Remote diagnosis efficiency improvement method and device, electronic equipment and storage medium

Abstract

The embodiment of the application discloses a remote diagnosis efficiency improving method and device, electronic equipment and storage medium, the method comprises the following steps: receiving a remote diagnosis request of a target object for a target vehicle; in response to the remote diagnosis request, obtaining the to-be-diagnosed data of the target vehicle through a remote diagnosis platform, wherein the to-be-diagnosed data is used to determine a diagnosis function; the to-be-diagnosed data is classified and compressed through the remote diagnosis platform to obtain a plurality of data blocks; the plurality of data blocks are sent to a diagnosis box through a plurality of transmission channels, wherein the transmission channel corresponds to the data block one by one; the plurality of data blocks are analyzed through the diagnosis box to obtain the to-be-diagnosed data; the target diagnosis function is determined based on the to-be-diagnosed data and the local data in the diagnosis box; and the target vehicle is diagnosed based on the target diagnosis function, so that the transmission time of data during remote diagnosis of the automobile is shortened, and the efficiency of remote diagnosis of the automobile is improved.

Description

Technical Field

[0001] This invention relates to the field of automotive diagnostics, and more particularly to a method, apparatus, electronic device, and storage medium for improving the efficiency of remote diagnostics. Background Technology

[0002] Currently, automotive diagnostic equipment plays a crucial role in vehicle diagnosis, maintenance, and performance optimization, helping to ensure vehicle reliability, safety, and efficiency.

[0003] As automotive electronic control systems become increasingly complex, the demand for diagnostic equipment is also growing. With the widespread adoption of internet and IoT technologies, more and more vehicles are being connected to the internet, leading to the development of remote diagnostics. Currently, however, a significant amount of time is spent on data transmission during remote automotive diagnostics. Summary of the Invention

[0004] The technical problem to be solved by the embodiments of the present invention is to provide a method, device, electronic device and storage medium for improving the efficiency of remote diagnosis, so as to shorten the data transmission time during remote diagnosis of automobiles and improve the efficiency of remote diagnosis of automobiles.

[0005] In a first aspect, embodiments of the present invention provide a method for improving remote diagnostic efficiency, including:

[0006] Receive remote diagnostic requests from the target object for the target vehicle;

[0007] In response to a remote diagnostic request, the system obtains diagnostic data for the target vehicle through a remote diagnostic platform. This diagnostic data is used to determine the diagnostic function.

[0008] The diagnostic data is categorized and compressed using a remote diagnostic platform to obtain multiple data blocks.

[0009] Multiple data blocks are sent to the diagnostic box through multiple transmission channels, with each transmission channel corresponding to a data block.

[0010] The diagnostic box parses multiple data blocks to obtain the data to be diagnosed;

[0011] The target diagnostic function is determined based on the data to be diagnosed and the local data in the diagnostic kit.

[0012] The target vehicle is diagnosed based on the target diagnostic function.

[0013] Secondly, embodiments of the present invention provide a remote diagnostic efficiency improvement device, comprising: a receiving unit and a processing unit;

[0014] The receiving unit is used to receive remote diagnostic requests from the target object for the target vehicle.

[0015] The processing unit is used to respond to remote diagnostic requests and obtain diagnostic data of the target vehicle through the remote diagnostic platform, wherein the diagnostic data is used to determine the diagnostic function.

[0016] The diagnostic data is categorized and compressed using a remote diagnostic platform to obtain multiple data blocks.

[0017] Multiple data blocks are sent to the diagnostic box through multiple transmission channels, with each transmission channel corresponding to a data block.

[0018] The diagnostic box parses multiple data blocks to obtain the data to be diagnosed;

[0019] The target diagnostic function is determined based on the data to be diagnosed and the local data in the diagnostic kit.

[0020] The target vehicle is diagnosed based on the target diagnostic function.

[0021] Thirdly, embodiments of the present invention provide an electronic device, including: a processor and a memory, the processor being connected to the memory, the memory being used to store a computer program, and the processor being used to execute the computer program stored in the memory, so that the electronic device performs the method as described in the first aspect.

[0022] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that causes a computer to perform the method as described in the first aspect.

[0023] Fifthly, embodiments of the present invention provide a computer program product including a non-transitory computer-readable storage medium storing a computer program, which is operable to cause the computer to perform the method as described in the first aspect.

[0024] Implementing the embodiments of the present invention has the following beneficial effects:

[0025] The system receives remote diagnostic requests from the target vehicle, responds to the requests, acquires the vehicle's diagnostic data through the remote diagnostic platform, classifies and compresses this data into multiple data blocks, and then sends these blocks to the diagnostic box via multiple transmission channels. The diagnostic box then parses these data blocks to obtain the diagnostic data, determines the target diagnostic function based on the diagnostic data and local data in the diagnostic box, and finally performs diagnostic operations on the target vehicle based on the target diagnostic function. This process shortens data transmission time and improves the efficiency of remote vehicle diagnostics. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the accompanying drawings used in the embodiments of the present invention or the background art will be described below.

