CN112487059A - Electronic menu data statistical method and device, storage medium and computer equipment - Google Patents
Electronic menu data statistical method and device, storage medium and computer equipment Download PDFInfo
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Abstract
The application discloses an electronic menu data statistical method and device, a storage medium and computer equipment, wherein the method comprises the following steps: acquiring a historical reference time period and electronic menu use data of the historical reference time period; counting the electronic menu use data to obtain analysis data of the electronic menu use condition corresponding to the historical reference time period; and generating production recommendation data of the electronic menu according to the analysis data. The method and the device help to improve the rationality of production plan formulation.
Description
Technical Field
The present application relates to the field of data processing technologies, and in particular, to a method and an apparatus for counting electronic menu data, a storage medium, and a computer device.
Background
In the prior art, when a production plan is made by merchants such as restaurants and the like, the production plan is generally made according to experience or according to old production content, the production plan cannot be planned accurately, the situations of overlarge deviation and undersize occur, the problem that the goods input amount cannot be accurately determined in the food material feeding process and the storage amount cannot be accurately estimated in the food material storage process due to unreasonable production plan often occurs, and the waste, the shortage and the improper storage of the food materials are caused.
Disclosure of Invention
In view of this, the present application provides an electronic recipe data statistical method and apparatus, a storage medium, and a computer device, which are helpful for improving the rationality of production plan formulation.
According to an aspect of the present application, there is provided an electronic recipe data statistical method, the method including:
acquiring a historical reference time period and electronic menu use data of the historical reference time period;
counting the electronic menu use data to obtain analysis data of the electronic menu use condition corresponding to the historical reference time period;
and generating production recommendation data of the electronic menu according to the analysis data.
Optionally, the obtaining the history reference period includes:
acquiring a time interval attribute of a target time interval, and acquiring a historical reference time interval corresponding to the target time interval according to the time interval attribute, wherein if the time interval attribute is a first attribute, the historical reference time interval comprises a plurality of historical time intervals which are matched with the first attribute within a first preset time, and if the time interval attribute is a second attribute, the historical reference time interval comprises a historical time interval which is matched with a second preset time before the target time interval; or,
and acquiring a custom time period corresponding to the target time period, and taking the custom time period as the historical reference time period.
Optionally, the counting the electronic menu usage data to obtain analysis data of the electronic menu usage corresponding to the historical reference time period includes:
counting the use data of the electronic menu to obtain the use number of the electronic menu corresponding to the counted time unit in the historical reference time period;
and generating use amount trend analysis data of the electronic menu in the historical reference time period according to the use amount of the electronic menu.
Optionally, the counting the electronic recipe usage data to obtain analysis data of the electronic recipe usage corresponding to the historical reference time period further includes:
counting the use data of the electronic menu to obtain the use number of the total electronic menu corresponding to the counting time period unit in the historical reference time period;
and generating use amount trend analysis data of the total electronic menu in the historical reference time period according to the use amount of the total electronic menu.
Optionally, the generating production recommendation data of the electronic menu according to the analysis data includes:
according to the usage trend analysis data of the electronic recipes, acquiring a first electronic recipe of which the usage trend meets a first preset trend condition, and generating production recommendation data corresponding to the target time period based on the first electronic recipe, wherein the usage increase rate corresponding to the first electronic recipe is larger than a first preset increase rate and/or the usage increase rate is ranked at a first preset number; and/or the presence of a gas in the gas,
and acquiring a second electronic menu of which the usage trend meets a second preset trend condition according to the usage trend analysis data of the total electronic menu, and generating production recommendation data corresponding to the target time period based on the second electronic menu, wherein the usage increase rate corresponding to the second electronic menu is greater than the usage increase rate corresponding to the total electronic menu.
Optionally, the method further comprises:
and acquiring a popular electronic menu and/or a new electronic menu corresponding to the current time period, and generating production recommendation data corresponding to the target time period based on the popular electronic menu and/or the new electronic menu.
Optionally, the production recommendation data includes production recommendation data corresponding to at least one merchant; after generating the production recommendation data of the electronic menu according to the analysis data, the method further comprises:
and obtaining the merchant production plan data based on the selection data of the production recommendation data corresponding to the merchant.
Optionally, after obtaining the merchant production plan data, the method further includes:
acquiring the merchant food material demand data based on the merchant production plan data;
and obtaining food material supply data of a general merchant according to the food material demand data, wherein the food material supply data comprises food material production data and/or food material purchasing data.
According to another aspect of the present application, there is provided an electronic recipe data statistics apparatus, the apparatus including:
the historical data acquisition module is used for acquiring a historical reference time period corresponding to a target time period and electronic menu use data of the historical reference time period;
the historical data analysis module is used for counting the electronic menu use data to obtain analysis data of the electronic menu use condition corresponding to the historical reference time period;
and the first data generation module is used for generating production recommendation data of the electronic menu according to the analysis data.
Optionally, the historical data obtaining module includes:
the device comprises a first time period obtaining unit, a second time period obtaining unit and a time period obtaining unit, wherein the first time period obtaining unit is used for obtaining a time period attribute of a target time period and obtaining a historical reference time period corresponding to the target time period according to the time period attribute, if the time period attribute is a first attribute, the historical reference time period comprises a plurality of historical time periods which are matched with the first attribute within a first preset time, and if the time period attribute is a second attribute, the historical reference time period comprises a historical time period which is matched with a second preset time before the target time period; or,
and the second time period acquisition unit is used for acquiring a custom time period corresponding to the target time period and taking the custom time period as the historical reference time period.
Optionally, the historical data analysis module includes:
the first usage data acquisition unit is used for counting the usage data of the electronic menu and acquiring the usage number of the electronic menu corresponding to a counting time unit in the historical reference time period;
and the first trend analysis unit is used for generating usage trend analysis data of the electronic menu in the historical reference time period according to the usage amount of the electronic menu.
