Reservation in-store maintenance control method and device, electronic equipment and storage medium

Abstract

The invention provides a reservation in-store maintenance control method and device, electronic equipment and a storage medium, and relates to the technical field of vehicle reservation maintenance. The method comprises the following steps: acquiring fault information sent by a user terminal; the fault information is generated by the user terminal after all fault assemblies are determined; a retrieval instruction is sent to all maintenance shops according to the fault information, so that all the maintenance shops make feedback to the server after determining inventory conditions of all the standby assemblies; taking the first type of maintenance shop and the second type of maintenance shop as optional maintenance shops; and arranging the selectable maintenance shops into a push list and sending the push list to the user terminal for the user to select and reserve. The problems that the maintenance period is prolonged and time is wasted due to the fact that a replaceable standby assembly is lacked in vehicle in-store maintenance are solved, and the experience of a user in the aspect of maintenance service can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle scheduled maintenance, and in particular to a method, device, electronic equipment and storage medium for scheduled in-store maintenance control. Background Art

[0002] In real life, when a vehicle breaks down, the owner will generally move the vehicle to a nearby repair shop for repair. However, due to different vehicle brands, the assembly specifications are also different, so that after the owner moves the vehicle to the repair shop, the repair shop tells him that the spare assembly that can be used to replace the faulty assembly is out of stock, resulting in the owner needing to move the vehicle to other repair shops again or waiting for the delivery of the spare assembly, which undoubtedly prolongs the maintenance cycle and wastes a lot of the owner's time, thereby reducing the user experience of the maintenance service.

[0003] There is currently no effective technical solution to the above problems. Summary of the invention

[0004] The purpose of the present invention is to provide a method, device, electronic device and storage medium for controlling appointment for in-store repair, so as to solve the problem of extended repair cycle and time waste due to lack of replaceable spare assemblies when vehicles are repaired in-store, which is conducive to improving the user experience in repair services.

[0005] In a first aspect, the present invention provides a method for controlling appointment for in-store repair, which is applied to a server of a repair appointment system, wherein the server is communicatively connected with a plurality of repair shops; The method for controlling scheduled in-store maintenance comprises the following steps: S1. Get fault information sent by the user terminal; the fault information is generated by the user terminal after determining all faults; S2. Sending a search command to all the repair shops according to the fault information, so that each of the repair shops can provide feedback to the server after determining the inventory of all spare assemblies for replacing each of the faulty assemblies; S3. The first type of repair shop and the second type of repair shop are selected as optional repair shops; the first type of repair shop is a repair shop that reports that all the spare assemblies exist; the second type of repair shop is a repair shop that reports that only some of the spare assemblies exist; S4. Arrange the optional repair shops into a push list and send the push list to the user terminal for the user to select an appointment; The specific steps in step S4 include: S41 obtains the first distance between each of the optional repair shops and the user terminal; S42. Arranging the optional repair shops in order into the push list according to the first journey; The specific steps in step S42 include: S42A1. When all the optional repair shops are the first type of repair shops, all the optional repair shops are arranged in order from near to far in the corresponding first distance into the push list; S42B1. When all the optional repair shops are the second type of repair shops, multiple optional repair shops that can just gather all the spare assemblies are selected as the group to be selected; S42B2 obtains the second distance between all the optional repair shops in the same selected group; S42B3 selects one of the optional repair shops as the preferred repair shop, the preferred repair shop and the second distance between all the optional repair shops in the same group of candidates are less than or equal to the first distance between the preferred repair shop and the user terminal, and the preferred repair shop group exists as the preferred group; S42B4. According to the first distance between the preferred repair shop corresponding to each preferred group and the user terminal, all the preferred groups are arranged into the push list in order from near to far.

[0006] The in-store maintenance reservation control method provided by the present invention ensures that the corresponding spare assemblies are available for replacement after the user transfers the vehicle to the repair shop by first confirming the inventory status with the repair shop, thereby avoiding the problems of extended maintenance cycle and time waste, and achieving the effect of improving user experience; not only considering the actual maintenance capacity of the repair shop, but also taking the geographical location factor into consideration, providing users with a more comprehensive and personalized selection basis; enabling the preferred repair shop to gather all spare assemblies, and then the vehicle can be repaired immediately after arriving at the preferred repair shop, which is conducive to improving maintenance efficiency and achieving the effect of shortening the maintenance cycle.

[0007] Furthermore, the fault information is generated by the user terminal after the user conducts question-and-answer interaction with a preset AI diagnostic model through the user terminal and determines the fault component.

[0008] The AI ​​diagnostic model can simulate the diagnostic process of professional technicians and provide more comprehensive and accurate preliminary diagnostic results. This not only improves the accuracy of fault location, but also greatly improves user experience and maintenance efficiency.

[0009] Furthermore, the method further comprises the steps of: S5. After the user chooses to make an appointment with the preferred repair shop, any preferred group that includes the preferred repair shop selected by the user is selected as the target group, and notification information is sent to each optional repair shop in the target group, so that all optional repair shops in the target group gather all the spare assemblies at the location of the preferred repair shop.

[0010] Furthermore, the fault information includes a record of interaction between the user and the AI ​​diagnostic model; The method for controlling appointment for in-store maintenance also includes the steps of: S6. After the user chooses to make an appointment with the optional repair shop, the optional repair shop selected by the user is used as the target repair shop and the fault information is sent to the target repair shop so that the maintenance personnel of the target repair shop can continue to determine the faulty parts in the faulty assembly by conducting question-and-answer interaction with the AI ​​diagnostic model based on the interaction record.

