Connection method, device and equipment of remote diagnosis order and storage medium

Abstract

Embodiments of the present application disclose a connection method, device and equipment for remote diagnosis order and a storage medium. The method is applied to a diagnosis device, the diagnosis device comprises a first diagnosis module and a second diagnosis module, and the first diagnosis module is connected with a target vehicle through a target joint. The method comprises the following steps: obtaining a vehicle identification code of the target vehicle through the first diagnosis module after the target joint is powered on; obtaining the number of order tasks based on the vehicle identification code; determining a target order task based on the number of order tasks; setting the connection state of the target order task as a first connection state, the first connection state being used for making the target order task in a selectable state; displaying the target order task to the second diagnosis module based on the first connection state; obtaining a target touch parameter of the second diagnosis module, the target touch parameter being used for selecting the target order task; and establishing a connection between the first diagnosis module and the second diagnosis module based on the target touch parameter, so as to execute the target order task.

Description

Technical Field

[0001] This invention relates to the field of vehicle maintenance technology, and more particularly to a method, apparatus, equipment, and storage medium for connecting remote diagnostic orders. Background Technology

[0002] In the past, diagnosing and repairing vehicle malfunctions primarily relied on car owners taking their vehicles to repair shops, where technicians would determine the problem through on-site inspection and the use of specialized equipment. However, with the continuous development of automotive technology, traditional diagnostic methods face numerous challenges. For some car owners, taking their vehicles to professional repair shops can be time-consuming and costly. Moreover, in certain emergency situations, such as a sudden breakdown while driving, traditional repair methods may not be able to provide timely assistance.

[0003] With the rapid development of communication technology and the Internet, remote vehicle diagnostics technology has emerged. Vehicle operating data can be transmitted to a remote server in real time, allowing professional technicians to diagnose, analyze, and repair vehicles remotely. Traditional remote diagnostics methods involve a repair technician accepting a repair order and automatically establishing a connection with the user's vehicle to complete the order. However, when a user publishes multiple repair orders, there's a possibility that a connection might be established with an order that isn't currently desired. In such cases, the order must be suspended after the connection is established, waiting for the next connection until the desired order is reached. This can lead to multiple invalid connections during remote repair diagnostics, thus reducing the efficiency of order execution.

[0004] Therefore, there is an urgent need for a connection method for remote diagnostic orders that reduces the number of invalid connections during remote maintenance and diagnostics, in order to improve the efficiency of remote diagnostic order completion. Summary of the Invention

[0005] To address the aforementioned issues, embodiments of the present invention provide a method, apparatus, device, and storage medium for connecting remote diagnostic orders, which can reduce the number of invalid connections during remote maintenance and diagnostic processes, thereby improving the efficiency of completing remote diagnostic orders.

[0006] In a first aspect, embodiments of the present invention provide a method for connecting a remote diagnostic order, the method being applied to a diagnostic device, the diagnostic device including a first diagnostic module and a second diagnostic module, the first diagnostic module being connected to a target vehicle via a target connector; the method includes:

[0007] After the target connector is powered on, the vehicle identification code of the target vehicle is obtained through the first diagnostic module;

[0008] The number of order tasks is obtained based on the vehicle identification code;

[0009] The target order tasks are determined based on the number of order tasks mentioned above;

[0010] Set the connection status of the target order task to a first connection status, which is used to make the target order task selectable.

[0011] Based on the first connection status, the target order task is displayed to the second diagnostic module;

[0012] Obtain the target touch parameters of the second diagnostic module, the target touch parameters being used to select the target order task;

[0013] A connection is established between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task.

[0014] Secondly, embodiments of the present invention provide a connection device for remote diagnostic orders, which is applied to a diagnostic device. The diagnostic device includes a first diagnostic module and a second diagnostic module. The first diagnostic module is connected to a target vehicle via a target connector. The connection device for remote diagnostic orders includes an acquisition unit and a processing unit.

[0015] The acquisition unit is used to acquire vehicle information of the target vehicle through the first diagnostic module after the target connector is powered on. The vehicle information of the target vehicle includes the vehicle identification code of the target vehicle.

[0016] The number of order tasks is obtained based on the vehicle information of the target vehicle;

[0017] The processing unit is used to determine the target order task based on the number of order tasks;

[0018] Set the connection status of the target order task to a first connection status, which is used to make the target order task selectable.

[0019] Based on the first connection status, the target order task is displayed to the second diagnostic module;

[0020] Obtain the target touch parameters of the second diagnostic module, the target touch parameters being used to select the target order task;

[0021] A connection is established between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task.

[0022] Thirdly, embodiments of the present invention provide a diagnostic device, the diagnostic 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 diagnostic device performs the method as described in the first aspect.

[0023] Fourthly, embodiments of the present invention provide a computer-readable storage medium storing a computer program that is executed by a processor to implement the method described in the first aspect.

[0024] Fifthly, embodiments of this application provide a computer program product, the computer program product including a non-transitory computer-readable storage medium storing a computer program, the computer being operable to perform the method as described in the first aspect.

