Order dispatching method and device of intelligent lock maintenance system, computer equipment and medium

Abstract

The invention relates to the technical field of intelligent locks, and discloses an order sending method and device of an intelligent lock maintenance system, computer equipment and a medium, and the method comprises the steps: receiving fault information of an intelligent lock in a preset range of the maintenance system; determining a corresponding target maintenance scheme according to the fault information, and judging whether the target maintenance scheme has a door-to-door demand or not; if the door-to-door demand exists, calculating adaptive scores of a plurality of service systems in a preset range based on a preset scoring module, and screening out a target service system from the service systems through the adaptive scores; and generating a maintenance service list by using the target maintenance scheme, and issuing the maintenance service list to the target service system. According to the invention, the problem of poor user experience caused by long response time, long service time and lack of dynamic adjustment capability of an existing intelligent lock maintenance order sending system is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of smart locks, and in particular to a dispatching method, device, computer equipment and medium for a smart lock maintenance system. Background Art

[0002] With the rapid development of the smart home market, smart locks, as key devices to ensure family safety, are becoming more and more popular. However, in actual use, smart locks will inevitably encounter various faults, such as battery exhaustion, circuit board damage, sensor failure, etc., which urgently require timely and efficient maintenance services to solve. In this context, the dispatching mechanism of the smart lock maintenance system is particularly important, which is directly related to the efficiency and quality of the maintenance service.

[0003] At present, the existing dispatch system has many shortcomings and drawbacks. On the one hand, the response time is long, and the existing dispatch system often takes a long time to assign tasks to technicians. And if the repair involves sending accessories, the entire service time will be further extended. On the other hand, there is a lack of dynamic adjustment capabilities, and it is impossible to make flexible adjustments based on real-time situations, such as changes in the status of technicians. These problems ultimately lead to poor user experience. Users may have to wait a long time to get service, which seriously affects user satisfaction with smart lock repair services. Summary of the invention

[0004] In view of this, an embodiment of the present invention provides a dispatching method, device, computer equipment and medium for a smart lock maintenance system to solve the problems of long response time, long service time and lack of dynamic adjustment capability in the existing smart lock maintenance dispatching system, which in turn leads to poor user experience.

[0005] In a first aspect, an embodiment of the present invention provides a method for dispatching an order for a smart lock maintenance system, the method comprising:

[0006] Receive fault information of smart locks within the preset range of the maintenance system;

[0007] Determine a corresponding target maintenance plan according to the fault information, and judge whether there is a door-to-door demand for the target maintenance plan;

[0008] If there is a need for on-site visits, the adaptation scores of multiple service systems within the preset range are calculated based on a preset scoring module, and a target service system is screened out from the service systems by the adaptation scores;

[0009] A maintenance service order is generated using the target maintenance plan, and the maintenance service order is sent to the target service system.

[0010] Further, determining a corresponding target maintenance plan according to the fault information includes:

[0011] Extracting first position data and fault type from the fault information;

[0012] Based on the association relationship between the preset fault type and the preset material list, obtaining the material list corresponding to the fault type;

[0013] A target maintenance plan is generated using the first location data, the fault type, and the bill of materials.

[0014] Furthermore, the calculating the adaptation scores of the plurality of service systems within the preset range based on the preset scoring module includes:

[0015] Acquire service data of each service indicator in a plurality of the service systems, wherein the service indicators include distance indicators, personnel indicators, and accessory indicators;

[0016] Calculate the index score of each of the service indicators according to the service data;

[0017] The adaptation score of each of the service systems is calculated based on the indicator scores of the respective service indicators.

[0018] Furthermore, when the service indicator is a distance indicator, calculating the indicator score of each service indicator according to the service data includes:

[0019] Acquire second location data of multiple technicians in the service data;

[0020] Determine the distance between the smart lock and the technician according to the first position data and the second position data in the target maintenance plan;

[0021] A first indicator score of the service system is calculated based on the distance between the smart lock and the technician.

[0022] Furthermore, when the service indicator is a personnel indicator, calculating the indicator score of each service indicator according to the service data includes:

[0023] Obtaining technical evaluation data of multiple technicians in the service data;

[0024] Using the technical evaluation data to score each technician, and obtaining a scoring result;

[0025] The number of personnel who meet the preset conditions is determined according to the scoring result, and the second indicator score of the service system is calculated based on the number of personnel and the total number of personnel in the service system.

[0026] Furthermore, when the service indicator is an accessory indicator, calculating the indicator score of each service indicator according to the service data includes:

[0027] Obtaining a parts inventory list in the service data;

[0028] Matching the bill of materials in the target maintenance plan with the parts inventory list to obtain a matching result;

[0029] A third indicator score of the service system is calculated according to the matching result.

[0030] Furthermore, after the maintenance service order is sent to the target service system, the method further includes:

[0031] Monitoring the maintenance progress of the target service system for the maintenance service order;

[0032] When the maintenance progress reaches a critical node, generating reminder information based on the service content in the maintenance service order;

[0033] The reminder information is sent to a mobile device associated with the key node.