Optionally, the historical data analysis module further includes:
the second usage data acquisition unit is used for counting the usage data of the electronic menu and acquiring the usage number of the total electronic menu corresponding to the counting time period unit in the historical reference time period;
and the second trend analysis unit is used for generating use amount trend analysis data of the total electronic menu in the historical reference time period according to the use amount of the total electronic menu.
Optionally, the first data generation module includes:
the first data generation unit is used for acquiring a first electronic menu of which the usage trend meets a first preset trend condition according to the usage trend analysis data of the electronic menu and generating production recommendation data corresponding to the target time period based on the first electronic menu, wherein the usage increase rate corresponding to the first electronic menu is greater than a first preset increase rate and/or the usage increase rate is ranked at a first preset number; and/or the presence of a gas in the gas,
and the second data generation unit is used for acquiring a second electronic menu of which the usage trend meets a second preset trend condition according to the usage trend analysis data of the total electronic menu, and generating production recommendation data corresponding to the target time period based on the second electronic menu, wherein the usage increase rate corresponding to the second electronic menu is greater than the usage increase rate corresponding to the total electronic menu.
Optionally, the apparatus further comprises:
and the second data generation module is used for acquiring a popular electronic menu and/or a new electronic menu corresponding to the current time period and generating production recommendation data corresponding to the target time period based on the popular electronic menu and/or the new electronic menu.
Optionally, the production recommendation data includes production recommendation data corresponding to at least one merchant; the device further comprises:
and the plan data generation module is used for obtaining the production plan data of the commercial tenant based on the selection data of the production recommendation data corresponding to the commercial tenant after the production recommendation data of the electronic menu is generated according to the analysis data.
Optionally, the apparatus further comprises:
a food material demand acquisition module, configured to obtain the merchant food material demand data based on the merchant production plan data after obtaining the merchant production plan data;
and the supply data acquisition module is used for acquiring food material supply data of a general merchant according to the food material demand data, wherein the food material supply data comprises food material production data and/or food material purchasing data.
According to yet another aspect of the present application, there is provided a storage medium having stored thereon a computer program which, when executed by a processor, implements the above-described electronic recipe data statistical method.
According to yet another aspect of the present application, there is provided a computer device, including a storage medium, a processor, and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the above electronic recipe data statistical method when executing the program.
By means of the technical scheme, the electronic menu data statistical method and device, the storage medium and the computer device, the historical reference time period and the corresponding electronic menu use data are obtained, the electronic menu use data are counted, the analysis data of the electronic menu use conditions in the historical reference time period are determined, and therefore production recommendation data of the electronic menu are generated. Compared with the mode of making a production plan according to the working experience or subjective intention of workers in the prior art, the embodiment of the application is based on the execution condition of the cooking equipment to the electronic menu program in the historical reference time period, the production recommendation data of the electronic menu is determined by carrying out statistical analysis on the use data of the electronic menu, scientific, reliable and basis guidance data are provided for merchants to formulate production plans, the merchants can formulate the production plans according to the production recommendation data determined based on the historical use conditions of the electronic menu, the rationality of formulating the production plans is improved, the problem that the goods quantity cannot be accurately determined in the food material stocking process due to unreasonable production plans is further avoided, and the problem that the storage capacity cannot be accurately estimated in the food material storage process is solved, and the problems of waste, insufficiency, improper preservation and the like of food materials are effectively avoided.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart illustrating an electronic recipe data statistics method according to an embodiment of the present application;
fig. 2 shows a schematic structural diagram of an electronic menu data statistics apparatus provided in an embodiment of the present application.
Detailed Description
The present application will be described in detail below with reference to the accompanying drawings in conjunction with embodiments. It should be noted that the embodiments and features of the embodiments in the present application may be combined with each other without conflict.
In this embodiment, an electronic recipe data statistical method is provided, as shown in fig. 1, the method includes:
102, counting the use data of the electronic menu to obtain analysis data of the use condition of the electronic menu corresponding to a historical reference time period;
and 103, generating production recommendation data of the electronic menu according to the analysis data.
The embodiment of the application can be applied to terminal equipment which can record electronic menu use data, such as a kitchen management terminal, a merchant management terminal, a central management terminal (used for managing cooking related work of merchants), and the like. The embodiment of the present application is explained by taking the application to a merchant management terminal as an example, but is not limited to this application scenario.
In the above embodiment, a history reference time period is obtained, where the history reference time period specifically refers to a time period in which historical data needs to be referred to when a production plan of a certain target time period is made, for example, historical data of monday to thursday may be referred to when a production plan of friday is made, and historical data of a new year's new year may be referred to when a production plan of a new year's new year is made. After the historical reference time period is determined, the electronic menu usage data of the historical reference time period can be inquired in the historical electronic menu usage data record saved by the merchant management terminal, for example, the electronic menu usage data of Monday to Thursday and the electronic menu usage data of the previous three year and New year day are obtained. And further performing statistical analysis on the electronic menu usage data in the historical reference time period to determine analysis data of the electronic menu usage situation in the historical reference time period, for example, since the cooking of dishes is realized based on the execution of an electronic menu program, the usage number of the electronic menu can reflect the cooking situation of the dishes of a merchant in the historical reference time period, and the statistics on the usage number of the electronic menu in the historical reference time period can be used for obtaining analysis data such as one or more types of electronic menu usage quantity trends and all types of electronic menu usage quantity trends in the historical reference time period. Production plan data based on the electronic menu can be formulated according to analysis data of the electronic menu using condition corresponding to the historical reference time period, specifically, production recommendation data of the electronic menu can be generated according to the analysis data, after the production recommendation data is confirmed by a merchant, a production plan is formulated according to the confirmed production recommendation data, and therefore work of production links such as food material stocking, storage and the like can be guided according to the production plan. For example, the electronic menu usage data of the historical reference time period includes the electronic menu usage number corresponding to the "roast duck" in the last 3 year of the new year, after statistical analysis, the change trend of the electronic menu usage number of the "roast duck" in the last 3 years is determined, and assuming that the change of the electronic menu usage number of the "roast duck" in the last 3 years is smooth, the production recommendation data of the "roast duck" electronic menu in the last year of the new year can be generated according to the average value of the electronic menu usage number of the "roast duck" in the last 3 years, and after confirmation of a merchant, the production recommendation data is used as the production plan of the "roast duck" in the last year, so that the production plan is used to determine how many raw materials, seasonings, sauces, ingredients and other food materials needed by the "roast duck" in advance, and determine the food material access, food material storage conditions and other plans.