[0025] Implementing the embodiments of this application has the following beneficial effects:

[0026] In this embodiment, after powering on the target connector, the vehicle identification code (VIC) of the target vehicle is obtained through the first diagnostic module, and the number of order tasks is obtained based on the VIC. Then, the target order task is determined based on the number of order tasks, and the connection status of the target order task is set to a first connection status, which makes the target order task selectable. Next, the target order task is displayed to the second diagnostic module based on the first connection status, and the target touch parameters of the second diagnostic module are obtained. The target touch parameters are used to select the target order task. Finally, a connection is established between the first and second diagnostic modules based on the target touch parameters to execute the target order task. Therefore, by determining the target vehicle through the target connector, obtaining the number of order tasks by acquiring the VIC of the target vehicle, and setting the connection status of the target order task for the second diagnostic module to select, connect, and execute, the number of invalid connections during remote maintenance and diagnosis can be reduced, thereby improving the efficiency of completing remote diagnostic orders. Attached Figure Description

[0027] To more clearly illustrate the technical solutions in the embodiments of the present invention or the background art, the drawings used in the embodiments of the present invention or the background art will be described below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0028] Figure 1 This is a schematic diagram of the architecture of a remote diagnostic order connection system provided in an embodiment of this application;

[0029] Figure 2 This is a flowchart illustrating a remote diagnostic order connection method provided in an embodiment of this application;

[0030] Figure 3 This is one example of a timing diagram provided in the embodiments of this application;

[0031] Figure 4 This is a second example of a timing diagram provided in the embodiments of this application;

[0032] Figure 5 This is the third example of a timing diagram provided in the embodiments of this application;

[0033] Figure 6 This is a schematic diagram of the structure of a connection device for remote diagnostic orders provided in an embodiment of this application;

[0034] Figure 7 This is a schematic diagram of the structure of a diagnostic device provided in an embodiment of this application. Detailed Implementation

[0035] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. 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.

[0036] The terms "first," "second," "third," and "fourth," etc., used in the specification, claims, and accompanying 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 device that includes a series of steps or modules is not limited to the listed steps or modules, but may optionally include steps or modules not listed, or may optionally include other steps or modules inherent to these processes, methods, products, or devices.

[0037] In this document, the term "embodiment" means that a particular feature, result, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0038] See Figure 1 , Figure 1This is a schematic diagram of the architecture of a remote diagnostic order connection system provided in an embodiment of this application. Figure 1 As shown in the embodiment of this application, the remote diagnostic order connection method is applied to a remote diagnostic order connection system 10. The remote diagnostic order connection system 10 includes a diagnostic device and a target vehicle 13. The diagnostic device includes a first diagnostic module 11 and a second diagnostic module 12. The first diagnostic module 11 is connected to the target vehicle 13 via a target connector. The first diagnostic module 11 and the second diagnostic module 12 can be connected via one or more of the following methods: Bluetooth, Wi-Fi, Universal Serial Bus (USB), mobile network, Zigbee, etc., without limitation.

[0039] See Figure 2 , Figure 2 This is a flowchart illustrating a remote diagnostic order connection method provided in an embodiment of this application. For example... Figure 2 As shown, the method includes, but is not limited to, the following steps:

[0040] Step S101: After powering on the target connector, obtain the vehicle identification code of the target vehicle through the first diagnostic module;

[0041] Step S102: Obtain the number of order tasks based on the vehicle identification code;

[0042] Step S103: Determine the target order tasks based on the number of order tasks;

[0043] Step S104: Set the connection status of the target order task to the first connection status;

[0044] The first connection state is used to make the target order task selectable.

[0045] Step S105: Display the target order task to the second diagnostic module based on the first connection status;

[0046] Step S106: Obtain the target touch parameters of the second diagnostic module;

[0047] The target touch parameters are used to select the target order task;

[0048] Step S107: Establish a connection between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task.

[0049] In one possible embodiment, the first diagnostic module corresponds to the C-end (user) and the second diagnostic module corresponds to the B-end (user). The C-end user plugs the target connector into the target vehicle to facilitate subsequent operation of order tasks for the target vehicle. After the target connector is powered on, the first diagnostic module is activated and establishes a communication connection with the target vehicle's On-Board Diagnostic (OBD) system. The first diagnostic module obtains the Vehicle Identification Number (VIN) from the vehicle's electronic control unit using a preset diagnostic protocol and interface. It then sends a diagnostic request command to the target vehicle's OBD system. The target vehicle's OBD system responds to the diagnostic request command and returns a data packet containing the VIN. The first diagnostic module parses this data packet to obtain the accurate VIN. Based on the obtained VIN, a request is sent to the server to obtain the number of order tasks related to the target vehicle. The first diagnostic module encodes the VIN and sends it to the server via the network. The server searches its database for order task records matching the VIN and returns the number of order tasks. Based on the number of order tasks, the target order task is determined according to preset rules. For example, the most recently created, most urgent, or most relevant order tasks can be prioritized as target order tasks. If multiple order tasks exist, they are comprehensively evaluated and ranked based on their attributes, such as creation time, urgency level, and the degree of match between the fault description and the current vehicle symptoms. The task with the highest ranking is then determined as the target order task. The connection status of the target order task is set to the first connection state, making it selectable. Relevant information about the target order task in the first connection state, such as task description and preliminary vehicle fault information, is displayed on the interface of the second diagnostic module, allowing the second diagnostic module to obtain detailed data about the target order task. The second diagnostic module monitors the operations of the B-end user corresponding to the second diagnostic module in real time via a touchscreen or other input device, converting the operations into corresponding touch parameters. Target touch parameters generated by the B-end user's operations on the second diagnostic module are obtained, such as clicks, swipes, or specific gestures. These parameters are used to clarify whether the B-end user corresponding to the second diagnostic module has selected the target order task. When the target touch parameters are detected to match the selected target order task, a connection establishment command is triggered. This establishes a stable data connection between the first and second diagnostic modules, enabling real-time interaction and information sharing to execute the target order task. Upon receiving the connection establishment command, the first diagnostic module initiates a secure and encrypted communication protocol, performs a handshake and authentication with the second diagnostic module, and establishes a direct data channel between them, achieving high-speed data transmission and real-time synchronization.After the two modules are connected, the B-end user corresponding to the second diagnostic module can start executing the target order task, exchanging data and performing diagnostic operations through the touch screen or other input devices of the second diagnostic module.

