CN117095490A - Intelligent canteen management method and system - Google Patents
Intelligent canteen management method and system Download PDFInfo
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- CN117095490A CN117095490A CN202310975200.8A CN202310975200A CN117095490A CN 117095490 A CN117095490 A CN 117095490A CN 202310975200 A CN202310975200 A CN 202310975200A CN 117095490 A CN117095490 A CN 117095490A
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C11/00—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
- G06Q50/12—Hotels or restaurants
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C11/00—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere
- G07C2011/04—Arrangements, systems or apparatus for checking, e.g. the occurrence of a condition, not provided for elsewhere related to queuing systems
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Abstract
The invention provides a smart canteen management method and a smart canteen management system, wherein an acquisition unit is used for acquiring food types corresponding to a window and queuing time length at each moment in a near-period time; the acquisition unit is used for acquiring a diet recipe of a diner; the searching unit is used for searching a corresponding window to be queued according to the food types in the diet recipe; the arrangement unit is used for arranging windows to be queued in different orders to form a plurality of queuing paths; the queuing path output unit is used for calculating the total queuing time length of each queuing path, outputting the queuing path with the shortest queuing time length, obtaining the historical queuing time length of each window of the dining room as a calculation basis, providing the queuing path with the shortest queuing time length for the diner according to the diet recipe of the diner, and improving dining experience, wherein the diner can spend the least time when queuing and taking the dinner according to the queuing path.
Description
Technical Field
The invention relates to the technical field of canteen management, in particular to an intelligent canteen management method and system.
Background
Food is usually made up of carbohydrate, fat, protein, water, can offer nutrition or pleasant substance for human or living beings by eating or drinking, is the most basic matter condition of human production and development, and food information is closely concerned by society all the time, in all kinds of school, mostly can set up the canteen for students to solve the daily meal problem, traditional canteen needs students to queue up according to the preference of diet to appointed window, then the staff in the window is according to the demand of students to play dishes, after the completion of the play dishes, price according to the knowledge of the staff to the price of dishes, and finally finish the whole process of the play dishes after the student checks out, the traditional mode can have the phenomenon that part of window lines are too long, in hot summer, food can also have the possibility of putrefaction.
With the development of internet technology, the modes of intellectualization +internet +products are applied to various industries, a traditional canteen is combined with the internet, a self-help mode is adopted, a student selects dishes and then automatically calls the canteen for settlement, and the use of staff is reduced, so that the queuing time can be shortened, however, when the student has a peak period of dining, the situation that part of windows are queued is still longer, when the student selects dishes, a plurality of dishes are often selected, the situation that a plurality of windows are queued exists, when the student queues in the current window, the queuing situation of the next window cannot be predicted, the situation that the queuing time is longer exists, and the current intelligent canteen cannot provide the student with the optimal queuing sequence when a plurality of dishes are used for making dishes.
Disclosure of Invention
In view of the above, the invention provides a smart canteen management method and a smart canteen management system, which can provide a queuing path with the shortest queuing time aiming at a diet recipe of a diner, increase dining experience of the diner and reduce queuing time.
The technical scheme of the invention is realized as follows:
an intelligent canteen management method comprises the following steps:
step S1, collecting food types corresponding to windows and queuing time length of each moment in a near-period time;
s2, obtaining a diet recipe of a diner;
step S3, searching a corresponding window to be queued according to the food types in the diet recipe;
s4, arranging windows to be queued in different orders to form a plurality of queuing paths;
and S5, calculating the total queuing time of each queuing path, and outputting the queuing path with the shortest total queuing time.
Preferably, the food in the step S1 includes cereals, potatoes, animal foods, vegetables and fruits, bean products, and pure energy foods.
Preferably, the specific steps of the step S2 are as follows:
s21, acquiring food edible by a diner, and dividing the food into a plurality of food databases according to different food types;
step S22, calculating the necessary nutrient content of each food in the food database, wherein the necessary nutrients comprise protein, carbohydrate, fiber and fat;
step S23, acquiring physical state data of a diner, and selecting corresponding food from a food database according to the physical state data and the necessary nutrient content to acquire an initial recipe;
step S24, obtaining taste change requirements of the diners, screening food from the initial recipes according to the taste change requirements, and obtaining the diet recipes.
