Cooking menu recommendation method and device, intelligent cooking machine and storage medium

Abstract

The invention relates to the technical field of cooking machines, and discloses a cooking menu recommendation method and device, an intelligent cooking machine and a storage medium, and the method comprises the steps: responding to a cooking reservation operation, and sending the triggering information of cooking reservation to target equipment; receiving feedback information returned by the target equipment according to the triggering information; when the feedback information is identified as execution information, executing a cooking task according to a preset cooking menu and food material storage information; and when the feedback information is identified as adjustment information, acquiring commuting data of the target equipment, and executing a cooking task according to the commuting data, a preset cooking menu and food material storage information, so that when the feedback information is identified as the adjustment information, the cooking task can be executed according to the commuting data, the preset cooking menu and the food material storage information. The cooking task corresponding to the preset cooking menu is executed, the time interval between the cooking task completion time and the user home returning time is shortened, the time interval is controlled to be within a reasonable range, and therefore the user experience is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of cooking menu recommendation, and in particular to a cooking menu recommendation method, device, intelligent cooking machine and storage medium. Background Art

[0002] With the development of automation technology, intelligent cooking machines with automatic cooking functions have emerged. Automated intelligent cooking machines can automatically stir-fry, fry, deep-fry, stir-fry, steam, cook, simmer, boil, stew, cook, and bake, and can prepare a variety of preset dishes.

[0003] Currently, users who work away from home can make an appointment with a smart cooking machine to cook dishes in advance so that they can eat as soon as possible when they return home. However, due to the influence of commuting data such as the means of transportation used by the user to go home and the road conditions when going home, the time when the user returns home is inconsistent with the user's expectations, resulting in a large time gap between the time when the user returns home and the time when the smart cooking machine finishes cooking the dishes, and the user experience is poor. Summary of the invention

[0004] Based on this, it is necessary to address the technical problem in the prior art that, under the influence of commuting data, the time when the user returns home is inconsistent with the user's expectations, resulting in a large time gap between the time when the user returns home and the time when the user schedules the smart cooking machine to complete cooking, resulting in poor user experience. A cooking menu recommendation method, device, smart cooking machine and storage medium are proposed.

[0005] In a first aspect, a cooking menu recommendation method is provided, the method comprising:

[0006] In response to the scheduled cooking operation, sending a trigger message of the scheduled cooking to a target device;

[0007] receiving feedback information returned by the target device according to the trigger information;

[0008] When the feedback information is identified as execution information, executing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area;

[0009] When the feedback information is identified as adjustment information, the commuting data of the target device is acquired, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information.

[0010] In a second aspect, a cooking menu recommendation device is provided, the device comprising:

[0011] A response module, configured to send a trigger message of the scheduled cooking to a target device in response to the scheduled cooking operation;

[0012] A receiving module, used for receiving feedback information returned by the target device according to the trigger information;

[0013] an identification module, configured to execute a cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area when identifying that the feedback information is execution information;

[0014] An execution module is used to obtain commuting data of the target device when recognizing that the feedback information is adjustment information, and execute the cooking task corresponding to the preset cooking menu according to the commuting data, the preset cooking menu and the food storage information.

[0015] Optionally, in some embodiments of the present application, the output module includes:

[0016] An estimating unit, configured to estimate the commuting time according to the commuting route and commuting mode in the commuting data;

[0017] An execution unit is used to execute a cooking task corresponding to the preset cooking menu according to the commuting time, the preset cooking menu and the food storage information.

[0018] Optionally, in some embodiments of the present application, the execution unit includes:

[0019] Get subunit, used to get current time;

[0020] A determination subunit, configured to determine a preparation start time and a preparation end time according to the current time, the commuting time, and the preparation time of the dish of the preset cooking menu;

[0021] The execution subunit is used to execute the cooking task corresponding to the preset cooking menu according to the preparation start time, the preparation end time, the preset cooking menu and the food storage information.

[0022] Optionally, in some embodiments of the present application, the execution subunit is specifically used for:

[0023] Obtaining a target cooking menu according to the preparation start time, the preparation end time and the preset cooking menu;

[0024] According to the target cooking menu and the food storage information, a cooking task corresponding to the target cooking menu is executed.

