Remote diagnosis order connection method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses a remote diagnosis order connection method and device, equipment and a storage medium, the method is applied to diagnosis equipment, the diagnosis equipment 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 steps that after a target joint is powered on, a vehicle identification code of a target vehicle is acquired through a first diagnosis module; obtaining the number of order tasks based on the vehicle identification code; determining a target order task based on the number of the order tasks; setting the connection state of the target order task as a first connection state, wherein the first connection state is used for enabling the target order task to be in a selectable state; displaying the target order task to a second diagnosis module based on the first connection state; obtaining a target touch parameter of a second diagnosis module, wherein the target touch parameter is used for selecting a target order task; and establishing a connection between the first diagnosis module and the second diagnosis module based on the target touch parameter to execute the target order task.

Description

Technical Field

[0001] The present invention relates to the field of vehicle maintenance technology, and in particular to a connection method, device, equipment and storage medium for a remote diagnosis order. Background Art

[0002] In the past, the diagnosis and repair of vehicle failures mainly relied on car owners to drive their vehicles to repair shops, where technicians would conduct on-site inspections and use special equipment to determine the problem. However, with the continuous development of automotive technology, traditional diagnostic methods face many challenges. For some car owners, sending their vehicles to professional repair shops may take a lot of time and money, and in some emergency situations, such as sudden failures of vehicles while driving, traditional repair methods may not be able to provide timely assistance.

[0003] With the rapid development of communication technology and the Internet, vehicle remote diagnosis technology has emerged. The vehicle's operating data can be transmitted to a remote server in real time, and professional technicians can diagnose, analyze and repair the vehicle remotely. The traditional remote diagnosis method is that after the user publishes a maintenance order task, the maintenance personnel accept the order and automatically establish a connection with the user's vehicle to complete the order. However, when a user publishes multiple maintenance order tasks, there may be a situation where the order task that the user does not currently expect to execute is connected first. In this case, the order can only be suspended after the connection is established, waiting for the next connection until it is connected to the order task that the user currently expects to execute. This may result in multiple invalid connections during the remote maintenance diagnosis process, thereby reducing the execution efficiency of the order task.

[0004] Therefore, there is an urgent need for a remote diagnosis order connection method that reduces the number of invalid connections during the remote repair diagnosis process to improve the completion efficiency of the remote diagnosis order. Summary of the invention

[0005] In order to solve the above problems, an embodiment of the present invention provides a connection method, device, equipment and storage medium for a remote diagnosis order, which can reduce the number of invalid connections during the remote repair diagnosis process, thereby improving the completion efficiency of the remote diagnosis order.

[0006] In a first aspect, an embodiment of the present invention provides a method for connecting a remote diagnostic order, the method being applied to a diagnostic device, the diagnostic device comprising 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 comprising:

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

[0008] Obtaining the number of order tasks based on the vehicle identification code;

[0009] Determine the target order task based on the number of order tasks;

[0010] Setting the connection state of the target order task to a first connection state, wherein the first connection state is used to make the target order task in a selectable state;

[0011] displaying the target order task to the second diagnosis module based on the first connection status;

[0012] Acquire a target touch parameter of the second diagnostic module, where the target touch parameter is 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 parameter to execute the target order task.

[0014] In a second aspect, an embodiment of the present invention provides a connection device for a remote diagnosis order, the connection device for the remote diagnosis order 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 through a target connector; the connection device for the remote diagnosis order 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, wherein the vehicle information of the target vehicle includes a vehicle identification code of the target vehicle;

[0016] Acquire the number of order tasks 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] Setting the connection state of the target order task to a first connection state, wherein the first connection state is used to make the target order task in a selectable state;

[0019] displaying the target order task to the second diagnosis module based on the first connection status;

[0020] Acquire a target touch parameter of the second diagnostic module, where the target touch parameter is 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 parameter to execute the target order task.

[0022] In a third aspect, an embodiment of the present invention provides a diagnostic device, comprising a processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory so that the diagnostic device performs the method described in the first aspect.

[0023] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and the computer program is executed by a processor to implement the method as described in the first aspect.

[0024] In a fifth aspect, an embodiment of the present application provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer is operable to cause the computer to execute the method described in the first aspect.