By applying the technical scheme of the embodiment, the historical reference time period and the corresponding electronic menu use data are obtained, the electronic menu use data are counted to determine the analysis data of the electronic menu use condition in the historical reference time period, and therefore the production recommendation data of the electronic menu are generated. Compared with the mode of making a production plan according to the working experience or subjective intention of workers in the prior art, the embodiment of the application is based on the execution condition of the cooking equipment to the electronic menu program in the historical reference time period, the production recommendation data of the electronic menu is determined by carrying out statistical analysis on the use data of the electronic menu, scientific, reliable and basis guidance data are provided for merchants to formulate production plans, the merchants can formulate the production plans according to the production recommendation data determined based on the historical use conditions of the electronic menu, the rationality of formulating the production plans is improved, the problem that the goods quantity cannot be accurately determined in the food material stocking process due to unreasonable production plans is further avoided, and the problem that the storage capacity cannot be accurately estimated in the food material storage process is solved, and the problems of waste, insufficiency, improper preservation and the like of food materials are effectively avoided.
In this embodiment of the present application, optionally, the "acquiring the historical reference time period" in step 101 may specifically include:
step 101-1, obtaining a time interval attribute of a target time interval, and obtaining a historical reference time interval corresponding to the target time interval according to the time interval attribute, wherein if the time interval attribute is a first attribute, the historical reference time interval comprises a plurality of historical time intervals matched with the first attribute within a first preset time, and if the time interval attribute is a second attribute, the historical reference time interval comprises a historical time interval matched with a second preset time before the target time interval; or,
and 101-2, acquiring a custom time period corresponding to the target time period, and taking the custom time period as a historical reference time period.
In the above embodiments, the target period specifically refers to a period for planning generation of a plan, for example, the target period is friday, or 3 months, or a period of a year. In step 101-1, the historical reference time interval may be determined based on time interval attributes of the target time interval, and specifically, time interval attributes corresponding to the target time interval are obtained, where the time interval attributes at least include a first attribute and a second attribute, the first attribute may be a holiday attribute, such as a birth date period, a national day period, a spring festival period, and the like, and the second attribute may be a non-holiday time interval attribute, such as a workday period. If the time interval attribute of the target time interval is the first attribute, the historical reference time interval may be a plurality of historical time intervals which are matched with the first attribute within a first preset time, for example, the target time interval is a spring festival period, and the historical reference time interval may be a spring festival period of each year within the last 5 years; if the period attribute of the target period is the second attribute, the historical reference period may be a historical period before the target period and matching with a second preset time, for example, the target period is friday, and the historical reference period may be 4 days before friday, that is, monday to thursday. In step 101-2, the historical reference time period may also be determined based on a customized time period specified by the merchant, and the customized time period set by the merchant and corresponding to the target time period is taken as the historical reference time period of the target time period, for example, the target time period is 1 month and 15 days, and the customized time period set by the merchant is 7 days before 1 month and 15 days.
In this embodiment of the present application, optionally, step 102 may specifically include:
102-1, counting the use data of the electronic menu, and acquiring the use number of the electronic menu corresponding to the counted time unit in the historical reference time period;
and 102-2, generating use amount trend analysis data of the electronic menu in the historical reference time period according to the use amount of the electronic menu.
In steps 102-1 to 102-2, statistics are made on the electronic recipe usage data, acquiring the using quantity of each kind of electronic menu in the historical reference time period according to the statistical time unit, for example, if the historical reference time period is 7 days before 15 days of 1 month, and the statistical time unit is 1 day, the usage amount of the electronic menu for each day in 7 days should be acquired respectively according to the unit of one day, further, according to the using quantity of each electronic menu corresponding to the statistical time unit, generating the using quantity trend analysis data of each electronic menu in the whole historical reference time period, for example, the data of the use trend analysis of the tomato egg-frying electronic menu within 7 days is generated according to the day unit, the usage trend analysis data … … of the electronic menu of "braised pork in soy sauce" within 7 days is generated according to the unit of day, and the growth rate of the usage amount of the electronic menu of "fried egg with tomato", "braised pork in soy sauce" and the like is determined.
Correspondingly, step 103 may specifically include:
step 103-1, obtaining a first electronic menu of which the usage trend meets a first preset trend condition according to the usage trend analysis data of the electronic menu, and generating production recommendation data corresponding to a target time period based on the first electronic menu, wherein the usage increase rate corresponding to the first electronic menu is greater than a first preset increase rate and/or the usage increase rate is ranked at a first preset number.
In step 103-1, based on the usage trend analysis data of each electronic recipe, a first electronic recipe in which the production situation is optimistic is obtained, so as to generate production recommendation data corresponding to the target time period based on the first electronic recipe, in this embodiment, the first electronic recipe is an electronic recipe that satisfies a first preset trend condition, where the condition may be that the usage increase rate corresponding to the first electronic recipe is greater than a first preset increase rate, for example, the usage increase rate corresponding to the "tomato scrambled egg" electronic recipe is greater than 5%, and the condition may also be that the usage increase rate corresponding to the first electronic recipe is ranked by a first preset number, for example, the "red-cooked meat" electronic recipe belongs to the top 10 electronic recipes in the usage increase rate ranking of all electronic recipes, and the electronic recipes of the two conditions satisfy one of the two conditions, and the production recommendation data corresponding to the target time period are determined as the first electronic recipe, Or the first electronic menu when the first electronic menu is satisfied at the same time.
In this embodiment of the application, optionally, step 102 may further include:
102-3, counting the use data of the electronic menu, and acquiring the use number of the total electronic menu corresponding to the statistical time interval unit in the historical reference time interval;
and 102-4, generating use amount trend analysis data of the total electronic menu in the historical reference time period according to the use amount of the total electronic menu.