[0025] Optionally, in some embodiments of the present application, the execution subunit is specifically used for:

[0026] Extracting cooking ingredient information from the target cooking menu to obtain cooking ingredient information;

[0027] If the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions, the cooking task corresponding to the target cooking menu is executed.

[0028] Optionally, in some embodiments of the present application, a sending module is further included, and the sending module is used to:

[0029] If the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, determining ingredient difference information of the cooking ingredient information and the ingredient storage information;

[0030] Generate purchased ingredient data according to the ingredient difference information;

[0031] Ingredients are purchased through a preset purchasing platform and purchasing ingredient data, order information is generated, and the order information is sent to the target device.

[0032] Optionally, in some embodiments of the present application, the identification module further includes:

[0033] An extraction unit, used for extracting each serving time in the preset cooking menu and the food material data and / or seasoning data corresponding to each serving time according to the current cooking mode;

[0034] The delivery unit is used to execute the cooking task corresponding to the preset cooking menu according to the delivery time, the food storage information and the food data and / or seasoning data corresponding to each delivery time.

[0035] In a third aspect, an intelligent cooking machine is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the above-mentioned cooking menu recommendation method when executing the computer program.

[0036] In a fourth aspect, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the above-mentioned cooking menu recommendation method are implemented.

[0037] The cooking menu recommendation method proposed in the present application sends a trigger information of the scheduled cooking to the target device in response to the scheduled cooking operation, and then receives feedback information returned by the target device according to the trigger information. Then, when the feedback information is identified as execution information, the cooking task corresponding to the preset cooking menu is executed according to the preset cooking menu and the ingredient storage information of the preset ingredient storage area. When the feedback information is identified as adjustment information, the commuting data of the target device is obtained, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. When the feedback information is identified as adjustment information, the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. This can reduce the time interval between the time when the cooking task is completed and the time when the user returns home, and control the above time interval within a reasonable range, thereby improving the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0039] in:

[0040] Figure 1 A diagram of an application environment of a cooking menu recommendation method in one embodiment;

[0041] Figure 2 A flowchart of a cooking menu recommendation method in one embodiment;

[0042] Figure 3 It is a structural block diagram of a cooking menu recommendation device in one embodiment;

[0043] Figure 4 1 is a structural block diagram of an intelligent cooking machine in one embodiment. DETAILED DESCRIPTION

[0044] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0045] In the following description, reference is made to “some embodiments”, which describe a subset of all possible embodiments, but it will be understood that “some embodiments” may be the same subset or different subsets of all possible embodiments and may be combined with each other without conflict.

[0046] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0047] The present application provides a cooking menu recommendation method, device, intelligent cooking machine and storage medium.

[0048] The cooking menu recommendation device can be integrated into a target device, which can be a smart phone, a tablet computer, a laptop computer, or a desktop computer, but is not limited thereto. The target device can be directly or indirectly connected to a server via wired or wireless communication. The server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers. It can also be a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. This application does not limit this.

[0049] For example, see Figure 1 The cooking menu recommendation device is integrated on a smart phone, and the smart phone communicates with the smart cooking machine through a network. The smart cooking machine can respond to the scheduled cooking operation of the smart phone to send the trigger information of the scheduled cooking to the smart phone; receive the feedback information returned by the smart phone according to the trigger information; when the smart cooking machine recognizes that the feedback information is execution information, it executes the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area; when the smart cooking machine recognizes that the feedback information is adjustment information, the smart cooking machine obtains the commuting data of the target device, and executes the cooking task corresponding to the preset cooking menu according to the commuting data, the preset cooking menu and the food storage information. When the feedback information is recognized as adjustment information, the smart cooking machine can execute the cooking task corresponding to the preset cooking menu according to the commuting data, the preset cooking menu and the food storage information, so that the time interval between the time when the cooking task is completed and the time when the user returns home is reduced, and the above time interval is controlled within a reasonable range, thereby improving the user experience.

[0050] It should be noted that the order of description of the following embodiments is not intended to limit the priority order of the embodiments.