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

[0026] In the implementation mode of the present application, after the target connector is powered on, the vehicle identification code of the target vehicle is obtained through the first diagnostic module, and the number of order tasks is obtained based on the vehicle identification code. Then, the target order task is determined based on the number of order tasks, and the connection state of the target order task is set to the first connection state, wherein the first connection state is used to make the target order task in a selectable state. Next, the target order task is displayed to the second diagnostic module based on the first connection state, and the target touch parameters of the second diagnostic module are obtained, wherein the target touch parameters are used to select the target order task. Finally, 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. Thus, the target vehicle is determined through the target connector, the number of order tasks is obtained by obtaining the vehicle identification code of the target vehicle, and the connection state of the target order task is set after the target order task is determined for the second diagnostic module to select, connect and execute, which can reduce the number of invalid connections during the remote maintenance diagnosis process, thereby improving the completion efficiency of remote diagnosis orders. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the background technology, the drawings required for use in the embodiments of the present invention or the background technology will be described below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0028] Figure 1 It is a schematic diagram of the architecture of a connection system for a remote diagnosis order provided in an embodiment of the present application;

[0029] Figure 2 is a flow chart of a connection method for a remote diagnosis order provided in an embodiment of the present application;

[0030] Figure 3 It is one of the examples of a timing relationship diagram provided in an embodiment of the present application;

[0031] Figure 4 This is the second example of a timing relationship diagram provided in an embodiment of the present application;

[0032] Figure 5 This is the third example of a timing relationship diagram provided in an embodiment of the present application;

[0033] Figure 6 It is a structural schematic diagram of a connection device for a remote diagnosis order provided in an embodiment of the present application;

[0034] Figure 7 It is a schematic diagram of the structure of a diagnostic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0035] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0036] The terms "first", "second", "third" and "fourth" etc. in the specification and claims of the present application and the drawings are used to distinguish different objects, rather than to describe a specific order. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. 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 optionally includes steps or modules that are not listed, or optionally includes other steps or modules inherent to these processes, methods, products or devices.

[0037] Reference to "embodiments" herein means that a particular feature, result, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0038] See also Figure 1 , Figure 1Schematic diagram of the architecture of a connection system for remote diagnosis orders provided in an embodiment of the present application. Figure 1 As shown, the connection method of the remote diagnosis order provided in the embodiment of the present application is applied to the connection system 10 of the remote diagnosis order, and the connection system 10 of the remote diagnosis order includes a diagnostic device and a target vehicle 13, and the diagnostic device includes a first diagnostic module 11 and a second diagnostic module 12, and the first diagnostic module 11 is connected to the target vehicle 13 through a target connector. Among them, the first diagnostic module 11 and the second diagnostic module 12 can be connected through one or more methods such as Bluetooth, Wi-Fi, Universal Serial Bus (USB), mobile network, Zigbee, etc., which are not limited here.

[0039] See also Figure 2 , Figure 2 1 is a flow chart of a method for connecting a remote diagnosis order provided by an embodiment of the present application. Figure 2 As shown, the method includes but is not limited to the following steps:

[0040] Step S101: after the target connector is powered on, the vehicle identification code of the target vehicle is obtained through the first diagnostic module;

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

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

[0043] Step S104: setting the connection state of the target order task to the first connection state;

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

[0045] Step S105: displaying the target order task to the second diagnosis module based on the first connection state;

[0046] Step S106: Acquire target touch parameters of the second diagnosis module;

[0047] The target touch parameter is used to select the target order task;

[0048] Step S107: establishing a connection between the first diagnosis module and the second diagnosis module based on the target touch parameter to execute the target order task.

[0049] In a possible embodiment, the first diagnostic module corresponds to the C end, and the second diagnostic module corresponds to the B end. The user plugs the target connector into the target vehicle through the C end corresponding to the first diagnostic module, so as to facilitate the subsequent operation of the order task of the target vehicle. After the target connector is powered on, the first diagnostic module is started and a communication connection is established with the on-board diagnostic (OBD) system of the target vehicle through the first diagnostic module. The first diagnostic module obtains the vehicle identification code (VIN) from the electronic control unit of the vehicle through a preset diagnostic protocol and interface, and sends a diagnostic request instruction to the OBD system of the target vehicle through the first diagnostic module. The OBD system of the target vehicle responds to the diagnostic request instruction and returns a data packet containing the VIN, and the first diagnostic module parses the data packet to obtain the accurate VIN. Based on the obtained vehicle identification code, a request is sent to the server to obtain the number of order tasks related to the target vehicle, and the VIN is encoded by the first diagnostic module and sent to the server through the network. The server searches for the order task record matching the VIN in the database and returns the number of order tasks. Based on the number of order tasks, the target order task is determined according to the preset rules. For example, the most recently created order task, the order task with high urgency or the order task related to the current vehicle fault symptom can be preferentially selected as the target order task. If there are multiple order tasks, a comprehensive evaluation and sorting is performed according to the attributes of each task, such as the creation time, urgency mark, the matching degree of the fault description with the current vehicle symptom, etc., and the task with the highest ranking is determined as the target order task. The connection state of the target order task is set to the first connection state, so that the task is in a selectable state. The relevant information of the target order task in the first connection state, such as the task description, the preliminary information of the vehicle fault, etc., is displayed on the interface of the second diagnosis module, so that the second diagnosis module obtains the detailed data of the target order task. The operation of the B-end user corresponding to the second diagnosis module is monitored in real time by the second diagnosis module, and the operation of the B-end user is monitored in real time by the touch screen or other input device, and the operation is converted into the corresponding touch parameters, and the target touch parameters generated by the B-end user operation on the second diagnosis module are obtained, such as click, slide or specific gesture, etc. These parameters are used to clarify that the B-end user corresponding to the second diagnosis module has selected the target order task. When it is detected that the target touch parameter matches the operation of selecting the target order task, the connection establishment instruction is triggered to establish a stable data connection between the first diagnostic module and the second diagnostic module so that both parties can interact and share information in real time, thereby executing the target order task. After the first diagnostic module receives the connection establishment instruction, it starts the secure encrypted communication protocol, performs handshake and authentication with the second diagnostic module, and establishes a direct data channel between the first diagnostic module and the second diagnostic module, realizing 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 through the touch screen or other input devices of the second diagnostic module to perform data exchange and diagnostic operations.