[0050] In this embodiment, by automatically acquiring the vehicle identification code and determining the relevant order task, the time spent on manual searching and screening is reduced, allowing diagnostic work to focus more quickly on critical tasks and improving diagnostic efficiency. By determining the target order task according to preset rules, priority can be given to handling the tasks currently expected by C-end users or the most critical and urgent tasks, enabling more effective allocation of diagnostic resources, ensuring that important order tasks are handled in a timely manner, improving overall work efficiency and service quality, and enhancing the relevance and effectiveness of repairs. By displaying the target order task in the second diagnostic module and allowing B-end users to select it through simple and intuitive touch operations, the complexity of operation is reduced, and the convenience of work for both B-end and C-end users is improved. By establishing a stable connection between modules, the security and accuracy of data transmission are guaranteed, avoiding diagnostic errors caused by information loss or errors.

[0051] Optionally, step S103, determining the target order task based on the number of order tasks, may include the following steps:

[0052] Step S201: When there is only one order task, the current order task of the target vehicle is taken as the target order task;

[0053] Step S202: When there are multiple order tasks, obtain multiple order tasks for the target vehicle;

[0054] Step S203: Determine the execution coefficient of each order task in the multiple order tasks to obtain multiple execution coefficients;

[0055] The execution coefficient is used to indicate the execution priority;

[0056] Step S204: Select the order task with the highest execution coefficient among multiple order tasks as the target order task.

[0057] In one possible implementation, when there is only one order task, the unique order task information for the target vehicle is obtained, including task description, vehicle fault details, customer requirements, etc., and this unique order task is directly marked as the target order task without any other complex judgment and selection operations. When there are multiple order tasks, detailed information of all multiple order tasks for the target vehicle is obtained. The detailed information may include data such as the creation time, urgency rating, estimated repair time, and correlation with the current vehicle fault for each task. An execution coefficient is calculated based on the detailed information of each order task. For example, the earlier the creation time, the higher the execution coefficient; the higher the urgency, the higher the execution coefficient; the shorter the estimated repair time, the higher the execution coefficient; the greater the correlation with the current vehicle fault, the higher the execution coefficient, and so on. By setting appropriate weights and algorithms, the execution coefficient of each order task is obtained by combining these factors. The execution coefficients of all order tasks are compared, and the order task with the highest execution coefficient is selected as the target order task. In this embodiment, when there is only a single order task, the target order task is directly determined, saving selection and judgment time and quickly entering the processing flow. When there are multiple order tasks, by calculating and comparing execution coefficients, the most important and urgent tasks can be prioritized, avoiding resource waste on secondary tasks and thus improving the overall efficiency of maintenance and diagnosis. By determining the target order task based on the execution coefficient, resources such as technicians, tools, and time can be allocated more rationally, ensuring that resources are concentrated on the tasks that need to be prioritized. By prioritizing urgent and important order tasks, user problems can be resolved more quickly, reducing user waiting time.

[0058] Optionally, step S203, determining the execution coefficient of each order task among multiple order tasks to obtain multiple execution coefficients, may include the following steps:

[0059] Step S301: Obtain the first order task from multiple order tasks;

[0060] Step S302: Set the execution coefficient for the first order task;

[0061] Step S303: Determine the timing relationship between multiple order tasks;

[0062] Step S304: Based on the execution coefficient of the first order task and the temporal relationship of the multiple order tasks, determine the execution coefficient of each order task in the multiple order tasks, and obtain multiple execution coefficients.

[0063] In one possible embodiment, the first order task can be selected by the C-end user from multiple order tasks. The first order task is the order task that the C-end user currently expects to execute among the multiple order tasks. The execution coefficient of the first order task can be a preset reference execution coefficient, for example, it can be 1, 10, 100, etc.

[0064] In one possible embodiment, the first order task may have one or more preceding order tasks. The preceding order tasks are order tasks that must be completed before the execution of the first order task. For the C-end user, it may not be possible to determine the temporal relationship between multiple order tasks, and they will only select the order task that they currently want to execute as the first order task. Therefore, it is necessary to determine the temporal relationship between multiple order tasks to determine the number of preceding order tasks for the first order task. The preceding order tasks of the first order task are set with an execution coefficient that is higher than that of the first order task. For the subsequent order tasks of the first order task or other order tasks that have no temporal relationship with the first order task, the execution coefficient of these order tasks can be set to be lower than that of the first order task, or set to zero.

[0065] For example, for the first order task, there may be one or more preceding order tasks. A preceding order task can be an order task among the current multiple order tasks that has a temporal relationship with the first order task and precedes it in the temporal sequence. A preceding order task can also be an order task generated based on the task requirements of the first order task, where the task requirements of the first order task are conditions that must be met before executing the first order task. When the first order task is to upgrade the system, the memory space occupied by the new system is the first memory space, and the current remaining memory space is less than the first memory space. Therefore, the preceding order task for the first order task of upgrading the system can be to clear part of the memory space so that the current remaining memory space is greater than or equal to the first memory space.