[0051] See also Figure 2 As shown, Figure 2 A flowchart of a cooking menu recommendation method provided by an embodiment of the present invention is provided. The cooking menu recommendation method is applied to an intelligent cooking machine and includes the following steps:

[0052] S101: In response to a cooking reservation operation, sending a trigger message of the cooking reservation to a target device;

[0053] The target device may be a PC, or a mobile terminal device with a display function such as a smart phone, a tablet computer, or a portable computer. The scheduled cooking operation may be triggered by a user, such as displaying a scheduled cooking button on the display screen of the target device, and in response to the user clicking the scheduled cooking button, triggering a scheduled cooking instruction, and then triggering the scheduled cooking operation according to the scheduled cooking instruction. Of course, the user may also set a scheduled cooking time in the smart cooking machine in advance, that is, when the current time reaches the scheduled cooking time, the scheduled cooking operation is triggered, such as setting a scheduled cooking time at 5 pm every day, and triggering the scheduled cooking operation when the current time reaches 5 pm.

[0054] Specifically, in response to the scheduled cooking operation, a trigger information for the scheduled cooking is sent to the target device, wherein the trigger information may include status information of the current smart cooking machine and the reservation information. The status information may include whether the smart cooking machine is connected to a power source and whether it is working. The reservation information includes at least the reservation time for starting the smart cooking machine.

[0055] S102: receiving feedback information returned by the target device according to the trigger information;

[0056] Specifically, when the target device obtains the trigger information, it generates feedback information according to the user's selection, and returns the feedback information to the intelligent cooking machine, wherein the intelligent cooking machine receives the feedback information returned by the target device according to the trigger information. For example, when the target device obtains the trigger information, it displays the trigger information and various feedback buttons on the display screen of the target device, and the user clicks the feedback button, and feedback information corresponding to the feedback button is generated, and the feedback information is returned to the intelligent cooking machine.

[0057] S103: When the feedback information is identified as execution information, executing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area;

[0058] Specifically, the feedback information is identified. When the feedback information is execution information, the current time is obtained, and the preset cooking menu is determined according to the current time. For example, when the current time is the noon time period, the preset cooking menu corresponding to the noon time period is obtained, and when the current time is the afternoon time period, the preset cooking menu corresponding to the afternoon time period is obtained. After obtaining the preset cooking menu, it is determined whether each dish in the preset cooking menu can be prepared through the food storage information of the preset food storage area. If it can be prepared, the intelligent cooking machine is controlled to execute the cooking task corresponding to the preset cooking menu, wherein the preset food storage area can be a kitchen and / or a refrigerator, and the food storage information refers to the type of food, the weight of each food, the type of seasoning, and the weight of the seasoning, etc.

[0059] As an example, the preparation conditions for preparing each dish in the preset cooking menu are determined, the preparation conditions including the type of ingredients required for the dish, the weight of each ingredient, the type of seasoning, and the weight of the seasoning. According to the stored information of the ingredients, it is determined whether the above preparation conditions are met.

[0060] It should also be noted that the preset cooking menu may include each dish and the time for the ingredients and seasonings required to prepare each dish, so that the intelligent cooking machine is controlled to perform the cooking task corresponding to the preset cooking menu according to the time. That is, the step of performing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area also includes:

[0061] S1031: extracting each serving time in the preset cooking menu and the ingredient data and / or seasoning data corresponding to each serving time according to the current cooking mode;

[0062] S1032: Execute the cooking task corresponding to the preset cooking menu according to the delivery time, the food storage information, and the food data and / or seasoning data corresponding to each delivery time.

[0063] For example, specifically, the current cooking mode is determined, and the cooking mode may include a semi-automatic cooking mode and a fully automatic cooking mode. Taking the semi-automatic cooking mode as an example, when the current cooking mode is the semi-automatic cooking mode, the respective delivery times of each dish in the semi-automatic cooking mode, and the ingredient data and / or seasoning data corresponding to each delivery time are extracted from the preset cooking menu. After obtaining the respective delivery times, and the ingredient data and / or seasoning data corresponding to each delivery time, the cooking task corresponding to the preset cooking menu can be executed through the delivery time, the ingredient storage information, and the ingredient data and / or seasoning data corresponding to each delivery time, and the ingredient storage information.