Preferably, the specific steps of the step S21 are as follows:
step S211, acquiring the total food for eating, and inquiring direct allergic food and direct contradicting food input by a diner;
step S212, acquiring hospital medical records and takeout detailed sheets of the diners, and extracting potential allergic foods and potential conflict foods of the diners from the hospital medical records and the takeout detailed sheets;
step S213, removing the direct allergic food, the direct contradicting food, the potential allergic food and the potential contradicting food from the food population;
step S214, dividing the food aggregate after the removal into a plurality of food databases according to different food types.
Preferably, the specific steps of the step S23 are as follows:
step S231, acquiring physical examination data of a diner, wherein the physical examination data comprise height, weight, body fat rate, blood sugar, blood fat and blood pressure;
step S232, inputting physical examination data into a trained neural network, and processing by the neural network to obtain the nutrient demand of a diner;
step S233, selecting a plurality of food combinations from the food database according to the nutrient demand and the necessary nutrient content of each food, and outputting the food combinations as an initial recipe.
Preferably, the specific steps of the step S24 are as follows:
step S241, obtaining takeaway order information and dining room dining information of a diner in a period of time recently, and extracting food preference and food types in the period of time recently according to the takeaway order information and the dining room dining information;
step S242, searching for food combinations containing the same or similar food types as those of the last time from the initial recipe according to the diet preference;
step S243, outputting the searched food combination as a diet recipe.
Preferably, the specific steps of the step S4 are as follows: randomly selecting one window to be queued as a first window to be queued, selecting the rest windows to be queued, forming a queuing path according to the selected sequence, and performing iterative selection until all the windows to be queued are selected as the first window to be queued.
Preferably, the specific steps of the step S5 are as follows:
step S51, acquiring historical queuing time length of the current moment of a first window to be queued;
step S52, acquiring historical queuing time length of a queuing end time of a previous window to be queued of a current window to be queued in a queuing path;
step S53, adding the historical queuing time lengths of all the windows to be queued in the queuing path, and obtaining the total queuing time length;
and S54, outputting the queuing path with the shortest total queuing time.
Preferably, the queuing path is provided with a queuing time threshold, the foods in the diet recipe are provided with priorities, and when the total queuing time of the queuing path with the shortest total queuing time output in the step S5 is greater than the queuing time threshold, the foods with the lowest priorities in the diet recipe are deleted from the queuing path, and then the step S5 is re-executed.
An intelligent canteen management system, comprising:
the collection unit is used for collecting the food types corresponding to the window and queuing time length of each moment in the near-period time;
an acquisition unit for acquiring a diet recipe of a diner;
the searching unit is used for searching a corresponding window to be queued according to the food types in the diet recipe;
the arrangement unit is used for arranging windows to be queued in different orders to form a plurality of queuing paths;
the queuing path output unit is used for calculating the total queuing time length of each queuing path and outputting the queuing path with the shortest total queuing time length;
the searching unit is respectively connected with the collecting unit, the acquiring unit and the arranging unit in a data mode, and the queuing path output unit is respectively connected with the arranging unit and the collecting unit in a data mode.
Compared with the prior art, the invention has the beneficial effects that:
according to the intelligent canteen management method and system, the queuing time in the window near-section time of the canteen is counted, the queuing sequence of the searched windows is arranged after the corresponding window is found according to the diet recipe of the diner, so that a plurality of queuing paths are formed, the queuing paths comprise the queuing sequence of the windows where all foods in the diet recipe are located, the queuing time of each window is different at different time points, the queuing time of other windows is also changed in real time in the queuing process of one window, and therefore the fastest queuing path can be obtained after the total queuing time of all queuing paths is calculated, the queuing time of the diner is shortened, and the dining experience is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only preferred embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a flow chart of a smart canteen management method of the present invention;
FIG. 2 is a flowchart of step S2 of a smart canteen management method according to the present invention;
FIG. 3 is a flowchart of step S21 of a smart canteen management method according to the present invention;
FIG. 4 is a flowchart of step S23 of a smart canteen management method according to the present invention;
FIG. 5 is a flowchart of step S24 of a smart canteen management method according to the present invention;
FIG. 6 is a flowchart of step S5 of a smart canteen management method according to the present invention;
FIG. 7 is a schematic diagram of a smart canteen management system according to the present invention;
in the figure, 1 is an acquisition unit, 2 is an acquisition unit, 3 is a search unit, 4 is an arrangement unit, and 5 is a queuing path output unit.
