Milk tea machine and tea making machine linkage method based on big data

Abstract

The invention discloses a linkage method of a milk tea machine and a tea making machine based on big data, and relates to the field of linkage of the milk tea machine and the tea making machine, and the method specifically comprises the following steps: S1, forming a scheme; s2, linkage processing; s3, processing the data by the tea making machine; s4, performing comparative analysis in S3; and S5, after the tea pre-making instruction in the S4 is sent, processing whether to make tea or not and processing tea making barrels corresponding to different tea soup at a user side of the tea making machine. According to the linkage method of the milk tea machine and the tea making machine based on the big data, the tea making machine and the milk tea machine which work independently originally are linked, communication between shop operators is omitted, meanwhile, the tea making time, the tea making type, the tea making amount and the like are analyzed through the big data and controlled by the milk tea machine, and the linkage method of the milk tea machine and the tea making machine is achieved. The problems that the raw material tea soup cannot be supplemented in time and the tea soup is excessive and wasted are reduced, the working efficiency of a store is improved, the scheme can also ensure that the tea soup of the store locks the tea fragrance, and the flavor of a beverage is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of linkage of milk tea machines and tea brewing machines, in particular to a linkage method of milk tea machines and tea brewing machines based on big data. BACKGROUND

[0002] In the existing beverage industry, milk tea machines and tea brewing machines are usually two independent devices. Among them, the milk tea machine mainly mixes tea, milk, juice and other raw materials, and the tea brewing machine mainly provides tea soup and other raw materials for the milk tea machine. However, this independent working mode of the two has many problems. The tea brewing machine and the milk tea machine are independent of each other, and lack effective information interaction. When the tea brewing machine is making tea soup, it cannot flexibly adjust the brewing parameters such as tea variety, dosage, water temperature, and brewing time according to the daily demand of the store after the cups are out, resulting in communication barriers between the front and back kitchens, such as too much or too little tea, and even out-of-time tea brewing leading to tea shortage, which greatly reduces the work efficiency of the store.

[0003] Therefore, it is necessary to propose a linkage method of milk tea machines and tea brewing machines based on big data to solve the above problems. SUMMARY

[0004] The main purpose of the present application is to provide a linkage method of milk tea machines and tea brewing machines based on big data, which can effectively solve the problems in the background art.

[0005] To achieve the above purpose, the technical scheme adopted by the present application is:

[0006] A linkage method of milk tea machines and tea brewing machines based on big data, comprising the following operation steps:

[0007] S1: constituting a scheme, including a milk tea machine, a tea brewing machine, a milk tea machine background big data, a big data processing middle platform and a user end;

[0008] S2: linkage processing, the user writes the formula of the corresponding tea soup on the milk tea machine background user end, including tea type, water amount, soaking time, stirring time and other information related to tea brewing steps, the milk tea machine acquires and stores the relevant information, and sends the tea brewing instruction and the formula of the relevant tea soup to the tea brewing machine when tea brewing is needed;

[0009] S3: tea brewing machine processes data, including the capacity L of the tea brewing machine P , the tea brewing amount X, and the comparison and analysis of the data through the big data processing middle platform. In the milk tea machine background, the tea brewing time T1 corresponding to each tea variety is set, and the preparation time T2 of the back kitchen staff is also considered;

[0010] S4: Through the comparative analysis of S3, the milk tea machine adds materials or prepares materials in time, and the milk tea machine sends a pre-brewing tea instruction to the back-end tea brewing machine. The tea brewing machine end accepts the instruction and reminds the operator to start brewing tea;

[0011] S5: After the pre-brewing tea instruction of S4 is sent, the milk tea machine user end processes whether to brew tea and the brewing barrels corresponding to different tea soup.

[0012] Preferably, in S1, the middle station is used to determine the brewing time, tea soup type, and brewing amount by reading and analyzing big data;

[0013] The milk tea machine pulls the results of the middle station big data analysis and sends a brewing instruction to the tea brewing machine;

[0014] The tea brewing machine is a single-cylinder double-barrel tea brewing machine that accepts brewing instructions and brews tea in order;

[0015] The milk tea machine back-end is mainly used to store tea soup brewing methods and related big data of store tea soup usage.