In steps 102-3 to 102-4, statistics may also be performed on the total usage amount of the electronic recipes in the historical reference period, and usage amount trend analysis data of the total electronic recipes is generated. For example, the number of the electronic recipes used in the historical reference period is 5, the historical reference period is 7 days before 15 days of 1 month, and the statistical time unit is 1 day, then the usage number of the electronic recipes for each day in 7 should be respectively obtained according to the unit of one day, and the overall usage trend analysis data … … of the 5 electronic recipes for 7 days is generated according to the unit of one day, so as to determine the growth rate of the usage number of the 5 electronic recipes.
Correspondingly, step 103 may specifically include:
and 103-2, according to the usage trend analysis data of the total electronic menu, acquiring a second electronic menu of which the usage trend meets a second preset trend condition, and generating production recommendation data corresponding to the target time period based on the second electronic menu, wherein the usage increase rate corresponding to the second electronic menu is greater than the usage increase rate corresponding to the total electronic menu.
In step 103-2, a second electronic recipe with a better usage condition of the electronic recipe is obtained based on the usage trend analysis data of the total electronic recipe, so as to generate production recommendation data corresponding to the target time period based on the second electronic recipe, in this embodiment, the second electronic recipe is an electronic recipe that satisfies a second preset trend condition, and the second electronic recipe may specifically be an electronic recipe with a usage increase rate that is greater than a usage increase rate corresponding to the total electronic recipe, for example, the usage increase rate corresponding to the "water-boiled fish" electronic recipe is 10%, the usage increase rate corresponding to the total electronic recipe is 5%, and the "water-boiled fish" electronic recipe may be determined as the second electronic recipe.
It should be noted that, the steps 102-1, 102-2 and 103-1 can be combined, the steps 102-1, 102-2, 102-3, 102-4 and 103-1, 103-2 can be combined, and the steps 102-1, 102-2, 102-3, 102-4 and 103-2 can be combined.
In this embodiment of the present application, optionally, step 102 may further include:
and 104, acquiring a popular electronic menu and/or a new electronic menu corresponding to the current time period, and generating production recommendation data corresponding to the target time period based on the popular electronic menu and/or the new electronic menu.
In step 104, production recommendation data may also be generated according to the popular electronic menu and the new electronic menu, for example, when calculating the production plan during the meta-denier, the reference historical data is the electronic menu usage data during the last 3 years of the meta-denier, but dish a has not been developed in the above historical period, but dish a is a popular dish with a high recent unit, so the electronic menu of dish a may be taken into account when making the plan, and in addition, the new electronic menu that the merchant may use as a main refresher may also be referred to.
In this embodiment of the application, optionally, after step 103 or step 104, the method may further include:
and 105, acquiring the production plan data of the merchants based on the selection data of the production recommendation data corresponding to the merchants.
In step 105, the merchant may select the production recommendation data in the intelligently generated target time period, and obtain the merchant production plan data based on the selection data of the merchant, for example, the production recommendation data includes plan usage recommendations of 10 electronic recipes, where 2 are electronic recipes that the merchant prepares to put on shelf in the target time period, then the merchant may select another 8 types of generated production plan data, and in addition, the merchant may modify and correct the plan usage recommendations in the intelligently generated production recommendation data.
Correspondingly, in the embodiment of the present application, step 105 may further include:
106, acquiring merchant food material demand data based on merchant production plan data;
step 107, obtaining food material supply data of a general merchant according to the food material demand data, wherein the food material supply data comprises food material production data and/or food material purchasing data.
In steps 106 to 107, based on the production plan data confirmed by the merchant and based on the planned usage amount of each electronic menu in the production plan data, merchant food material demand data is determined, and specifically, by analyzing each electronic menu, demand data of dishes corresponding to each electronic menu on food materials and articles such as various food materials, ingredients, seasonings, packaging boxes, disposable tableware and the like is determined, and then demand data of food materials and articles corresponding to all electronic menus in the merchant production plan data, that is, the merchant food material demand data and the merchant article demand data, are determined. Further, the food material supply center can sum and count the merchant food material demand data of all merchants supplying food materials by the food material supply center, and determine the food material supply data of the total merchants, wherein the food material supply data can include food material production data, food material purchase data, food material rough processing data, food material transportation data and the like, the food material production data can be food material planting and breeding data, and the rough processing of the food material can be rough processing of raw food materials, such as potato mash removal, live chicken slaughter and the like.
After the commercial tenant purchases food materials based on the production plan data, the step of purchasing the obtained food materials to be warehoused to warehouse the food materials further comprises the following steps:
step 201, acquiring storage data and an electronic menu of food materials to be warehoused based on food material labels of the food materials to be warehoused;
step 202, determining target warehousing data corresponding to the food materials to be warehoused according to the storage data, and associating the target warehousing data with the electronic menu, wherein the target warehousing data comprise storage positions and/or storage environment parameters matched with the storage data in a target warehouse.
The embodiment of the application can be applied to systems related to food material warehousing management, such as a warehouse management system, a merchant management system capable of being in communication connection with the warehouse management system, and the like, so as to manage food material warehousing problems. For example, the warehouse management system may determine warehousing data of food materials based on food material tags attached to food materials to be warehoused, and control warehousing and storage of the food materials according to the food material warehousing data, and for example, the warehouse management system may be applied to a central control system in communication connection with the warehouse management system, determine the food material warehousing data by the central control system, and then send the food material warehousing data to the warehouse management system, and the warehouse management system manages warehousing and storage of the food materials according to the food material warehousing data. Unless otherwise stated, the embodiments of the present application are explained by taking the application to a warehouse management system as an example. In addition, in the embodiment of the present application, the types of food materials to be warehoused may include multiple types, for example, the food materials to be warehoused may be unprocessed raw materials (for example, potatoes), or may be finished clean vegetables (for example, shredded potatoes after being cleaned, peeled, and shredded), and the like, where when the food materials to be warehoused are clean vegetables, the clean vegetables may specifically include large clean vegetable packages packed according to the types of the food materials, for example, shredded potatoes clean vegetable packages and tomato clean vegetable packages, or may include single clean vegetable packages packed according to the recipe requirements, for example, shredded green peppers and shredded potatoes required by shredded green peppers are packed into one clean vegetable package.