Detailed Description
For a better understanding of the technical content of the present invention, a specific example is provided below, and the present invention is further described with reference to the accompanying drawings.
Referring to fig. 1 to 6, the intelligent canteen management method provided by the invention comprises the following steps:
step S1, collecting food types corresponding to windows and queuing time of each moment in a near-period time, wherein the food types comprise grains, potatoes, animal foods, vegetables and fruits, bean products and pure energy foods;
in the intelligent canteen, a self-service meal ordering mode is adopted, a diner can move to a window where corresponding food is located, the whole dishes are taken out for evaluation, or weighing evaluation is carried out after the dishes are ordered by oneself, most of the windows in the canteen are divided according to the types of the food, dishes of the same type are placed in the same window area, the diner can conveniently take the meal according to the type requirements, and meanwhile, the flavor of the foods can be avoided.
Because the taste of each diner is different and the taste of the diner is changed, the diners go to the dining room to purchase dishes are different each time, when calculating the queuing time of the diners, the diners need to know what the diners eat, therefore, the food recipe of the diners is obtained through the step S2, the invention provides a food recipe recommending function, the food recipes of the diners are obtained through the preference, physical condition, taste change and the like of the diners, and then the calculation of the queuing is carried out according to the food recipes, wherein when the food recipes are recommended, the food which can be eaten by the diners is firstly divided into a plurality of food databases according to different food types through the step S21, and because the food which can be eaten by the diners needs to be recommended to the diners is obtained, before the recommendation, the food is classified into a plurality of databases according to different food types, when the food recipes are recommended to the diners, the food recipes in a plurality of the diners can be selected, and when the food recipes in the food recipes are recommended to be removed, and the food recipes in the food recipes are not required to be different from the specific food databases, and the food which can not be taken by the diners, the specific food is not needed, and the food is different from the step:
step S211, acquiring the total food for eating, inquiring the direct allergic food and the direct contradicting food input by the diner, wherein the direct allergic food and the direct contradicting food are the names of the food directly input by the diner in the method and the system and can be used for directly eliminating, but not all the diners can directly input, so that the allergic food and the contradicting food of the diner need to be potentially acquired through other ways;
step S212, acquiring hospital medical records and takeout detailed sheets of the diners, and extracting potential allergic foods and potential conflict foods of the diners from the hospital medical records and the takeout detailed sheets;
because allergic food can cause allergic symptoms on diners and seriously endanger lives, the allergic food needs to be removed from the food population, for example, part of diners can be allergic to seafood, mango and the like, the allergic food needs to be removed from the food population in advance, contradicting foods such as coriander, cress and the like can be obtained according to the preference of the diners, the allergic food and the contradicting foods of the diners can be potentially obtained through medical records of hospitals and takeaway detailed sheets also need to be removed from the food population.
Step S213, removing the direct allergic food, the direct contradicting food, the potential allergic food and the potential contradicting food from the food population;
in step S214, the removed food is generally divided into a plurality of food databases according to different types of foods, and no food which cannot be eaten by the diner is contained in the food databases, so that the calculation amount can be reduced and the calculation efficiency can be improved after the food is removed.
Step S22, calculating the necessary nutrient content of each food in the food database, wherein the necessary nutrients comprise protein, carbohydrate, fiber and fat;
in the recommended food for the diner, the necessary energy required for the life of the human body is required to be contained, so after the food database is obtained, the necessary nutrient content contained in each food needs to be calculated, including protein, carbohydrate, fiber, fat and the like, wherein the protein can help the body to repair itself, the carbohydrate can provide energy for the body and the brain, the fiber can promote the peristalsis of the intestines and the stomach, and the fat can increase the satiety, so that the recommended food combination should contain a certain amount of necessary nutrients when the food is recommended later, so as to provide the energy required for the daily activity for the diner.
