Dining store management method and device based on dining mode and storage medium

Abstract

This specification provides a method, device, and storage medium for restaurant management based on dining methods. The method includes: acquiring store customer traffic data and the current number of employees on duty; determining a target model criterion from a preset model criterion library based on the store customer traffic data, preset dining methods, and the current number of employees on duty; determining a target production line model based on the target model criterion; and starting / stopping corresponding printers and / or sending prompt messages to corresponding store employees based on the target production line model and the preset dining methods. The technical solution provided in this application is used to solve the problem of needing to readjust the correspondence between dishes and printers when switching operating modes.

Description

Technical Field

[0001] This document relates to the field of digital catering, and in particular to a method, device and storage medium for managing catering establishments based on dining methods. Background Technology

[0002] The main tools used to manage kitchen production in restaurants are printers or KDS (Kitchen Display System) screens. Typically, the management system is configured with corresponding printers or KDS screens for each dish. When a customer places an order, the order is printed from the corresponding printer or displayed on the KDS screen.

[0003] The diversification of dining options necessitates that stores manage their kitchens based on each type of dining method. For example, during periods when dine-in customers are few and far between, but takeout orders explode, the printers used for dine-in orders may need to handle a portion of the takeout orders.

[0004] However, printers used for dine-in order taking handle a portion of the sales orders or restore order types, requiring readjustment of the corresponding menu items for printing. This means restarting the entire store's management system, which reduces store efficiency. Furthermore, multiple restarts may cause mismatches between printers and operating areas. Summary of the Invention

[0005] Based on the above analysis, this application aims to propose a restaurant store management method, device, and storage medium based on dining methods, which enables flexible adjustment of the printer used for printing receipts without restarting the management system, thereby improving the store's work efficiency.

[0006] Firstly, one or more embodiments of this specification provide a restaurant management method based on dining style, including:

[0007] Obtain store customer traffic data and the current number of employees on duty;

[0008] Based on the store customer traffic data, the preset dining method, and the current number of store employees on duty, the target model criterion is determined from the preset model criterion library;

[0009] The target pipeline model is determined based on the target model criteria.

[0010] Based on the current number of store employees on duty, the target production line model, and the preset dining method, start and stop the corresponding printers and / or send reminder messages to the corresponding store employees.

[0011] Furthermore, the model criterion library contains multiple model criteria, each of which includes: a passenger flow threshold, an order number threshold corresponding to the preset dining method, and a target number of employees on duty;

[0012] The store customer traffic data includes: the number of orders corresponding to the preset dining method;

[0013] The step of determining the target model criterion from a preset model criterion library based on the store's customer traffic data, preset dining methods, and the current number of store employees includes:

[0014] Based on the aforementioned passenger flow data, determine the current passenger flow;

[0015] The current customer flow is compared with the customer flow threshold of each model criterion, the current number of store employees on duty is compared with the target number of employees on duty of each model criterion, and the number of orders corresponding to the preset dining method is compared with the number of orders corresponding to the preset dining method threshold of each model criterion.

[0016] Based on the comparison results, the criteria for determining the target model are determined.

[0017] Further, the step of determining the target model criterion based on the comparison results includes:

[0018] Determine whether a first model criterion exists in the model criterion library that matches the current passenger flow threshold;

[0019] If it does not exist, the current model criterion is determined to be the target model criterion;

[0020] If it exists, determine from the first model criterion whether there is a second model criterion that matches the order number threshold;

[0021] If it exists, the second model criterion is determined as the target model criterion;

[0022] If it does not exist, the model criterion that matches the employee attendance threshold with the current number of employees at the store is determined from the first model criterion and is taken as the target model criterion.

[0023] Furthermore, the parameters of the target production line model include: the target number of employees on duty and the number of printers corresponding to the preset dining method;

[0024] The step of starting and stopping the corresponding printers based on the current number of store employees on duty, the target production line model, and the preset dining method includes:

[0025] When the number of current store employees on duty is the same as the target number of employees on duty, start and stop the corresponding printers according to the number of printers corresponding to the preset dining method.