[0066] In one possible embodiment, all order tasks related to the target vehicle are retrieved from an order task database or storage system. One of these order tasks is selected as the first order task based on pre-set rules, such as creation time order or urgency. When setting the execution coefficient of the first order task, the range and influencing factors of the execution coefficient are determined. For the first order task, its urgency, importance, and expected processing time are comprehensively considered to assign it an execution coefficient value. When determining the temporal relationship of multiple order tasks, the creation time, specified execution time requirements, and possible dependencies of each order task are analyzed to obtain the analysis results. Based on the analysis results, a temporal order list of order tasks is established, clarifying the order and relationships of each task. Alternatively, a temporal relationship diagram can be created, connecting order tasks with temporal relationships and leaving task orders without temporal or relational relationships unconnected. This makes the temporal relationship between multiple order tasks clearer and facilitates the determination of the execution coefficient of each order task. The execution coefficient of each order task within a set of orders is determined based on the execution coefficient of the first order task and the temporal relationship between the multiple order tasks. When multiple execution coefficients are obtained, the execution coefficient of the first order task is used as a benchmark, and relative execution coefficients are set for subsequent order tasks according to the temporal relationship. For example, if the time interval between a subsequent task and the first task is short, the execution coefficient can gradually decrease; if the interval is long, the decrease can be increased. For order tasks with dependencies, the execution coefficient is adjusted according to the tightness of the dependency. For example, the execution coefficient of the dependent task can be appropriately increased. After calculation and adjustment, the execution coefficient of each order task is determined, thus obtaining multiple execution coefficients.

[0067] In one possible embodiment, see [reference] Figure 3 , Figure 3 for Figure 3 This is one example of a timing diagram provided in the embodiments of this application. For example... Figure 3 As shown, Figure 3 The five order tasks are a, b, c, d, and e, and their temporal relationship is as follows: Figure 3When e is the first order task, its preceding order tasks include c and d, d's preceding order task is b, and b and c's preceding order tasks are a. Setting the execution coefficient of e to 1, according to the timing diagram, the execution coefficients for these five order tasks can be set to 2, 1.8, 1.5, 1.2, and 1 respectively. Therefore, the execution order of these five order tasks is a, b, c, d, and e. Since a has the highest execution coefficient, a is chosen as the target order task, and its connection state is set to the first connection state, ready for execution by B after establishing a connection. After a completes execution, with the target connector powered on, the connection states of b, c, d, and e can be sequentially set to the first connection state for execution by B after establishing a connection.

[0068] Optionally, step S303, determining the temporal relationship of multiple order tasks, may include the following steps:

[0069] Step S401: Obtain the task content of each order task from multiple order tasks to obtain multiple task contents;

[0070] Step S402: Determine the content tag for each task content in the multiple task contents based on the multiple task contents, and obtain multiple content tags;

[0071] Step S403: Determine the dependency coefficient between every two task contents in multiple task contents based on multiple content tags, and obtain at least one dependency coefficient;

[0072] Step S404: Determine the temporal relationship of multiple task contents based on at least one dependency coefficient.

[0073] In one possible embodiment, when obtaining the task content of each of multiple order tasks, resulting in multiple task contents, detailed descriptions of the multiple order tasks are extracted from the database of the order task management system. The extracted information is then cleaned and preprocessed to remove irrelevant characters and formatting, resulting in clear and accurate task content text. When determining content tags for each task content based on the multiple task contents, resulting in multiple content tags, natural language processing techniques and machine learning algorithms are used to perform lexical analysis, syntactic analysis, and semantic understanding on each task content. Based on the analysis results, words or phrases that represent the core theme and key elements of the task are extracted as content tags. For example, if the task is "replace engine spark plugs and check the ignition system," the extracted tags might be one or more of the following: "engine," "spark plugs," "ignition system," "replace," and "check." When determining the dependency coefficient of every two task contents across multiple task contents based on multiple content tags, and obtaining at least one dependency coefficient, the tag sets of each pair of task contents are compared and matched, and the overlap, inclusion relationship, or correlation degree of the two task content tags is calculated. According to pre-defined rules and algorithms, the overlap or correlation degree is converted into a dependency coefficient. For example, if two tasks have 50% overlap in tags, the dependency coefficient can be set to 0.5. When determining the temporal relationship of multiple task contents based on at least one dependency coefficient, the task pairs are sorted according to the magnitude of the dependency coefficient. For task pairs with higher dependency coefficients, their dependency relationship is closer, and a closer connection line distance can be set in the temporal relationship graph. For order tasks without direct dependencies, their relative positions in the temporal relationship are determined based on urgency and creation time.

[0074] In this embodiment, by analyzing the dependencies of task content, the order of task execution can be accurately determined, avoiding repetitive work or errors caused by improper task execution order. Executing tasks according to a reasonable time sequence can reduce waiting time and resource idleness, making the entire workflow smoother and thus improving work efficiency. Ensuring that closely dependent tasks are executed in the correct order can reduce the risk and errors of subsequent tasks caused by incomplete or improperly completed preceding tasks.

[0075] Optionally, step S304, determining the execution coefficient of each order task among the multiple order tasks based on the execution coefficient of the first order task and the temporal relationship of the multiple order tasks, to obtain multiple execution coefficients, may include the following steps:

[0076] Step S501: Determine the number of preceding tasks for the first order task based on the temporal relationship of multiple order tasks;

[0077] Step S502: If the number of prerequisite tasks for the first order task is not zero, obtain all prerequisite tasks for the first order task and get at least one prerequisite task.

[0078] Step S503: Determine the execution time of each of the at least one preceding task to obtain multiple execution times;

[0079] Step S504: Based on the preset idle time, multiple execution times, and the temporal relationship of multiple order tasks, determine the execution coefficient of each order task in the multiple order tasks, and obtain multiple execution coefficients.