In the above embodiment, the food material to be warehoused may be a food material package in which a food material tag is preset, the food material tag carries storage data and an electronic menu corresponding to the corresponding food material to be warehoused, the food material tag may be determined based on order information, for example, statistics of order data of a store is performed, an electronic menu corresponding to each order is determined, a food material tag is generated according to a required food material and a required food material specification which are included in the electronic menu and a storage environment parameter corresponding to the required food material, and the food material tag may specifically include a food material type, a food material specification, a food material storage time and a storage environment parameter, where the storage environment parameter may specifically include a storage temperature parameter, a storage humidity parameter and the like. For example, the food material tag may be a two-dimensional code identifier, the warehouse management system may include a two-dimensional code scanning device, the two-dimensional code identifier of the food material to be warehoused is scanned by the two-dimensional code scanning device to obtain the stored data and the electronic recipe, the food material tag may also be an RFID electronic tag, and the warehouse management system may include an RFID electronic tag reader, so as to read the stored data and the electronic recipe in the RFID electronic tag. Certainly, the food materials to be warehoused can be attached with only one identification code, and the warehouse management system matches preset food material label information based on the identification code, so that the stored data and the electronic menu corresponding to the food materials to be warehoused are obtained. The storage form of the food material tag information is not limited, and the food material tag is described as an example of a two-dimensional code identification tag for convenience of description.
The warehouse management system reads the food material labels corresponding to the food materials to be warehoused, and therefore storage data and electronic recipes of the food materials to be warehoused carried by the food material labels are obtained. The storage data is matched with information such as categories and forms of food materials to be warehoused, and the storage data corresponding to the shredded potatoes and the potato blocks are different. The storage data may be data such as a storage location and a storage environment parameter directly read from the food material tag, for example, the food material tag carries a storage location planned in advance and a storage temperature parameter determined in advance; the stored data may also be data obtained by performing certain data analysis processing based on data read from the food material tag, for example, the food material tag carries an electronic recipe identifier or an electronic recipe, and the electronic recipe records storage environment parameters of the required food material, that is, after the electronic recipe is acquired by the food material tag, the storage environment parameters are determined by using the electronic recipe, and the storage environment parameters recorded in the electronic recipe are set to be suitable for different food material types, food material forms, and dishes. And further determining target warehousing data corresponding to the food materials to be warehoused based on the storage data, wherein the target warehousing data comprises at least one of a storage position and a storage environment parameter, for example, for a warehouse comprising a plurality of storage spaces, the storage data can be the storage position, the food materials are directly put into the corresponding storage space when being warehoused, the storage data can also be the storage position and the storage environment parameter, the food materials are not only put into the corresponding storage space when being warehoused, but also working parameters of the corresponding storage space are configured according to the storage environment parameter, so that the environment parameters of the storage space are matched with the storage environment parameter, for example, for a warehouse only comprising one storage space, the storage data can be the storage environment parameter, and the food materials are put into the warehouse and the working parameters of the warehouse are configured when being warehoused. Therefore, the warehousing food materials are stored in a more reasonable environment, and the quality and freshness of the warehousing food materials are guaranteed and kept. Specifically, the target warehousing data in the embodiment of the application may be used to control the warehousing and storage of the food materials to be warehoused, and the target warehousing data may be a section of executable program, and the warehousing and storage of the food materials are controlled by executing the section of program, for example, opening and closing a warehouse door, adjusting environmental parameters in a warehouse, and the like are realized by executing the program. Furthermore, target warehousing data and electronic recipes can be associated, the target warehousing data and the electronic recipes are associated with food material warehousing information and stored in a warehouse management system, so that what food materials stored in a certain storage position can be conveniently inquired in the warehouse management system, and the food materials in the storage position are used for cooking dishes corresponding to the electronic recipes, when a certain dish is cooked, the required food materials of the dish can be inquired through the warehouse management system, and what the required food materials are stored in the dish, so that the warehouse-out management of the cooking food materials is facilitated, the cooking of the food materials is realized based on the electronic recipes, and the food material cooking process management is facilitated. Therefore, warehousing management and storage management of food materials are realized, the food materials are convenient to store, the quality and the freshness of the food materials are guaranteed, workers can conveniently check the purposes and the usage of the warehoused food materials, and the associated electronic menu provides a reliable basis for subsequent cooking.
The method comprises the steps of determining storage data of food materials to be warehoused and an electronic menu required for cooking and processing the food materials to be warehoused based on food material labels of the food materials to be warehoused, generating corresponding target warehousing data by using the storage data corresponding to the food materials to be warehoused to guide and control the food materials to be warehoused, and associating the target warehousing data with the electronic menu to realize management of the food materials to be warehoused. Compared with the mode of relying on manual experience to store food materials and select cooking food materials in the prior art, the storage data and the electronic menu corresponding to the food material tags of the food materials to be stored are determined, the storage position and the storage environment parameters of the food materials to be stored are determined by the aid of the storage data, storage management and quality and freshness preservation management of the food materials are achieved, food material storage efficiency is improved, food material quality is guaranteed, and basis is provided for food material selection and cooking process determination in a food material cooking process by associating target storage data and the electronic menu, so that cooking is more intelligent and accurate.
In the embodiment of the application, based on the type of information carried by the food material tag of the food material to be warehoused, the storage data obtained based on the food material tag of the food material to be warehoused in step 201 are different, and optionally, the storage data comprises first storage data, wherein the first storage data comprises a storage location and/or a storage environment parameter; step 201 may specifically include:
step 201-1, reading first storage data corresponding to the food material tag.