[0011] In a second aspect, the present invention provides a maintenance reservation control device for a shop, which is applied to a server of a maintenance reservation system, wherein the server is communicatively connected with a plurality of maintenance shops; The in-store maintenance reservation control device comprises: An acquisition module, used for acquiring fault information sent by a user terminal; the fault information is generated by the user terminal after all fault components are determined; A first sending module, configured to send a search instruction to all the repair shops according to the fault information, so that each of the repair shops can provide feedback to the server after determining the inventory status of all spare assemblies for replacing each of the faulty assemblies; A management module is used to select a first-category repair shop and a second-category repair shop as optional repair shops; the first-category repair shop is a repair shop that reports that all the spare assemblies are available; the second-category repair shop is a repair shop that reports that only some of the spare assemblies are available; A sorting module, used for arranging the optional repair shops into a push list and sending the push list to the user terminal for the user to select and make an appointment; The sorting module is used to compile the optional repair shops into a push list and send the push list to the user terminal for the user to select an appointment. S41 obtains the first journey of each optional repair shop and the user terminal; S42. Arrange the optional repair shops in an orderly manner into a push list according to the first journey; The sorting module is used to arrange the optional repair shops into a push list in order according to the first journey. S42A1. When all optional repair shops are first-class repair shops, all optional repair shops are arranged into a push list in order from near to far according to the corresponding first distance; S42B1. When all optional repair shops are of the second category, multiple optional repair shops that can just gather all spare assemblies are selected as the candidate group; S42B2 obtains the second journey between all optional repair shops in the same candidate group; S42B3 selects an optional repair shop as the preferred repair shop, the preferred repair shop and the second distance between all optional repair shops in the same candidate group are less than or equal to the first distance between the preferred repair shop and the user terminal, there will be a preferred repair shop in the candidate group as the preferred group; S42B4. According to the first distance between the preferred repair shop corresponding to each preferred group and the user terminal, all preferred groups are arranged into a push list in order from near to far.

[0012] The reservation control device for in-store maintenance provided by the present invention uses this reservation control method, so that users can confirm whether the maintenance shop has the required spare assembly before departure, avoiding the situation of finding out of stock after arrival. At the same time, the maintenance shop can also understand the user's needs in advance, make corresponding preparations, and improve service efficiency.

[0013] In a third aspect, the present invention provides an electronic device comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the in-store maintenance appointment control method provided in the first aspect are executed.

[0014] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps of the method for controlling scheduled in-store repairs provided in the first aspect are executed.

[0015] As can be seen from the above, the in-store maintenance appointment control method provided by the present invention predetermines the faulty assembly of the vehicle and then notifies each repair shop to confirm the inventory status, thereby screening out repair shops that have spare assemblies for replacing the faulty assembly and pushing them to the user for selection, thereby preventing users from blindly selecting repair shops and ensuring that users can quickly complete the repair after transferring the vehicle to the repair shop, thereby shortening the maintenance cycle, reducing time waste and improving user experience.

[0016] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or be understood by implementing the embodiments of the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 A flow chart of a method for controlling scheduled in-store maintenance provided by an embodiment of the present invention.

[0018] Figure 2 A schematic diagram of a location of a preferred repair shop in an embodiment of the present invention.

[0019] Figure 3A schematic diagram of the structure of a maintenance reservation control device provided in an embodiment of the present invention.

[0020] Figure 4 A schematic diagram of the structure of an electronic device provided by an embodiment of the present invention.

[0021] Description of labels: 100, acquisition module; 200, first sending module; 300, management module; 400, sorting module; 500, second sending module; 600, third sending module; 13, electronic device; 1301, processor; 1302, memory; 1303, communication bus. DETAILED DESCRIPTION

[0022] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. The components of the embodiments of the present invention generally described and shown in the drawings here can be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the drawings is not intended to limit the scope of the claimed invention, but merely represents the selected embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative work belong to the scope of protection of the present invention.

[0023] It should be noted that similar reference numerals and letters represent similar items in the following drawings, so once an item is defined in one drawing, it does not need to be further defined and explained in the subsequent drawings. At the same time, in the description of the present invention, the terms "first", "second", etc. are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0024] In real life, when a high-end sedan has an engine failure, the owner selects the nearest repair shop A through the reservation system. However, after arriving at repair shop A, the owner is informed that the shop lacks specific engine spare parts for this model. Repair shop A recommends that the owner transfer the vehicle to repair shop B, which is 20 kilometers away, or wait 3-5 working days for spare parts to be transferred. In this case, the owner has to choose between extra time and energy consumption, which seriously affects the maintenance efficiency and user experience.

[0025] Reference Figure 1 , the present invention provides a method for controlling appointment for in-store maintenance, which is applied to a server of a maintenance appointment system, and the server is connected in communication with a plurality of maintenance shops; The method for controlling appointment for in-store maintenance includes the following steps: S1. Obtain fault information sent by the user terminal; fault information is generated by the user terminal after determining all faults; S2. Sending a search command to all repair shops according to the fault information, so that each repair shop can make feedback to the server after determining the inventory of all spare assemblies used to replace each faulty assembly; S3. The first category and the second category are considered optional repair shops; the first category is the repair shop that reported that all spare assemblies are available; the second category is the repair shop that reported that only some spare assemblies are available; S4. Arrange the optional repair shops into a push list and send the push list to the user terminal for the user to select and make an appointment.

[0026] In this embodiment, the system can ensure that the selected repair shop has the necessary repair conditions before the user actually goes to the repair shop through unified management and scheduling by the server. This not only avoids the trouble of users moving vehicles multiple times, but also improves the repair efficiency.

[0027] In actual applications, the system can further optimize the arrangement logic of the push list. For example, the distance threshold can be set to 15 kilometers, and repair shops within this range can be pushed first; recommended repair shops can be set for different models based on historical repair data; and the busy and idle status of repair shops can be displayed in real time to help users make better choices.

[0028] Through this reservation control method, users can confirm whether the repair shop has the required spare assembly before departure, avoiding the situation of finding out of stock after arrival. At the same time, the repair shop can also understand user needs in advance, make corresponding preparations, and improve service efficiency. This two-way interactive mechanism effectively improves the user experience of maintenance services and shortens the maintenance cycle.