[0064] As an example, in the semi-automatic cooking mode, the release times are t1, t2, and t3, and the food data and seasoning data corresponding to t1 are used as the first release material; the food data and seasoning data corresponding to t2 are used as the second release material; the food data and seasoning data corresponding to t3 are used as the third release material, wherein t3 is later than t2, and t2 is later than t1; when the time reaches t1, according to the first release material, the specific storage location of the first release material is determined in the food storage information, and the user is prompted to put the first release material into the cooking utensils of the smart cooking machine within the preset time. The preset time can be a factory setting, for example, the specific storage location of the first release material is displayed on the display screen of the smart cooking machine, and the specific storage location of the first release material is highlighted, bolded, and other font processing is performed on the display screen. When it is detected that the user puts the first material into the cooking utensils of the intelligent cooking machine within the preset time, it is determined whether the current time has reached t2. When the time reaches t2, the specific storage location of the second material is determined in the food storage information according to the second material, and the user is prompted to put the second material into the cooking utensils of the intelligent cooking machine within the preset time. When it is detected that the user puts the second material into the cooking utensils of the intelligent cooking machine within the preset time, it is determined whether the current time has reached t3. When the time reaches t3, the specific storage location of the third material is determined in the food storage information according to the third material, and the user is prompted to put the third material into the cooking utensils of the intelligent cooking machine within the preset time.

[0065] S104: When the feedback information is identified as adjustment information, the commuting data of the target device is obtained, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the food storage information.

[0066] Specifically, the feedback information is identified. When the feedback information is adjustment information, it means that the user may be affected by the commuting data, so that the time when the user returns home is inconsistent with the user's expectations, resulting in a large time interval between the time when the user returns home and the time when the smart cooking machine completes cooking. The commuting data refers to the means of transportation used by the user to go home and the road conditions when going home. Therefore, when the feedback information is adjustment information. Obtain the commuting data of the target device, for example, you can connect to the map website through the API (Application Programming Interface) interface to obtain the commuting data.

[0067] After obtaining the commuting data, for example, the preset cooking menu can be adjusted according to the commuting data, so that the cooking task corresponding to the adjusted preset cooking menu and the ingredient storage information is executed, so as to reduce the large time interval between the time when the user returns home and the time when the smart cooking machine completes cooking the dish, and control the above time interval within a reasonable range.

[0068] The cooking menu recommendation method proposed in this embodiment sends a trigger information of the scheduled cooking to the target device in response to the scheduled cooking operation, and then receives feedback information returned by the target device according to the trigger information. Then, when the feedback information is identified as execution information, the cooking task corresponding to the preset cooking menu is executed according to the preset cooking menu and the ingredient storage information of the preset ingredient storage area. When the feedback information is identified as adjustment information, the commuting data of the target device is obtained, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. When the feedback information is identified as adjustment information, the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. This can reduce the time interval between the time when the cooking task is completed and the time when the user returns home, and control the above time interval within a reasonable range, thereby improving the user experience.

[0069] In one embodiment, executing a cooking task corresponding to a preset cooking menu according to commuting data, a preset cooking menu, and food storage information includes:

[0070] S201: Estimate commuting time based on commuting routes and commuting methods in commuting data;

[0071] Among them, commuting methods may include bus, subway, cycling, walking, etc. According to different commuting methods, a better commuting route corresponding to the commuting method is obtained. The commuting route refers to the route from the user's current location to the destination of home.

[0072] As an example, a trained commuting time prediction model is used to obtain the commuting time. For example, the commuting route and commuting method are input into the trained commuting time prediction model to obtain the prediction result output by the trained commuting time prediction model. The prediction result is the commuting time, wherein the similarity model can be obtained based on training of a recurrent neural network (RNN).

[0073] S202: Execute a cooking task corresponding to the preset cooking menu according to the commuting time, the preset cooking menu and the food storage information.

[0074] For example, after obtaining the commuting time, the preset cooking menu can be adjusted according to the commuting time, so that the cooking task corresponding to the adjusted preset cooking menu is executed according to the adjusted preset cooking menu and the food storage information.

[0075] As another example, the serving time and cooking temperature of each dish in the preset cooking menu can be controlled according to the commuting time and the time to prepare the dish, so as to reduce or increase the cooking time.