In the above embodiment, if the food material tag corresponding to the food material to be warehoused already carries data including a storage location, a storage environment parameter, or a combination of the two, the data can be directly read as storage data of the food material to be warehoused. The following describes the case where the food tag carrying data includes a storage environment parameter, a storage location parameter, and a combination of the two.
In this embodiment of the application, corresponding to step 201-1, when the storage data includes the storage environment parameter, the step 202 determines, according to the storage data, target warehousing data corresponding to the food material to be warehoused, which may specifically include:
step 202-1, obtaining a storage position matched with the storage environment parameter in the target warehouse according to the storage environment parameter, current storage data corresponding to the target warehouse and a preset storage constraint condition, wherein the preset storage constraint condition comprises the size of the residual space and the rated environment parameter.
In the above embodiment, if the food material tag of the food material to be warehoused carries storage environment parameters but does not carry a storage location, or the carried storage location is a rough range, so that the specific warehousing location of the food material to be warehoused cannot be determined, for example, the storage location carried by the food material tag is an area a, but the area a includes a plurality of storage spaces, or, when the food material tag carries a specific storage location but the specified storage location cannot meet the storage condition of the food material to be warehoused through query, for example, the storage location carried by the food material tag is an area a space 1, but the area a space 1 is occupied, and other food materials cannot be stored. For the above scenario, the storage location of the food material to be warehoused can be determined according to the storage environment parameters, in combination with the current storage condition of the warehouse and the preset storage constraint conditions agreed in advance, for example, the storage environment parameter corresponding to the food material to be warehoused is the storage temperature range of 5-10 ℃, then which storage spaces simultaneously satisfy the storage temperature constraint condition of the food material to be warehoused and the constraint condition of the remaining storage space can be determined according to the current storage data of the target warehouse, specifically, if the space 1 in the area a in the warehouse is free and the rated temperature range of the space is matched with the 5-10 ℃ corresponding to the food material to be warehoused, then the space 1 in the area a can be determined as the storage location corresponding to the food material to be warehoused, so that the warehousing location of the food material is determined intelligently, the food material warehousing management is facilitated, and the storage location can be guaranteed to satisfy the environmental constraint condition required by the food material, the quality and freshness of the food materials are guaranteed and preserved. For a larger storage space, even if some food materials are already stored, sufficient remaining space may be available for storing other food materials, and then whether the food materials to be warehoused can be stored in the space can be further judged by combining the size of the storage space required by the food materials to be warehoused, so that the utilization rate of the storage space is improved.
In this embodiment of the application, corresponding to step 201-1, when the storage data is a storage location parameter, or the storage data includes the storage location parameter and a storage environment parameter, specifically, the storage location is determined based on the storage environment parameter indicated by the electronic recipe corresponding to the food material to be warehoused.
In the above embodiment, the storage location of the food material to be warehoused can be determined in advance according to the storage environment required by the food material to be warehoused, and the storage environment parameters and the storage location are written into the food material tag, for example, after a user places an order, the order platform counts the food material required by the order, determines the storage location of the food material according to the storage environment parameters of the food material and the rated parameters of each storage space in the target warehouse, and writes the storage location into the food material tag, so that the food material can be directly placed into the corresponding location according to the storage location carried by the food material tag when the food material is warehoused, and the warehousing and storage of the food material are realized. If the storage location corresponding to the food material is a location where the working parameter is fixed or the parameter does not need to be changed, for example, the storage temperature corresponding to the storage location is 5 degrees centigrade and cannot be changed, or the storage temperature corresponding to the storage location is 5 degrees centigrade and meets the storage condition of the food material without being changed, the storage data may only include the storage location parameter. If the operating parameters of the storage location need to be adjusted to ensure the quality and freshness of the food material, the storage data should include the storage location and the storage temperature.
In the embodiment of the present application, optionally, the storage data includes second storage data; step 201 may specifically include:
step 201-2, acquiring at least one electronic menu corresponding to the food material label;
step 201-3, second storage data corresponding to the electronic menu is obtained, wherein the second storage data comprises storage environment parameters corresponding to the electronic menu.
Correspondingly, in step 202, the determining target warehousing data corresponding to the food materials to be warehoused according to the storage data may specifically include:
step 202-2, acquiring a storage position matched with the storage environment parameters in the target warehouse according to the storage environment parameters, current storage data corresponding to the target warehouse and preset storage constraint conditions, wherein the preset storage constraint conditions comprise the size of the residual space and the rated environment parameters.
In the above embodiment, the storage environment parameters corresponding to the food materials to be warehoused may also be determined by using an electronic menu carried by the food material tags, and then the storage location of the food materials to be warehoused is determined by combining the current storage data of the target warehouse and the preset constraint condition, and the specific manner of determining the storage location may refer to the description corresponding to step 202-1, which is not described herein again.
In this embodiment of the application, optionally, after "determining target warehousing data corresponding to the food material to be warehoused according to the stored data" in step 202, the method may specifically include:
step 203, monitoring actual warehousing data corresponding to the target warehouse;
204, when the food materials to be warehoused, which are matched with the food material specifications, are monitored to be stored in the storage positions, configuring working parameters of the storage positions according to the storage environment parameters, and confirming that the food materials to be warehoused are successfully warehoused; or configuring working parameters of the storage position according to the storage environment parameters, and confirming that the food materials to be warehoused are successfully warehoused when the fact that the food materials to be warehoused matched with the food material specifications are prestored in the storage position is monitored.
In the above embodiment, when the food materials are warehoused, the warehousing condition of the food materials in the target warehouse can be monitored, actual warehousing data is obtained, and if the monitored actual warehousing data is matched with the target warehousing data, successful warehousing of the food materials can be confirmed, so that the target warehousing data is associated with the electronic menu. In a specific application scenario, the food material warehousing process includes not only a process of placing food materials to be warehoused into a storage position, but also a process of configuring storage environment parameters corresponding to the storage position, the food materials can be stored firstly and then the storage environment parameters are adjusted, the storage environment parameters can also be adjusted firstly and then the food materials are stored, whether the food materials are stored successfully or not can be judged based on electronic scales, cameras and other devices arranged at corresponding storage positions, for example, whether the added value is matched with a weight value corresponding to the food materials to be warehoused or not is judged based on a weight added value sensed by the electronic scales, and whether the warehoused food materials are the food materials to be warehoused or not is judged based on image recognition of images of the food materials to be warehoused, which are acquired by the.