[0029] Specifically, for example, a user reports a vehicle failure through a vehicle maintenance application on a smartphone. The application has a built-in AI diagnostic module that determines the vehicle's faulty assembly through interactive questions and answers with the user. For example, a user reports an abnormal engine noise, and the AI ​​diagnostic module preliminarily determines that it may be a crankshaft assembly failure through a series of questions (such as the characteristics of the abnormal noise, the timing of occurrence, etc.). Subsequently, the application generates fault information containing the faulty assembly information and sends it to the server of the maintenance reservation system.

[0030] After receiving the fault information, the server immediately sends a search command to all the cooperative repair shops in the system. After receiving the command, the inventory management system of each repair shop automatically checks the inventory of crankshaft bearings and related spare parts, and feedbacks the results to the server within 30 seconds. Based on the feedback, the server divides the repair shops into two categories: the first category of repair shops has all the required spare parts, and the second category of repair shops only has some spare parts.

[0031] The system then compiles a push list of 10 repair shops based on factors such as the shop category, distance from the user's current location, and historical reviews. In the list, the first-category repair shops are prioritized, followed by the second-category repair shops. This list is pushed to the user through the app, and the user can view detailed information about each repair shop, including distance, estimated waiting time, spare parts status, etc., and make an appointment directly in the app.

[0032] Compared with the existing technology, in the traditional mode, users may need to contact multiple repair shops in person to inquire about spare parts, or find out that necessary spare parts are missing after arriving at the repair shop. This application greatly improves the efficiency of repair matching through intelligent fault diagnosis and real-time inventory query. For example, in an actual application, the entire process from reporting a fault to successfully making an appointment with a suitable repair shop took only 5 minutes, while the traditional method may take hours or even days.

[0033] In addition, the solution of this application can effectively reduce unnecessary vehicle movement. In the traditional mode, users may need to move their vehicles from one repair shop to another, increasing the risk of faulty vehicles on the road. Through the reservation system of this application, users can directly choose a repair shop that has all the required spare parts and complete the repair in one go, which not only saves time but also reduces safety risks.

[0034] In addition, this approach not only facilitates user selection, but also provides repair shops with an incentive to improve inventory management. Data analysis after the system has been running for a period of time shows that repair shops participating in this system have increased their spare parts availability by an average of 15%, which directly improves users' repair experience and repair efficiency.

[0035] In some embodiments, the fault information is generated by the user terminal after the user conducts a question-and-answer interaction with a preset AI diagnostic model through the user terminal and determines the fault component.

[0036] This embodiment determines the faulty assembly through question-and-answer interaction between the user and the AI ​​diagnostic model. This method can improve diagnostic accuracy, provide a user-friendly interactive method, improve efficiency, standardize the diagnostic process, and achieve data accumulation. The fault information generated in this way is more accurate and comprehensive, providing a reliable basis for subsequent maintenance appointments and actual maintenance work. At the same time, this method also improves the efficiency and user experience of the entire appointment maintenance process. In addition, with the assistance of the AI ​​diagnostic model, the user only needs to confirm the fault to a specific assembly without confirming the specific accessories. On the one hand, this is conducive to reducing the interaction time, thereby shortening the maintenance cycle, while also reducing the development requirements of the AI ​​diagnostic model. On the other hand, it can be better suitable for users who are not familiar with vehicle knowledge, ensuring that the user interacts with the AI ​​diagnostic model more smoothly.

[0037] AI diagnostic models can be implemented in a variety of ways. For example, a deep learning-based natural language processing model, such as BERT or GPT, can be used to understand the fault description entered by the user. The model can be trained with a large amount of historical maintenance data to learn the relationship between various fault symptoms and the corresponding fault assembly.

[0038] Another implementation method is to use a rule-based expert system combined with a decision tree algorithm. The system can guide users to describe the fault symptoms through a series of targeted questions according to the preset fault diagnosis rules, and finally locate the possible fault assembly.

[0039] The question-and-answer interaction process can be designed as a multi-round dialogue. Based on the user's initial description, the AI ​​diagnostic model can ask a series of follow-up questions, such as "Does the vehicle make an abnormal sound?", "Is the fault light on?", etc., to collect more detailed information. The user's answer will be analyzed in real time, affecting the choice of the next question, thereby gradually narrowing the scope of the fault.

[0040] After determining the fault assembly, the user terminal will generate a fault information report containing the fault description, possible fault assembly, and the entire question-and-answer process record. This report not only provides accurate information for maintenance appointments, but also provides valuable reference for subsequent maintenance work.

[0041] The technical solution of this application is closely integrated with the other steps of the maintenance appointment control method to form a complete fault diagnosis and maintenance appointment process. The accurate fault information generated by the AI ​​diagnostic model makes the subsequent repair shop screening and appointment process more accurate and efficient. For example, based on the AI ​​diagnostic results, the system can more accurately send retrieval instructions to the repair shop to query the inventory of the required spare assemblies, thereby improving the efficiency and accuracy of the entire appointment process.

[0042] Specifically, suppose a user's vehicle experiences abnormal shaking and unstable idling. The user interacts with the AI ​​diagnostic model through a mobile app: User: My car has been shaking a lot when idling recently, which doesn’t feel normal.

[0043] AI: Got it. Have you noticed the following: 1. Is the engine warning light on? 2. Is the shaking accompanied by any abnormal sound? 3. Does the vibration also occur when accelerating? User: The engine warning light did not come on, but there was indeed a slight abnormal sound, and the shaking was reduced when accelerating.

[0044] AI: According to your description, there may be problems with the following components: 1. Spark plug; 2. Fuel injector; 3. Vacuum pipeline.

[0045] I recommend focusing your inspection on these parts. Do you notice anything else that's unusual? User: I also noticed that the fuel consumption seemed a bit higher than usual.

[0046] AI: Got it. Considering the increase in fuel consumption, the most likely fault is the fuel system, especially the fuel injector. It is recommended that you make an appointment with a repair shop to check the fuel system, especially the condition of the fuel injector.