[0026] Furthermore, the step of starting and stopping the corresponding printers and sending notification messages to the corresponding store employees based on the current number of store employees on duty, the target production line model, and the preset dining method includes:

[0027] When it is determined that the current number of employees on duty at the store is different from the target number of employees on duty, it is determined whether the number of printers corresponding to the preset dining method matches the current number of employees on duty at the store.

[0028] When it is determined that the number of printers corresponding to the preset dining method matches the number of current store employees on duty, the store employees are rearranged according to the number of current store employees on duty and the number of printers corresponding to the preset dining method, and a prompt message is sent to the store employees who need to be rearranged.

[0029] Furthermore, the step of starting and stopping the corresponding printers and sending notification messages to the corresponding store employees based on the current number of store employees on duty, the target production line model, and the preset dining method includes:

[0030] If the number of printers corresponding to the preset dining method does not match the number of current store employees on duty, the current printer operation status is maintained.

[0031] Based on the target number of employees on duty and the current employee on duty threshold, determine the number of employees that need to be added;

[0032] Based on the number of employees needed, a notification message will be sent to remind the relevant store employees to report to their posts.

[0033] Furthermore, before acquiring store customer traffic data and the current number of store employees on duty, the method further includes:

[0034] Acquire data on customer traffic, dining habits, and on-duty employees;

[0035] Based on the passenger flow data, the dining methods, and the on-duty employee data, at least one model criterion is determined;

[0036] Based on each of the model criteria, a pipeline model is created, which is used to manage store printers and store staff.

[0037] The model criteria and the pipeline model are stored accordingly.

[0038] Secondly, one or more embodiments of this specification provide a restaurant management device based on dining methods, including: an acquisition module, a criterion determination module, and a data processing module;

[0039] The acquisition module acquires store customer traffic data and the current number of store employees on duty.

[0040] The criterion determination module determines the target model criterion from the preset model criterion library based on the store customer flow data, preset dining methods and the current number of store employees on duty;

[0041] The data processing module is used to determine the target production line model based on the target model criteria; and to start / stop the corresponding printers and / or send reminder information to the corresponding store employees based on the current number of store employees on duty, the target production line model, and the preset dining method.

[0042] Furthermore, the model criterion library contains multiple model criteria, each of which includes: a passenger flow threshold, an order number threshold corresponding to the preset dining method, and a target number of employees on duty;

[0043] The store customer traffic data includes: the number of orders corresponding to the preset dining method;

[0044] The data processing model is used to determine the current customer flow based on the customer flow data; compare the current customer flow with the customer flow threshold of each model criterion, the current number of store employees on duty with the target number of employees on duty of each model criterion, the number of orders corresponding to the preset dining method with the order number threshold of each model criterion; and determine the target model criterion based on the comparison results.

[0045] Thirdly, one or more embodiments of this specification provide a storage medium, including:

[0046] Used to store computer-executable instructions, which, when executed, implement the method described in the first aspect.

[0047] Compared with the prior art, this application can achieve at least the following technical effects:

[0048] Based on store traffic data, store layout data, and store order types, a pre-created production line model is used to digitize kitchen management strategies. Store management can select appropriate model criteria based on the actual situation of the store, and then switch models to manage the store's kitchen. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in one or more embodiments of this specification or in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this specification. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 A flowchart illustrating a restaurant management method based on dining style, provided for one or more embodiments of this specification;

[0051] Figure 2 A store layout diagram provided for one or more embodiments of this specification;

[0052] Figure 3 Another store layout diagram provided for one or more embodiments of this specification;

[0053] Figure 4 Another store layout diagram provided for one or more embodiments of this specification;

[0054] Figure 5 This is yet another store layout diagram provided for one or more embodiments of this specification. Detailed Implementation

[0055] To enable those skilled in the art to better understand the technical solutions in one or more embodiments of this specification, the technical solutions in one or more embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this specification, and not all of the embodiments. Based on one or more embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the protection scope of this document.