Further, as a specific implementation of the method in fig. 1, an embodiment of the present application provides an electronic recipe data statistics apparatus, as shown in fig. 2, the apparatus includes:
a historical data acquiring module 31, configured to acquire a historical reference time period corresponding to a target time period and electronic menu usage data of the historical reference time period;
a historical data analysis module 32, configured to count the electronic menu usage data to obtain analysis data of the electronic menu usage corresponding to the historical reference time period;
the first data generation module 33 is configured to generate production recommendation data of the electronic menu according to the analysis data.
Optionally, the historical data obtaining module 31 includes:
a first time period obtaining unit 311, configured to obtain a time period attribute of a target time period, and obtain a historical reference time period corresponding to the target time period according to the time period attribute, where if the time period attribute is a first attribute, the historical reference time period includes a plurality of historical time periods that are matched with the first attribute within a first preset time, and if the time period attribute is a second attribute, the historical reference time period includes a historical time period that is matched with a second preset time before the target time period; or,
a second time period obtaining unit 312, configured to obtain a custom time period corresponding to the target time period, and use the custom time period as the history reference time period.
Optionally, the historical data analysis module 32 includes:
a first usage data acquiring unit 321, configured to count the usage data of the electronic recipes, and acquire the usage number of the electronic recipes corresponding to the counted time unit in the historical reference time period;
a first trend analysis unit 322, configured to generate usage trend analysis data for the electronic recipes in the historical reference time period according to the usage amount of the electronic recipes.
Optionally, the historical data analysis module 32 further includes:
a second usage data acquiring unit 323 configured to count the usage data of the electronic recipes, and acquire the usage number of the total electronic recipes corresponding to the unit of the counted time period in the historical reference time period;
a second trend analysis unit 324, configured to generate trend analysis data on the usage amount of the total electronic menu in the historical reference time period according to the usage amount of the total electronic menu.
Optionally, the first data generating module 33 includes:
the first data generation unit 331 is configured to obtain a first electronic recipe of which usage trend meets a first preset trend condition according to usage trend analysis data of the electronic recipe, and generate production recommendation data corresponding to the target time period based on the first electronic recipe, where a usage increase rate corresponding to the first electronic recipe is greater than a first preset increase rate and/or a usage increase rate ranked a first preset number before; and/or the presence of a gas in the gas,
the second data generating unit 332 is configured to obtain a second electronic recipe, of which a usage trend meets a second preset trend condition, according to the usage trend analysis data of the total electronic recipe, and generate production recommendation data corresponding to the target time period based on the second electronic recipe, where a usage increase rate corresponding to the second electronic recipe is greater than a usage increase rate corresponding to the total electronic recipe.
Optionally, the apparatus further comprises:
the second data generating module 34 is configured to obtain a popular electronic menu and/or a new electronic menu corresponding to the current time period, and generate production recommendation data corresponding to the target time period based on the popular electronic menu and/or the new electronic menu.
Optionally, the production recommendation data includes production recommendation data corresponding to at least one merchant; the device further comprises:
the plan data generating module 35 is configured to obtain the merchant production plan data based on the selection data of the production recommendation data corresponding to the merchant after the production recommendation data of the electronic menu is generated according to the analysis data.
Optionally, the apparatus further comprises:
a food material demand obtaining module 36, configured to obtain, based on the merchant production plan data, the merchant food material demand data after obtaining the merchant production plan data;
a supply data obtaining module 37, configured to obtain food material supply data of a general merchant according to the food material demand data, where the food material supply data includes food material production data and/or food material purchasing data.
It should be noted that other corresponding descriptions of the functional units related to the electronic menu data statistics apparatus provided in the embodiment of the present application may refer to the corresponding descriptions in the method in fig. 1, and are not described herein again.
Based on the method shown in fig. 1, correspondingly, the present application further provides a storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for counting electronic menu data shown in fig. 1 is implemented.
Based on such understanding, the technical solution of the present application may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.), and includes several instructions for enabling a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the implementation scenarios of the present application.
Based on the method shown in fig. 1 and the virtual device embodiment shown in fig. 2, in order to achieve the above object, the present application further provides a computer device, which may specifically be a personal computer, a server, a network device, and the like, where the computer device includes a storage medium and a processor; a storage medium for storing a computer program; a processor for executing a computer program to implement the above-mentioned electronic recipe data statistical method shown in fig. 1.
Optionally, the computer device may also include a user interface, a network interface, a camera, Radio Frequency (RF) circuitry, sensors, audio circuitry, a WI-FI module, and so forth. The user interface may include a Display screen (Display), an input unit such as a keypad (Keyboard), etc., and the optional user interface may also include a USB interface, a card reader interface, etc. The network interface may optionally include a standard wired interface, a wireless interface (e.g., a bluetooth interface, WI-FI interface), etc.
It will be appreciated by those skilled in the art that the present embodiment provides a computer device architecture that is not limiting of the computer device, and that may include more or fewer components, or some components in combination, or a different arrangement of components.
The storage medium may further include an operating system and a network communication module. An operating system is a program that manages and maintains the hardware and software resources of a computer device, supporting the operation of information handling programs, as well as other software and/or programs. The network communication module is used for realizing communication among components in the storage medium and other hardware and software in the entity device.