Since the physical condition of the diner is not constant, the requirements for digestion and necessary nutrient content of the food are different with the change of the physical function and the change of various indexes of the body, and therefore, before the recommendation of the recipe is performed, the physical state data of the diner needs to be evaluated, in step S23, the physical state data of the diner is obtained, and the corresponding food is selected from the food database according to the physical state data and the necessary nutrient content to obtain the initial recipe, which comprises the following specific steps:
step S231, acquiring physical examination data of the diner, wherein the physical examination data comprise height, weight, body fat rate, blood sugar, blood fat and blood pressure, and the physical condition of the diner can be known according to the physical examination data, so that a recipe suitable for the physical condition of the diner can be correspondingly recommended later, and the physical condition is prevented from being reduced and influenced by overeating or improper diet of the unhealthy diner.
Step S232, inputting physical examination data into a trained neural network, processing the physical examination data by the neural network to obtain nutrient demand of the diners, training the neural network by collecting other human body data, outputting the physical examination data to obtain the nutrient demand, and quickly obtaining the nutrient demand of the diners by adopting a machine learning and history data form, wherein the neural network is suitable for the demands of normal diners, and for some diners with special demands, the neural network needs to be correspondingly regulated, after the physical examination data of the diners are obtained for a period of time, the neural network can be used for judging whether the diners are in a weight-losing or body-building state, when the diners are in the weight-losing or body-building state, the nutrient demand of the diners for each food is reduced, and parameters of the neural network need to be regulated at the moment, so that the nutrient demand of the diners obtained by the neural network processing is reduced, and the obtained nutrient demand can be suitable for the diners in the weight-losing or body-building state.
In step S233, multiple food combinations are selected from the food database according to the nutrient requirements and the necessary nutrient content of each food, and output as an initial recipe, after the nutrient requirements of the diners are obtained, the corresponding food needs to be selected from the food database, and the sum of the necessary nutrient contents of the selected food needs to be equal to or slightly greater than the nutrient requirements of the diners, and because the number of the foods is various, multiple food combinations exist in the obtained initial recipe, and all the food combinations are output as the initial recipe.
The initial recipe contains a large number of food combinations which, although meeting the energy requirements of the diner, do not necessarily meet the taste requirements of the diner and the taste of the diner may change after a period of time, and for this purpose step S24 obtains the taste change requirements of the diner, screens the food from the initial recipe according to the taste change requirements and obtains the diet recipe, which comprises the following specific steps:
step S241, obtaining takeaway order information and dining room dining information of a diner in a period of time recently, and extracting food preference and food types in the period of time recently according to the takeaway order information and the dining room dining information;
the dining information and the takeout order information include food types purchased by the diners, such as beef, pork, fish, and the like, and in addition, the dining information and the takeout order information can also be used for acquiring the food preference of the diners, such as meat/food/fruit, and the like.
The final food combination is affected by different food preferences and the food types in the near-term, so that step S242 searches the initial recipe for the food combination containing the same or similar food types as the food types in the near-term according to the food preferences, selects the corresponding food combination according to the food preferences of the diner, and selects the selected food combination containing the food types consumed in the near-term if the food combination does not contain the food types consumed in the near-term, and selects the similar food to replace, for example, when the food consumed in the near-term is beef, but the food combination does not contain beef, the pork can be selected to replace.
Because the food preference and the food category in the near-term time are added as the restrictions, the food combination which does not meet the requirements in the initial recipe can be screened out, and then the searched food combination is output as the diet recipe in step S243, so that the food combination in the diet recipe can meet the energy requirement of the diner and the taste requirement of the diner.
Step S3, searching corresponding windows to be queued according to the types of foods in the diet recipe, wherein the acquired diet recipe contains various foods, after extracting the types of foods in the diet recipe, searching windows corresponding to the foods in the diet recipe according to the types of foods corresponding to the canteen windows, taking the windows as windows which are required to be queued by a diner, and outputting the windows as the windows to be queued.