[0034] In a second aspect, an embodiment of the present invention provides a dispatching device for a smart lock maintenance system, the device comprising:

[0035] A receiving module, used to receive fault information of smart locks within a preset range of the maintenance system;

[0036] A judgment module, used to determine a corresponding target maintenance plan according to the fault information, and to judge whether there is a door-to-door demand for the target maintenance plan;

[0037] A calculation module, for calculating the adaptation scores of the plurality of service systems within the preset range based on the preset scoring module if there is a door-to-door demand, and screening out a target service system from the service systems by the adaptation scores;

[0038] The sending module is used to generate a maintenance service order using the target maintenance plan, and send the maintenance service order to the target service system.

[0039] In a third aspect, an embodiment of the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method of the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0040] In a fourth aspect, an embodiment of the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method of the first aspect or any corresponding embodiment thereof.

[0041] The method provided in the embodiment of the present application has the following beneficial effects:

[0042] The method provided in the embodiment of the present application can accurately focus on the smart locks that need to be repaired in a specific area by receiving the fault information of the smart locks within a preset range, and provide basic data support for the subsequent targeted formulation of maintenance plans and dispatching, ensuring that maintenance resources can be concentrated on the fault handling within the range, and improving the utilization efficiency of maintenance resources. By extracting the first position data and the fault type in the fault information, and obtaining the bill of materials based on the association between the preset fault type and the preset bill of materials, and then generating a target maintenance plan, it is possible to customize a dedicated maintenance plan according to the specific situation of the fault, and improve the accuracy and pertinence of the maintenance plan. At the same time, by judging whether there is a door-to-door demand, different maintenance scenarios can be distinguished, resources can be reasonably allocated, and unnecessary door-to-door services can be used to avoid waste of resources. For faults that can be solved without door-to-door visits, more efficient remote guidance and other methods can be used to improve the overall maintenance efficiency. By obtaining the service data of various service indicators such as distance indicators, personnel indicators, and accessories indicators in multiple service systems, and calculating the indicator score and adaptation score based on this, the adaptability of the service system and the maintenance task is comprehensively evaluated from multiple dimensions. This method can comprehensively consider the actual situation of the service system, ensure that the selected target service system is more in line with the maintenance task requirements in terms of distance, personnel technical capabilities, spare parts reserves, etc., improve the rationality and scientificity of dispatching orders, and thus improve the timeliness and quality of maintenance services. By sending the maintenance service order generated based on the target maintenance plan to the target service system, the maintenance task is accurately communicated, so that the target service system can clearly know the key information such as maintenance content and requirements, provide clear guidance for the subsequent efficient maintenance service, ensure that the maintenance work is carried out in an orderly manner, and improve the execution efficiency of maintenance services. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0044] Figure 1 is a flow chart of a dispatching method of a smart lock maintenance system according to an embodiment of the present invention;

[0045] Figure 2 is a schematic diagram of the structure of a technician scoring rule according to an embodiment of the present invention;

[0046] Figure 3 is a workflow diagram of a dispatching system of a smart lock maintenance system according to an embodiment of the present invention;

[0047] Figure 4 is a structural block diagram of a dispatching device of a smart lock maintenance system according to an embodiment of the present invention;

[0048] Figure 5 It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution 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 part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0050] According to an embodiment of the present invention, a dispatching method, apparatus, computer equipment and medium for a smart lock maintenance system are provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0051] In this embodiment, a method for dispatching orders for a smart lock maintenance system is provided. Figure 1 is a flow chart of a dispatching method of a smart lock maintenance system according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0052] Step S11, receiving fault information of smart locks within a preset range of the maintenance system.

[0053] In the embodiment of the present application, the fault information generated by the smart lock is collected for a specific range set by the maintenance system. The fault information may include but is not limited to a specific description of the fault, such as a detailed description of a specific problem such as battery exhaustion, circuit board damage, sensor failure, etc. of the smart lock; the user address to accurately locate the location of the fault; and information such as the user level and urgency. The collected fault information lays the foundation for the operation of the entire maintenance dispatch system.

[0054] Step S12, determining a corresponding target maintenance plan according to the fault information, and judging whether there is a door-to-door visit requirement for the target maintenance plan.

[0055] In the embodiment of the present application, determining the corresponding target maintenance plan according to the fault information includes the following steps A1-A3:

[0056] Step A1, extracting first position data and fault type from fault information.

[0057] Specifically, the first location data represents the geographical location of the smart lock, which is crucial for determining whether on-site maintenance is required, calculating the distance between the technician and the fault location, and arranging appropriate service resources. Accurately obtaining location data can ensure the geographical positioning of maintenance services and improve service response speed. The fault type clarifies the specific category of the problem with the smart lock, such as battery exhaustion, circuit board damage, or sensor failure. Different fault types correspond to different maintenance methods and required materials. Extracting the fault type lays the foundation for the subsequent formulation of targeted maintenance plans, making the maintenance plans more accurate and effective.

[0058] Step A2: based on the association between the preset fault type and the preset material list, obtain the material list corresponding to the fault type.