[0056] Current dining options are broadly categorized into dine-in, takeout, and delivery. Therefore, in existing technology, each mode corresponds to a separate printer. Since printers or KDS systems lack the ability to pre-store or invoke management models, store managers either modify the correspondence between menu items and printers or KDS displays by resetting and restarting, or simply use only one mode to manage the kitchen.

[0057] However, the above solutions suffer from poor applicability and low efficiency. Specifically,

[0058] Scene 1

[0059] With more and more people choosing food delivery as their dining option, delivery orders often far exceed dine-in and takeout orders. In this situation, using one printer per order would be wasteful of printer resources. If a printer designated for dine-in orders were to handle some of the sales orders, it would require restarting, which would also reduce the store's management efficiency.

[0060] Scene 2

[0061] Depending on the food delivery platform, consumers ordering takeout can be divided into several groups. In such cases, a particular platform may see a significantly higher number of orders from one consumer group compared to others. To ensure high order processing efficiency for this platform, a dedicated printer is required. Clearly, the existing printer configuration is insufficient for this scenario.

[0062] To address the aforementioned problems, this application provides a restaurant management method based on dining style, comprising the following steps:

[0063] Step 1: Obtain store customer traffic data and the current number of employees on duty.

[0064] In this embodiment, the store traffic data can be historical data. For example, the head office obtains traffic data and order numbers uploaded by each branch.

[0065] Step 2: Based on the store's customer traffic data, preset dining methods, and the current number of store employees on duty, determine the target model criteria from the preset model criterion library.

[0066] In this embodiment, a pre-set model criterion library contains multiple model criteria, each including: a customer flow threshold, a preset order number threshold corresponding to a dining method, and a target employee attendance number. In real-world scenarios, higher customer flow leads to more orders for various products, resulting in a greater number of printers being activated. A sharp increase in orders corresponding to a particular dining method necessitates activating more printers to alleviate pressure. Therefore, this application adjusts store operations based on customer flow and the order number corresponding to each dining method. The customer flow threshold can be derived from historical data, such as big data statistics on daily customer flow changes for each store. Furthermore, the relationship between order increases for various products and changes in customer flow can be calculated based on historical data. The preset order number threshold corresponding to a dining method can also be derived from historical data. Changing the operating method may require adjustments to the number of employees on duty. Therefore, this application incorporates the target employee attendance number into the criteria to support changes in the operating method.

[0067] In determining the target model criteria, the current customer flow is first determined based on the aforementioned customer flow data. The current customer flow is then compared with the customer flow thresholds for each model criterion, the current number of employees on duty is compared with the target number of employees on duty for each model criterion, and the number of orders corresponding to the preset dining method is compared with the order number thresholds for the preset dining method for each model criterion. Based on the comparison results, the target model criterion is determined.

[0068] Specifically, determine whether there exists a first model criterion in the model criterion library that matches the current passenger flow threshold; if not, determine the current model criterion as the target model criterion.

[0069] If it exists, determine from the first model criterion whether there is a second model criterion that matches the order number threshold.

[0070] If it exists, determine the second model criterion as the target model criterion. If it does not exist, determine the model criterion from the first model criterion that matches the employee attendance threshold with the current number of employees at the store as the target model criterion. It should be noted that if the current model criterion continues to be used, it is not necessary to redetermine the production line model. Matching the customer flow threshold with the current customer flow means that the difference between the customer flow threshold and the current customer flow is within a preset range, and the current customer flow is within the range based on the customer flow threshold. Matching the employee attendance threshold with the current number of employees at the store means that the difference between the employee attendance threshold and the current number of employees at the store is within a preset range, and the current number of employees at the store is within the range based on the employee attendance threshold.

[0071] In this embodiment of the application, the model criterion needs to be preset, and the setting process is as follows:

[0072] Acquire customer traffic data, dining patterns, and on-duty employee data; based on the customer traffic data, dining patterns, and on-duty employee data, determine at least one model criterion; based on each model criterion, create a pipeline model, which is used to manage store printers and store employees; store the model criterion and the pipeline model accordingly.