And S4, arranging the windows to be queued in different sequences to form a plurality of queuing paths, wherein one window to be queued is required to be selected randomly as a first window to be queued, then the rest windows to be queued are selected randomly, queuing paths are formed according to the selected sequence, iterative selection is carried out until all the windows to be queued are selected as the first windows to be queued, and the number of the queuing paths formed by arranging and combining is far greater than that of the foods in the diet recipe because the foods in the diet recipe are a plurality of.
After all queuing paths are obtained, calculating the total queuing time of each queuing path through a step S5, and outputting the queuing path with the shortest total queuing time, wherein the specific steps are as follows:
step S51, acquiring the historical queuing time of the current moment of the first window to be queued, taking the current moment as the queuing time of the first window to be queued, searching the queuing time at the same moment as the current moment from the historical data, averaging to obtain the historical queuing time of the current moment of the first window to be queued, sequentially calculating the queuing time of the subsequent window to be queued according to a queuing path, and taking the moment when the queuing of the previous window to be queued is ended as the moment when the queuing of the subsequent window to be queued is started during the calculation, so that the historical queuing time of the queuing end moment of the previous window to be queued in the queuing path is acquired through step S52, and the historical queuing time of all the windows to be queued can be obtained through the same type of calculation, and then adding the historical queuing time of all the windows to be queued in the queuing path to obtain the total queuing time; and finally, step S54 outputs the queuing path with the shortest total queuing time, and the diner can select the corresponding window for queuing according to the output queuing path in sequence, so that the queuing time is shortest, and the dining experience of the diner can be improved.
Preferably, the queuing path is provided with a queuing time threshold, the foods in the diet recipe are provided with priorities, and when the total queuing time of the queuing path with the shortest total queuing time output in the step S5 is greater than the queuing time threshold, the foods with the lowest priorities in the diet recipe are deleted from the queuing path, and then the step S5 is re-executed.
In addition, if the total queuing time of the queuing path calculated finally is still longer, the total queuing time of the queuing path can be recalculated after the food with the lowest priority in the diet recipe of the diner is deleted, so as to save the queuing time of the diner.
Referring to fig. 7, there is shown an intelligent canteen management system comprising:
the acquisition unit 1 is used for acquiring the food types corresponding to the windows and queuing time length of each moment in the near-period time;
an acquisition unit 2 for acquiring a dietetic recipe of a diner;
a searching unit 3, configured to find a corresponding window to be queued according to the food category in the diet recipe;
the arrangement unit 4 is used for arranging windows to be queued in different orders to form a plurality of queuing paths;
a queuing path output unit 5, configured to calculate a total queuing time length of each queuing path, and output a queuing path with the shortest total queuing time length;
the searching unit 3 is respectively connected with the acquisition unit 1, the acquisition unit 2 and the arrangement unit 4 in a data way, and the queuing path output unit 5 is respectively connected with the arrangement unit 4 and the acquisition unit 1 in a data way.
The acquisition unit 1 sends the food types of the acquired windows to the search unit 3, the acquisition unit 2 sends the diet recipes of the eaters to the search unit 3, the search unit 3 searches the diet recipes corresponding to the food types of the windows one by one, determines the window where the food in the diet recipes is located, outputs the determined window as a window to be queued to the arrangement unit 4, the arrangement unit 4 forms a queuing path after arranging and combining the windows to be queued, and sends the queuing path to the queuing path output unit 5, and the queuing path output unit 5 receives the queuing time of each window at each moment in the near-period time acquired by the acquisition unit 1, calculates the queuing time of each window in the queuing path, can obtain the total queuing time of the queuing path, and finally outputs the queuing path with the shortest total queuing time, so that the eaters can queue according to the output queuing path, the queuing time of the eaters is shortened, and the dining experience of the eaters is improved.
The foregoing description of the preferred embodiments of the invention is not intended to be limiting, but rather is intended to cover all modifications, equivalents, alternatives, and improvements that fall within the spirit and scope of the invention.
Claims (10)
1. An intelligent canteen management method is characterized by comprising the following steps:
step S1, collecting food types corresponding to windows and queuing time length of each moment in a near-period time;
s2, obtaining a diet recipe of a diner;
step S3, searching a corresponding window to be queued according to the food types in the diet recipe;
s4, arranging windows to be queued in different orders to form a plurality of queuing paths;
and S5, calculating the total queuing time of each queuing path, and outputting the queuing path with the shortest total queuing time.