[0059] Specifically, after extracting the fault type, the bill of materials required to solve the fault is determined based on the pre-set association between the fault type and the bill of materials. The preset association is a knowledge system accumulated and summarized by the system over a long period of time, which accurately matches different fault types with corresponding maintenance materials.

[0060] For example, when the fault type is battery exhaustion, the corresponding bill of materials may only include the appropriate battery; if the fault type is circuit board damage, the bill of materials will include the corresponding model of circuit board and possible accessories such as welding tools and screws. Through this kind of association matching, the system can quickly and accurately obtain all the material information required to solve a specific fault, provide the necessary material support for generating a complete target maintenance plan, and ensure that the maintenance process will not be delayed due to the lack of key materials.

[0061] Step A3: Generate a target maintenance plan using the first location data, the fault type, and the bill of materials.

[0062] Specifically, the first location data provides geographic location information, which is of great significance for dispatching technicians and resources. If the fault location is remote, priority should be given to nearby and experienced technicians, taking into account traffic factors. The fault type clarifies the core and direction of maintenance, and guides technicians to adopt appropriate maintenance methods and processes. Different fault types correspond to different detection tools and techniques. The bill of materials lists the materials required for maintenance in detail, so that technicians know in advance what tools and accessories to bring to prevent maintenance interruptions due to missing materials. The target maintenance plan generated by these three elements comprehensively plans all aspects of maintenance, provides clear and accurate guidelines for subsequent services, and fundamentally ensures smooth maintenance.

[0063] In an embodiment of the present application, after determining the target maintenance plan, it is necessary to further determine whether the plan requires a technician to visit the site, which determines the execution method and resource allocation direction of the subsequent maintenance service. If the judgment result is that there is no on-site demand, it means that the fault can be solved online, such as simple setting problems, software failures, etc. The system directly provides the solution to the user online, and the user handles the fault on his own. If the judgment result is that there is a demand for on-site visits, it means that the fault is more complicated and requires the operation of a technician to solve it. In this case, the system will transfer the task flow to the scheduling module, and the scheduling module will arrange suitable technicians to visit the user to solve the problem according to a series of rules. Through this judgment mechanism, the system can reasonably allocate resources according to the actual situation of the fault, ensure that the maintenance service is carried out in the most appropriate way, and improve service efficiency and quality.

[0064] Step S13: if there is a demand for on-site service, the adaptation scores of multiple service systems within a preset range are calculated based on a preset scoring module, and a target service system is screened out from the service systems according to the adaptation scores.

[0065] In an embodiment of the present application, the adaptation scores of multiple service systems within a preset range are calculated based on a preset scoring module, including: obtaining service data of each service indicator in the multiple service systems, wherein the service indicators include distance indicators, personnel indicators, and accessory indicators. Calculating the index score of each service indicator based on the service data. Calculating the adaptation score of each service system based on the index score of each service indicator.

[0066] In the embodiment of the present application, when the service indicator is a distance indicator, the indicator score of each service indicator is calculated according to the service data, including the following steps B1-B3:

[0067] Step B1, obtaining second location data of multiple technicians in the service data.

[0068] Specifically, in the process of calculating the score of the distance index of the service system, the second location data of multiple technicians must be obtained first. The second location data represents the current geographical location information of each technician. These data are an important basis for the subsequent calculation of the distance between the technician and the smart lock. By collecting the location information of multiple technicians, the system can fully understand the spatial distribution of deployable human resources. For example, location data such as the specific address or longitude and latitude of each technician. These data usually come from channels such as the positioning information of the mobile devices carried by the technicians and the address information pre-recorded in the service system. Ensuring the accuracy and real-time nature of the data is crucial for reasonably evaluating the distance between the technicians and the faulty smart locks, and then accurately calculating the distance index score, and finally screening out the appropriate service system.

[0069] Step B2, determining the distance between the smart lock and the technician based on the first position data and the second position data in the target maintenance plan.

[0070] Specifically, after obtaining the first location data in the target maintenance plan (i.e., the location information of the smart lock) and the second location data of multiple technicians, a specific algorithm is used to determine the distance between the smart lock and each technician. Usually, a geospatial distance calculation method such as the Haversine formula is used to convert the longitude and latitude coordinates into actual geographic distances. Technicians who are closer can reach the fault site more quickly, shorten the maintenance response time, and improve user satisfaction.

[0071] Step B3, calculating the first indicator score of the service system according to the distance between the smart lock and the technician.

[0072] Specifically, after determining the distance between the smart lock and the technician, the distance information is converted into the first indicator score of the service system based on the pre-set rules. According to the given rules, the shorter the distance, the higher the score. For example, when the distance is less than 10 kilometers, 0 points are scored; when it is greater than 10 kilometers and less than 30 kilometers, 5 points are deducted; when it is greater than 30 kilometers and less than 50 kilometers, 10 points are deducted; when it is greater than 50 kilometers, 20 points are deducted.

