloud device, and perform data acquisition on all signals in a preset time period to obtain a data packet;
an invalid signal filtering module 620, configured to filter data of an invalid signal in the data packet according to the bus identifier and the signal valid range of each signal;
and a message sending module 630, configured to send the data message to the cloud device.
In an embodiment of the present application, the message sending module 630 includes:
the second edge calculation sub-module is used for carrying out second edge calculation on the data message according to the current communication state of the communication module and the data size of the data message, and determining a first transmission rate of each signal sent to the cloud device by the communication module;
And the first message sending sub-module is used for sending the data message to the cloud device through the communication module based on the first transmission rate of each signal.
In an embodiment of the present application, the data sending apparatus 600 further includes:
the third edge calculation module is used for carrying out third edge calculation on the data message according to the current load state and the data size of the data message, and determining a second transmission rate of each signal sent to the communication module;
and the second message sending module is used for sending the data message to the communication module based on the second transmission rate of each signal.
The data transmission apparatus 600 is configured to perform the corresponding steps in the above-described data transmission method, and specific implementation of each function is not described herein. Further, the alternative example in embodiment 2 is also applicable to the data transmission apparatus 600 of embodiment 4.
The embodiment of the present application further provides a computer device, where the computer device includes a memory and a processor, where the memory stores a computer program, and the computer program implements the data processing method as in embodiment 1 or the data sending method as in embodiment 2 when executed by the processor.
The instruction sending module 510, the message parsing module 520, the quality index determining module 530, the data temporary storage module 540, the processing policy executing module 550, the data collecting module 610, the invalid signal filtering module 620, the message sending module 630 and the like in the embodiment of the present application are all stored in the memory as program units, and the processor executes the program units stored in the memory to realize corresponding functions.
The processor includes a kernel, and the kernel fetches the corresponding program unit from the memory. The kernel can be provided with one or more than one, and a data processing method is provided by adjusting kernel parameters so as to solve the problem that a large amount of data with abnormal data quality is stored in the cloud device.
The memory may include volatile memory, random Access Memory (RAM), and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM), among other forms in computer readable media, the memory including at least one memory chip.
The present application also provides a machine-readable storage medium having stored thereon a computer program which, when executed by a processor, implements the data processing method as in embodiment 1 or the data transmission method as in embodiment 2.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, etc., such as Read Only Memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.
Machine-readable storage media, including both non-transitory and removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.

Claims (13)