[0073] The model criteria will be explained using the following scenario as an example:

[0074] The store experiences multiple peaks in customer traffic throughout the day. Based on the customer traffic data, multiple customer traffic thresholds are determined, and each threshold represents a peak.

[0075] For each customer traffic threshold, based on printer distribution data and store employee distribution data, the number of printers to be turned on, the identifier of the printers in operation, and the number of employees on duty are determined. For example, suppose there are three customer traffic thresholds for a store, M, N, and O in ascending order. The store has three printers, and each printer requires one employee to operate. The corresponding criteria and pipeline model are as follows: when customer traffic does not exceed M, turn on one printer and assign one employee; when customer traffic exceeds M but does not exceed N, turn on two printers and assign two employees; when customer traffic exceeds N but does not exceed O, turn on three printers and assign three employees.

[0076] In the above scenario, the customer flow threshold is used as the model criterion to arrange printer start / stop and employee attendance as the assembly line model. Therefore, in this embodiment, the purpose of the model criterion is to present the criterion to store managers in the form of data. This allows store managers to compare the actual situation with the model criterion, thereby selecting the model criterion that best suits the current situation and providing a basis for subsequent selection of the assembly line model.

[0077] In this embodiment, the store offers multiple dining options, including dine-in, takeout, and delivery. When customer traffic reaches peak levels, each order type needs to correspond to at least one printer.

[0078] Based on the number of orders for each store's order type, determine the number of printers to be used and their identifiers; based on the number of orders for each store's order type, create a mapping between store order types and printer identifiers.

[0079] Specifically, when the number of orders is small, only one printer is turned on. When the number of orders of a certain type exceeds a threshold or the total number of orders exceeds a threshold, other printers are turned on, and the newly turned-on printers handle some of the orders, or a certain type of order.

[0080] Step 3: Determine the target pipeline model based on the target model criteria.

[0081] In this embodiment, for a restaurant, the process of placing an order, receiving an order, preparing ingredients, preparing the food, and serving (delivering) constitutes a complete production line. This production line includes multiple key nodes, each consisting of a printer and a store employee. Therefore, the production line model is a production line composed of multiple key nodes, meaning that store managers can manage the store printer and store employees based on the production line model.

[0082] It's important to note that while pipeline models are designed for automated scheduling of printers and store staff, they don't necessarily reflect the specific application scenarios. Model criteria, on the other hand, can effectively describe application scenarios but don't directly reflect the distribution of printers and store staff. Therefore, step 3 effectively guides store managers in selecting the optimal model based on the actual situation. For example, if a store manager faces scenario A, and multiple pipeline models exist, they still cannot determine which model is best suited for scenario A. In this case, the store manager can compare scenario A with the model criteria to find the closest one, and then select the pipeline model corresponding to that criterion.

[0083] In this embodiment, food delivery orders typically come from a wide range of sources, including: phone orders, WeChat delivery, self-pickup, POS delivery, Meituan delivery, Ele.me delivery, and mini-program delivery, with each source generating a different number of orders. To further increase efficiency, one or more printers are set up separately for platforms with a large number of orders. That is, a correspondence is created between the food delivery platform identifier and the printer identifier based on the number of orders corresponding to each food delivery platform.

[0084] Step 4: Based on the target production line model and preset dining methods, start and stop the corresponding printers and / or send reminder messages to the corresponding store employees.

[0085] In this embodiment, the parameters of the target production line model include: the target number of employees on duty and the number of printers corresponding to the preset dining method. In actual operation, the printers in the store are operated based on the above parameters.

[0086] Specifically, determine if the current number of employees present at the store matches the target number. If the current number of employees present matches the target number, start and stop the corresponding printers according to the preset number of printers for each dining method. If the current number of employees present does not match the target number, determine if the preset number of printers for each dining method matches the current number of employees present.

[0087] When the number of printers corresponding to the preset dining method matches the current number of store employees, the store employees are reassigned based on this ratio, and a notification message is sent to the employees requiring reassignment. It's important to note that matching the current number of store employees with the preset number of printers means ensuring that the currently assigned employees are capable of operating the corresponding number of printers. For example, if one person can operate two printers, then the current number of store employees matches the preset number of printers; otherwise, it does not.