[0073] As an example, the service system position compliance rate is used for calculation, that is, the proportion of technicians in the service system with a distance score greater than 90 points. For example, if the full score is set to 20 points, the basic score accounts for 80% (i.e. 16 points), and the performance score accounts for 20% (i.e. 4 points). Assuming that the service system technician position compliance rate is 75%, the actual score is calculated as follows: Actual score = 16 + (90% - 75%) / (100% - 75%) * 4 = 16 + 15% / 25% * 4 = 16 + 0.6 * 4 = 16 + 2.4 = 18.4 points.

[0074] Through this scoring method, the important factor of distance is quantified into specific scores, which can intuitively reflect the advantages or disadvantages of the service system in terms of distance. These scores will be used as an important part of calculating the adaptation score of the service system, and will be comprehensively considered together with the scores of other indicators (such as personnel indicators and accessories indicators) to comprehensively evaluate the degree of adaptation between the service system and the maintenance task. Finally, by comparing the adaptation scores of each service system, the service system with the best performance in terms of distance is selected to ensure that the maintenance task can be responded to and handled as soon as possible by technicians at the appropriate distance.

[0075] In the embodiment of the present application, when the service indicator is a personnel indicator, the indicator score of each service indicator is calculated according to the service data, including the following steps C1-C3:

[0076] Step C1, obtaining technical evaluation data of multiple technicians in the service data.

[0077] Specifically, the starting point for evaluating service system personnel indicators is to collect technical evaluation data of multiple technicians from various channels. These data are a quantitative reflection of the technicians' work ability and performance. Data sources can include historical maintenance work order records, user evaluation feedback, regular skill assessment results, etc. For example, from historical maintenance work orders, we can obtain information such as the time it takes for technicians to complete various maintenance tasks and the quality of maintenance; user evaluation feedback can reflect the technicians' professionalism and problem-solving ability during the service process; and regular skill assessment results show the technicians' mastery of new knowledge and new skills. The purpose of collecting these multi-dimensional data is to comprehensively and objectively evaluate the technical level of each technician, and provide a rich and reliable basis for subsequent accurate scoring.

[0078] Step C2, using the technical evaluation data to score each technician and obtain a scoring result.

[0079] Specifically, after obtaining the technical evaluation data, a quantitative score is given to each technician based on the pre-set scoring rules. Figure 2 As shown, the scoring rules include a variety of factors, such as order reminder rate, timely appointment rate, timely door-to-door rate, order completion efficiency, MOT positive rate, negative review rate (PPM) and test pass rate.

[0080] Taking the order reminder rate as an example, if the proportion of service orders with order reminder tags to completed service orders in the current month is higher than the target value (for example, 0.5% is higher than the target value of 0.4%), the score is calculated according to the formula "basic score + (target value - current month's achieved value) / target value * target score" to obtain the technician's score on the order reminder rate factor. By performing similar calculations on each relevant factor and adding up the scores of each item, the final score for each technician is obtained. This score result intuitively reflects the level of each technician in terms of technical capabilities and service performance, and provides a clear quantitative standard for the subsequent screening of suitable technicians.

[0081] Step C3, determining the number of personnel who meet the preset conditions according to the scoring results, and calculating the second indicator score of the service system based on the number of personnel and the total number of personnel in the service system.

[0082] Specifically, after obtaining the scoring results of each technician, the technicians who meet the requirements are screened out according to the preset conditions. The preset conditions can be set based on business needs, for example, only technicians with scores higher than the score line (such as 90 points) meet the conditions. The number of personnel who meet the preset conditions is counted, and then combined with the total number of personnel in the service system, the second indicator score of the service system is obtained according to a specific calculation method.

[0083] As an example, suppose a service system has 100 technicians. The following takes technician A as an example to show the calculation process of each indicator score:

[0084] Order reminder rate: The proportion of completed service orders with order reminder tags in the current month is 0.3%, and the standard value is 0.4%. According to the formula "basic score + (standard value - current month's achieved value) / standard value * standard score", where the basic score is 15 points and the standard score is 10 points, the order reminder rate score can be obtained: 15 + (0.4% - 0.3%) / 0.4% * 10 = 17.5 points.

[0085] Timely appointment rate: The proportion of timely appointment label installation orders to completed installation orders in the month is 98.5%, and the standard value is 99%. According to the formula "basic score + (current month's achievement value - standard value) / (1-standard value) * standard score", the basic score is 6 points, the standard score is 4 points, and the timely appointment rate score is: 6 + (98.5% - 99%) / (1-99%) * 4 = 4 points.

[0086] On-time visit rate: The proportion of on-time visit label installation orders to completed installation orders in the month is 98.8%, and the standard value is 99%. Similarly, the score of on-time visit rate can be obtained as follows: 6 + (98.8% - 99%) / (1-99%) * 4 = 5.2 points.

[0087] Efficiency in order completion: The proportion of completed orders within three days is 94%, and the standard value is 95%. The basic score is 6 points, the standard score is 4 points, and the efficiency score in order completion is: 6 + (94% - 95%) / (1-95%) * 4 = 5.2 points.