1. The data processing method is applied to cloud equipment and is characterized by comprising the following steps of:
transmitting a data acquisition instruction to data acquisition equipment;
analyzing a first data message sent by the data acquisition equipment to obtain first analysis data of the first data message;
based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data, performing first edge calculation on the first analysis data, and determining a first quality index of the first analysis data;
determining first analysis data of which the first quality index is in a preset quality index range as temporary storage data;
and executing a processing strategy of the temporary storage data based on the similarity between the second analysis data and the temporary storage data and the second quality index of the second analysis data, wherein the second analysis data is obtained by analyzing a second data message sent by the data acquisition equipment within a first time period after the first data message is sent, and the processing strategy comprises deleting the temporary storage data and storing the temporary storage data into a data warehouse.
2. The data processing method according to claim 1, characterized in that the data processing method further comprises:
and deleting the first analysis data and sending a first sending stop instruction to the data acquisition equipment under the condition that the first quality index is smaller than the lower limit value of the preset quality index range, wherein the first sending stop instruction is used for controlling the data acquisition equipment to stop sending the data message within a second duration.
3. The data processing method according to claim 2, characterized in that the data processing method further comprises:
acquiring a first number of times of sending the first sending stop instruction in a first preset period, wherein the first preset period is longer than the second duration;
and under the condition that the first time number is larger than a first time number threshold value, sending a first acquisition stop instruction, wherein the first acquisition stop instruction is used for controlling data acquisition equipment to stop acquiring the data message in a first preset period.
4. The data processing method according to claim 1, wherein the executing the processing policy of the temporary stored data based on the similarity of the second analysis data and the temporary stored data, and the second quality index of the second analysis data, comprises:
Storing the temporary storage data to the data warehouse when the similarity between each piece of second analysis data and the temporary storage data is larger than a preset similarity and the number of second analysis data with the second quality index in the preset quality index range is larger than a preset number;
and deleting the first analysis data and sending a second sending stopping instruction to the data acquisition equipment under the condition that the similarity of at least one piece of second analysis data and the temporary storage data is smaller than or equal to a preset similarity and/or the number of second analysis data with the second quality index within a preset quality index range is smaller than or equal to a preset number, wherein the second sending stopping instruction is used for controlling the data acquisition equipment to stop sending the data message within a third duration.
5. The data processing method according to claim 4, characterized in that the data processing method further comprises:
acquiring a second number of times of sending the second sending stop instruction in a second preset period, wherein the second preset period is longer than the third duration;
and sending a second acquisition stop instruction under the condition that the second times are larger than a second times threshold, wherein the second acquisition stop instruction is used for controlling data acquisition equipment to stop acquiring the data message in a second preset period.
6. The data processing method according to claim 1, characterized in that the data processing method further comprises:
and storing the first analysis data to a data warehouse under the condition that the first quality index is larger than the upper limit value of the preset quality index range.
7. A data transmission method applied to a data acquisition device, the data transmission method comprising:
responding to a data acquisition instruction of the cloud device, and acquiring data of all signals in a preset time period to obtain a data message;
filtering the data of invalid signals in the data message according to the bus identification of each signal and the signal effective range;
and sending the data message to the cloud device.
8. The method of sending data according to claim 7, wherein the data acquisition device includes a communication module, and the sending the data packet to the cloud device includes:
according to the current communication state of the communication module and the data size of the data message, performing second edge calculation on the data message, and determining a first transmission rate of each signal sent to the cloud device by the communication module;
And based on the first transmission rate of each signal, sending the data message to the cloud device through the communication module.
9. The data transmission method according to claim 8, characterized in that the data transmission method further comprises:
according to the current load state and the data size of the data message, performing third edge calculation on the data message, and determining a second transmission rate of each signal sent to the communication module;
and transmitting the data message to the communication module based on the second transmission rate of each signal.
10. A data processing apparatus applied to a cloud device, wherein the data processing apparatus includes:
the instruction sending module is used for sending a data acquisition instruction to the data acquisition equipment;
the message analysis module is used for analyzing the first data message sent by the data acquisition equipment to obtain first analysis data of the first data message;
the quality index determining module is used for performing first edge calculation on the first analysis data based on the data integrity rate, the uploading success rate and the data consistency rate of the first analysis data to determine a first quality index of the first analysis data;
The data temporary storage module is used for determining the first analysis data with the first quality index within the preset quality index range as temporary storage data;
the processing policy executing module is configured to execute a processing policy of the temporary storage data based on a similarity between second analysis data and the temporary storage data and a second quality index of the second analysis data, where the second analysis data is obtained by analyzing a second data packet sent by the data acquisition device within a first duration after sending the first data packet, and the processing policy includes deleting the temporary storage data and storing the temporary storage data in a data warehouse.
11. A data transmission device applied to a data acquisition apparatus, the data transmission device comprising:
the data acquisition module is used for responding to a data acquisition instruction of the cloud device, and acquiring data of all signals in a preset time period to obtain a data message;
the invalid signal filtering module is used for filtering the data of the invalid signals in the data message according to the bus identification of each signal and the signal valid range;
and the message sending module is used for sending the data message to the cloud device.
12. A computer device, characterized in that it comprises a memory and a processor, the memory storing a computer program which, when executed by the processor, implements the data processing method according to any one of claims 1 to 6 or the data transmission method according to any one of claims 7 to 9.
13. A machine-readable storage medium, having stored thereon a computer program which, when executed by a processor, implements the data processing method according to any one of claims 1 to 6 or the data transmission method according to any one of claims 7 to 9.
CN202310961685.5A 2023-07-28 2023-07-28 Data processing method, data transmitting device, computer equipment and medium Pending CN117278657A (en)

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