[0027] Figure 1 This is a schematic diagram of a remote diagnostic efficiency improvement system provided by an embodiment of the present invention;

[0028] Figure 2 This is a flowchart of a method for improving remote diagnostic efficiency provided by an embodiment of the present invention;

[0029] Figure 3 This is a schematic diagram of a diagnostic function provided by an embodiment of the present invention;

[0030] Figure 4 This is a schematic diagram of a remote diagnostic efficiency improvement device provided by an embodiment of the present invention;

[0031] Figure 5 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. Detailed Implementation

[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0033] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and drawings of this application are used to distinguish different objects, not to describe a specific order. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion. For example, a process, method, system, product, or apparatus that includes a series of steps or units is not limited to the listed steps or units, but may optionally include steps or units not listed, or may optionally include other steps or units inherent to these processes, methods, products, or apparatuses.

[0034] In this document, the term "implementation" means that a specific feature, result, or characteristic described in connection with an implementation may be included in at least one implementation of this application. The appearance of this phrase in various places in the specification does not necessarily refer to the same implementation, nor is it a separate or alternative implementation mutually exclusive with other implementations. It will be explicitly and implicitly understood by those skilled in the art that the implementations described herein can be combined with other implementations.

[0035] See Figure 1, Figure 1 This is a schematic diagram of a remote diagnostic efficiency improvement system provided by an embodiment of the present invention. The remote diagnostic efficiency improvement system 10 includes a remote diagnostic platform 101, a diagnostic box 102, and a target vehicle 103.

[0036] In this embodiment, based on Figure 1 The remote diagnostic efficiency improvement system 10 shown in the diagram, when a target object sends a remote diagnostic request to a target vehicle 103, the remote diagnostic platform 101 responds to the request, obtains the data to be diagnosed from the target vehicle 103 for determining the diagnostic function, then classifies and compresses the data to be diagnosed into multiple data blocks, and sends these data blocks to the diagnostic box 102 through multiple transmission channels, with each transmission channel corresponding to one data block. The diagnostic box 102 parses the multiple data blocks to obtain the data to be diagnosed, then determines the target diagnostic function based on the data to be diagnosed and the local data in the diagnostic box 102, and finally performs diagnostic operations on the target vehicle 103 based on the target diagnostic function. This reduces the data transmission time during remote vehicle diagnostics and improves the efficiency of remote vehicle diagnostics.

[0037] See Figure 2 , Figure 2 This is a flowchart of a method for improving remote diagnostic efficiency provided by an embodiment of the present invention. The method includes, but is not limited to, the following steps:

[0038] 201: Receive remote diagnostic requests from the target object for the target vehicle.

[0039] When a vehicle experiences a malfunction or requires diagnostic checks, the target user initiates a diagnostic request through an application, website, or other interface provided by the remote diagnostic platform. To ensure security and accuracy, the remote diagnostic platform typically requires the target user to authenticate themselves, which can be done through username and password login, fingerprint recognition, or other methods. Once the target user is authenticated, the diagnostic request is transmitted to the remote diagnostic platform.

[0040] The target object can include any of the following: target vehicle, repair personnel, vehicle owner, etc. There are no restrictions here. When the target object is the target vehicle, a remote diagnostic request can be triggered actively. When the target object is the repair personnel or vehicle owner, a remote diagnostic request can be triggered passively.

[0041] As can be seen, by receiving diagnostic requests from the target object for the target vehicle, the remote diagnostic platform can ensure accurate detection and diagnosis of vehicle faults, improve repair quality, quickly locate problems, reduce repair time and costs, obtain diagnostic information from various vehicle systems, provide comprehensive fault analysis, follow unified standards and protocols, facilitate diagnosis of vehicles of different brands and models, receive vehicle diagnostic requests in real time, handle faults promptly, enable repair personnel to conveniently perform vehicle diagnostics, and help repair personnel improve their fault diagnosis and repair capabilities.