[0088] MOT favorable rate: The proportion of installation orders with very satisfactory MOT results in the month is 98% of the evaluated installation orders, and the standard value is 99%. The basic score is 9 points, the standard score is 6 points, and the MOT favorable rate score is: 9 + (98% - 99%) / (1-99%) * 6 = 3 points.

[0089] Bad review rate (PPM): The proportion of installation orders with bad review labels in the month is 0.03% of the total number of installation orders, and the standard value is 0.04%. The basic score is 12 points, the performance score is 8 points, and the bad review rate (PPM) score is: 12 + (0.04% - 0.03%) / 0.04% * 8 = 14 points.

[0090] Exam pass rate: The exam score for this month is 75 points. According to the rules, 1 point will be deducted for scores between 70 and 80, so the exam pass rate score is: 10-2=8 points.

[0091] Adding up the scores of each item, the final score of technician A is: 17.5+4+5.2+5.2+3+14+8=56.9 points. After all 100 technicians in the service system were scored as above, it was determined that the preset condition was that only technicians with a score higher than 90 points met the condition. According to statistics, there were 20 technicians who met this condition. Assuming the full score is 30 points, the basic score accounts for 90% (i.e. 27 points) and the performance score accounts for 10% (i.e. 3 points). Based on these data, the second indicator score of the service system is calculated as follows:

[0092] The skill score achievement rate of service system technicians = 20 / 100*100% = 20%;

[0093] Actual score = 27 + (20% - 90%) / (100% - 90%) * 3 = 27 - 21 = 6 points.

[0094] In the embodiment of the present application, the second indicator score may also take into account the scheduling of each technician in the service system, and the specific method is as follows:

[0095] First, obtain the scheduling information of each technician in the service system for a preset future time period (i.e., the service time reserved by the user), and divide it into 4 levels: busy (6 service orders), moderately busy (>4 service orders), average (>2 service orders), and idle (<2 service orders). Secondly, calculate the passing rate of the technician scheduling score in the service system, that is, count the proportion of the number of technicians with busy and extremely busy scheduling status in the service system to the total number of technicians, and require this proportion to be less than 80%. Finally, calculate the score of the service system in terms of technician scheduling according to the passing rate of the scheduling score. The full score is set at 45 points, of which the basic score accounts for 90%, that is, 40.5 points; the performance score accounts for 10%, which is 4.5 points. For example, if the proportion of the number of technicians with busy and extremely busy scheduling status in the service system is 70% of the total number of technicians, the actual score = 40.5 + (70% - 90%) / (100% - 90%) * 4.5 = 40.5 - 9 = 31.5 points.

[0096] Adjust the scheduling score of this technician to the second index score calculated based on the technical evaluation data before (for example, perform weighted summation according to a certain weight), so as to more comprehensively reflect the overall situation of the service system in terms of personnel indicators, provide a more perfect consideration of the personnel dimension for comprehensively evaluating the adaptation score of the service system, and help screen out a service system with more reasonable personnel arrangements and better meeting the requirements of maintenance tasks.

[0097] Through such a calculation method, the individual scoring situation of technicians is converted into the score of the service system in terms of personnel indicators. This score can reflect the quality level of the overall technicians in the service system, provide an important consideration of the personnel dimension for comprehensively evaluating the adaptation score of the service system, and help screen out a service system whose personnel technical capabilities better meet the requirements of maintenance tasks.

[0098] In the embodiment of the present application, when the service indicator is the parts indicator, calculate the indicator scores of each service indicator according to the service data, including the following steps D1 - D3:

[0099] Step D1, obtain the parts inventory list in the service data.

[0100] Specifically, in the parts indicator link for evaluating the adaptation score of the service system, first obtain the parts inventory list in the service data. This list details the information of various parts owned by the service system, including the types, quantities, specifications, etc. of the parts. By obtaining this list, the current parts reserve situation of each service system can be determined, providing basic data support for subsequent judgment of whether it has the required parts to complete specific maintenance tasks. Only by accurately mastering the parts inventory information can it be further matched with the bill of materials required for the maintenance task, so as to scientifically evaluate the adaptation degree of the service system to the maintenance task in terms of parts.

[0101] Step D2, matching the bill of materials in the target maintenance plan with the spare parts inventory list to obtain a matching result.

[0102] Specifically, after obtaining the bill of materials in the target maintenance plan (the list is a list of accessories required to complete the maintenance task determined according to the fault type) and the accessories inventory list in the service data, the two are matched. The matching process can be to check whether each accessory in the bill of materials exists in the accessories inventory list one by one. If a certain accessory in the bill of materials can be found in the inventory list with the corresponding type and specification, and the quantity meets the maintenance requirements (if there is a quantity requirement), the accessory is considered to be matched successfully; otherwise, the matching fails. Through meticulous matching operations, the system can fully understand the fit between the existing accessories inventory of the service system and the actual needs of the maintenance task, and obtain a clear matching result. This matching result intuitively reflects the service system's support capabilities for maintenance tasks in terms of accessories, and provides a key basis for the subsequent calculation of the service system's accessories index score.

[0103] Step D3, calculating the third indicator score of the service system according to the matching results.