[0016] Preferably, in S2, the milk tea machine sends a brewing instruction, which includes:

[0017] Human judgment of the required tea soup type and brewing amount, human operation of the milk tea machine to send a brewing instruction and brewing information to the tea brewing machine, and confirmation of the tea brewing machine back-end after receiving the relevant brewing information to brew tea in order;

[0018] The milk tea machine automatically sends an instruction to the tea brewing machine. The milk tea machine sends an instruction including a pre-brewing tea instruction and a brewing instruction. The milk tea machine pulls the back-end big data, including but not limited to the number of cups per week and the usage of different types of tea soup on the same day, and determines the brewing time through comparative analysis.

[0019] Preferably, in S3, the processing data specifically includes the following steps:

[0020] S301: Determine the pre-cup number A in the first time period M after the store opens on the same day;

[0021] Determine the usage B1 / B2 / B3... of the tea leaves in different products;

[0022] Determine the weight C of the standard tea bag of the store;

[0023] According to the formula, the brewing amount X is obtained, and the formula is:

[0024]

[0025] Where X is rounded, and X < brewing machine capacity L P ; Based on this, the required brewing amount X is obtained within time period M;

[0026] S302: Set the tea soup warning amount Y in the milk tea machine program, then Y:

[0027]

[0028] Set the remaining amount of tea soup W, after the tea is brewed, the data is transmitted to the expiration printer to print the expiration date QR code, the milk tea machine identifies the expiration date QR code, and adds the tea soup amount X to the milk tea machine software program, at this time, the remaining amount of tea soup is calculated, that is:

[0029] W=X-(B1+B2+B 3+... );

[0030] When W < Y, the milk tea machine sends a tea brewing instruction to the tea brewing machine, and the tea brewing machine starts working, and the process is repeated.

[0031] Preferably, the S4 further comprises:

[0032] In the material management of the milk tea machine, the warning value of the tea soup can be set, and during the beverage making process, the milk tea machine calculates the tea soup usage in real time, and if the warning value is reached without sending a pre-brewing tea instruction, the milk tea machine will also send a tea brewing instruction to the tea brewing machine to remind the back-end personnel to brew tea;

[0033] The control of the above tea brewing time and tea brewing amount is completed by comparing the data of the same day, and the tea brewing amount and tea brewing scheme are increased or decreased by the back-end according to the formula;

[0034] The big data processing platform is to collect and process the tea brewing data and material usage data stored in the milk tea machine back-end.

[0035] Preferably, in the S4, when the milk tea machine sends a pre-brewing tea instruction to the back-end tea brewing machine, the big data processing platform queries the tea brewing records of the day to determine whether it is an early tea brewing; if there is no tea brewing record, it is an early tea brewing, and all materials that need to be brewed in the back-end will be brewed in order; at this time, the big data platform calculates the current tea brewing amount X by querying the historical usage amount E of a single material within one hour; if the big data processing platform queries the historical usage amount E within one hour and determines whether E is greater than 6000, the formula is:

[0036] E≥6000

[0037]

[0038] E<6000

[0039]

[0040] Wherein X is the tea brewing amount, E is the historical usage amount of the material within one hour, and G is the water usage amount of the material per serving.

[0041] If no bubble tea record is found after the big data processing platform queries, and there is no historical use data, then:

[0042]

[0043] Based on this, the relevant data is calculated and the corresponding tea brewing instructions are sent to the tea brewing machine;

[0044] If there is a bubble tea record, the non-morning tea brewing amount is calculated by the following formula:

[0045]

[0046] Preferably, the tea brewing machine is a single-cylinder double-barrel tea brewing machine, and the tea brewing machine provides hot water for two tea brewing barrels through a heating water tank. When the milk tea machine continuously sends tea brewing instructions, the same temperature tea leaves can be brewed at the same time, and different temperature tea leaves can also be brewed in sequence.

[0047] Preferably, in S5, the tea brewing machine updates the tea brewing state in real time on the big data processing platform, and the milk tea machine obtains the tea brewing state in real time. After the tea brewing is completed, the milk tea machine obtains the tea brewing completion state, sends an instruction to the expiration date printer, and prints the expiration date label and pastes it to the relative tea soup. At the same time, the milk tea machine completes the management and addition of material reserves in the user interface through the identification of the expiration date two-dimensional code.