[0047] Based on this interaction, the user terminal generates a detailed fault information report, including the symptoms described by the user, the AI ​​analysis process and the final possible fault assembly (fuel system). This report is sent to the maintenance reservation system, which inquires about the inventory of spare parts related to the fuel system from various repair shops and finally recommends a suitable repair shop to the user.

[0048] Compared with traditional fault diagnosis methods, traditional methods usually rely on users' own judgment or simple fault code query, which can easily lead to misjudgment or omission of important information. The AI ​​diagnostic model can simulate the diagnostic process of professional technicians and provide more comprehensive and accurate preliminary diagnostic results. This not only improves the accuracy of fault location, but also greatly improves user experience and maintenance efficiency. At the same time, the AI ​​diagnostic model can continuously learn and update. As data accumulates, the diagnostic accuracy will continue to improve, laying the foundation for future intelligent vehicle maintenance services.

[0049] In some embodiments, the specific steps in step S4 include: S41 obtains the first journey of each optional repair shop and the user terminal; S42. Arrange the optional repair shops in order into a push list according to the first trip.

[0050] This embodiment solves the problem of how to reasonably sort the optional repair shops by obtaining the first distance between each optional repair shop and the user terminal, and arranging the push list based on this distance information. Specifically, firstly, the distance information between the user terminal and each optional repair shop is obtained to provide the necessary data basis for subsequent sorting. Then, using this distance information, the optional repair shops are orderly arranged to form the final push list. This method takes into account the user's geographical location and uses distance as an important basis for sorting, which helps users find nearby repair shops more quickly, thereby saving time and transportation costs, while improving the efficiency of users in selecting repair shops.

[0051] In the implementation process, there are many ways to obtain the first journey. For example, the current location of the user terminal can be obtained using GPS positioning technology, and the actual driving distance from the user terminal to each repair shop can be calculated through the map service API. Another way is to use the address information provided by the user, such as the home address or work address, as the starting point to calculate the distance. In addition, the real-time traffic conditions can be considered, and the estimated driving time can be used as the sorting basis to provide users with more accurate reference information.

[0052] When the optional repair shops are arranged into a push list in order according to the first journey, a variety of sorting strategies can be used. The simplest way is to sort by distance from near to far, and put the repair shop closest to the user at the front of the list. You can also set a distance threshold, such as giving priority to repair shops within 10 kilometers, and then sorting by distance. More complex strategies may involve comprehensive consideration of multiple factors, such as weighted calculation of factors such as distance, repair shop rating, and estimated waiting time, and sorting after obtaining a comprehensive score.

[0053] This distance-based sorting method is closely related to the optional repair shop screening process in the previous step. After determining the repair shop with the required spare assembly, the geographical location factor is further considered, so that users can not only find shops capable of repair, but also give priority to options that are closer. This method of combining spare parts inventory and geographical location greatly improves the efficiency and convenience of users in choosing repair shops.

[0054] In specific implementation, a dynamic push list interface can be designed. For example, when a user opens the maintenance appointment page, the system automatically obtains the user's current location and calculates the distance to each optional repair shop in real time. Suppose there are three optional repair shops A, B, and C, which are 5 kilometers, 8 kilometers, and 12 kilometers away from the user respectively. The system will sort these repair shops from near to far and display the specific distance information of each repair shop in the list. Users can view more options by sliding, and each option can also contain additional information such as the repair shop's rating, estimated waiting time, etc., to help users make a more comprehensive judgment.

[0055] In addition, the system can also provide a map view function, marking the user's location and each repair shop on the map, so that the user can intuitively see the relative location of each repair shop and get more detailed information by clicking on the mark on the map. This visual method further enhances the user's selection experience.

[0056] Compared with the traditional maintenance appointment method, in the traditional method, users usually need to find nearby repair shops by themselves, and then contact them one by one to confirm whether they have the required spare assembly. This process is not only time-consuming, but may also make suboptimal choices due to incomplete information. The solution of this application combines spare parts inventory and geographical location information in an automated way to provide users with an optimized and sorted list of repair shops. This not only greatly saves users' time and energy, but also helps users find the most suitable repair shop faster.

[0057] In this way, the application effectively solves the difficulties faced by users in choosing a repair shop, and improves the efficiency and user experience of the entire appointment repair process. It not only takes into account the actual repair capabilities of the repair shop, but also takes into account the geographical location factor, providing users with a more comprehensive and personalized selection basis. This intelligent recommendation method helps to optimize resource allocation and reduce unnecessary trips for users, thus generating significant practical value in actual applications.

[0058] In some preferred embodiments, the specific steps in step S42 include: S42A1. When all optional repair shops are first-class repair shops, all optional repair shops are arranged into a push list in order from near to far according to the corresponding first distance.

[0059] In some embodiments, the specific steps in step S42 include: S42B1. When all optional repair shops are of the second category, multiple optional repair shops that can just gather all spare assemblies are selected as the candidate group; S42B2 obtains the second journey between all optional repair shops in the same candidate group; S42B3 selects an optional repair shop as the preferred repair shop, the preferred repair shop and the second distance between all optional repair shops in the same candidate group are less than or equal to the first distance between the preferred repair shop and the user terminal, there will be a preferred repair shop in the candidate group as the preferred group; S42B4. According to the first distance between the preferred repair shop corresponding to each preferred group and the user terminal, all preferred groups are arranged into a push list in order from near to far.

[0060] In actual application, a vehicle may have multiple faulty assemblies and therefore needs to prepare corresponding spare assemblies for each faulty assembly. However, the optional repair shops may not always have all spare assemblies. Therefore, in this embodiment, multiple optional repair shops that can gather all spare assemblies are used as a candidate group. By comparing the second distance between each optional repair shop in the candidate group and the first distance between each optional repair shop and the user terminal, if it is determined that there is a preferred repair shop, it means that in the process of the user transferring the vehicle to the preferred repair shop, other optional repair shops in the preferred group except the preferred repair shop can retrieve the spare assemblies to the preferred repair shop, so that the preferred repair shop can gather all spare assemblies, and then the vehicle can be repaired immediately after arriving at the preferred repair shop, which is conducive to improving the maintenance efficiency and achieving the effect of shortening the maintenance cycle. At the same time, the second distance between the preferred repair shop and each optional repair shop is less than or equal to the first distance between the preferred repair shop and the user terminal, which is conducive to completing the retrieval of spare assemblies from each optional repair shop before the user's vehicle arrives at the preferred repair shop, thereby reducing the waste of user time.