[0088] If the number of printers corresponding to the preset dining mode does not match the current number of employees on duty, maintain the current printer's running status. Determine the number of additional employees needed based on the target number of employees on duty and the current employee attendance threshold. Send notification messages to the relevant employees to remind them to report for duty. Using this method, store managers can gradually switch modes or quickly switch operating modes after employees arrive. For example, after changing the operating mode, six printers need to be turned on, but only two employees are currently on duty. After the store manager sends a notification message to the relevant employees, employees will arrive gradually. At this time, the store manager can gradually turn on the printers according to the actual number of employees on duty until all printers are turned on. If all employees arrive within a short time, all printers can be turned on directly, thus quickly completing the operating mode switch.

[0089] To illustrate the feasibility of the above embodiments, the following specific implementation methods are provided, such as... Figures 2-5 As shown.

[0090] like Figure 2 The diagram shows the customer flow layout of a store. Besides dine-in service, the store primarily handles online food delivery orders. During off-peak hours, only KDS3 is activated to display both dine-in and delivery orders. During peak hours, KDS1 and KD2 display delivery orders from different platforms, while KDS3 displays dine-in orders. This aggregation facilitates order pickup for delivery drivers from different platforms, preventing conflicts between delivery orders and dine-in customers.

[0091] like Figure 3 As shown, during off-peak hours, the store has only two staff members: one in the kitchen and one in the front of house. Orders from dine-in customers and delivery platforms are displayed in KDS3. After preparation, W1 handles packaging, distribution, and serving. The parameters of the target production line model are: a preset number of printers of 1, a preset number of employees on duty of 2, and a preset printer start / stop status of: KDS3 on, others off.

[0092] With the increase in customer traffic and food delivery orders, such as Figure 4 As shown, when a store adds one employee, KDS2 is opened, dine-in orders are displayed in KDS3, and takeout orders are displayed in KDS2. The parameters of the target pipeline model are: preset number of printers 2, preset number of employees on duty 3, and preset printer start / stop status information: KDS3 and KDS2 are on, others are off.

[0093] As customer traffic and food delivery orders continue to increase, Figure 5As shown, when a store adds one employee, KDS2 is opened, dine-in orders are displayed in KDS3, M platform takeout orders are displayed in KDS2, and E platform takeout orders are displayed in KDS1. The parameters of the target pipeline model are: preset number of printers 3, preset number of employees on duty 4, and preset printer start / stop status information: KDS3, KDS2, and KDS1 are all on.

[0094] This application provides a restaurant management device based on dining methods, including: an acquisition module, a criterion determination module, and a data processing module;

[0095] The acquisition module acquires store customer traffic data and the current number of store employees on duty.

[0096] The criterion determination module determines the target model criterion from the preset model criterion library based on the store customer flow data, preset dining methods and the current number of store employees on duty;

[0097] The data processing module is used to determine the target production line model based on the target model criteria; and to start / stop the corresponding printers and / or send reminder information to the corresponding store employees based on the current number of store employees on duty, the target production line model, and the preset dining method.

[0098] In this embodiment of the application, the model criterion library is provided with multiple model criteria, each of which includes: a passenger flow threshold, an order number threshold corresponding to the preset dining method, and a target number of employees on duty;

[0099] The store customer traffic data includes: the number of orders corresponding to the preset dining method;

[0100] The data processing model is used to determine the current customer flow based on the customer flow data; compare the current customer flow with the customer flow threshold of each model criterion, the current number of store employees on duty with the target number of employees on duty of each model criterion, the number of orders corresponding to the preset dining method with the order number threshold of each model criterion; and determine the target model criterion based on the comparison results.

[0101] This application provides a storage medium, including:

[0102] Used to store computer-executable instructions, which, when executed, implement the methods described in the above embodiments.