[0042] It should be noted that before receiving a remote diagnostic request from the target object for the target vehicle, it is also necessary to obtain the diagnostic interface of the target vehicle. The diagnostic interface corresponds to the communication protocol parameters. Common diagnostic interfaces include the On-Board Diagnostic (OBD) interface, the Unified Diagnostic Services (UDS) interface, etc. The communication protocol parameters related to the diagnostic interface may include at least one of the following: protocol type, baud rate, data bits, stop bits, parity bits, protocol security parameters, etc. Different diagnostic interfaces use different communication protocols and parameters. For example, a remote diagnostic software corresponding to the communication protocol parameters is determined. This remote diagnostic software is used to establish a wireless communication connection with the remote diagnostic platform. Using the remote diagnostic software corresponding to the communication protocol parameters can accurately obtain real-time vehicle data, including engine performance, emissions data, and vehicle health status, which helps to identify problems in a timely manner. Selecting the appropriate remote diagnostic software can ensure accurate diagnosis of vehicle problems, avoid unnecessary guesswork and trial and error, and allow users to access vehicle diagnostic information from a remote location without having to go to the vehicle's location. This is very useful for situations where diagnosis and monitoring are required when the vehicle is not nearby. It provides real-time vehicle diagnostic data and performance indicators, allowing users to monitor the vehicle's status and health at any time, which helps to identify potential problems in a timely manner and take necessary measures to solve them. Through the intuitive user interface and simple operation process of the remote diagnostic software, users can easily perform remote diagnosis and operation.

[0043] 202: Respond to a remote diagnostic request and obtain the diagnostic data of the target vehicle through the remote diagnostic platform.

[0044] In this embodiment, the data to be diagnosed is used to determine the diagnostic function. Once the target vehicle has been authenticated, the diagnostic request is transmitted to the remote diagnostic platform. After successful authentication, the remote diagnostic platform attempts to establish a remote connection with the target vehicle. This may be achieved through the vehicle's onboard communication module, such as a 4G or 5G connection, or through the vehicle's own Wi-Fi connection. After the remote diagnostic platform establishes a remote connection with the target vehicle, it acquires the data to be diagnosed from the target vehicle to determine the diagnostic function.

[0045] As can be seen, the remote diagnostic platform can monitor the status and performance of the target vehicle in real time and identify potential problems or faults in a timely manner. This helps to discover and solve problems in advance and avoid situations that may lead to more serious damage or accidents.

[0046] 203: The diagnostic data is classified and compressed through a remote diagnostic platform to obtain multiple data blocks.

[0047] In this embodiment, for example, the diagnostic data is classified through a remote diagnostic platform to obtain multiple categories of diagnostic data, each corresponding to a system. Specifically, vehicles typically include engine systems, transmission systems, braking systems, suspension systems, steering systems, electrical systems, lighting systems, safety systems, auxiliary systems, emission control systems, etc. Based on the system categories of the target vehicle, the diagnostic data is classified through the remote diagnostic platform, with each category corresponding to a system, resulting in multiple categories of diagnostic data. It can be seen that systematic data classification helps to better manage and analyze large amounts of vehicle data. By associating data with specific systems, data can be more easily organized, stored, and retrieved, improving data utilization and value.

[0048] For example, each category of data to be diagnosed is compressed into multiple data blocks. Specifically, each category of data is first preprocessed, including data cleaning, noise removal, and normalization, to ensure data quality and consistency. Then, for different types of data, appropriate compression algorithms and formats are selected. Common compression algorithms include Zone Information Protocol (ZIP) and Lempel-Ziv-Markov chain algorithm (LZMA), while common compression formats include ZIP and Roshal Archive (RAR). The compression method and format can be chosen based on the actual situation and are not limited here. Based on the selected appropriate compression algorithm and format, the data is compressed into multiple data blocks. During the compression process, the compression ratio needs to be controlled to balance the size of the compressed data and the decompression speed. The compression parameters are adjusted according to the characteristics of the data and application requirements to achieve the best compression effect. As can be seen, compressed data blocks are typically smaller than the original data, saving storage space. This is crucial for large-scale data storage, reducing storage costs, and improving data management efficiency. Compressed data blocks require less bandwidth and time during transmission, which is highly beneficial for applications such as network transmission, remote data transmission, and cloud storage, improving data transmission efficiency and user experience. Because compressed data blocks require less bandwidth and transmission time, data transmission costs are reduced. Compressed data blocks also enhance data security; compressing diagnostic data into multiple blocks allows for more effective data management and maintenance. Smaller data blocks also reduce the error rate during transmission. Even if transmission errors occur, only a portion of the data blocks will be affected, not the entire dataset, thus improving data transmission reliability.

[0049] 204: Send multiple data blocks to the diagnostic box through multiple transmission channels.

[0050] In this embodiment, a transmission channel is configured for each of the multiple data blocks, resulting in multiple transmission channels. Specifically, each data block is assigned its own transmission channel, enabling parallel transmission of data blocks. This improves data transmission speed and efficiency, reduces transmission time, and is particularly beneficial for large amounts of data or real-time transmission. Ensuring each data block has an independent transmission channel allows for individual management and adjustment of transmission parameters for each channel. If a transmission channel fails or is interrupted, only the corresponding data block's transmission will be affected, without impacting other data blocks. This reduces the overall system's impact of failures and improves system stability and reliability. It should be noted that each transmission channel corresponds to a specific transmission protocol, which is related to the data block's attribute information.