[0080] In one possible embodiment, the expected or actual execution time of each preceding task can be predicted based on relevant records or schedules. The preset idle time can be selected and determined by the end customer, and the preset idle time represents the available execution time for multiple current order tasks.

[0081] In one possible embodiment, see [reference] Figure 4 , Figure 4 This is a second example of a timing diagram provided in the embodiments of this application. Figure 4 As shown, Figure 4 The four order tasks are f, g, h, and i, and their timing relationship is as follows: Figure 4 When h is the first order task, the preceding order tasks of h include f and g, and the following task of h is i. The execution coefficient of h is set to 1. According to the timing diagram, the execution coefficients for these four order tasks can be set to 2, 2, 1, and 0.5 respectively. For f and g with the same execution coefficient, the execution time of f and g is determined. When the execution times of f and g are 1 hour and 2 hours respectively, and the preset idle time is 1.5 hours, the execution coefficients of f and g are adjusted to 2.1 and 1.9 respectively. Therefore, the execution order of these four order tasks is f, g, h, and i. Since f has the highest execution coefficient, f is chosen as the target order task, and the connection state of f is set to the first connection state, allowing B to execute f after establishing a connection.

[0082] Optionally, step S301, obtaining the first order task from multiple order tasks, may include the following steps:

[0083] Step S61: Obtain the creation time of each order task in the multiple order tasks to get multiple creation times;

[0084] Step S62: Determine the first weight of each creation time among multiple creation times to obtain multiple first weights;

[0085] Step S63: Determine the task priority of each order task based on the task type of each order task in the multiple order tasks, and obtain multiple task priorities;

[0086] Step S64: Determine the second weight of each task priority among multiple task priorities, and obtain multiple second weights;

[0087] Step S65: Determine the first order task among multiple order tasks based on multiple first weights and multiple second weights.

[0088] In one possible embodiment, the first order task can be determined based on the creation time and task priority of each of the multiple order tasks, without requiring selection by the end user.

[0089] In one possible embodiment, different task types correspond to different task priorities, and the correspondence can be predetermined by the end user. For example, emergency repair tasks have a higher priority than regular maintenance tasks.

[0090] In one possible embodiment, the creation time record of each order task is extracted from the database of the order task management system. The extracted creation times are standardized to ensure uniformity and accuracy. A weighting rule for creation time is determined; for example, the earlier the creation time, the higher the weight. The weighting can be linear or non-linear according to the chronological order. Based on the determined rule, a first weight value is determined for each creation time. A weighting rule for task priority is also determined, with different priorities corresponding to different weight values. The higher the task priority, the higher the second weight value. A second weight value is determined for each task priority. The first weight of each order task's creation time and the second weight of its priority are combined and calculated. A weighted average is used to compare the combined weight values ​​of multiple order tasks, and the order task with the highest combined weight value is determined as the first order task. In this embodiment, when the C-end user does not manually select the first order task, by considering both creation time and task priority, the decision is avoided based on a single factor, making the selection of the first order task more comprehensive and reasonable.

[0091] Optionally, step S301, obtaining the first order task from multiple order tasks, may include the following steps:

[0092] Step S71: Obtain at least one historical order task for the target vehicle;

[0093] Step S72: Determine the execution information of each historical order task in at least one historical order task, and obtain at least one execution information;

[0094] Execution information includes execution frequency and execution node;

[0095] Step S73: Determine the first order task among multiple order tasks based on at least one execution information.

[0096] In one possible embodiment, the first order task can be determined by the execution information of each historical order task in at least one historical order task, without requiring selection by the C-end user.

[0097] In one possible embodiment, all historical order task data related to the target vehicle are extracted from the vehicle's maintenance record database or related order management system. The extracted data is then filtered and organized to remove duplicate or invalid records, ensuring the accuracy and completeness of the obtained historical order tasks. For each historical order task, its execution record is analyzed in detail to obtain the number of times each historical order task is executed to determine the execution frequency. The specific time point or time period of each historical order task's execution is also obtained as the execution node. Evaluation rules are set; for example, some order tasks are executed weekly or daily, and the execution nodes of some order tasks are seasonal. Order tasks with high execution frequency, or whose current execution time corresponds to the execution node, are weighted and evaluated. The order task with the highest weight value in the evaluation results is selected as the first order task. In this embodiment, even when the C-end user does not manually select the first order task, the vehicle's historical maintenance and service data can be used to determine the current first order task based on practical experience. By analyzing the execution frequency and nodes, the reliability of the decision is improved.

[0098] In one possible embodiment, see [reference] Figure 5 , Figure 5 This is the third example of a timing diagram provided in the embodiments of this application. Figure 5 As shown, Figure 5 The four order tasks are j, k, m, and n, and their timing relationship is as follows: Figure 5 When the first order task is n, the preceding order task of n is j. K and m have no temporal relationship with n. When the execution coefficient of n is 1, the execution coefficients of j, k, m and n can be set to 1.5, 0, 0 and 1 respectively. It can be seen that since j has the highest execution coefficient, j is taken as the target order task, and the connection state of j is set to the first connection state, so that the B end can execute j after establishing a connection.