[0061] In this embodiment, step S42B1 can be implemented in the following way: the system can use a combination algorithm to traverse the spare assembly conditions of all optional repair shops and find all combinations that can complete all spare assemblies. For example, if spare assemblies A, B, and C are required, repair shop 1 has A and B, repair shop 2 has B and C, and repair shop 3 has A and C, then the combination of repair shop 1 and repair shop 2, or the combination of repair shop 1 and repair shop 3, can be used as a group to be selected.

[0062] For step S42B2, the system can use the map API or pre-stored distance data to calculate the distance between each repair shop in the selected group. For example, the first route and the second route can call the map service API to obtain the actual road distance and estimated driving time. The system will use this distance information as the basis for sorting, and the closer the repair shop is, the higher the ranking will be. In order to improve the user experience, the push list can simultaneously display the specific distance value of each repair shop, such as "500 meters away from you", "2 kilometers away from you", etc., to help users intuitively understand the distance information.

[0063] In step S42B3, the system may adopt an iterative method to sequentially select each repair shop in the candidate group as a candidate preferred repair shop to check whether it meets the conditions. Specifically, the system may first calculate the first distance from the candidate preferred repair shop to the user terminal, and then compare it with the second distance from the repair shop to all other repair shops in the candidate group. Only when all the second distances are less than or equal to the first distance, the repair shop can be determined as the preferred repair shop, and the corresponding candidate group can become the preferred group.

[0064] Finally, in step S42B4, the system may use a sorting algorithm, such as quick sort or merge sort, to sort the first distance from the preferred repair shop to the user terminal from small to large to form a final push list.

[0065] In the process of solving technical problems, this method fully considers the availability of spare assemblies, the distance relationship between repair shops, and the convenience of users. By selecting a combination of repair shops that can gather all spare assemblies as a candidate group, the feasibility of the repair work is ensured. By comparing the distance between repair shops and the distance from the repair shop to the user, the preferred repair shop and the preferred group are selected, which facilitates the allocation of spare assemblies that may be needed, while also considering the convenience of users. The final sorting step further optimizes the user experience, so that repair shops that are closer are displayed first.

[0066] Reference Figure 2 Let's take a specific example: suppose the user's vehicle needs to replace three spare assemblies A, B, and C. After searching, the system finds that there are 5 optional repair shops, namely repair shop 1 (with A and B), repair shop 2 (with B and C), repair shop 3 (with A and C), repair shop 4 (with A and B), and repair shop 5 (with B and C). The system first finds all combinations that can make up A, B, and C, and obtains three candidate groups: (1,2), (1,3), and (4,5). Then the system calculates the distance between the repair shops in each candidate group, as well as the distance from each repair shop to the user. Suppose in group (1,2), the distance from repair shop 1 to repair shop 2 is 5 kilometers, the distance from repair shop 1 to the user is 10 kilometers, and the distance from repair shop 2 to the user is 12 kilometers. Then repair shop 1 can become a preferred repair shop because its distance to repair shop 2 (5 kilometers) is less than its distance to the user (10 kilometers). Similarly, the system will check other candidate groups and finally obtain all the preferred repair shops. Finally, the system sorts these preferred repair shops according to their distance from the user from near to far to form the final push list.

[0067] Compared with the prior art, the traditional method may only consider whether the repair shop has all the spare assemblies, or only consider the distance between the repair shop and the user. The method of the present application not only considers the integrity of the spare assembly, but also considers the distance relationship between the repair shops, which facilitates the possible allocation of spare assemblies. At the same time, by selecting and sorting the preferred repair shops, the feasibility of the repair is guaranteed and the user experience is optimized. This comprehensive consideration of multiple factors enables the method of the present application to better solve the problem of how to reasonably recommend repair shops when all repair shops only have some spare assemblies.

[0068] In some embodiments, the specific steps in step S42 include: S42C1. When a portion of the optional repair shops are first-category repair shops and another portion of the optional repair shops are second-category repair shops, all first-category repair shops and all preferred repair shops are arranged into a push list in order from near to far according to the corresponding first distance.

[0069] In this embodiment, since the preferred repair shop can prepare all spare assemblies before the user arrives, the preferred repair shop is equivalent to the first-class repair shop in a sense. For the user, the user only needs to consider the distance between the user and the repair shop when making a choice of a repair shop. Therefore, arranging all the first-class repair shops and all the preferred repair shops in order according to the first distance can provide the user with reliable information, thereby facilitating the user to repair the vehicle and helping to improve the user experience in terms of repair services.

[0070] In some embodiments, the method for controlling appointment for in-store maintenance further includes the steps of: S5. After the user selects to make an appointment with a preferred repair shop, any preferred group that includes the preferred repair shop selected by the user is selected as the target group, and notification information is sent to each optional repair shop in the target group, so that all optional repair shops in the target group gather all spare assemblies at the location of the preferred repair shop.

[0071] In this embodiment, after the user selects to make an appointment with a preferred repair shop, the system will select the preferred group including the preferred repair shop that the user has made an appointment with from all preferred groups as the target group. This selection method ensures that all repair shops in the target group can provide all the required spare assemblies together.

[0072] Next, the system will send a notification message to each optional repair shop in the target group. This notification message can contain a variety of content, such as: 1. Information about the preferred repair shop that the user has booked; 2. The specific model and quantity of spare assemblies that need to be deployed; 3. Time requirements for deployment; 4. Recommendations on the mode of transportation for deployment.