[0051] For example, multiple data blocks are sent to the diagnostic box via multiple transmission channels. Specifically, multiple network interface cards (NICs) are first installed on the diagnostic box. These NICs are interfaces connecting the diagnostic box to the wireless network, used for sending multiple data blocks to the diagnostic box via multiple transmission channels. A transmission channel refers to a wireless channel used to transmit data between devices. These channels transmit data via wireless media, such as air. The NICs receive and send data through the transmission channels, thereby enabling communication between the diagnostic box and the remote diagnostic platform. Transmission channels and NICs are two important components for wireless communication; they work together to achieve data transmission and communication between devices. It can be seen that by utilizing multiple transmission channels, it is possible to better adapt to network environments and conditions, enabling fast and stable data transmission.

[0052] It should be noted that multiple transmission channels include n transmission channels. Before sending multiple data blocks to the diagnostic box through these channels, it is necessary to determine m transmission channels between the remote diagnostic platform and the diagnostic box, where m is an integer greater than 1. Then, the attribute information of each of the m transmission channels is obtained, resulting in m attribute information. Attribute information may include at least one of the following: bandwidth, latency, signal-to-noise ratio, packet loss rate, etc., which are not limited here. Next, channel evaluation is performed on each of the m transmission channels based on the m attribute information, resulting in m channel evaluation values. A target channel evaluation value greater than a preset threshold is selected from the m channel evaluation values. The preset threshold can be set according to system requirements to ensure fast and accurate data transmission. Then, the transmission channels corresponding to the target channel evaluation values ​​are obtained, resulting in n transmission channels, where n is an integer less than or equal to m and greater than 1. These channels are considered high-quality channels and can be used to send data to the diagnostic box, ensuring that transmission channels with good channel quality are selected before sending data to the diagnostic box, thereby improving the stability and reliability of data transmission.

[0053] 205: The diagnostic box is used to parse multiple data blocks to obtain the data to be diagnosed.

[0054] In this embodiment, the acquired data blocks are decompressed using a diagnostic box. Depending on the type of compression algorithm, appropriate decompression tools or libraries can be used to restore the data. After decompression, the decompressed data blocks are combined together, and multiple data blocks are correctly combined according to their order in the original data to obtain the data to be diagnosed. Parsing the data blocks can extract diagnostic information, which helps in subsequent operations based on the data to be diagnosed.

[0055] 206: Determine the target diagnostic function based on the data to be diagnosed and the local data in the diagnostic kit.

[0056] In this embodiment, for example, a first diagnostic function is determined based on the data source of the data to be diagnosed, and a second diagnostic function is determined based on the data source of the local data in the diagnostic box. Specifically, the diagnostic function can help identify faults and problems in the vehicle system, including various aspects such as the engine system, transmission system, and braking system. The diagnostic function can help identify potential problems and fault risks, take preventative maintenance measures, prevent faults from occurring in advance, extend the vehicle's service life, and reduce maintenance costs. The diagnostic function can monitor and evaluate the performance of the vehicle system, including fuel efficiency, acceleration performance, and braking performance. By analyzing data and providing corresponding optimization suggestions, it can help car owners optimize vehicle performance, improve driving experience, and fuel economy. The diagnostic function can help detect and prevent safety hazards in the vehicle system, including braking system faults, tire abnormalities, and vehicle stability issues. Timely detection and resolution of these problems can improve driving safety and reduce the likelihood of accidents. Some diagnostic functions can also realize remote monitoring and management of the vehicle system, including remote diagnostics, remote control, and remote locking functions. This allows car owners to easily understand the vehicle status at any time, take timely measures to deal with emergencies, and improve vehicle safety and management convenience. (See also...) Figure 3 , Figure 3 This is a schematic diagram of a diagnostic function provided by an embodiment of the present invention. The diagnostic function 30 includes fault code scanning and diagnosis, engine diagnosis, transmission system diagnosis, braking system diagnosis, suspension system diagnosis, tire pressure monitoring, emission system diagnosis, safety system diagnosis, electrical system diagnosis, body diagnosis, etc.

[0057] First, determine which systems in the target vehicle the data source of the data to be diagnosed belongs to, and which systems in the target vehicle the data source of the local data in the diagnostic box belongs to. Then, based on the determined systems, determine the first diagnostic function corresponding to the data source of the data to be diagnosed, and the second diagnostic function corresponding to the data source of the local data in the diagnostic box. Finally, determine the target diagnostic function based on the first and second diagnostic functions.