2. The intelligent canteen management method according to claim 1, wherein the food category of step S1 includes cereals and potatoes, animal foods, vegetables and fruits, bean products, pure energy foods.
3. The intelligent canteen management method according to claim 1, wherein the specific steps of step S2 are:
s21, acquiring food edible by a diner, and dividing the food into a plurality of food databases according to different food types;
step S22, calculating the necessary nutrient content of each food in the food database, wherein the necessary nutrients comprise protein, carbohydrate, fiber and fat;
step S23, acquiring physical state data of a diner, and selecting corresponding food from a food database according to the physical state data and the necessary nutrient content to acquire an initial recipe;
step S24, obtaining taste change requirements of the diners, screening food from the initial recipes according to the taste change requirements, and obtaining the diet recipes.
4. A smart canteen management method according to claim 3, wherein the specific steps of step S21 are:
step S211, acquiring the total food for eating, and inquiring direct allergic food and direct contradicting food input by a diner;
step S212, acquiring hospital medical records and takeout detailed sheets of the diners, and extracting potential allergic foods and potential conflict foods of the diners from the hospital medical records and the takeout detailed sheets;
step S213, removing the direct allergic food, the direct contradicting food, the potential allergic food and the potential contradicting food from the food population;
step S214, dividing the food aggregate after the removal into a plurality of food databases according to different food types.
5. A smart canteen management method according to claim 3, wherein the specific steps of step S23 are:
step S231, acquiring physical examination data of a diner, wherein the physical examination data comprise height, weight, body fat rate, blood sugar, blood fat and blood pressure;
step S232, inputting physical examination data into a trained neural network, and processing by the neural network to obtain the nutrient demand of a diner;
step S233, selecting a plurality of food combinations from the food database according to the nutrient demand and the necessary nutrient content of each food, and outputting the food combinations as an initial recipe.
6. A smart canteen management method according to claim 3, wherein the specific steps of step S24 are:
step S241, obtaining takeaway order information and dining room dining information of a diner in a period of time recently, and extracting food preference and food types in the period of time recently according to the takeaway order information and the dining room dining information;
step S242, searching for food combinations containing the same or similar food types as those of the last time from the initial recipe according to the diet preference;
step S243, outputting the searched food combination as a diet recipe.
7. The intelligent canteen management method according to claim 1, wherein the specific steps of step S4 are: randomly selecting one window to be queued as a first window to be queued, selecting the rest windows to be queued, forming a queuing path according to the selected sequence, and performing iterative selection until all the windows to be queued are selected as the first window to be queued.
8. The intelligent canteen management method according to claim 1, wherein the specific steps of step S5 are:
step S51, acquiring historical queuing time length of the current moment of a first window to be queued;
step S52, acquiring historical queuing time length of a queuing end time of a previous window to be queued of a current window to be queued in a queuing path;
step S53, adding the historical queuing time lengths of all the windows to be queued in the queuing path, and obtaining the total queuing time length;
and S54, outputting the queuing path with the shortest total queuing time.
9. The intelligent canteen management method according to claim 1, wherein the queuing path is provided with a queuing time threshold, the foods in the diet recipe are provided with priorities, and when the total queuing time of the queuing path with the shortest total queuing time output in the step S5 is longer than the queuing time threshold, the foods with the lowest priorities in the diet recipe are deleted from the queuing path, and then the step S5 is executed again.
10. A system according to any one of claims 1-9, characterized by comprising:
the collection unit is used for collecting the food types corresponding to the window and queuing time length of each moment in the near-period time;
an acquisition unit for acquiring a diet recipe of a diner;
the searching unit is used for searching a corresponding window to be queued according to the food types in the diet recipe;
the arrangement unit is used for arranging windows to be queued in different orders to form a plurality of queuing paths;
the queuing path output unit is used for calculating the total queuing time length of each queuing path and outputting the queuing path with the shortest total queuing time length;
the searching unit is respectively connected with the collecting unit, the acquiring unit and the arranging unit in a data mode, and the queuing path output unit is respectively connected with the arranging unit and the collecting unit in a data mode.
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