[0050] In the embodiment of the present application, by automatically acquiring the vehicle identification code and determining the relevant order tasks, the time for manual search and screening is reduced, so that the diagnostic work can focus on key tasks more quickly, and the diagnostic efficiency is improved. By determining the target order tasks according to preset rules, the tasks that the C-end user currently expects to process or the most critical and urgent tasks can be given priority, and diagnostic resources can be allocated more effectively to ensure that important order tasks are processed in a timely manner, improve overall work efficiency and service quality, and improve the pertinence and effectiveness of maintenance. By displaying the target order tasks in the second diagnostic module and allowing the B-end user to select through simple and intuitive touch operations, the complexity of the operation is reduced and the work convenience of the B-end and C-end users is improved. By establishing a stable connection between the modules, the security and accuracy of data transmission are guaranteed, and diagnostic errors caused by information loss or errors are avoided.

[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 the number of order tasks is single, the current order task of the target vehicle is used as the target order task;

[0053] Step S202: when there are multiple order tasks, multiple order tasks of the target vehicle are obtained;

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

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

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

[0057] In a possible embodiment, when the number of order tasks is single, the unique order task information of the target vehicle is obtained, including task description, vehicle fault details, customer needs, etc., and the unique order task is directly marked as the target order task without other complex judgment and selection operations. When the number of order tasks is multiple, the detailed information of all multiple order tasks of the target vehicle is obtained. The detailed information may include data such as the creation time, urgency rating, estimated maintenance time, and correlation with the current fault of the vehicle of each task, and the execution coefficient is calculated according to the detailed information of each order task. For example, it can be set that the earlier the creation time, the higher the execution coefficient; the higher the urgency, the higher the execution coefficient; the shorter the estimated maintenance time, the higher the execution coefficient; the greater the correlation with the current fault of the vehicle, the higher the execution coefficient, and so on. By setting the corresponding weights and algorithms, the execution coefficient of each order task is obtained by combining these factors, and the execution coefficient of all order tasks is compared to find the order task with the highest execution coefficient, and the order task with the highest execution coefficient is selected as the target order task. In the embodiment of the present application, when there is only a single order task, the target order task is directly determined, which saves the time of selection and judgment and quickly enters the processing flow. When there are multiple order tasks, the most important and urgent tasks can be processed first by calculating and comparing the execution coefficients, avoiding wasting resources on minor tasks, thereby improving the overall maintenance and diagnosis efficiency. By determining the target order task based on the execution coefficient, resources such as technicians, tools and time can be allocated more reasonably to ensure that resources are concentrated on the tasks that need to be prioritized the most. By giving priority to urgent and important order tasks, user problems can be solved more quickly and user waiting time can be reduced.

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

[0059] Step S301: obtaining the first order task among multiple order tasks;

[0060] Step S302: setting the execution coefficient of the first order task;

[0061] Step S303: determining the time sequence relationship of multiple order tasks;

[0062] Step S304: determining the execution coefficient of each of the multiple order tasks based on the execution coefficient of the first order task and the time sequence relationship of the multiple order tasks to obtain multiple execution coefficients.

[0063] In a possible embodiment, the first order task can be selected and determined by the C-end user from multiple order tasks, and 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 a possible embodiment, there may be one or more predecessor order tasks for the first order task, and the predecessor order task is an order task that must be completed before executing the first order task. For C-end users, it may be impossible to determine the timing relationship between multiple order tasks, and only the order task currently expected to be executed will be selected as the first order task. Therefore, it is necessary to determine the timing relationship of multiple order tasks to determine the number of predecessor order tasks of the first order task, and set an execution coefficient higher than the execution coefficient of the first order task for the predecessor order task of the first order task. For the post-order tasks of the first order task in the timing relationship of multiple order tasks or other order tasks that have no timing relationship with the first order task, the execution coefficients of these order tasks can be set to be lower than the execution coefficient of the first order task, or to zero.