[0073] In this way, all optional repair shops in the target group can work together to gather all spare assemblies at the location of the preferred repair shop. This process can be completed before the user arrives at the preferred repair shop, greatly shortening the user's waiting time.

[0074] In practical applications, the technical solution of the present application can be further optimized. For example, the system can formulate the optimal spare assembly allocation plan based on the inventory status, distance, transportation capacity and other influencing factors of each repair shop. Assume that there are three repair shops A, B and C in the target group, and the preferred repair shop is A.

[0075] For example, it is necessary to select a repair shop that has a total of 4 spare assemblies, namely a, b, c and d, among which repair shop A only has spare assembly a, repair shop B only has spare assemblies b and c, and repair shop C only has spare assemblies c and d.

[0076] In this regard, the system can formulate the following deployment plan: Solution 1: Repair shop B is responsible for delivering spare assembly b to repair shop A, and repair shop C is responsible for delivering spare assemblies c and d to repair shop A; Solution 2: Repair shop B is responsible for delivering spare assemblies b and c to repair shop A, and repair shop C is responsible for delivering spare assembly d to repair shop A; At this time, considering that the distance between repair shop B and repair shop A is shorter, it is more convenient for repair shop B to transport a large number of spare assemblies than repair shop C, so plan 2 is selected as the best plan.

[0077] Or considering that repair shop C is equipped with a dedicated truck, it is safer and more reliable for repair shop C to transport a large number of spare assemblies than repair shop B, so plan 1 is selected as the best plan.

[0078] This refined allocation plan can further improve efficiency and reduce unnecessary logistics costs.

[0079] In addition, the technical solution of the present application can also be combined with a real-time traffic information system. The system can dynamically adjust the transportation route of spare assemblies according to current traffic conditions to ensure that all spare assemblies are concentrated at the preferred repair shop in the shortest time.

[0080] Through the above technical solution, this application effectively solves the problem of spare assemblies being scattered in different repair shops. Compared with the traditional method, the advantages of this application are mainly reflected in the following aspects: First, the application realizes the intelligent allocation of spare assemblies. By sending notification information to each repair shop in the target group, the system can coordinate the resources of multiple repair shops to ensure that all the required spare assemblies are ready before the user arrives.

[0081] Secondly, the method of the present application is highly flexible and adaptable. No matter which preferred repair shop the user chooses, the system can quickly find the corresponding target group and start the deployment process of the spare assembly.

[0082] Finally, the technical solution of this application significantly improves the user experience. Users no longer need to worry about delaying the repair time after arriving at the repair shop and finding that some spare assemblies are missing. Instead, they can expect to start the repair process immediately after arrival, thereby greatly shortening the entire repair cycle.

[0083] In some embodiments, the fault information includes a record of the user's interaction with the AI ​​diagnostic model; The method for controlling appointment for in-store maintenance also includes the following steps: S6. After the user selects an optional repair shop for appointment, the optional repair shop selected by the user for appointment is used as the target repair shop and the fault information is sent to the target repair shop so that the maintenance personnel of the target repair shop can continue to determine the faulty parts in the faulty assembly by conducting question-and-answer interaction with the AI ​​diagnosis model based on the interaction record.

[0084] This embodiment includes the interaction records between the user and the AI ​​diagnostic model in the fault information and sends this information to the target repair shop, so that the maintenance personnel can continue to conduct more in-depth fault analysis based on the diagnosis completed by the user. This method effectively utilizes the interaction results between the previous user and the AI ​​diagnostic model, avoids duplication of work, and also provides more background information for the maintenance personnel. The maintenance personnel can continue to interact with the AI ​​diagnostic model through question and answer based on the user's interaction records, which can more accurately locate the specific faulty parts. This not only improves the accuracy of fault diagnosis, but also saves maintenance time and improves overall maintenance efficiency.

[0085] In a specific implementation, fault information may include multiple forms of interaction records. For example, it may be a text-based question-and-answer record, including questions asked by the user and answers given by the AI ​​diagnostic model. It may also be a text transcription of voice interaction, or a selection record of the user interacting with the AI ​​diagnostic model by selecting options. These interaction records may be arranged in chronological order to form a complete record of the diagnostic process.

[0086] After receiving the fault information, the maintenance personnel can access the AI ​​diagnostic model through a dedicated maintenance terminal device. This terminal device can be a tablet or a professional diagnostic device that can display the user's interaction records and allow the maintenance personnel to continue to interact with the AI ​​diagnostic model. The maintenance personnel can selectively refer to the user's interaction records based on their professional judgment and ask more professional and in-depth questions.

[0087] When interacting with maintenance personnel, the AI ​​diagnostic model can dynamically adjust its response strategy based on previous user interaction records and maintenance personnel's new input. For example, if the user's previous interaction has ruled out certain possibilities, the AI ​​diagnostic model will no longer raise these ruled-out questions when interacting with the maintenance personnel. This approach can greatly improve diagnostic efficiency and avoid unnecessary repetition.

[0088] In practical applications, the technical solution of this application can be seamlessly connected with the previous appointment in-store repair control method. For example, after the user preliminarily determines the fault assembly through the AI ​​diagnostic model, the system will recommend a suitable repair shop to the user based on the fault information. After the user selects a repair shop, the system will not only send the fault information to the target repair shop, but also send the complete interaction record between the user and the AI ​​diagnostic model.

[0089] An important advantage of this approach is that it achieves a seamless connection between user diagnosis and professional repair. The preliminary diagnosis results obtained by the user at home or on the road by interacting with the AI ​​diagnostic model will not be discarded or ignored when arriving at the repair shop, but will become an important input to the repair process. This not only improves the coherence of the entire repair process, but also makes full use of the first-hand information provided by the user.