[0099] In one possible implementation, for multiple order tasks on the C-end, it's possible to complete these tasks by sequentially establishing connections with multiple B-ends. The C-end can pre-configure connectable order tasks, allowing only B-ends to connect to the prepared C-end order tasks. This prevents B-ends corresponding to other C-end order tasks from connecting to the C-end, which would result in invalid connections and waste time for both B-end and C-end users, thus improving the efficiency of C-end order task execution. Specifically, after the C-end connector is powered on, it reads the VIN of the vehicle requiring remote access, queries the number of order tasks corresponding to the current VIN of the C-end connector, and if there is only one task, it directly sets this task to a connectable state, allowing the corresponding B-end to connect and process the task. If multiple tasks exist, the C-end user is prompted to select the target order task to be executed. If the C-end user does not select one within a preset time, the last published order task among the multiple order tasks can be selected by default as the target order task, and only the target order task selected by the C-end user or the last published order task is set to a connectable state. If no task is available, the C-end user is prompted that there are no remote order tasks for the target vehicle, and asked if they want to publish an order task for that target vehicle. The B-end checks whether the C-end corresponding to the order task can connect. If a connection is possible, the system automatically connects to the available C-end to complete the super remote task order. In this embodiment, after the C-end connector is powered on, the status of tasks available for B-end connection is automatically set. If the C-end user needs to select the task to be executed, the C-end user can select it in advance, avoiding invalid connections between the B-end and C-end when multiple tasks exist on the C-end, which would require order suspension and reconnection, thus improving order completion efficiency.

[0100] In summary, in this embodiment, after powering on the target connector, the first diagnostic module obtains the vehicle identification code (VIC) of the target vehicle and the number of order tasks based on the VIC. Then, based on the number of order tasks, a target order task is determined, and its connection status is set to a first connection status, which makes the target order task selectable. Next, based on the first connection status, the target order task is displayed to the second diagnostic module, and target touch parameters are obtained from the second diagnostic module. These target touch parameters are used to select the target order task. Finally, a connection is established between the first and second diagnostic modules based on the target touch parameters to execute the target order task. Therefore, by determining the target vehicle through the target connector, obtaining the number of order tasks by acquiring the VIC of the target vehicle, and setting the connection status of the target order task for the second diagnostic module to select, connect, and execute, the number of invalid connections during remote maintenance and diagnostics can be reduced, thereby improving the efficiency of completing remote diagnostic orders.

[0101] The methods of the embodiments of the present invention have been described in detail above, and the apparatus of the embodiments of the present invention is provided below.

[0102] See Figure 6 , Figure 6 This is a schematic diagram of a remote diagnostic order connection device provided in an embodiment of this application. The remote diagnostic order connection device 600 is applied to a diagnostic device, which includes a first diagnostic module and a second diagnostic module. The first diagnostic module is connected to a target vehicle via a target connector. The remote diagnostic order connection device 600 includes an acquisition unit 601 and a processing unit 602.

[0103] The acquisition unit 601 is used to acquire the vehicle information of the target vehicle through the first diagnostic module after the target connector is powered on. The vehicle information of the target vehicle includes the vehicle identification code of the target vehicle.

[0104] The number of order tasks is determined based on the vehicle information of the target vehicle;

[0105] Processing unit 602 is used to determine the target order task based on the number of order tasks;

[0106] Set the connection status of the target order task to the first connection status. The first connection status is used to make the target order task selectable.

[0107] Based on the first connection status, the target order task is displayed to the second diagnostic module;

[0108] Obtain the target touch parameters from the second diagnostic module. The target touch parameters are used to select the target order task.

[0109] A connection is established between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task.

[0110] In some possible embodiments, in determining the target order task based on the number of order tasks, the processing unit 602 is specifically used for:

[0111] When there is only one order task, the current order task of the target vehicle will be used as the target order task.

[0112] When there are multiple order tasks, retrieve multiple order tasks for the target vehicle;

[0113] Determine the execution coefficient for each of the multiple order tasks to obtain multiple execution coefficients, which are used to represent the execution priority;

[0114] The order task with the highest execution coefficient among multiple order tasks is selected as the target order task.

[0115] In some possible embodiments, in determining the execution coefficient of each order task among multiple order tasks to obtain multiple execution coefficients, the processing unit 602 is specifically used for:

[0116] Retrieve the first order task from a set of multiple order tasks;

[0117] Set the execution coefficient for the first order task;

[0118] Determine the temporal relationship between multiple order tasks;

[0119] Based on the execution coefficient of the first order task and the temporal relationship of multiple order tasks, the execution coefficient of each order task in the multiple order tasks is determined, resulting in multiple execution coefficients.

[0120] In some possible embodiments, in determining the temporal relationship of multiple order tasks, processing unit 602 is specifically used for:

[0121] Retrieve the task content of each of the multiple order tasks to obtain multiple task contents;

[0122] Based on multiple task contents, determine the content tags for each task content to obtain multiple content tags;

[0123] Based on multiple content tags, determine the dependency coefficient between every two task contents in multiple task contents, and obtain at least one dependency coefficient;

[0124] The temporal relationship between multiple task contents is determined based on at least one dependency coefficient.

[0125] In some possible embodiments, in determining the execution coefficient of each of the multiple order tasks based on the execution coefficient of the first order task and the temporal relationship of the multiple order tasks, to obtain multiple execution coefficients, the processing unit 602 is specifically used for:

[0126] The number of preceding tasks for the first order task is determined based on the temporal relationship of multiple order tasks;

[0127] If the number of prerequisite tasks for the first order is not zero, obtain all prerequisite tasks for the first order and get at least one prerequisite task.

[0128] Determine the execution time of each of the at least one prerequisite tasks to obtain multiple execution times;

[0129] Based on the preset idle time, multiple execution times, and the temporal relationship of multiple order tasks, the execution coefficient of each order task in the multiple order tasks is determined, resulting in multiple execution coefficients.