[0065] Exemplarily, there may be one or more predecessor order tasks for the first order task. The predecessor order task may be an order task that has a time sequence relationship with the first order task and is before the first order task among the current multiple order tasks. The predecessor order task may also be an order task generated based on the task requirements of the first order task. 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, then the predecessor order task of the first order task of the upgraded system may 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 a possible embodiment, all order tasks related to the target vehicle are retrieved from the order task database or storage system, and one of the order tasks is determined as the first order task according to pre-set rules, such as the order of creation time or urgency. When setting the execution coefficient of the first order task, the value range and influencing factors of the execution coefficient are determined. For the first order task, the urgency, importance, estimated processing time and other factors are comprehensively considered to assign an execution coefficient value to it. When determining the temporal relationship of multiple order tasks, the creation time of each order task, the specified execution time requirements, and the possible dependencies between them are analyzed to obtain the analysis results. According to the analysis results, a time sequence list of order tasks is established to clarify the order and correlation of each task. A time sequence relationship diagram can also be created to establish connecting lines between order tasks with a time sequence relationship, and no connecting lines are set between task orders without a time sequence relationship or correlation relationship, so that the temporal relationship between multiple order tasks is clearer and easier to determine the execution coefficient of each order task in the multiple order tasks. When the execution coefficient of each of the multiple order tasks is determined based on the execution coefficient of the first order task and the timing relationship of the multiple order tasks, and 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 timing relationship. For example, if the time interval between the subsequent task and the first task is short, the execution coefficient can be gradually reduced, and if the interval is long, the reduction can be increased. For order tasks with dependent relationships, the execution coefficient is adjusted according to the degree of dependence. 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, thereby obtaining multiple execution coefficients.

[0067] In one possible embodiment, see Figure 3 , Figure 3 for Figure 3 This is one example of a timing relationship diagram provided in an embodiment of the present application. Figure 3 As shown, Figure 3 The five order tasks in are a, b, c, d and e. The time sequence relationship of the five order tasks is as follows: Figure 3, when e is the first order task, the predecessor order tasks of e include c and d, the predecessor order task of d is b, the predecessor order task of b and c is a, and the execution coefficient of e is set to 1. Then, according to the timing relationship diagram, the execution coefficients of the five order tasks can be set to 2, 1.8, 1.5, 1.2 and 1 respectively. It can be obtained that the execution order of the five order tasks is a, b, c, d and e. Since a has the highest execution coefficient, a is taken as the target order task, and the connection state of a is set to the first connection state, so that the B end can execute a after the connection is established. After a is executed, when the target connector is powered on, the connection states of b, c, d and e can be set to the first connection state in sequence, so that the B end can execute after the connection is established.

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

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

[0070] Step S402: determining a content label of each task content in the multiple task contents based on the multiple task contents to obtain multiple content labels;

[0071] Step S403: determining a dependency coefficient between every two task contents in the plurality of task contents based on the plurality of content tags, and obtaining at least one dependency coefficient;

[0072] Step S404: determining a temporal relationship among a plurality of task contents based on at least one dependency coefficient.

[0073] In a possible embodiment, when obtaining the task content of each order task in multiple order tasks and obtaining multiple task contents, detailed description information of multiple order tasks is extracted from the database of the order task management system, and the extracted information is cleaned and preprocessed to remove irrelevant characters and formats to obtain clear and accurate task content text. When determining the content label of each task content in multiple task contents based on the multiple task contents and obtaining multiple content labels, natural language processing technology and machine learning algorithms are used to perform lexical analysis, syntactic analysis and semantic understanding on each task content. According to the analysis results, words or phrases that can represent the core theme and key elements of the task are extracted as content labels. For example, if the task is "replace the engine spark plug and check the ignition system", the labels that may be extracted are one or more labels of "engine", "spark plug", "ignition system", "replace", and "check". When the dependency coefficient of each two task contents in the multiple task contents is determined based on multiple content tags and at least one dependency coefficient is obtained, the tag sets of each two task contents are compared and matched, and the overlap, inclusion relationship or association degree of the two task content tags are calculated. According to the pre-set rules and algorithms, the overlap or association degree is converted into a dependency coefficient. For example, if the tags of two tasks overlap by 50%, the dependency coefficient can be set to 0.5. When the temporal relationship of multiple task contents is determined based on at least one dependency coefficient, the task pairs are sorted according to the size of the dependency coefficient. For task pairs with higher dependency coefficients, the dependency relationship between them is closer, and a closer connection line distance of the temporal relationship diagram can be set. For order tasks without direct dependency, their relative positions in the temporal relationship are determined according to the urgency and creation time.