[0076] It should be noted that when the commuting time is longer than the time it takes to prepare a dish, the time it takes to put each dish in the preset cooking menu is extended and the cooking temperature is lowered to increase the cooking time. When the commuting time is shorter than the time it takes to prepare a dish, the time it takes to put each dish in the preset cooking menu is shortened and the cooking temperature is increased to reduce the cooking time.

[0077] The cooking menu recommendation method proposed in this embodiment estimates the commuting time based on the commuting route and commuting mode in the commuting data, and then executes the cooking tasks corresponding to the preset cooking menu based on the commuting time, the preset cooking menu and the ingredient storage information. The cooking tasks corresponding to the preset cooking menu can be executed through the commuting time, the preset cooking menu and the ingredient storage information, so that the time interval between the time when the cooking task is completed and the time when the user returns home is reduced, and the above time interval is controlled within a reasonable range, thereby improving the user experience.

[0078] In one embodiment, the cooking task corresponding to the preset cooking menu is executed according to the commuting time, the preset cooking menu and the food storage information, including:

[0079] S301: Get current time;

[0080] S302: Determine the preparation start time and the preparation end time according to the current time, the commuting time, and the preparation time of the preset cooking menu;

[0081] S303: Execute a cooking task corresponding to the preset cooking menu according to the preparation start time, the preparation end time, the preset cooking menu and the food storage information.

[0082] For example, after obtaining the current time, the target time for the user to arrive at the destination is obtained through the current time and the commuting time. For example, the current time is 12:00 and the commuting time is 30 minutes, so the target time may be between 12:25 and 12:35; then the dish preparation time is extracted from the preset cooking menu. The dish preparation time refers to the sum of the time for preparing each dish in the preset cooking menu. For example, the preset cooking menu includes dish A, dish B, dish C and dish D. The time for preparing dish A is 5 minutes, the time for preparing dish B is 6 minutes, the time for preparing dish C is 7 minutes, and the time for preparing dish D is 8 minutes, so the dish preparation time is 26 minutes.

[0083] After obtaining the preparation time, the preparation start time and preparation end time are determined by the preparation time and the target time. For example, if the preparation time is 30 minutes and the target time is 12:30, then the preparation start time can be between 12:00 and 12:03, and the preparation end time can be between 12:30 and 12:33.

[0084] After obtaining the preparation start time and the preparation end time, the preset cooking menu can be adjusted according to the preparation start time and the preparation end time, so as to execute the cooking task corresponding to the adjusted preset cooking menu according to the adjusted preset cooking menu and the food storage information.

[0085] The cooking menu recommendation method proposed in the present embodiment obtains the current time, and then determines the preparation start time and the preparation end time according to the current time, the commuting time and the preparation time of the preset cooking menu, and finally executes the cooking task corresponding to the preset cooking menu according to the preparation start time, the preparation end time, the preset cooking menu and the food storage information. The cooking task corresponding to the preset cooking menu can be executed by the preparation start time, the preparation end time, the preset cooking menu and the food storage information, so that the time interval between the time when the cooking task is completed and the time when the user returns home is reduced, and the above time interval is controlled within a reasonable range, thereby improving the user experience.

[0086] In one embodiment, according to the preparation start time, the preparation end time, the preset cooking menu and the food storage information, executing the cooking task corresponding to the preset cooking menu includes:

[0087] S401: Obtaining a target cooking menu according to the preparation start time, the preparation end time and the preset cooking menu;

[0088] S402: Execute a cooking task corresponding to the target cooking menu according to the target cooking menu and the food storage information.

[0089] Specifically, the preparation completion time of each dish in the preset cooking menu is adjusted by the preparation start time and the preparation end time, and the adjusted preset cooking menu is used as the target cooking menu. For example, the preset cooking menu includes dish A, dish B, dish C and dish D. The preparation time of dish A is 5 minutes, the preparation time of dish B is 6 minutes, the preparation time of dish C is 7 minutes, and the preparation time of dish D is 8 minutes. If the preparation start time is 12:00 and the preparation end time is 12:20, in order to complete the preparation of the dishes at around 12:20, the preparation time of dish A, dish B, dish C and dish D is shortened respectively, and the first dish to be prepared and the last dish to be prepared are determined among dish A, dish B, dish C and dish D. The dish to be prepared first needs to be prepared at the preparation start time 12:00. It should be noted that the first dish to be prepared and the last dish to be prepared can be determined by the ingredients used in the dishes or the preparation time of the dishes. For example, if the ingredients used in dish A are vegetables, then dish A is the last dish to be prepared, and if the ingredients used in dish B are meat, it is the first dish to be prepared.