[0058] It should be noted that before determining the target diagnostic function based on the data to be diagnosed and the local data in the diagnostic box, it is also necessary to obtain historical diagnostic data through the diagnostic box, classify the historical diagnostic data to obtain multiple types of diagnostic data, each type of diagnostic data corresponds to a diagnostic function, the same as the classification method of the data to be diagnosed, each type of data to be diagnosed corresponds to a system and also corresponds to a diagnostic function. Then, based on multiple types of diagnostic data, the diagnostic frequency of each diagnostic function is determined, resulting in multiple diagnostic frequencies. From these multiple diagnostic frequencies, a diagnostic frequency greater than a first threshold is selected, resulting in at least one diagnostic frequency. The diagnostic function corresponding to at least one diagnostic frequency is set as a frequently used diagnostic function, and the diagnostic data corresponding to the frequently used diagnostic function is saved locally in the diagnostic box, resulting in local data. Specifically, for each diagnostic function, its diagnostic frequency is determined based on the frequency of occurrence of historical diagnostic data. From all diagnostic frequencies, diagnostic functions with a diagnostic frequency greater than a first threshold are selected. The first threshold can be set according to specific circumstances. The diagnostic functions corresponding to these diagnostic frequencies with frequencies higher than the threshold are marked as frequently used diagnostic functions. Frequently used diagnostic functions are usually functions that occur frequently in the system and have a significant impact on the vehicle's operating status. The diagnostic data corresponding to these frequently used diagnostic functions is saved in the local storage of the diagnostic box as local data. This ensures that every vehicle will execute these frequently used diagnostic functions, enabling diagnosis and inspection even without specific faults, thus reducing the probability of danger. It should be noted that a timed task or trigger can also be set in the diagnostic box of each vehicle to ensure that common diagnostic functions are executed automatically at certain time intervals. This ensures that these functions are performed regularly for each vehicle, and that diagnosis and inspection can be carried out even when there is no specific fault. Diagnostic data in local storage can also be managed and cleaned regularly to ensure sufficient storage space and to delete outdated or no longer needed data. If any abnormalities are found when performing common diagnostic functions, such as diagnostic failure or abnormal diagnostic data, they should be recorded in time and appropriate measures should be taken to handle them to ensure the accuracy and reliability of the diagnosis.

[0059] 207: Perform diagnostic operations on the target vehicle based on the target diagnostic function.

[0060] In this embodiment, based on the target diagnostic function, corresponding diagnostic operations are performed on the target vehicle. These operations include checking sensor data, executing self-test procedures, and analyzing fault codes. The data obtained after performing the diagnostic function is then analyzed, including comparing actual data with expected results, identifying any anomalies or malfunctions, and determining possible causes. Based on the data analysis results, a diagnostic report or outcome is generated, including identifying the problems found and providing relevant suggestions or repair solutions. The diagnostic results are then fed back to the target vehicle, and as needed, the identified problems are repaired, vehicle settings are adjusted, or further inspections and maintenance are scheduled. Finally, the performed diagnostic operations, analysis results, and measures taken are recorded, thus establishing a diagnostic history for the vehicle and providing a reference for future maintenance and analysis.

[0061] In summary, the system receives and responds to remote diagnostic requests from the target vehicle, acquires the vehicle's diagnostic data through a remote diagnostic platform, categorizes and compresses this data into multiple data blocks, sends these blocks to the diagnostic box via multiple transmission channels, parses the data blocks to obtain the diagnostic data, determines the target diagnostic function based on the diagnostic data and local data in the diagnostic box, and finally performs diagnostic operations on the target vehicle based on the target diagnostic function. This process shortens data transmission time and improves the efficiency of remote vehicle diagnostics.

[0062] See Figure 4 , Figure 4 This is a schematic diagram of a remote diagnostic efficiency improvement device provided by an embodiment of the present invention. Figure 4 As shown, the remote diagnostic efficiency improvement device 400 includes a receiving unit 401 and a processing unit 402.

[0063] The receiving unit 401 is used to receive a remote diagnostic request from the target object for the target vehicle.

[0064] The processing unit 402 is used to respond to remote diagnostic requests and obtain diagnostic data of the target vehicle through the remote diagnostic platform, wherein the diagnostic data is used to determine the diagnostic function.

[0065] The diagnostic data is categorized and compressed using a remote diagnostic platform to obtain multiple data blocks.

[0066] Multiple data blocks are sent to the diagnostic box through multiple transmission channels, with each transmission channel corresponding to a data block.

[0067] The diagnostic box parses multiple data blocks to obtain the data to be diagnosed;

[0068] The target diagnostic function is determined based on the data to be diagnosed and the local data in the diagnostic kit.