[0074] In the embodiments of the present application, by analyzing the dependency relationship of the task content, the order of task execution can be accurately determined to avoid duplication of work or errors caused by improper task execution order. By executing tasks according to a reasonable timing relationship, waiting time and idle resources can be reduced, making the entire workflow smoother, thereby improving work efficiency, ensuring that tasks with close dependencies are executed in the correct order, and reducing the risks and errors of subsequent tasks caused by unfinished or improperly completed predecessor tasks.

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

[0076] Step S501: determining the number of predecessor tasks of a first order task based on the time sequence relationship of multiple order tasks;

[0077] Step S502: if the number of the predecessor tasks of the first order task is not zero, obtain all the predecessor tasks of the first order task to obtain at least one predecessor task;

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

[0079] Step S504: determining the execution coefficient of each of the multiple order tasks based on the preset idle time, multiple execution times and the temporal relationship of the multiple order tasks to obtain multiple execution coefficients.

[0080] In a possible embodiment, the estimated or actual execution time of each predecessor task can be predicted based on the relevant records or planned arrangements of each predecessor task. The preset idle time can be selected and determined by the C-end customer, and the preset idle time is the time when multiple current order tasks can be executed.

[0081] In one possible embodiment, see Figure 4 , Figure 4 This is the second example of a timing relationship diagram provided in the embodiment of the present application. Figure 4 As shown, Figure 4 The four order tasks in are f, g, h and i. The timing relationship of the four order tasks is as follows: Figure 4 . When h is the first order task, the preceding order tasks of h include f and g, the subsequent task of h is i, and the execution coefficient of h is set to 1. Then, according to the timing relationship diagram, the execution coefficients of the four order tasks can be set to 2, 2, 1, and 0.5 respectively. For f and g with the same execution coefficients, the execution time of f and g is determined. When the execution time of f and g is 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. It can be obtained that the execution order of the four order tasks is f, g, h, and i. Since f has the highest execution coefficient, f is taken as the target order task, and the connection state of f is set to the first connection state, so that the B end can execute f after establishing a connection.

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

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

[0084] Step S62: determining a first weight of each creation time among a plurality of creation times, and obtaining a plurality of first weights;

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

[0086] Step S64: determining a second weight of each task priority among the plurality of task priorities to obtain a plurality of second weights;

[0087] Step S65: determining a first order task among the plurality of order tasks based on the plurality of first weights and the plurality of second weights.

[0088] In a possible embodiment, the first order task may be determined based on the creation time of each order task among the multiple order tasks and the task priority of each order task among the multiple order tasks, without the need for the C-end user to make a selection.

[0089] In a possible embodiment, different task types correspond to different task priorities, and the corresponding relationship can be predetermined by the C-end user. For example, the priority of an emergency maintenance task is higher than that of a regular maintenance task.

[0090] In a possible embodiment, the creation time record of each order task is extracted from the database of the order task management system, and the extracted creation time is standardized to ensure that the format is unified and accurate, and the weight distribution rules for the creation time are determined. For example, the earlier the creation time, the higher the weight. Linear or nonlinear weight distribution can be performed in chronological order, and the first weight value of each creation time is determined according to the determined rules. Determine the weight distribution rules for task priorities, different priorities correspond to different weight values, the higher the task priority, the higher the second weight value, and determine the second weight value of each task priority. The first weight of the creation time of each order task and the second weight of the task priority are comprehensively calculated, and the weighted average is used to compare the comprehensive weight values ​​of multiple order tasks, and the order task with the highest comprehensive weight value is determined as the first order task. In the embodiment of the present application, when the C-end user does not manually select the first order task, by considering the creation time and task priority at the same time, it is avoided to make a decision based on only a single factor, so that the selection of the first order task is more comprehensive and reasonable.

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

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

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

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

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

[0096] In a possible embodiment, the first order task may be determined by the execution information of each historical order task in at least one historical order task, without the need for the C-end user to make a selection and determination.

[0097] In a possible embodiment, all historical order task data related to the target vehicle are extracted from the vehicle maintenance record database or the related order management system, and the extracted data are screened and sorted to remove duplicate or invalid records to ensure that the acquired historical order tasks are accurate and complete. For each historical order task, its execution record is analyzed in detail, the number of executions of each historical order task is obtained to determine the execution frequency, and the specific time point or time period of each execution of each historical order task is obtained as the execution node. The evaluation rules are set. For example, the execution frequency of some order tasks is once a week or once a day, and the execution nodes of some order tasks are related to the season. For order tasks with high execution frequency or the current execution time corresponding to the execution node, a weight evaluation is performed, and the order task with the highest weight value in the evaluation result is used as the first order task. In the embodiment of the present application, when the C-end user does not manually select the first order task, the historical maintenance and service data of the vehicle can be used to determine the current first order task based on actual experience, and the reliability of the decision can be improved by analyzing the execution frequency and nodes.