[0090] After obtaining the target cooking menu, the cooking task corresponding to the target cooking menu is executed through the target cooking menu and the ingredient storage information, thereby reducing the time interval between the time when the cooking task is completed and the time when the user returns home, and controlling the above time interval within a reasonable range, thereby improving the user experience.

[0091] In one embodiment, executing a cooking task corresponding to the target cooking menu according to the target cooking menu and the food storage information includes:

[0092] S501: extracting cooking ingredient information from a target cooking menu to obtain cooking ingredient information;

[0093] S502: If the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions, the cooking task corresponding to the target cooking menu is executed.

[0094] In this embodiment, the target cooking menu is firstly extracted from the cooking ingredient information to obtain the cooking ingredient information. As an example, the target cooking menu includes dishes A, B, C and D, and the cooking ingredient information includes the ingredient information required for preparing dish A, the ingredient information required for preparing dish B, the ingredient information required for preparing dish C and the ingredient information required for preparing dish D, and the ingredient information includes the type of ingredients and the weight of each ingredient, and the type of seasoning and the weight of each seasoning.

[0095] After obtaining the cooking ingredient information, it is determined whether the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions. If the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions, the cooking task corresponding to the target cooking menu is executed.

[0096] As an example, the ingredient storage information includes the type of each ingredient and the weight of each ingredient in the preset ingredient storage area, as well as the type of seasoning and the weight of each seasoning. The ingredient storage information and the cooking ingredient information are compared to determine whether the materials required to prepare each dish in the target cooking menu are met. If so, the preset cooking ingredient conditions are met.

[0097] The cooking menu recommendation method proposed in the present embodiment obtains cooking ingredient information by extracting cooking ingredient information from a target cooking menu, and then executes a cooking task corresponding to the target cooking menu if the cooking ingredient information and the ingredient storage information satisfy a preset cooking ingredient condition. The cooking task corresponding to the target cooking menu can be executed when the preset cooking ingredient condition is satisfied, thereby reducing the time interval between the time when the cooking task is completed and the time when the user returns home, and controlling the above time interval within a reasonable range, thereby improving the user experience.

[0098] In one embodiment, after extracting cooking ingredient information from a target cooking menu and obtaining the cooking ingredient information, the method further includes:

[0099] S601: If the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, determining ingredient difference information of the cooking ingredient information and the ingredient storage information;

[0100] S602: Generate purchased food data according to food difference information;

[0101] S603: Procurement of ingredients through a preset procurement platform and procurement ingredient data, generation of order information, and sending of the order information to a target device.

[0102] In this embodiment, when the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, it means that the ingredients stored in the preset ingredient storage area are insufficient to prepare the dishes in the target cooking menu. Therefore, when the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, the ingredients and seasonings missing from preparing the dishes in the target cooking menu in the preset ingredient storage area are determined by comparing the cooking ingredient information and the ingredient storage information, as the ingredient difference information.

[0103] After obtaining the ingredient difference information, the ingredient purchase data is generated through the ingredient difference information, wherein the purchase data includes the types and weights of the ingredients and seasonings to be purchased. Then, the ingredients are purchased through the preset purchasing platform and the purchased ingredient data, order information is generated, and the order information is sent to the target device. For example, the preset purchasing platform is connected through the API interface, and the purchase is carried out on the preset purchasing platform according to the purchased ingredient data, order information is generated, and the order information is sent to the target device. When the target device obtains the order information, the user can view the order information on the display screen of the target device and determine whether to pay for the order.