[0090] At the same time, this method also fully utilizes the advantages of the AI ​​diagnostic model. The AI ​​diagnostic model not only plays a role in the user's initial diagnosis, but also continues to provide support during the professional maintenance process. This continuous AI assistance can help maintenance personnel locate specific faulty parts more quickly and accurately. Especially for some complex or rare faults, the AI ​​diagnostic model can provide valuable reference information to help maintenance personnel make more accurate judgments.

[0091] Compared with traditional maintenance methods, in traditional methods, after the user arrives at the repair shop, the repairman usually needs to re-diagnose the fault, which is not only time-consuming, but may also lead to diagnostic errors due to incomplete information. The method of the present application enables the repairman to quickly understand the fault situation by transmitting a complete interaction record, and conduct a more in-depth analysis based on this. This not only saves time, but also improves the accuracy of diagnosis.

[0092] In addition, the method of the present application can also help improve the user experience. When using the AI ​​diagnostic model for preliminary diagnosis, users may worry that the information they provide is not professional or complete enough. Knowing that this information will be directly delivered to professional maintenance personnel and become an important reference for the maintenance process can increase the user's sense of participation and trust. This approach can also encourage users to describe the fault more carefully and in more detail, thereby providing more valuable information for subsequent maintenance.

[0093] Please refer to Figure 3 , Figure 3 A maintenance reservation control device for a store visit in some embodiments of the present invention is applied to a server of a maintenance reservation system. The maintenance reservation control device for a store visit is integrated in a back-end control device in the form of a computer program. The maintenance reservation control device for a store visit includes: The acquisition module 100 is used to acquire the fault information sent by the user terminal; the fault information is generated by the user terminal after all fault components are determined; The first sending module 200 is used to send a search instruction to all repair shops according to the fault information, so that each repair shop can feedback to the server after determining the inventory status of all spare assemblies for replacing each faulty assembly; The management module 300 is used to select a first-category repair shop and a second-category repair shop as optional repair shops; the first-category repair shop is a repair shop that reports that all spare assemblies are available; the second-category repair shop is a repair shop that reports that only some spare assemblies are available; The sorting module 400 is used to organize the optional repair shops into a push list and send the push list to the user terminal for the user to select and make an appointment.

[0094] In some embodiments, the sorting module 400 is used to organize the optional repair shops into a push list and send the push list to the user terminal for the user to select an appointment when executing: S41 obtains the first journey of each optional repair shop and the user terminal; S42. Arrange the optional repair shops in order into a push list according to the first trip.

[0095] In some embodiments, when the sorting module 400 is used to arrange the optional repair shops into a push list in order according to the first journey, it executes: S42A1. When all optional repair shops are first-class repair shops, all optional repair shops are arranged into a push list in order from near to far according to the corresponding first distance.

[0096] In some embodiments, when the sorting module 400 is used to arrange the optional repair shops into a push list in order according to the first journey, it executes: S42B1. When all optional repair shops are of the second category, multiple optional repair shops that can just gather all spare assemblies are selected as the candidate group; S42B2 obtains the second journey between all optional repair shops in the same candidate group; S42B3 selects an optional repair shop as the preferred repair shop, the preferred repair shop and the second distance between all optional repair shops in the same candidate group are less than or equal to the first distance between the preferred repair shop and the user terminal, there will be a preferred repair shop in the candidate group as the preferred group; S42B4. According to the first distance between the preferred repair shop corresponding to each preferred group and the user terminal, all preferred groups are arranged into a push list in order from near to far.

[0097] In some embodiments, when the sorting module 400 is used to arrange the optional repair shops into a push list in order according to the first journey, it executes: S42C1. When a portion of the optional repair shops are first-category repair shops and another portion of the optional repair shops are second-category repair shops, all first-category repair shops and all preferred repair shops are arranged into a push list in order from near to far according to the corresponding first distance.

[0098] In some embodiments, the device for controlling appointment for in-store maintenance further includes: The second sending module 500 is used to select any preferred group that includes the preferred repair shop selected by the user as the target group after the user selects to make an appointment with the preferred repair shop, and send notification information to each optional repair shop in the target group, so that all optional repair shops in the target group will gather all spare assemblies at the location of the preferred repair shop.

[0099] In some embodiments, the fault information includes a record of interaction between the user and the AI ​​diagnostic model; and the in-store maintenance reservation control device further includes: The third sending module 600 is used to, after the user selects an optional repair shop for appointment, use the optional repair shop selected by the user as the target repair shop and send the fault information to the target repair shop so that the maintenance personnel of the target repair shop can continue to determine the faulty parts in the faulty assembly through question-and-answer interaction with the AI ​​diagnostic model based on the interaction record.

[0100] Please refer to Figure 4 , Figure 4 The present invention provides a structural diagram of an electronic device provided by an embodiment of the present invention. The present invention provides an electronic device 13, including: a processor 1301 and a memory 1302. The processor 1301 and the memory 1302 are interconnected and communicate with each other through a communication bus 1303 and / or other forms of connection mechanisms (not shown). The memory 1302 stores computer-readable instructions executable by the processor 1301. When the electronic device is running, the processor 1301 executes the computer-readable instructions to execute the reservation in-store maintenance control method in any optional implementation of the above embodiment, so as to achieve The following functions are provided: obtaining fault information sent by a user terminal; the fault information is generated by the user terminal after all faulty assemblies are determined; a search instruction is sent to all repair shops according to the fault information, so that each repair shop can give feedback to the server after determining the inventory status of all spare assemblies for replacing each faulty assembly; the first-category repair shops and the second-category repair shops are selected as optional repair shops; the first-category repair shops are repair shops that give feedback that all spare assemblies are available; the second-category repair shops are repair shops that give feedback that only some spare assemblies are available; the optional repair shops are arranged into a push list and the push list is sent to the user terminal for the user to select and make an appointment.