[0098] In one possible embodiment, see Figure 5 , Figure 5 This is the third example of a timing relationship diagram provided in the embodiment of the present application. Figure 5 As shown, Figure 5 The four order tasks in are j, k, m and n. The timing relationship of the four order tasks is as follows: Figure 5 When the first order task is n, the preceding order task of n is j, and k and m have no timing 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 end B can execute j after establishing a connection.

[0099] In a possible embodiment, for multiple order tasks of the C-end, there may be a way to complete multiple order tasks of the C-end by establishing connections with multiple B-ends in sequence. The C-end sets the connectable order tasks in advance, and only allows the B-end to connect to the order tasks prepared by the C-end, so as to avoid the B-end corresponding to other order tasks of the C-end connecting to the C-end, resulting in invalid connection, wasting the time of the B-end and C-end users, so as to improve the execution efficiency of the C-end order tasks. Specifically, after the C-end connector is powered on, the vehicle VIN of the remote vehicle is read, and the number of order tasks corresponding to the current VIN of the C-end connector is queried. According to the number of order tasks, if there is only one task, the task is directly set to a connectable state, and the B-end corresponding to the order task is allowed to connect and process the task. If there are multiple tasks, the C-end user is prompted to select the target order task currently expected to be executed. If the C-end user does not select within the preset time, the last published order task can be selected by default according to the release time of each order task in the multiple order tasks, and it is used 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 there is no task, the C-end user is prompted that there is no remote order task for the target vehicle, and whether the order task for the target vehicle needs to be released. The B-end queries whether the C-end corresponding to the order task can be connected. If it can be connected, the C-end that can be connected is automatically connected to complete the super remote task order. In the embodiment of the present application, after the C-end connector is powered on, the status of the task available for connection to the B-end is automatically set. If the C-end user needs to select the task that needs to be executed currently, the C-end user can select it first, avoiding the invalid connection between the B-end and the C-end when there are multiple tasks on the C-end, which causes the order to be suspended and reconnected, thereby improving the efficiency of order completion.

[0100] In summary, in the implementation mode of the present application, after the target connector is powered on, the vehicle identification code of the target vehicle is obtained through the first diagnostic module, and the number of order tasks is obtained based on the vehicle identification code. Then, the target order task is determined based on the number of order tasks, and the connection state of the target order task is set to the first connection state, wherein the first connection state is used to make the target order task in a selectable state. Next, the target order task is displayed to the second diagnostic module based on the first connection state, and the target touch parameters of the second diagnostic module are obtained, wherein the target touch parameters are used to select the target order task. Finally, 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. Thus, the target vehicle is determined through the target connector, the number of order tasks is obtained by obtaining the vehicle identification code of the target vehicle, and the connection state of the target order task is set after the target order task is determined for the second diagnostic module to select, connect and execute, which can reduce the number of invalid connections during the remote maintenance diagnosis process, thereby improving the completion efficiency of remote diagnosis orders.

[0101] The method of the embodiment of the present invention is described in detail above, and the device of the embodiment of the present invention is provided below.

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

[0103] An acquisition unit 601 is used to acquire vehicle information of a target vehicle through a first diagnostic module after the target connector is powered on, wherein the vehicle information of the target vehicle includes a vehicle identification code of the target vehicle;

[0104] Obtain the number of order tasks based on the vehicle information of the target vehicle;

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

[0106] Setting the connection state of the target order task to a first connection state, where the first connection state is used to make the target order task in a selectable state;

[0107] Displaying the target order task to the second diagnosis module based on the first connection state;

[0108] Acquire target touch parameters of the second diagnosis module, where the target touch parameters are used to select a target order task;

[0109] A connection is established between the first diagnosis module and the second diagnosis module based on the target touch parameter 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 configured to:

[0111] When the number of order tasks is single, the current order task of the target vehicle is used as the target order task;

[0112] When there are multiple order tasks, multiple order tasks of the target vehicle are obtained;

[0113] Determine the execution coefficient of each order task among the multiple order tasks to obtain multiple execution coefficients, where the execution coefficients are used to indicate the execution priority;

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

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

[0116] Get the first order task among multiple order tasks;

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

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

[0119] The execution coefficient of each of the multiple order tasks is determined based on the execution coefficient of the first order task and the time sequence relationship of the multiple order tasks to obtain multiple execution coefficients.