[0048] Compared with the prior art, the present application provides a big data-based milk tea machine and tea brewing machine linkage method, which has the following beneficial effects:

[0049] The big data-based milk tea machine and tea brewing machine linkage method links the originally independent tea brewing machine and milk tea machine, saves the communication between store operators, controls the tea brewing time, tea brewing type, tea brewing amount, etc. through big data analysis, reduces the problem of not being able to timely supplement the tea soup raw material and tea soup surplus waste, and improves the work efficiency of the store. At the same time, due to the lack of data interaction in the store, there may be problems of over-brewing or forgetting to brew. Tea has a shelf life, and the shorter the time, the better the tea aroma preservation. Therefore, the scheme can also ensure that the store tea soup locks the tea aroma, improves the flavor of the beverage, and based on this, the tea brewing time can be obtained through big data comparison and analysis, and tea can be prepared to ensure sufficient tea soup. BRIEF DESCRIPTION OF DRAWINGS

[0050] Figure 1 is the working logic diagram of the present application;

[0051] Figure 2 is the working flowchart of the present application. DETAILED DESCRIPTION

[0052] In order to make the technical means, creative features, purposes and effects of the present application easy to understand, the present application is further described below in conjunction with specific embodiments.

[0053] As shown in Figure 1 , Figure 2 A linkage method of a milk tea machine and a tea making machine based on big data, comprising the following operation steps:

[0054] S1: constituting a scheme, comprising a milk tea machine, a tea making machine, a milk tea machine background big data, a big data processing middle platform, and a user end, the middle platform is used for judging the tea making time, tea type, and tea making amount by reading and analyzing the big data;

[0055] The milk tea machine pulls the results of the middle platform big data analysis, and sends the tea making instruction to the tea making machine. The tea making machine is a single-cylinder double-barrel tea making machine. The tea making machine provides hot water for two tea making barrels through a heating water tank. When the milk tea machine continuously sends the tea making instruction, the same temperature tea leaves can be made at the same time, and different temperature tea leaves can also be made in sequence according to the order. Compared with the traditional double-head tea making machine, the cost is saved, and the function of the traditional double-head tea making machine can also be realized, such as: the milk tea machine sends the tea making instruction of black tea and green tea. The kitchen can preferentially make black tea, and prepare green tea at the same time of making black tea, and use a single-cylinder double-barrel tea making machine to make tea in sequence.

[0056] The tea making machine is a single-cylinder double-barrel tea making machine, which receives the tea making instruction and makes tea in sequence.

[0057] The milk tea machine background is mainly used to store the tea making method and the related big data of the tea shop tea making situation.

[0058] S2: linkage processing, the user writes the corresponding tea formula in the milk tea machine background user end, including tea type, water amount, soaking time, stirring time, and related information of tea making steps, the milk tea machine obtains the related information and stores it, when tea making is needed, the milk tea machine sends the tea making instruction and sends the related tea formula to the tea making machine, the milk tea machine sends the tea making instruction, including:

[0059] The human judges the required tea type and tea making amount, and manually operates the milk tea machine to send the tea making instruction and tea making information to the tea making machine. After the tea making machine backend receives the related tea making information, it confirms and makes tea in sequence.

[0060] The milk tea machine automatically sends instructions to the tea making machine, and the milk tea machine sends instructions including pre-tea making instructions and tea making instructions. The milk tea machine pulls the background big data, including but not limited to the cup output of the same day every week and the usage of different types of tea soup on the same day, and obtains the tea making time through comparative analysis. For example, at 9 o'clock in the morning on the same day, the tea making amount and the tea making time are determined by comparing multiple data of the same day at the same time, the material preparation and the tea making time are calculated, and the tea making instruction is sent in advance.

[0061] S3: The tea making machine processes data, including the capacity L of the tea making machine P , the tea making amount X, and compares and analyzes the data in the big data processing platform. In the background of the milk tea machine, the tea making time T1 corresponding to each type of tea is set, and the preparation time T2 of the kitchen staff is considered. The data processing includes the following steps:

[0062] S301: Determine the pre-cup output A in the first time period M after the morning of the same day;

[0063] Determine the usage B1 / B2 / B3... of the tea in different products;

[0064] Determine the weight C of the standard tea bag of the store;

[0065] According to the formula, the tea making amount X is obtained, and the formula is:

[0066]

[0067] Where X is rounded, X < tea making machine capacity L P ; Based on this, the tea making amount X required in the time period M is obtained;

[0068] S302: Set the tea soup warning amount Y in the milk tea machine program, then according to the formula, Y:

[0069]

[0070] Set the remaining amount of tea soup as W. After the tea making is completed, the data is transmitted to the expiration printer to print the expiration two-dimensional code. After the milk tea machine recognizes the expiration two-dimensional code, the tea soup amount X is added to the milk tea machine software program. At this time, the remaining amount of tea soup is calculated, that is:

[0071] W = X - (B1 + B2 + B 3+... );

[0072] When W < Y, the milk tea machine sends a tea making instruction to the tea making machine, and the tea making machine starts working. Repeat the process.