[0104] Specifically, based on the matching results, the third indicator score of the service system is calculated according to the pre-set rules. According to the given rules, if the spare parts inventory of the service system contains all the spare parts required by the user for maintenance, that is, the matching result is a complete match, then the service system can get 5 points in the spare parts indicator; if there is at least one spare part that does not match, that is, the matching result does not fully meet the maintenance needs, then 0 points will be obtained.

[0105] This scoring method quantifies the matching of spare parts inventory and maintenance needs into a specific score, which can intuitively reflect the adaptability of the service system in terms of spare parts. As an important part of calculating the service system adaptation score, this score, together with other indicator scores such as distance indicators and personnel indicators, helps to comprehensively evaluate the overall adaptability of the service system and maintenance tasks, and then select service systems with greater advantages in spare parts supply, so as to ensure that maintenance tasks can be carried out smoothly and avoid maintenance delays due to missing parts.

[0106] In the embodiment of the present application, after calculating the adaptation scores of multiple service systems within a preset range based on the preset scoring module, the system will select the target service system that is most suitable for handling the smart lock maintenance task from the numerous service systems based on these scores. The adaptation score comprehensively reflects the degree of fit between the service system and the maintenance task in terms of multiple key indicators such as distance, personnel skills, and spare parts inventory. The higher the score, the more the service system can meet the needs of the maintenance task in all aspects.

[0107] The method provided in the embodiment of the present application uses this screening mechanism based on the adaptation score, and the system can achieve the optimal configuration of service resources. Compared with random selection or selecting a service system based on a single factor, this method can more comprehensively and scientifically evaluate the actual capabilities and conditions of each service system, thereby ensuring that the selected target service system has higher advantages in all aspects, can complete the smart lock maintenance task more efficiently and with higher quality, improve the quality and efficiency of the overall maintenance service, and meet the user's expectations for fast and accurate maintenance services.

[0108] Step S14: Generate a maintenance service order using the target maintenance plan, and send the maintenance service order to the target service system.

[0109] It should be noted that the target maintenance plan is based on a comprehensive analysis of the fault information in the early stage. It contains key information such as the fault type, the required material list, and the fault location. Generating a maintenance service order based on this is to convert the content of the plan into a specific, detailed and clearly instructive task document. The maintenance service order will record all aspects of the maintenance task in detail, such as the specific description of the fault, so that the technicians can understand the problem in advance; list the required material list to ensure that the technicians can prepare all the necessary tools and accessories before going to the maintenance site; mark the location information of the faulty smart lock so that the technicians can accurately navigate to the maintenance site. In addition, the service order can also contain relevant information of the user, such as the user's address, contact number, etc., so that the technicians can contact the user when necessary. By generating a maintenance service order, a clear and accurate operating guide is provided for subsequent maintenance work.

[0110] In an embodiment of the present application, among many service systems, the adaptation score is calculated by a preset scoring module, and the target service system that is most suitable for undertaking this maintenance task has been screened out. The generated maintenance service order is sent to the target service system, indicating that the maintenance task is officially assigned. After receiving the maintenance service order, the target service system can quickly arrange suitable technicians and allocate the required resources according to the detailed information therein to carry out maintenance work in an orderly manner. This process realizes seamless connection from fault acceptance to task execution, ensuring that maintenance tasks can be efficiently and accurately transmitted to the service system responsible for execution, avoiding delays and errors caused by poor information transmission or unclear task allocation, and laying the foundation for ensuring the smooth progress of smart lock maintenance work. At the same time, it also makes the entire maintenance process more standardized and systematic, improving the overall maintenance efficiency and service quality.

[0111] In the embodiment of the present application, after the maintenance service order is sent to the target service system, the method further includes:

[0112] Step S21, monitoring the maintenance progress of the target service system for the maintenance service order.

[0113] In the embodiment of the present application, after the maintenance service order is sent to the target service system, the maintenance progress is tracked and monitored in real time. Various status information about the maintenance service order is obtained through the data interaction mechanism established with the target service system. For example, it is known whether the technician has accepted the order, whether he has set out for the maintenance location, whether he has arrived at the site to start maintenance, and what specific stage the maintenance work is in. This information enables the system to promptly detect delays or abnormalities that may occur during the maintenance process.

[0114] Step S22: When the maintenance progress reaches a critical node, a reminder message is generated based on the service content in the maintenance service order.

[0115] In an embodiment of the present application, the system pre-sets a series of key nodes in the maintenance process, such as the time when the technician fails to set out within the specified time after receiving the order, the time when the maintenance starts after arriving at the site, and the estimated completion time of the maintenance. When it is monitored that the maintenance progress reaches these key nodes, the reminder information generation mechanism is triggered. The generation of reminder information is based on the detailed service content in the maintenance service form. For example, if the maintenance service form clearly specifies the specific accessories required for the maintenance, and when the maintenance reaches a certain key point, it is found that there may be supply problems with the accessories, the reminder information will highlight this point. For example, if the maintenance work involves multiple steps, at the time node of the key step, the reminder information will once again clarify the key points and precautions of the step.