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

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

[0122] Determine a content label of each task content in the multiple task contents based on the multiple task contents to obtain multiple content labels;

[0123] Determine a dependency coefficient between every two task contents in the plurality of task contents based on the plurality of content tags, and obtain at least one dependency coefficient;

[0124] A temporal relationship among a plurality of 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 timing relationship of the multiple order tasks to obtain the multiple execution coefficients, the processing unit 602 is specifically configured to:

[0126] Determine the number of predecessor tasks of the first order task based on the temporal relationship of the multiple order tasks;

[0127] If the number of predecessor tasks of the first order task is not zero, obtain all predecessor tasks of the first order task to obtain at least one predecessor task;

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

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

[0130] In some possible embodiments, in acquiring the first order task among the multiple order tasks, the processing unit 602 is specifically configured to:

[0131] Get the creation time of each order task in multiple order tasks to obtain multiple creation times;

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

[0133] Determine a task priority of each of the multiple order tasks based on a task type of each of the multiple order tasks to obtain multiple task priorities;

[0134] Determine a second weight of each task priority among the plurality of task priorities to obtain a plurality of second weights;

[0135] A first order task among the plurality of order tasks is determined based on the plurality of first weights and the plurality of second weights.

[0136] In some possible embodiments, in acquiring the first order task among the multiple order tasks, the processing unit 602 is specifically configured to:

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

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

[0139] A first order task among the plurality of order tasks is determined based on the at least one execution information.

[0140] See also Figure 7 , Figure 7 Schematic diagram of the structure of a diagnostic device provided in an embodiment of the present application. Figure 7 As shown, the diagnostic device 700 includes a transceiver 701, a processor 702 and a memory 703. They are connected via a bus 704. The memory 703 is used to store computer programs and data, and can transmit the data stored in the memory 703 to the processor 702. The diagnostic device can be the connection device of the above-mentioned remote diagnostic order, and the processor 702 can be the above-mentioned acquisition unit 601 and processing unit 602.

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

[0142] After the target connector is powered on, vehicle information of the target vehicle is acquired through the first diagnostic module, the vehicle information of the target vehicle including a vehicle identification code of the target vehicle;

[0143] Obtain the number of order tasks based on the vehicle information of the target vehicle;

[0144] Determine the target order task based on the number of order tasks;

[0145] Setting the connection state of the target order task to a first connection state, where the first connection state is used to make the target order task in a selectable state;

[0146] Displaying the target order task to the second diagnosis module based on the first connection state;

[0147] Acquire target touch parameters of the second diagnosis module, where the target touch parameters are used to select a target order task;

[0148] A connection is established between the first diagnosis module and the second diagnosis module based on the target touch parameter 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 the number of order tasks is single, the current order task of the target vehicle is used as the target order task;

[0151] When there are multiple order tasks, multiple order tasks of the target vehicle are obtained;

[0152] Determine the execution coefficient of each order task among the multiple order tasks to obtain multiple execution coefficients, where the execution coefficients are used to indicate the execution priority;

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

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

[0155] Get the first order task among multiple order tasks;

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

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

[0158] The execution coefficient of each of the multiple order tasks is determined based on the execution coefficient of the first order task and the time sequence relationship of the multiple order tasks to obtain multiple execution coefficients.

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

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

[0161] Determine a content label of each task content in the multiple task contents based on the multiple task contents to obtain multiple content labels;

[0162] Determine a dependency coefficient between every two task contents in the plurality of task contents based on the plurality of content tags, and obtain at least one dependency coefficient;

[0163] A temporal relationship among a plurality of 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 to obtain the multiple execution coefficients, the processor 702 is specifically configured to perform the following operations:

[0165] Determine the number of predecessor tasks of the first order task based on the temporal relationship of the multiple order tasks;

[0166] If the number of predecessor tasks of the first order task is not zero, obtain all predecessor tasks of the first order task to obtain at least one predecessor task;

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

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

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

[0170] Get the creation time of each order task in multiple order tasks to obtain multiple creation times;

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

[0172] Determine a task priority of each of the multiple order tasks based on a task type of each of the multiple order tasks to obtain multiple task priorities;

[0173] Determine a second weight of each task priority among the plurality of task priorities to obtain a plurality of second weights;

[0174] A first order task among the plurality of order tasks is determined based on the plurality of first weights and the plurality of second weights.

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

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

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

[0178] A first order task among the plurality of order tasks is determined based on the at least one execution information.

[0179] An embodiment of the present application also provides a computer-readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement part or all of the steps of the method for implementing the connection of any remote diagnostic order recorded in the above method embodiments.

[0180] An embodiment of the present application also provides a computer program product, which includes a non-transitory computer-readable storage medium storing a computer program, and the computer program is operable to cause a computer to execute part or all of the steps of any one of the remote diagnostic order connection methods recorded in the above method embodiments.

[0181] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0182] In the above embodiments, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0183] In the several embodiments provided in the present application, it should be understood that the disclosed device can be implemented in other ways. For example, the device embodiments described above are only schematic, such as the division of the modules, which is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection of the device or module can be electrical or other forms.

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

[0185] In addition, each functional module in each embodiment of the present application can be integrated into a processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The above integrated modules can be implemented in the form of hardware or software program modules.