[0073] S4: Through the comparative analysis of S3, timely add materials or make materials for milk tea machine, milk tea machine sends a pre-brewing tea instruction to the back-end tea brewing machine, the tea brewing machine end accepts the instruction and reminds the operator to start brewing tea, also includes:

[0074] In the material management of milk tea machine, the pre-warning value of tea soup can be set. During the beverage making process, the milk tea machine calculates the tea soup usage in real time. If the pre-warning value is reached before the pre-brewing tea instruction is sent, the milk tea machine will also send a brewing tea instruction to the tea brewing machine to remind the back-end personnel to brew tea;

[0075] The above-mentioned brewing time and brewing amount control is completed by comparing the same day data, and the brewing amount and brewing scheme are increased or decreased by the back-end corresponding formula in proportion;

[0076] The big data processing platform is to summarize and process the tea brewing data and material usage data stored in the back-end of the milk tea machine;

[0077] When the milk tea machine sends a pre-brewing tea instruction to the back-end tea brewing machine, the big data processing platform will query the tea brewing records of the day to determine whether it is an early brewing; If there is no tea brewing record, it is an early brewing, and all materials that need to be brewed in the back-end will be brewed in order. At this time, the big data platform calculates the current brewing amount X by querying the historical usage amount E of a single material within one hour; If the big data processing platform queries the historical usage amount E within one hour and judges whether E is greater than 6000, the formula is:

[0078] E≥6000

[0079]

[0080] E<6000

[0081]

[0082] Where X is the brewing amount, E is the historical usage amount of the material within one hour, and G is the water usage per serving of the material;

[0083] If the big data processing platform finds that there is no tea brewing record after querying, and there is no historical usage data, then:

[0084]

[0085] Based on this, the relevant data is calculated and sent to the tea brewing machine;

[0086] If there is a tea brewing record, the non-early brewing is calculated by the following formula to calculate the required brewing amount, the formula is:

[0087]

[0088] S5: After the pre-brewing tea instruction of S4 is sent, whether to brew tea and the brewing barrels corresponding to different tea soup are processed at the user end of the tea brewing machine. The tea brewing machine updates the brewing state in real time in the big data processing platform. The milk tea machine acquires the brewing state in real time. After the brewing is completed, the milk tea machine acquires the state of the brewing completion, sends an instruction to the shelf life printer, and prints the shelf life label and pastes it to the corresponding tea soup. At the same time, the milk tea machine completes the management and addition of the material remaining amount, the shelf life in the user interface through the identification of the shelf life two-dimensional code.

[0089] The above shows and describes the basic principles and main features of the present application and the advantages of the present application. Those skilled in the art should understand that the present application is not limited to the above-mentioned embodiments, and the above-mentioned embodiments and descriptions in the specification are only to illustrate the principles of the present application. Without departing from the spirit and scope of the present application, various changes and improvements can be made to the present application, and these changes and improvements all fall within the scope of the claimed present application. The scope of protection of the present application is defined by the appended claims and their equivalents.

Claims

1. A big data-based milk tea machine and tea maker linkage method, characterized in that: The method comprises the following steps: S1: constituting a scheme, including a milk tea machine, a tea making machine, a milk tea machine background big data, a big data processing platform, and a user terminal; S2: linkage processing, the user writes the formula of the corresponding tea soup on the milk tea machine background user terminal, including tea type, water quantity, soaking time, and stirring time, the milk tea machine obtains the relevant information and stores it, and sends the tea making instruction to the tea making machine when needed; S3: the tea maker processes data, including the tea maker capacity L P , the tea making amount X, and compares and analyzes through the data of the big data processing platform. In the background of the milk tea machine, the tea making time T1 corresponding to each tea leaf is set, and the preparation time T2 of the kitchen staff is considered. S4: through the comparative analysis of S3, the milk tea machine adds materials or prepares materials in time, and sends a pre-tea making instruction to the back-end tea making machine, and the tea making machine end accepts the instruction and reminds the operator to start tea making; S5: after the pre-tea making instruction of S4 is sent, whether to make tea and the tea making barrel corresponding to different tea soup are processed on the tea making machine user terminal.