[0130] In some possible embodiments, in retrieving the first order task from a plurality of order tasks, the processing unit 602 is specifically configured to:

[0131] Obtain the creation time of each order task from multiple order tasks, resulting in multiple creation times;

[0132] Determine the first weight for each creation time among multiple creation times to obtain multiple first weights;

[0133] The task priority of each order task is determined based on the task type of each order task in the multiple order tasks, thus obtaining multiple task priorities;

[0134] Determine the second weight for each task priority among multiple task priorities, thus obtaining multiple second weights;

[0135] The first order task among multiple order tasks is determined based on multiple first weights and multiple second weights.

[0136] In some possible embodiments, in retrieving the first order task from a plurality of order tasks, the processing unit 602 is specifically configured to:

[0137] Obtain at least one historical order task for the target vehicle;

[0138] Determine the execution information of each historical order task in at least one historical order task, and obtain at least one execution information, including execution frequency and execution node;

[0139] The first order task among multiple order tasks is determined based on at least one execution information.

[0140] See Figure 7 , Figure 7 This is a schematic diagram of the structure of a diagnostic device provided in an embodiment of this application. Figure 7 As shown, the diagnostic device 700 includes a transceiver 701, a processor 702, and a memory 703. These are connected via a bus 704. The memory 703 stores computer programs and data, and can transmit data stored in the memory 703 to the processor 702. This diagnostic device can be the aforementioned connection device for remote diagnostic orders, and the processor 702 can be the aforementioned acquisition unit 601 and processing unit 602.

[0141] Processor 702 is used to read the computer program in memory 703 and perform the following operations:

[0142] After the target connector is powered on, the vehicle information of the target vehicle is obtained through the first diagnostic module. The vehicle information of the target vehicle includes the vehicle identification code of the target vehicle.

[0143] The number of order tasks is determined based on the vehicle information of the target vehicle;

[0144] The target order tasks are determined based on the number of order tasks.

[0145] Set the connection status of the target order task to the first connection status. The first connection status is used to make the target order task selectable.

[0146] Based on the first connection status, the target order task is displayed to the second diagnostic module;

[0147] Obtain the target touch parameters from the second diagnostic module. The target touch parameters are used to select the target order task.

[0148] A connection is established between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task.

[0149] In some possible embodiments, in determining the target order task based on the number of order tasks, the processor 702 is specifically configured to perform the following operations:

[0150] When there is only one order task, the current order task of the target vehicle will be used as the target order task.

[0151] When there are multiple order tasks, retrieve multiple order tasks for the target vehicle;

[0152] Determine the execution coefficient for each of the multiple order tasks to obtain multiple execution coefficients, which are used to represent the execution priority;

[0153] The order task with the highest execution coefficient among multiple order tasks is selected as the target order task.

[0154] In some possible embodiments, in determining the execution coefficient of each order task among a plurality of order tasks, and obtaining a plurality of execution coefficients, the processor 702 is specifically configured to perform the following operations:

[0155] Retrieve the first order task from a set of multiple order tasks;

[0156] Set the execution coefficient for the first order task;

[0157] Determine the temporal relationship between multiple order tasks;

[0158] Based on the execution coefficient of the first order task and the temporal relationship of multiple order tasks, the execution coefficient of each order task in the multiple order tasks is determined, resulting in multiple execution coefficients.

[0159] In some possible embodiments, in determining the timing relationship of multiple order tasks, processor 702 is specifically configured to perform the following operations:

[0160] Retrieve the task content of each of the multiple order tasks to obtain multiple task contents;

[0161] Based on multiple task contents, determine the content tags for each task content to obtain multiple content tags;

[0162] Based on multiple content tags, determine the dependency coefficient between every two task contents in multiple task contents, and obtain at least one dependency coefficient;

[0163] The temporal relationship between multiple task contents is determined based on at least one dependency coefficient.

[0164] In some possible embodiments, in determining the execution coefficient of each of the multiple order tasks based on the execution coefficient of the first order task and the timing relationship of the multiple order tasks, and obtaining multiple execution coefficients, the processor 702 is specifically configured to perform the following operations:

[0165] The number of preceding tasks for the first order task is determined based on the temporal relationship of multiple order tasks;

[0166] If the number of prerequisite tasks for the first order is not zero, obtain all prerequisite tasks for the first order and get at least one prerequisite task.

[0167] Determine the execution time of each of the at least one prerequisite tasks to obtain multiple execution times;

[0168] Based on the preset idle time, multiple execution times, and the temporal relationship of multiple order tasks, the execution coefficient of each order task in the multiple order tasks is determined, resulting in multiple execution coefficients.

[0169] In some possible embodiments, in retrieving the first order task among a plurality of order tasks, the processor 702 is specifically configured to perform the following operations:

[0170] Obtain the creation time of each order task from multiple order tasks, resulting in multiple creation times;

[0171] Determine the first weight for each creation time among multiple creation times to obtain multiple first weights;

[0172] The task priority of each order task is determined based on the task type of each order task in the multiple order tasks, thus obtaining multiple task priorities;

[0173] Determine the second weight for each task priority among multiple task priorities, thus obtaining multiple second weights;

[0174] The first order task among multiple order tasks is determined based on multiple first weights and multiple second weights.

[0175] In some possible embodiments, in retrieving the first order task among a plurality of order tasks, the processor 702 is specifically configured to perform the following operations:

[0176] Obtain at least one historical order task for the target vehicle;

[0177] Determine the execution information of each historical order task in at least one historical order task, and obtain at least one execution information, including execution frequency and execution node;

[0178] The first order task among multiple order tasks is determined based on at least one execution information.

[0179] 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 the method for connecting any of the remote diagnostic orders as described in the above method embodiments.