Through the description of the above embodiments, those skilled in the art can clearly understand that the present application can be implemented by software plus a necessary general hardware platform, and also can obtain a historical reference time period and electronic menu usage data corresponding to the historical reference time period through hardware implementation, and statistically determine analysis data of the usage condition of the electronic menu in the historical reference time period by using the electronic menu usage data, thereby generating production recommendation data for the electronic menu. Compared with the mode of making a production plan according to the working experience or subjective intention of workers in the prior art, the embodiment of the application is based on the execution condition of the cooking equipment to the electronic menu program in the historical reference time period, the production recommendation data of the electronic menu is determined by carrying out statistical analysis on the use data of the electronic menu, scientific, reliable and basis guidance data are provided for merchants to formulate production plans, the merchants can formulate the production plans according to the production recommendation data determined based on the historical use conditions of the electronic menu, the rationality of formulating the production plans is improved, the problem that the goods quantity cannot be accurately determined in the food material stocking process due to unreasonable production plans is further avoided, and the problem that the storage capacity cannot be accurately estimated in the food material storage process is solved, and the problems of waste, insufficiency, improper preservation and the like of food materials are effectively avoided.
Those skilled in the art will appreciate that the figures are merely schematic representations of one preferred implementation scenario and that the blocks or flow diagrams in the figures are not necessarily required to practice the present application. Those skilled in the art will appreciate that the modules in the devices in the implementation scenario may be distributed in the devices in the implementation scenario according to the description of the implementation scenario, or may be located in one or more devices different from the present implementation scenario with corresponding changes. The modules of the implementation scenario may be combined into one module, or may be further split into a plurality of sub-modules.
The above application serial numbers are for description purposes only and do not represent the superiority or inferiority of the implementation scenarios. The above disclosure is only a few specific implementation scenarios of the present application, but the present application is not limited thereto, and any variations that can be made by those skilled in the art are intended to fall within the scope of the present application.
Claims (11)
1. An electronic menu data statistical method is characterized by comprising the following steps:
acquiring a historical reference time period and electronic menu use data of the historical reference time period;
counting the electronic menu use data to obtain analysis data of the electronic menu use condition corresponding to the historical reference time period;
and generating production recommendation data of the electronic menu according to the analysis data.
2. The method of claim 1, wherein obtaining the historical reference period comprises:
acquiring a time interval attribute of a target time interval, and acquiring a historical reference time interval corresponding to the target time interval according to the time interval attribute, wherein if the time interval attribute is a first attribute, the historical reference time interval comprises a plurality of historical time intervals which are matched with the first attribute within a first preset time, and if the time interval attribute is a second attribute, the historical reference time interval comprises a historical time interval which is matched with a second preset time before the target time interval; or,
and acquiring a custom time period corresponding to the target time period, and taking the custom time period as the historical reference time period.
3. The method of claim 1, wherein the counting the electronic recipe usage data to obtain the analysis data of the electronic recipe usage corresponding to the historical reference period comprises:
counting the use data of the electronic menu to obtain the use number of the electronic menu corresponding to the counted time unit in the historical reference time period;
and generating use amount trend analysis data of the electronic menu in the historical reference time period according to the use amount of the electronic menu.
4. The method of claim 3, wherein the counting the electronic recipe usage data to obtain the analysis data of the electronic recipe usage corresponding to the historical reference period further comprises:
counting the use data of the electronic menu to obtain the use number of the total electronic menu corresponding to the counting time period unit in the historical reference time period;
and generating use amount trend analysis data of the total electronic menu in the historical reference time period according to the use amount of the total electronic menu.
5. The method of claim 4, wherein generating production recommendation data for the electronic recipe based on the analysis data comprises:
according to the usage trend analysis data of the electronic recipes, acquiring a first electronic recipe of which the usage trend meets a first preset trend condition, and generating production recommendation data corresponding to the target time period based on the first electronic recipe, wherein the usage increase rate corresponding to the first electronic recipe is larger than a first preset increase rate and/or the usage increase rate is ranked at a first preset number; and/or the presence of a gas in the gas,
and acquiring a second electronic menu of which the usage trend meets a second preset trend condition according to the usage trend analysis data of the total electronic menu, and generating production recommendation data corresponding to the target time period based on the second electronic menu, wherein the usage increase rate corresponding to the second electronic menu is greater than the usage increase rate corresponding to the total electronic menu.
6. The method of claim 1, further comprising:
and acquiring a popular electronic menu and/or a new electronic menu corresponding to the current time period, and generating production recommendation data corresponding to the target time period based on the popular electronic menu and/or the new electronic menu.
7. The method of claim 1, wherein the production recommendation data comprises production recommendation data corresponding to at least one merchant; after generating the production recommendation data of the electronic menu according to the analysis data, the method further comprises:
and obtaining the merchant production plan data based on the selection data of the production recommendation data corresponding to the merchant.
8. The method of claim 7, wherein after obtaining the merchant production plan data, the method further comprises:
acquiring the merchant food material demand data based on the merchant production plan data;
and obtaining food material supply data of a general merchant according to the food material demand data, wherein the food material supply data comprises food material production data and/or food material purchasing data.
9. An electronic recipe data statistics device, characterized in that the device comprises:
the historical data acquisition module is used for acquiring a historical reference time period corresponding to a target time period and electronic menu use data of the historical reference time period;
the historical data analysis module is used for counting the electronic menu use data to obtain analysis data of the electronic menu use condition corresponding to the historical reference time period;
and the first data generation module is used for generating production recommendation data of the electronic menu according to the analysis data.
10. A storage medium on which a computer program is stored, wherein the computer program, when executed by a processor, implements the electronic recipe data statistical method according to any one of claims 1 to 8.
11. A computer device comprising a storage medium, a processor and a computer program stored on the storage medium and executable on the processor, wherein the processor implements the electronic recipe data statistical method according to any one of claims 1 to 8 when executing the computer program.
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CN107833159A (en) * | 2017-11-16 | 2018-03-23 | 四川长虹智能制造技术有限公司 | A kind of intelligent food and drink cloud system |
CN107886272A (en) * | 2017-11-06 | 2018-04-06 | 北京戴纳实验科技有限公司 | A kind of food management method |
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CN107886272A (en) * | 2017-11-06 | 2018-04-06 | 北京戴纳实验科技有限公司 | A kind of food management method |
CN107833159A (en) * | 2017-11-16 | 2018-03-23 | 四川长虹智能制造技术有限公司 | A kind of intelligent food and drink cloud system |
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