2. The method of claim 1, wherein the method is based on big data. In S1, the platform is used to determine the tea making time, tea soup type, and tea making quantity by reading and analyzing the big data; The milk tea machine pulls the results of the big data analysis of the platform and sends the tea making instruction to the tea making machine; The tea making machine is a single-cylinder double-cylinder tea making machine, which accepts the tea making instruction and makes tea in order; The milk tea machine background is mainly used to store the tea making method and the relevant big data of the tea soup use of the store.

3. The method of claim 1, wherein the method is based on big data. In S2, the milk tea machine sends the tea making instruction, which includes: Human judgment of the required tea soup type and the tea making quantity, human operation of the milk tea machine to send the tea making instruction and the tea making information to the tea making machine, and confirmation of the tea making machine back end after receiving the relevant tea making information to make tea in order; Automatic sending of the instruction from the milk tea machine to the tea making machine, which includes the pre-tea making instruction and the tea making instruction, and the milk tea machine pulls the back-end big data, including but not limited to the cup output quantity of the day and the use quantity of different types of tea soup, and obtains the tea making time through comparative analysis.

4. The method of claim 1, wherein the method is based on big data. In S3, the processing data specifically comprises the following steps: S301: determining the pre-cup output quantity A in the first time period M after the store opens in the day; Determining the use quantity B1 / B2 / B3... of the tea in different products; Determining the weight C of the standard tea bag of the store; According to the formula, the tea making quantity X is obtained, and the formula is: Wherein X is an integer, X < the capacity of the tea maker L P Based on this, it is concluded that the amount of tea X needed in the time period M; S302: assuming that the tea soup early warning quantity in the milk tea machine program is Y, then according to the formula, Y: Assuming that the remaining quantity of the tea soup is W, after the tea making is completed, the data is transmitted to the expiration printer to print the expiration two-dimensional code, the milk tea machine identifies the expiration two-dimensional code, adds the tea making quantity X to the milk tea machine software program, and at this time, the remaining quantity of the tea soup is calculated, that is: W = X - (B1 + B2 + B 3+... ); When WY, the milk tea machine sends the tea making instruction to the tea making machine, and the tea making machine starts to work, and the process is repeated.

5. The method of claim 1, wherein the method is based on big data. In S4, it also includes: In the material management of the milk tea machine, the early warning value of the tea soup can be set, the milk tea machine calculates the tea soup use quantity in real time during the beverage making process, and if the early warning value is reached under the premise that the pre-tea making instruction is not sent, the milk tea machine also sends the tea making instruction to the tea making machine to remind the back-end personnel to make tea; The control of the above-mentioned tea making time and tea making quantity is completed by comparing the data of the same day, and the tea making quantity and the tea making scheme are increased or decreased by the corresponding formula of the back-end; The big data processing middle platform is to store the tea data and material use data in the milk tea machine background and summarize the processing.

6. The method of claim 1, wherein the method is based on big data. In S4, the milk tea machine sends a pre-brewing tea instruction to the backend brewing machine, and the big data processing middle platform queries the brewing record of the day to determine whether it is an early brewing tea. If there is no brewing record, it is an early brewing tea, and all brewing materials in the background will be brewed in order. At this time, the big data middle platform calculates the current brewing amount X by querying the historical usage amount E of a single material within one hour. If the big data processing middle platform queries the historical usage amount E within one hour and determines whether E is greater than 6000, the formula is: Where X is the brewing amount, E is the historical usage amount of the material within one hour, and G is the water usage of the material per serving. If the big data processing middle platform finds no brewing record after querying, and there is no historical usage data, then: Based on this, the relevant data is calculated and sent to the brewing machine corresponding to the brewing instruction. If there is a brewing record, then the non-early brewing tea calculates the required brewing amount by the following formula:

7. The method of claim 1, wherein the method is based on big data. The brewing machine is a single-cylinder double-barrel brewing machine. The brewing machine provides hot water for two brewing barrels through a heating water tank. When the milk tea machine sends a continuous brewing instruction, the same temperature tea can be brewed at the same time, and different temperature tea can also be brewed in sequence.

8. The method of claim 1, wherein the method is a method of linking a milk tea machine and a tea maker based on big data. In S5, the brewing machine will update the brewing status in real time in the big data processing middle platform, and the milk tea machine will obtain the brewing status in real time. After the brewing is completed, the milk tea machine obtains the brewing completion status and sends an instruction to the expiration printer. The printer prints the expiration label and pastes it to the relative tea soup. At the same time, the milk tea machine completes the management and addition of material remaining amount, expiration date in the user interface through the identification of the expiration date QR code.

Images