[0101] An embodiment of the present invention provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a processor, the method for controlling in-store maintenance reservation in any optional implementation of the above-mentioned embodiment is executed to achieve the following functions: acquiring fault information sent by a user terminal; the fault information is generated by the user terminal after all faulty assemblies are determined; sending a search instruction to all repair shops according to the fault information, so that each repair shop makes feedback to a server after determining the inventory status of all spare assemblies for replacing each faulty assembly; taking a first-category repair shop and a second-category repair shop as optional repair shops; a first-category repair shop is a repair shop that reports that all spare assemblies exist; a second-category repair shop is a repair shop that reports that only some spare assemblies exist; arranging the optional repair shops into a push list and sending the push list to the user terminal for the user to select and make an appointment.

[0102] Among them, the computer-readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable red-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk or optical disk.

[0103] In the embodiments provided by the present invention, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units 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 communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

[0104] In addition, the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0105] Furthermore, the functional modules in the various embodiments of the present invention may be integrated together to form an independent part, or each module may exist independently, or two or more modules may be integrated to form an independent part.

[0106] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any such actual relationship or order between these entities or operations.

[0107] The above description is only an embodiment of the present invention and is not intended to limit the protection scope of the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for controlling appointment for in-store maintenance, applied to a server of a maintenance appointment system, characterized in that: The server is communicatively connected with a plurality of repair shops; The method for controlling scheduled in-store maintenance comprises the following steps: S1. Get fault information sent by the user terminal; the fault information is generated by the user terminal after determining all faults; S2. Sending a search command to all the repair shops according to the fault information, so that each of the repair shops can provide feedback to the server after determining the inventory of all spare assemblies for replacing each of the faulty assemblies; S3. The first type of repair shop and the second type of repair shop are selected as optional repair shops; the first type of repair shop is a repair shop that reports that all the spare assemblies exist; the second type of repair shop is a repair shop that reports that only some of the spare assemblies exist; S4. Arrange the optional repair shops into a push list and send the push list to the user terminal for the user to select an appointment; The specific steps in step S4 include: S41 obtains the first distance between each of the optional repair shops and the user terminal; S42. Arranging the optional repair shops in order into the push list according to the first journey; The specific steps in step S42 include: S42A1. When all the optional repair shops are the first type of repair shops, all the optional repair shops are arranged in order from near to far in the corresponding first distance into the push list; S42B1. When all the optional repair shops are the second type of repair shops, multiple optional repair shops that can just gather all the spare assemblies are selected as the group to be selected; S42B2 obtains the second distance between all the optional repair shops in the same selected group; S42B3 selects one of the optional repair shops as the preferred repair shop, the preferred repair shop and the second distance between all the optional repair shops in the same group of candidates are less than or equal to the first distance between the preferred repair shop and the user terminal, and the preferred repair shop group exists as the preferred group; S42B4. According to the first distance between the preferred repair shop corresponding to each preferred group and the user terminal, all the preferred groups are arranged into the push list in order from near to far.

2. The method for controlling scheduled in-store maintenance according to claim 1, characterized in that: The fault information is generated by the user terminal after the user conducts question-and-answer interaction with a preset AI diagnosis model through the user terminal and determines the fault component.

3. The method for controlling scheduled in-store maintenance according to claim 1, characterized in that: Also includes the steps: S5. After the user chooses to make an appointment with the preferred repair shop, any preferred group that includes the preferred repair shop selected by the user is selected as the target group, and notification information is sent to each optional repair shop in the target group, so that all optional repair shops in the target group gather all the spare assemblies at the location of the preferred repair shop.

4. The method for controlling scheduled in-store maintenance according to claim 2, characterized in that: The fault information includes a record of interaction between the user and the AI ​​diagnostic model; The method for controlling appointment for in-store maintenance also includes the steps of: S6. After the user chooses to make an appointment with the optional repair shop, the optional repair shop selected by the user is used as the target repair shop and the fault information is sent to the target repair shop so that the maintenance personnel of the target repair shop can continue to determine the faulty parts in the faulty assembly by conducting question-and-answer interaction with the AI ​​diagnostic model based on the interaction record.

5. A maintenance reservation control device, applied to a server of a maintenance reservation system, characterized in that: The server is communicatively connected with a plurality of repair shops; The in-store maintenance reservation control device comprises: An acquisition module, used for acquiring fault information sent by a user terminal; the fault information is generated by the user terminal after all fault components are determined; A first sending module, configured to send a search instruction to all the repair shops according to the fault information, so that each of the repair shops can provide feedback to the server after determining the inventory status of all spare assemblies for replacing each of the faulty assemblies; A management module is used to select a first-category repair shop and a second-category repair shop as optional repair shops; the first-category repair shop is a repair shop that reports that all the spare assemblies are available; the second-category repair shop is a repair shop that reports that only some of the spare assemblies are available; A sorting module, used for arranging the optional repair shops into a push list and sending the push list to the user terminal for the user to select and make an appointment; The sorting module is used to compile the optional repair shops into a push list and send the push list to the user terminal for the user to select an appointment when executing: S41 obtains the first journey of each optional repair shop and the user terminal; S42. Arrange the optional repair shops in an orderly manner into a push list according to the first journey; The sorting module is used to arrange the optional repair shops into a push list in order according to the first journey. S42A1. When all optional repair shops are first-class repair shops, all optional repair shops are arranged into a push list in order from near to far according to the corresponding first distance; S42B1. When all optional repair shops are of the second category, multiple optional repair shops that can just gather all spare assemblies are selected as the candidate group; S42B2 obtains the second journey between all optional repair shops in the same candidate group; S42B3 selects an optional repair shop as the preferred repair shop, the preferred repair shop and the second distance between all optional repair shops in the same candidate group are less than or equal to the first distance between the preferred repair shop and the user terminal, there will be a preferred repair shop in the candidate group as the preferred group; S42B4. According to the first distance between the preferred repair shop corresponding to each preferred group and the user terminal, all preferred groups are arranged into a push list in order from near to far.

6. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method for controlling scheduled in-store repairs as described in any one of claims 1 to 4 are executed.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by the processor, the steps of the method for controlling scheduled in-store repairs as described in any one of claims 1 to 4 are executed.

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