[0069] The target vehicle is diagnosed based on the target diagnostic function.

[0070] In some possible implementations, in determining the target diagnostic function based on the data to be diagnosed and local data in the diagnostic kit, the processing unit 402 is specifically configured to:

[0071] The first diagnostic function is determined based on the data source of the data to be diagnosed, and the second diagnostic function is determined based on the data source of the local data in the diagnostic box.

[0072] The target diagnostic function is determined based on the first and second diagnostic functions.

[0073] In some possible implementations, the processing unit 402 is further specifically used for:

[0074] Historical diagnostic data can be obtained through the diagnostic kit;

[0075] Historical diagnostic data is classified into multiple categories, with each category corresponding to a diagnostic function.

[0076] The diagnostic frequency of each diagnostic function is determined based on multiple types of diagnostic data, resulting in multiple diagnostic frequencies.

[0077] Select diagnostic frequencies that are greater than a first threshold from multiple diagnostic frequencies to obtain at least one diagnostic frequency, and set the diagnostic function corresponding to at least one diagnostic frequency as a commonly used diagnostic function.

[0078] The diagnostic data corresponding to commonly used diagnostic functions is saved locally on the diagnostic box to obtain local data.

[0079] In some possible implementations, in classifying and compressing the diagnostic data to be diagnosed through a remote diagnostic platform to obtain multiple data blocks, the processing unit 402 is specifically used for:

[0080] The data to be diagnosed is classified through a remote diagnostic platform to obtain multiple categories of data to be diagnosed, with each category corresponding to a system.

[0081] Each type of data to be diagnosed is compressed to obtain multiple data blocks.

[0082] In some possible implementations, in sending multiple data blocks to the diagnostic box via multiple transmission channels, the processing unit 402 is specifically configured to:

[0083] Configure a transmission channel for each of the multiple data blocks to obtain multiple transmission channels. Each transmission channel corresponds to a transmission protocol, and the transmission protocol is related to the attribute information of the data block.

[0084] Multiple data blocks are sent to the diagnostic box via multiple transmission channels.

[0085] In some possible implementations, where multiple transmission channels include n transmission channels, before sending multiple data blocks to the diagnostic box through the multiple transmission channels, the processing unit 402 is specifically used for:

[0086] Determine m transmission channels between the remote diagnostic platform and the diagnostic box, where m is an integer greater than 1;

[0087] Obtain the attribute information of each of the m transmission channels to get m attribute information;

[0088] Based on m attribute information, channel evaluation is performed on each of the m transmission channels to obtain m channel evaluation values;

[0089] Select the target channel evaluation value that is greater than a preset threshold from m channel evaluation values, and obtain the transmission channel corresponding to the target channel evaluation value to obtain n transmission channels, where n is an integer less than or equal to m and greater than 1.

[0090] In some possible implementations, before receiving a remote diagnostic request from the target object for the target vehicle, the processing unit 402 is specifically configured to:

[0091] Obtain the diagnostic interface of the target vehicle, where the diagnostic interface corresponds to the communication protocol parameters;

[0092] Determine the remote diagnostic software corresponding to the communication protocol parameters, wherein the remote diagnostic software is used to establish a wireless communication connection with the remote diagnostic platform.

[0093] See Figure 5 , Figure 5 This is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. For example... Figure 5 As shown, the electronic device 500 includes a transceiver 501, a processor 502, and a memory 503. These are connected via a bus 504. The memory 503 stores computer programs and data, and can transmit data stored in the memory 503 to the processor 502. This electronic device can be the diagnostic device described above, and the processor 502 can be the processing unit 402 described above.

[0094] Processor 502 is used to read the computer program in memory 503 and perform the following operations:

[0095] Receive remote diagnostic requests from the target object for the target vehicle;

[0096] In response to a remote diagnostic request, the system obtains diagnostic data for the target vehicle through a remote diagnostic platform. This diagnostic data is used to determine the diagnostic function.

[0097] The diagnostic data is categorized and compressed using a remote diagnostic platform to obtain multiple data blocks.

[0098] Multiple data blocks are sent to the diagnostic box through multiple transmission channels, with each transmission channel corresponding to a data block.

[0099] The diagnostic box parses multiple data blocks to obtain the data to be diagnosed;

[0100] The target diagnostic function is determined based on the data to be diagnosed and the local data in the diagnostic kit.

[0101] The target vehicle is diagnosed based on the target diagnostic function.

[0102] In some possible implementations, in determining the target diagnostic function based on the data to be diagnosed and local data in the diagnostic kit, the processor 502 is specifically configured to:

[0103] The first diagnostic function is determined based on the data source of the data to be diagnosed, and the second diagnostic function is determined based on the data source of the local data in the diagnostic box.