[0103] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0104] In the 1930s, improvements to a technology could be clearly distinguished as either hardware improvements (e.g., improvements to the circuit structure of diodes, transistors, switches, etc.) or software improvements (improvements to the methodology). However, with technological advancements, many improvements to the methodology today can be considered direct improvements to the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved methodology into the hardware circuit. Therefore, it cannot be said that an improvement to the methodology cannot be implemented using hardware physical modules. For example, a Programmable Logic Device (PLD) (such as a Field Programmable Gate Array (FPGA)) is such an integrated circuit whose logic function is determined by the user programming the device. Designers can program and "integrate" a digital system onto a PLD themselves, without needing chip manufacturers to design and manufacture dedicated integrated circuit chips. Furthermore, nowadays, instead of manually manufacturing integrated circuit chips, this programming is mostly implemented using "logic compiler" software. Similar to the software compiler used in program development, the original code before compilation must also be written in a specific programming language, called a Hardware Description Language (HDL). There are many HDLs, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also understand that by simply performing some logic programming on the method flow using one of these hardware description languages ​​and programming it into an integrated circuit, the hardware circuit implementing the logical method flow can be easily obtained.

[0105] The controller can be implemented in any suitable manner. For example, it can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, application-specific integrated circuits (ASICs), programmable logic controllers, and embedded microcontrollers. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicon Labs C8051F320. A memory controller can also be implemented as part of the control logic of the memory. Those skilled in the art will also recognize that, in addition to implementing the controller in purely computer-readable program code form, the same functionality can be achieved by logically programming the method steps to make the controller take the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers. Therefore, such a controller can be considered a hardware component, and the means included therein for implementing various functions can also be considered as structures within the hardware component. Alternatively, the means for implementing various functions can be considered as both software modules implementing the method and structures within the hardware component.

[0106] The systems, devices, modules, or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0107] For ease of description, the above apparatus is described by dividing it into various functional units. Of course, when implementing the embodiments of this specification, the functions of each unit can be implemented in one or more software and / or hardware.

[0108] Those skilled in the art will understand that one or more embodiments of this specification can be provided as a method, system, or computer program product. Therefore, one or more embodiments of this specification may take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this specification may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0109] This specification is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this specification. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0110] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0111] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0112] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0113] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0114] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0115] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0116] One or more embodiments of this specification can be described in the general context of computer-executable instructions, such as program modules, that are executed by a computer. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform a particular task or implement a particular abstract data type. One or more embodiments of this specification can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0117] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to interchangeably. Each embodiment focuses on describing the differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments.

[0118] The above description is merely an embodiment of this document and is not intended to limit the scope of this document. Various modifications and variations can be made to this document by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this document should be included within the scope of the claims of this document.

Claims

1. A dining store management method based on a dining method, characterized by, The method comprises the following steps: obtaining store passenger flow data and the current number of employees on duty in the store; determining a target model criterion from a preset model criterion library according to the store passenger flow data, a preset dining mode and the current number of employees on duty in the store; the model criterion library is provided with a plurality of model criteria, and each of the model criteria comprises a passenger flow threshold, an order number threshold corresponding to the preset dining mode and a target number of employees on duty; determining a target pipeline model according to the target model criterion; the parameters of the target pipeline model comprise a target number of employees on duty and a number of printers corresponding to the preset dining mode; starting and stopping corresponding printers and / or sending prompt information to corresponding employees in the store based on the current number of employees on duty in the store, the target pipeline model and the preset dining mode; the step of starting and stopping corresponding printers based on the current number of employees on duty in the store, the target pipeline model and the preset dining mode comprises the following steps: when the current number of employees on duty in the store is the same as the target number of employees on duty, starting and stopping corresponding printers according to the number of printers corresponding to the preset dining mode.

2. The method of claim 1, wherein: the store passenger flow data comprises an order number corresponding to the preset dining mode; the step of determining a target model criterion from a preset model criterion library according to the store passenger flow data, a preset dining mode and the current number of employees on duty in the store comprises the following steps: determining a current passenger flow according to the passenger flow data; respectively comparing the current passenger flow with the passenger flow threshold of each of the model criteria, the current number of employees on duty in the store with the target number of employees on duty of each of the model criteria, the order number corresponding to the preset dining mode with the order number threshold corresponding to the preset dining mode of each of the model criteria; determining a target model criterion according to the comparison results.