[0180] 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 order connection methods described in the above method embodiments.

[0181] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all 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 according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0182] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0183] 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 modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules 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 modules may be electrical or other forms.

[0184] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network modules. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0185] Furthermore, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated modules described above can be implemented in hardware or as software program modules.

[0186] If the integrated module 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 described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0187] 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 medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0188] 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 description of the above 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 connection method for remote diagnosis of an order, characterized by, The method is applied to a diagnostic device, which includes a first diagnostic module and a second diagnostic module, wherein the first diagnostic module is connected to a target vehicle via a target connector; the method includes: After the target connector is powered on, the vehicle identification code of the target vehicle is obtained through the first diagnostic module; The number of order tasks is obtained based on the vehicle identification code; The target order tasks are determined based on the number of order tasks mentioned above; Set the connection status of the target order task to a first connection status, which is used to make the target order task selectable. Based on the first connection status, the target order task is displayed to the second diagnostic module; Obtain the target touch parameters of the second diagnostic module, the target touch parameters being used to select the target order task; A connection is established between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task; The step of determining the target order task based on the number of order tasks includes: When the number of order tasks is single, the current order task of the target vehicle is taken as the target order task; When there are multiple order tasks, obtain multiple order tasks for the target vehicle; The execution coefficient of each order task in the plurality of order tasks is determined, resulting in a plurality of execution coefficients, which are used to represent the execution priority. The order task with the highest execution coefficient among the multiple order tasks is selected as the target order task.

2. The method of claim 1, wherein, The determination of the execution coefficient for each of the multiple order tasks yields multiple execution coefficients, including: Obtain the first order task from the plurality of order tasks; Set the execution coefficient for the first order task; Determine the temporal relationship between the multiple order tasks; The execution coefficient of each of the multiple order tasks is determined based on the execution coefficient of the first order task and the temporal relationship of the multiple order tasks, thus obtaining the multiple execution coefficients.

3. The method of claim 2, wherein, Determining the temporal relationship of the multiple order tasks includes: Obtain the task content of each of the multiple order tasks to obtain multiple task contents; Based on the multiple task contents, a content tag is determined for each task content to obtain multiple content tags; Based on the multiple content tags, determine the dependency coefficient between every two task contents in the multiple task contents, and obtain at least one dependency coefficient; The temporal relationship of the multiple task contents is determined based on the at least one dependency coefficient.

4. The method of claim 3, wherein, The process of determining the execution coefficient of each of the multiple order tasks based on the execution coefficient of the first order task and the temporal relationship of the multiple order tasks, to obtain the multiple execution coefficients, includes: The number of preceding tasks for the first order task is determined based on the temporal relationship of the multiple order tasks; If the number of prerequisite tasks for the first order task is not zero, obtain all prerequisite tasks for the first order task and get at least one prerequisite task. The execution time of each of the at least one prerequisite tasks is determined to obtain multiple execution times; The execution coefficient of each order task in the multiple order tasks is determined based on the preset idle time, the multiple execution times, and the temporal relationship of the multiple order tasks, thus obtaining the multiple execution coefficients.

5. The method according to any one of claims 2 to 4, wherein, The step of obtaining the first order task from the plurality of order tasks includes: Obtain the creation time of each of the multiple order tasks to obtain multiple creation times; Determine the first weight for each of the multiple creation times to obtain multiple first weights; Based on the task type of each of the multiple order tasks, the task priority of each of the multiple order tasks is determined, resulting in multiple task priorities; Determine the second weight of each task priority among the plurality of task priorities to obtain a plurality of second weights; The first order task among the multiple order tasks is determined based on the multiple first weights and the multiple second weights.

6. The method according to any one of claims 2 to 4, wherein, The step of obtaining the first order task from the plurality of order tasks includes: Obtain at least one historical order task for the target vehicle; Determine the execution information of each historical order task in the at least one historical order task to obtain at least one execution information, the execution information including execution frequency and execution node; The first order task among the plurality of order tasks is determined based on the at least one execution information.

7. A connection device for remote diagnosis of an order, characterized in that The device is applied to a diagnostic equipment, which includes a first diagnostic module and a second diagnostic module. The first diagnostic module is connected to a target vehicle via a target connector. The connection device for the remote diagnostic order includes an acquisition unit and a processing unit. The acquisition unit is used to acquire vehicle information of the target vehicle through the first diagnostic module after the target connector is powered on. The vehicle information of the target vehicle includes the vehicle identification code of the target vehicle. The number of order tasks is obtained based on the vehicle information of the target vehicle; The processing unit is used to determine the target order task based on the number of order tasks; Set the connection status of the target order task to a first connection status, which is used to make the target order task selectable. Based on the first connection status, the target order task is displayed to the second diagnostic module; Obtain the target touch parameters of the second diagnostic module, the target touch parameters being used to select the target order task; A connection is established between the first diagnostic module and the second diagnostic module based on the target touch parameters to execute the target order task; The step of determining the target order task based on the number of order tasks includes: When the number of order tasks is single, the current order task of the target vehicle is taken as the target order task; When there are multiple order tasks, obtain multiple order tasks for the target vehicle; The execution coefficient of each order task in the plurality of order tasks is determined, resulting in a plurality of execution coefficients, which are used to represent the execution priority. The order task with the highest execution coefficient among the multiple order tasks is selected as the target order task.

8. A diagnostic device, characterized by include: A processor and a memory, the processor being connected to the memory, the memory being used to store a computer program, the processor being used to execute the computer program stored in the memory such that the diagnostic device performs the method as described in any one of claims 1-6.

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

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