[0116] The reminder information generated in this way is highly targeted and instructive, which can help technicians accurately grasp the rhythm of maintenance, ensure that each key link is properly handled, and avoid maintenance delays or quality problems due to negligence or forgetfulness. At the same time, it also helps technicians prepare for the next step of work in advance and improve the consistency and efficiency of maintenance work.

[0117] Step S23, sending the reminder information to the mobile device associated with the key node.

[0118] In the embodiment of the present application, the mobile device is usually a mobile phone or other mobile terminal used by the technician responsible for the maintenance task. The reminder information is directly delivered to the technician through text messages, APP push or voice calls.

[0119] This timely information transmission method allows technicians to obtain important reminders at the first time, so that they can adjust their work arrangements in time according to the reminder content to ensure the smooth progress of maintenance work. The reminder information is accurately sent to mobile devices associated with key nodes, which realizes efficient information transmission and timely feedback, helps to improve the controllability and efficiency of maintenance work, and ultimately improves user satisfaction with maintenance services. At the same time, this is also an important part of ensuring service quality and efficiency in the entire maintenance service process. Through effective communication and reminder mechanisms, it ensures that each maintenance link can be closely connected and reduces problems caused by poor information flow.

[0120] This embodiment provides a dispatching system for a smart lock maintenance system, the system comprising: a data acquisition module, a fault analysis module, a dispatching decision module, a preset scoring module and a reminder module;

[0121] A data acquisition module, used to collect fault information of smart locks within a preset range and send the fault information to a fault analysis module;

[0122] A fault analysis module is used to receive the fault information sent by the data acquisition module, parse the fault information, extract the first position data and the fault type therein; based on the association between the preset fault type and the preset material list, obtain the material list corresponding to the fault type; generate a target maintenance plan using the first position data, the fault type and the obtained material list, and determine whether there is a door-to-door demand for the target maintenance plan, and send the generated target maintenance plan, the door-to-door demand determination result and related information to the dispatch decision module;

[0123] The dispatch decision module is used to receive the information of the on-site demand sent by the fault analysis module, call the scoring calculation module, and calculate the adaptation scores of multiple service systems within a preset range based on the preset scoring module; specifically, the dispatch decision module selects the target service system with the highest adaptation score among these service systems according to the adaptation scores of each service system calculated by the preset scoring module; generates a maintenance service order using the target maintenance plan generated by the fault analysis module, and sends the maintenance service order to the selected target service system;

[0124] A preset scoring module is used to obtain service data of each service indicator in multiple service systems according to the instructions of the dispatch decision module; calculate the indicator score of each service indicator according to the service data; calculate the adaptation score of each service system based on the indicator score of each service indicator, and return the calculation result to the dispatch decision module;

[0125] The reminder module is used to monitor the maintenance progress of the target service system for the maintenance service order after the dispatch decision module sends the maintenance service order to the target service system; when the maintenance progress reaches a critical node, a reminder message is generated based on the service content in the maintenance service order, and the reminder message is sent to the mobile device associated with the critical node.

[0126] In the embodiment of the present application, the workflow of the dispatching system of the smart lock maintenance system is as follows: Figure 3 As shown, it includes: the data acquisition module collects fault information in real time and sends it to the fault analysis module, parses the information, extracts the location and fault type, obtains the bill of materials, generates a target maintenance plan, and determines the need for on-site visits before sending it to the dispatch decision module; if there is a need for on-site visits, the dispatch decision module calls the preset scoring module, which obtains the service data, calculates the scores of each indicator, and returns the adapted score. The dispatch decision module selects the target service system based on this and issues a maintenance service order; then the reminder module monitors the progress of maintenance, generates reminder information at key nodes and sends it to the associated mobile device. If there is no need for on-site visits, the reminder module directly sends the plan to the user and provides guidance, and the process ends.

[0127] In this embodiment, a dispatching device for a smart lock maintenance system is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and will not be repeated here. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0128] This embodiment provides a dispatching device for a smart lock maintenance system, such as Figure 4 As shown, including:

[0129] A receiving module 41 is used to receive fault information of smart locks within a preset range of the maintenance system;

[0130] A judgment module 42 is used to determine a corresponding target maintenance plan according to the fault information, and to determine whether there is a door-to-door demand for the target maintenance plan;

[0131] A calculation module 43 is used to calculate the adaptation scores of multiple service systems within a preset range based on a preset scoring module if there is a door-to-door demand, and screen out a target service system from the service systems by the adaptation scores;

[0132] The sending module 44 is used to generate a maintenance service order using the target maintenance plan and send the maintenance service order to the target service system.

[0133] In an optional embodiment of the present application, the judgment module 42 is used to extract the first position data and the fault type in the fault information; based on the association between the preset fault type and the preset material list, obtain the material list corresponding to the fault type; and generate a target maintenance plan using the first position data, the fault type and the material list.

[0134] In an optional embodiment of the present application, the calculation module 43 is used to obtain service data of each service indicator in multiple service systems, wherein the service indicators include distance indicators, personnel indicators and accessories indicators; calculate the indicator score of each service indicator according to the service data; and calculate the adaptation score of each service system based on the indicator score of each service indicator.