[0104] The target diagnostic function is determined based on the first and second diagnostic functions.

[0105] In some possible implementations, processor 502 is also specifically used for:

[0106] Historical diagnostic data can be obtained through the diagnostic kit;

[0107] Historical diagnostic data is classified into multiple categories, with each category corresponding to a diagnostic function.

[0108] The diagnostic frequency of each diagnostic function is determined based on multiple types of diagnostic data, resulting in multiple diagnostic frequencies.

[0109] Select diagnostic frequencies that are greater than a first threshold from multiple diagnostic frequencies to obtain at least one diagnostic frequency, and set the diagnostic function corresponding to at least one diagnostic frequency as a commonly used diagnostic function.

[0110] The diagnostic data corresponding to commonly used diagnostic functions is saved locally on the diagnostic box to obtain local data.

[0111] In some possible implementations, in classifying and compressing the diagnostic data to be diagnosed via a remote diagnostic platform to obtain multiple data blocks, the processor 502 is specifically used for:

[0112] The data to be diagnosed is classified through a remote diagnostic platform to obtain multiple categories of data to be diagnosed, with each category corresponding to a system.

[0113] Each type of data to be diagnosed is compressed to obtain multiple data blocks.

[0114] In some possible implementations, in sending multiple data blocks to the diagnostic box via multiple transmission channels, processor 502 is specifically used for:

[0115] Configure a transmission channel for each of the multiple data blocks to obtain multiple transmission channels. Each transmission channel corresponds to a transmission protocol, and the transmission protocol is related to the attribute information of the data block.

[0116] Multiple data blocks are sent to the diagnostic box via multiple transmission channels.

[0117] In some possible implementations, where multiple transmission channels include n transmission channels, before sending multiple data blocks to the diagnostic box via the multiple transmission channels, the processor 502 is specifically used for:

[0118] Determine m transmission channels between the remote diagnostic platform and the diagnostic box, where m is an integer greater than 1;

[0119] Obtain the attribute information of each of the m transmission channels to get m attribute information;

[0120] Based on m attribute information, channel evaluation is performed on each of the m transmission channels to obtain m channel evaluation values;

[0121] Select the target channel evaluation value that is greater than a preset threshold from m channel evaluation values, and obtain the transmission channel corresponding to the target channel evaluation value to obtain n transmission channels, where n is an integer less than or equal to m and greater than 1.

[0122] In some possible implementations, before receiving a remote diagnostic request from the target object for the target vehicle, processor 502 is specifically configured to:

[0123] Obtain the diagnostic interface of the target vehicle, where the diagnostic interface corresponds to the communication protocol parameters;

[0124] Determine the remote diagnostic software corresponding to the communication protocol parameters, wherein the remote diagnostic software is used to establish a wireless communication connection with the remote diagnostic platform.

[0125] It should be understood that the electronic devices mentioned in this application may include smartphones (such as Android phones, iOS phones, Windows Phones, etc.), tablet computers, PDAs, laptops, mobile internet devices (MIDs) or wearable devices, servers, edge computing nodes, etc. The above-mentioned electronic devices are merely examples and not exhaustive, and include, but are not limited to, the electronic devices mentioned above. In practical applications, the above-mentioned electronic devices may also include: intelligent vehicle terminals, computer equipment, etc.

[0126] This application also provides a computer-readable storage medium storing a computer program that is executed by a processor to implement some or all of the steps of any of the remote diagnostic efficiency improvement methods described in the above method embodiments.

[0127] This application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program operable to cause a computer to perform some or all of the steps of any of the remote diagnostic efficiency improvement methods described in the above method embodiments.

[0128] It should be noted that, for the sake of simplicity, the aforementioned methods are described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are optional, and the actions and modules involved are not necessarily essential to this application.

[0129] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0130] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical or other forms.

[0131] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0132] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software program module.

[0133] If the integrated unit is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0134] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing related hardware. The program can be stored in a computer-readable storage device, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0135] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The above description of the embodiments is only for the purpose of helping to understand the method and core ideas of this application. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for improving efficiency of remote diagnosis, characterized by, The method comprises: receiving a remote diagnosis request of a target object for a target vehicle; obtaining, in response to the remote diagnosis request, to-be-diagnosed data of the target vehicle through a remote diagnosis platform, wherein the to-be-diagnosed data is used to determine a diagnosis function; classifying and compressing the to-be-diagnosed data through the remote diagnosis platform to obtain a plurality of data blocks; sending the plurality of data blocks to a diagnosis box through a plurality of transmission channels, wherein the transmission channels correspond to the data blocks one by one; analyzing the plurality of data blocks through the diagnosis box to obtain the to-be-diagnosed data; determining a target diagnosis function based on the to-be-diagnosed data and local data in the diagnosis box; performing a diagnosis operation on the target vehicle based on the target diagnosis function; wherein the plurality of transmission channels comprises n transmission channels, and before the plurality of data blocks are sent to the diagnosis box through the plurality of transmission channels, the method further comprises: determining m transmission channels between the remote diagnosis platform and the diagnosis box, wherein m is an integer greater than 1; obtaining attribute information of each transmission channel in the m transmission channels to obtain m attribute information; evaluating each transmission channel in the m transmission channels according to the m attribute information to obtain m channel evaluation values; selecting a target channel evaluation value greater than a preset threshold value from the m channel evaluation values, and obtaining a transmission channel corresponding to the target channel evaluation value to obtain the n transmission channels, wherein n is an integer less than or equal to m and greater than 1.