[0104] The cooking menu recommendation method proposed in this embodiment determines the ingredient difference information of the cooking ingredient information and the ingredient storage information if the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, then generates the purchased ingredient data according to the ingredient difference information, and finally purchases the ingredients through the preset purchasing platform and the purchased ingredient data, generates order information, and sends the order information to the target device. It can generate the purchased ingredient data according to the ingredient difference information and purchase on the preset purchasing platform, so that the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions, and then execute the cooking task corresponding to the target cooking menu, so that the time interval between the time when the cooking task is completed and the time when the user returns home is reduced, and the above time interval is controlled within a reasonable range, thereby improving the user experience.

[0105] See also Figure 3 As shown, in one embodiment, a cooking menu recommendation device is provided, the device comprising:

[0106] A response module 10, configured to send a trigger message of the scheduled cooking to a target device in response to the scheduled cooking operation;

[0107] The receiving module 20 is used to receive feedback information returned by the target device according to the trigger information;

[0108] The identification module 30 is used to execute the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area when the feedback information is identified as execution information;

[0109] The execution module 10 is used to obtain the commuting data of the target device when the feedback information is identified as adjustment information, and execute the cooking task corresponding to the preset cooking menu according to the commuting data, the preset cooking menu and the ingredient storage information.

[0110] The cooking menu recommendation method proposed in this embodiment sends a trigger information of the scheduled cooking to the target device in response to the scheduled cooking operation, and then receives feedback information returned by the target device according to the trigger information. Then, when the feedback information is identified as execution information, the cooking task corresponding to the preset cooking menu is executed according to the preset cooking menu and the ingredient storage information of the preset ingredient storage area. When the feedback information is identified as adjustment information, the commuting data of the target device is obtained, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. When the feedback information is identified as adjustment information, the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. This can reduce the time interval between the time when the cooking task is completed and the time when the user returns home, and control the above time interval within a reasonable range, thereby improving the user experience.

[0111] Optionally, in some embodiments of the present application, the output module includes:

[0112] An estimating unit, configured to estimate the commuting time according to the commuting route and commuting mode in the commuting data;

[0113] An execution unit is used to execute a cooking task corresponding to the preset cooking menu according to the commuting time, the preset cooking menu and the food storage information.

[0114] Optionally, in some embodiments of the present application, the execution unit includes:

[0115] Get subunit, used to get current time;

[0116] A determination subunit, configured to determine a preparation start time and a preparation end time according to the current time, the commuting time, and the preparation time of the dish of the preset cooking menu;

[0117] The execution subunit is used to execute the cooking task corresponding to the preset cooking menu according to the preparation start time, the preparation end time, the preset cooking menu and the food storage information.

[0118] Optionally, in some embodiments of the present application, the execution subunit is specifically used for:

[0119] Obtaining a target cooking menu according to the preparation start time, the preparation end time and the preset cooking menu;

[0120] According to the target cooking menu and the food storage information, a cooking task corresponding to the target cooking menu is executed.

[0121] Optionally, in some embodiments of the present application, the execution subunit is specifically used for:

[0122] Extracting cooking ingredient information from the target cooking menu to obtain cooking ingredient information;

[0123] If the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions, the cooking task corresponding to the target cooking menu is executed.

[0124] Optionally, in some embodiments of the present application, a sending module is further included, and the sending module is used to:

[0125] If the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, determining ingredient difference information of the cooking ingredient information and the ingredient storage information;

[0126] Generate purchased ingredient data according to the ingredient difference information;

[0127] Ingredients are purchased through a preset purchasing platform and purchasing ingredient data, order information is generated, and the order information is sent to the target device.

[0128] Optionally, in some embodiments of the present application, the identification module further includes:

[0129] An extraction unit, used for extracting each serving time in the preset cooking menu and the food material data and / or seasoning data corresponding to each serving time according to the current cooking mode;

[0130] The delivery unit is used to execute the cooking task corresponding to the preset cooking menu according to the delivery time, the food storage information and the food data and / or seasoning data corresponding to each delivery time.

[0131] In one embodiment, a smart cooking machine is provided. The smart cooking machine may be a server, and its internal structure diagram may be as follows: Figure 4 As shown. The intelligent cooking machine includes a processor, a memory, a network interface and a database connected through a system bus. Among them, the processor of the intelligent cooking machine is used to provide computing and control capabilities. The memory of the intelligent cooking machine includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the intelligent cooking machine is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it implements the functions or steps of a cooking menu recommendation method server side.