[0135] In an optional implementation of the present application, the calculation module 43 includes: a first calculation submodule, a second calculation submodule and a third calculation submodule;

[0136] The first calculation submodule is used to obtain the second position data of multiple technicians in the service data; determine the distance between the smart lock and the technician based on the first position data and the second position data in the target maintenance plan; and calculate the first indicator score of the service system based on the distance between the smart lock and the technician.

[0137] The second calculation submodule is used to obtain technical evaluation data of multiple technicians in the service data; use the technical evaluation data to score each technician to obtain a scoring result; determine the number of personnel who meet the preset conditions according to the scoring result, and calculate the second indicator score of the service system based on the number of personnel and the total number of personnel in the service system.

[0138] The third calculation submodule is used to obtain the spare parts inventory list in the service data; match the material list in the target maintenance plan with the spare parts inventory list to obtain a matching result; and calculate the third indicator score of the service system according to the matching result.

[0139] In an optional embodiment of the present application, the device also includes: a monitoring module for monitoring the maintenance progress of the target service system for the maintenance service order; when the maintenance progress reaches a critical node, generating reminder information based on the service content in the maintenance service order; and sending the reminder information to a mobile device associated with the critical node.

[0140] See also Figure 5 , Figure 5 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 5As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system).

[0141] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0142] The memory 20 stores instructions executable by at least one processor 10, so that at least one processor 10 executes the method shown in the above embodiment.

[0143] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created by the use of a computer device based on the presentation of a small program landing page, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0144] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0145] The computer device further comprises a communication interface 30 for the computer device to communicate with other devices or a communication network.

[0146] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0147] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for dispatching orders for a smart lock maintenance system, characterized in that: The method comprises: Receive fault information of smart locks within the preset range of the maintenance system; Determine a corresponding target maintenance plan according to the fault information, and judge whether there is a door-to-door demand for the target maintenance plan; If there is a need for on-site visits, the adaptation scores of multiple service systems within the preset range are calculated based on a preset scoring module, and a target service system is screened out from the service systems by the adaptation scores; A maintenance service order is generated using the target maintenance plan, and the maintenance service order is sent to the target service system.

2. The method according to claim 1, characterized in that: Determining a corresponding target maintenance plan according to the fault information includes: Extracting first position data and fault type from the fault information; Based on the association relationship between the preset fault type and the preset material list, obtaining the material list corresponding to the fault type; The target maintenance plan is generated using the first location data, the fault type, and the bill of materials.

3. The method according to claim 2, characterized in that The calculating the adaptation scores of the plurality of service systems within the preset range based on the preset scoring module includes: Acquire service data of each service indicator in a plurality of the service systems, wherein the service indicators include distance indicators, personnel indicators, and accessory indicators; Calculate the index score of each of the service indicators according to the service data; The adaptation score of each of the service systems is calculated based on the indicator scores of the respective service indicators.

4. The method according to claim 3, characterized in that When the service indicator is a distance indicator, calculating the indicator score of each service indicator according to the service data includes: Acquire second location data of multiple technicians in the service data; Determine the distance between the smart lock and the technician according to the first position data and the second position data in the target maintenance plan; A first indicator score of the service system is calculated based on the distance between the smart lock and the technician.

5. The method according to claim 3, characterized in that: When the service indicator is a personnel indicator, calculating the indicator score of each service indicator according to the service data includes: Obtaining technical evaluation data of multiple technicians in the service data; Using the technical evaluation data to score each technician, and obtaining a scoring result; The number of personnel who meet the preset conditions is determined according to the scoring result, and the second indicator score of the service system is calculated based on the number of personnel and the total number of personnel in the service system.

6. The method according to claim 3, characterized in that When the service indicator is an accessory indicator, calculating the indicator score of each service indicator according to the service data includes: Obtaining a parts inventory list in the service data; Matching the bill of materials in the target maintenance plan with the parts inventory list to obtain a matching result; A third indicator score of the service system is calculated according to the matching result.

7. The method according to claim 1, characterized in that After sending the maintenance service order to the target service system, the method further includes: Monitoring the maintenance progress of the target service system for the maintenance service order; When the maintenance progress reaches a critical node, generating reminder information based on the service content in the maintenance service order; The reminder information is sent to a mobile device associated with the key node.

8. A dispatching device for a smart lock maintenance system, characterized in that: The device comprises: A receiving module, used to receive fault information of smart locks within a preset range of the maintenance system; A judgment module, used to determine a corresponding target maintenance plan according to the fault information, and to judge whether there is a door-to-door demand for the target maintenance plan; A calculation module, for calculating the adaptation scores of the plurality of service systems within the preset range based on the preset scoring module if there is a door-to-door demand, and screening out a target service system from the service systems by the adaptation scores; The sending module is used to generate a maintenance service order using the target maintenance plan, and send the maintenance service order to the target service system.

9. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method according to any one of claims 1 to 7 by executing the computer instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method according to any one of claims 1 to 7.

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