2. The method of claim 1, wherein, The method further comprises: determining a first diagnosis function based on the data source of the to-be-diagnosed data, and determining a second diagnosis function based on the data source of the local data in the diagnosis box; determining the target diagnosis function based on the first diagnosis function and the second diagnosis function.

3. The method of claim 2, wherein, The method further comprises: obtaining historical diagnosis data through the diagnosis box; classifying the historical diagnosis data to obtain a plurality of types of diagnosis data, wherein each type of diagnosis data corresponds to a diagnosis function; determining a diagnosis frequency of each diagnosis function according to the plurality of types of diagnosis data to obtain a plurality of diagnosis frequencies; selecting a diagnosis frequency greater than a first threshold value from the plurality of diagnosis frequencies to obtain at least one diagnosis frequency, and setting a diagnosis function corresponding to the at least one diagnosis frequency as a commonly used diagnosis function; saving diagnosis data corresponding to the commonly used diagnosis function to the local of the diagnosis box to obtain the local data.

4. The method according to any one of claims 1 to 3, characterized in that, The method further comprises: classifying the to-be-diagnosed data through the remote diagnosis platform to obtain a plurality of types of to-be-diagnosed data, wherein each type of to-be-diagnosed data corresponds to a system; compressing each type of to-be-diagnosed data in the plurality of types of to-be-diagnosed data to obtain the plurality of data blocks.

5. The method according to any one of claims 1 to 3, characterized in that, The method further comprises: configuring one transmission channel for each data block in the plurality of data blocks to obtain the plurality of transmission channels, wherein each transmission channel corresponds to one transmission protocol, and the transmission protocol is related to attribute information of the data block; sending the plurality of data blocks to the diagnostic box through the plurality of transmission channels.

6. The method according to any one of claims 1 to 3, characterized in that, Before receiving the remote diagnosis request of the target object for the target vehicle, the method further comprises: obtaining a diagnostic interface of the target vehicle, wherein the diagnostic interface corresponds to a communication protocol parameter; determining a remote diagnosis software corresponding to the communication protocol parameter, wherein the remote diagnosis software is used to establish a wireless communication connection with the remote diagnosis platform.

7. A device for improving efficiency of remote diagnosis, characterized by comprising: The device comprises a receiving unit and a processing unit. The receiving unit is configured to receive a remote diagnosis request of a target object for a target vehicle. The processing unit is configured to obtain to-be-diagnosed data of the target vehicle through a remote diagnosis platform in response to the remote diagnosis request, wherein the to-be-diagnosed data is used to determine a diagnostic function. The to-be-diagnosed data is classified and compressed through the remote diagnosis platform to obtain a plurality of data blocks. The plurality of data blocks are sent to a diagnostic box through a plurality of transmission channels, wherein the transmission channels correspond to the data blocks one by one. The plurality of data blocks are analyzed through the diagnostic box to obtain the to-be-diagnosed data. A target diagnostic function is determined based on the to-be-diagnosed data and local data in the diagnostic box. The target vehicle is diagnosed based on the target diagnostic function. The plurality of transmission channels comprise n transmission channels, and before the plurality of data blocks are sent to the diagnostic box through the plurality of transmission channels, the method further comprises: determining m transmission channels between the remote diagnosis platform and the diagnostic box, wherein m is an integer greater than 1; obtaining attribute information of each transmission channel in the m transmission channels to obtain m attribute information; channel evaluating each transmission channel in the m transmission channels according to the m attribute information to obtain m channel evaluation values; selecting a target channel evaluation value greater than a preset threshold value in the m channel evaluation values, and obtaining a transmission channel corresponding to the target channel evaluation value to obtain the n transmission channels, wherein n is an integer less than or equal to m and greater than 1.

8. An electronic device, comprising: The device comprises a processor, a memory, a communication interface, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the processor, and the one or more programs comprise instructions for executing steps in the method of any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method of any one of claims 1-6.

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