3. The method of claim 2, wherein: the step of determining a target model criterion according to the comparison results comprises the following steps: determining whether there is a first model criterion in the model criterion library in which the passenger flow threshold matches the current passenger flow; if not, determining that the current model criterion is the target model criterion; if so, determining whether there is a second model criterion in the first model criterion in which the order number threshold matches the order number; if so, determining that the second model criterion is the target model criterion; if not, determining that the model criterion in which the employee on-duty number threshold matches the current number of employees on duty in the store in the first model criterion is the target model criterion.

4. The method of claim 1, wherein: the step of starting and stopping corresponding printers and sending prompt information to corresponding employees in the store based on the current number of employees on duty in the store, the target pipeline model and the preset dining mode comprises the following steps: when the current number of employees on duty in the store is not the same as the target number of employees on duty, determining whether the number of printers corresponding to the preset dining mode matches the current number of employees on duty in the store. When it is determined that the number of printers corresponding to the preset dining mode matches the number of current store employees on duty, the store employees are rearranged according to the number of current store employees on duty and the number of printers corresponding to the preset dining mode, and prompt information is sent to the store employees who need to be rearranged.

5. The method of claim 4, wherein, the starting and stopping of the corresponding printers and the sending of the prompt information to the corresponding store employees based on the number of current store employees on duty, the target flow line model and the preset dining mode comprises: when it is determined that the number of printers corresponding to the preset dining mode does not match the number of current store employees on duty, the current state of the printers is maintained; determining the number of employees that need to be supplemented according to the target number of employees on duty and the current number of employees on duty threshold; prompting the corresponding store employees to report for duty by sending prompt information according to the number of employees that need to be supplemented.

6. The method of claim 1, wherein, before the store customer flow data and the number of current store employees on duty are obtained, the method further comprises: obtaining customer flow data, dining mode and on-duty employee data; determining at least one model criterion based on the customer flow data, the dining mode and the on-duty employee data; creating a flow line model based on each of the model criteria, the flow line model being used to manage store printers and store employees; storing the model criteria and the flow line model correspondingly.

7. A dining store management apparatus based on a dining style, characterized by, comprises: an acquisition module, a criterion determination module and a data processing module; the acquisition module acquires store customer flow data and the number of current store employees on duty; the criterion determination module determines a target model criterion from a preset model criterion library according to the store customer flow data, a preset dining mode and the number of current store employees on duty; the model criterion library is provided with a plurality of model criteria, and each of the model criteria comprises a customer flow threshold, an order number threshold corresponding to the preset dining mode and a target number of employees on duty; the data processing module is configured to determine a target flow line model according to the target model criterion, and parameters of the target flow line model comprise a target number of employees on duty and a number of printers corresponding to the preset dining mode; starting and stopping the corresponding printers and / or sending prompt information to the corresponding store employees based on the number of current store employees on duty, the target flow line model and the preset dining mode; the starting and stopping of the corresponding printers based on the number of current store employees on duty, the target flow line model and the preset dining mode comprises: when it is determined that the number of current store employees on duty is the same as the target number of employees on duty, starting and stopping the corresponding printers according to the number of printers corresponding to the preset dining mode.

8. The apparatus of claim 7, wherein, the store customer flow data comprises an order number corresponding to the preset dining mode. The data processing model is used to determine a current passenger flow according to the passenger flow data, compare the current passenger flow with passenger flow thresholds of each model criterion respectively, compare a current number of employees on duty of the store with target numbers of employees on duty of each model criterion respectively, compare an order number corresponding to the preset dining mode with order number thresholds corresponding to the preset dining mode of each model criterion respectively, and determine a target model criterion according to a comparison result.

9. A storage medium characterized by comprising: Comprise: A computer readable medium storing computer executable instructions that, when executed, implement the method of any of claims 1-6.

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