[0186] If the integrated module is implemented in the form of a software program module and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of the present 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, which is stored in a memory and includes several instructions for a computer device (which can be a personal computer, a server or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned memory includes: U disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), mobile hard disk, disk or optical disk and other media that can store program codes.

[0187] A person skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable memory, and the memory can include: a flash drive, a read-only memory (English: Read-Only Memory, abbreviated as: ROM), a random access memory (English: Random Access Memory, abbreviated as: RAM), a magnetic disk or an optical disk, etc.

[0188] The embodiments of the present application are introduced in detail above. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method and core idea of ​​the present application. At the same time, for general technical personnel in this field, according to the idea of ​​the present application, there will be changes in the specific implementation method and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A connection method for a remote diagnosis order, characterized in that: 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 through a target connector; the method includes: After the target connector is powered on, obtaining a vehicle identification code of the target vehicle through the first diagnostic module; Obtaining the number of order tasks based on the vehicle identification code; Determine the target order task based on the number of order tasks; Setting the connection state of the target order task to a first connection state, wherein the first connection state is used to make the target order task in a selectable state; displaying the target order task to the second diagnosis module based on the first connection status; Acquire a target touch parameter of the second diagnostic module, where the target touch parameter is 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 parameter to execute the target order task.

2. The method according to claim 1, characterized in that The determining the target order task based on the number of order tasks includes: When the number of the order tasks is single, the current order task of the target vehicle is used as the target order task; When there are multiple order tasks, obtain multiple order tasks for the target vehicle; Determine the execution coefficient of each order task in the plurality of order tasks to obtain a plurality of execution coefficients, wherein the execution coefficients are used to indicate the execution priority; The order task with the highest execution coefficient among the multiple order tasks is used as the target order task.

3. The method according to claim 2, characterized in that The determining the execution coefficient of each of the multiple order tasks to obtain multiple execution coefficients includes: Obtaining a first order task among the multiple order tasks; Setting the execution coefficient of the first order task; Determining the timing relationship of 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 timing relationship between the multiple order tasks to obtain the multiple execution coefficients.

4. The method according to claim 3, characterized in that Determining the temporal relationship of the multiple order tasks includes: Obtaining the task content of each order task in the multiple order tasks to obtain multiple task contents; Determine a content label of each task content in the multiple task contents based on the multiple task contents to obtain multiple content labels; Determine a dependency coefficient between every two task contents in the plurality of task contents based on the plurality of content tags to obtain at least one dependency coefficient; The temporal relationship of the plurality of task contents is determined based on the at least one dependency coefficient.

5. The method according to claim 4, characterized in that The step of determining the execution coefficient of each of the multiple order tasks based on the execution coefficient of the first order task and the time sequence relationship of the multiple order tasks to obtain the multiple execution coefficients includes: Determine the number of predecessor tasks of the first order task based on the temporal relationship of the multiple order tasks; If the number of predecessor tasks of the first order task is not zero, obtain all predecessor tasks of the first order task to obtain at least one predecessor task; Determining the execution time of each predecessor task of the at least one predecessor task to obtain multiple execution times; The execution coefficient of each of 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 to obtain the multiple execution coefficients.

6. The method according to any one of claims 3 to 5, characterized in that: The obtaining of the first order task among the multiple order tasks includes: Obtaining the creation time of each order task in the multiple order tasks to obtain multiple creation times; Determine a first weight of each creation time among the multiple creation times to obtain multiple first weights; Determine a task priority of each of the multiple order tasks based on a task type of each of the multiple order tasks to obtain multiple task priorities; Determine a second weight of each task priority among the plurality of task priorities to obtain a plurality of second weights; A first order task among the plurality of order tasks is determined based on the plurality of first weights and the plurality of second weights.

7. The method according to any one of claims 3 to 5, characterized in that: The obtaining of the first order task among the multiple order tasks includes: Obtain at least one historical order task of the target vehicle; Determine execution information of each historical order task in the at least one historical order task to obtain at least one execution information, wherein the execution information includes an execution frequency and an execution node; A first order task among the plurality of order tasks is determined based on the at least one execution information.

8. A connection device for a remote diagnosis order, characterized in that: Applied to a diagnostic device, the diagnostic device comprises 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 of the remote diagnostic order comprises 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, wherein the vehicle information of the target vehicle includes a vehicle identification code of the target vehicle; Acquire the number of order tasks 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; Setting the connection state of the target order task to a first connection state, wherein the first connection state is used to make the target order task in a selectable state; displaying the target order task to the second diagnosis module based on the first connection status; Acquire a target touch parameter of the second diagnostic module, where the target touch parameter is 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 parameter to execute the target order task.

9. A diagnostic device, characterized in that: include: A processor and a memory, wherein the processor is connected to the memory, the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory so that the diagnostic device executes the method according to any one of claims 1 to 7.

10. 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 according to any one of claims 1 to 7.

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