[0132] In one embodiment, a smart cooking machine is provided, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the following steps when executing the computer program:

[0133] In response to the scheduled cooking operation, sending a trigger message of the scheduled cooking to a target device;

[0134] receiving feedback information returned by the target device according to the trigger information;

[0135] When the feedback information is identified as execution information, executing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area;

[0136] When the feedback information is identified as adjustment information, the commuting data of the target device is acquired, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information.

[0137] The cooking menu recommendation method proposed in this embodiment sends a trigger information of the scheduled cooking to the target device in response to the scheduled cooking operation, and then receives feedback information returned by the target device according to the trigger information. Then, when the feedback information is identified as execution information, the cooking task corresponding to the preset cooking menu is executed according to the preset cooking menu and the ingredient storage information of the preset ingredient storage area. When the feedback information is identified as adjustment information, the commuting data of the target device is obtained, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. When the feedback information is identified as adjustment information, the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. This can reduce the time interval between the time when the cooking task is completed and the time when the user returns home, and control the above time interval within a reasonable range, thereby improving the user experience.

[0138] In one embodiment, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the following steps are implemented:

[0139] In response to the scheduled cooking operation, sending a trigger message of the scheduled cooking to a target device;

[0140] receiving feedback information returned by the target device according to the trigger information;

[0141] When the feedback information is identified as execution information, executing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area;

[0142] When the feedback information is identified as adjustment information, the commuting data of the target device is acquired, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information.

[0143] The cooking menu recommendation method proposed in this embodiment sends a trigger information of the scheduled cooking to the target device in response to the scheduled cooking operation, and then receives feedback information returned by the target device according to the trigger information. Then, when the feedback information is identified as execution information, the cooking task corresponding to the preset cooking menu is executed according to the preset cooking menu and the ingredient storage information of the preset ingredient storage area. When the feedback information is identified as adjustment information, the commuting data of the target device is obtained, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. When the feedback information is identified as adjustment information, the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information. This can reduce the time interval between the time when the cooking task is completed and the time when the user returns home, and control the above time interval within a reasonable range, thereby improving the user experience.

[0144] It should be noted that the above functions or steps that can be implemented by the computer-readable storage medium or the intelligent cooking machine can be found in the corresponding descriptions of the server side and the client side in the aforementioned method embodiment. To avoid repetition, they will not be described one by one here.

[0145] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0146] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be distributed and completed by different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0147] The embodiments described above are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A cooking menu recommendation method, characterized in that: The method comprises: In response to the scheduled cooking operation, sending a trigger message of the scheduled cooking to a target device; receiving feedback information returned by the target device according to the trigger information; When the feedback information is identified as execution information, executing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area; When the feedback information is identified as adjustment information, the commuting data of the target device is acquired, and the cooking task corresponding to the preset cooking menu is executed according to the commuting data, the preset cooking menu and the ingredient storage information.

2. The cooking menu recommendation method according to claim 1, characterized in that: The performing a cooking task corresponding to the preset cooking menu according to the commuting data, the preset cooking menu and the food storage information includes: estimating the commuting time based on the commuting route and commuting mode in the commuting data; The cooking task corresponding to the preset cooking menu is performed according to the commuting time, the preset cooking menu and the food storage information.

3. The cooking menu recommendation method according to claim 2, characterized in that: The performing a cooking task corresponding to the preset cooking menu according to the commuting time, the preset cooking menu and the food storage information includes: Get the current time; Determine the preparation start time and the preparation end time according to the current time, the commuting time, and the preparation time of the preset cooking menu; According to the preparation start time, the preparation end time, the preset cooking menu and the food storage information, a cooking task corresponding to the preset cooking menu is performed.

4. The cooking menu recommendation method according to claim 3, characterized in that: The performing a cooking task corresponding to the preset cooking menu according to the preparation start time, the preparation end time, the preset cooking menu and the food storage information includes: Obtaining a target cooking menu according to the preparation start time, the preparation end time and the preset cooking menu; According to the target cooking menu and the food storage information, a cooking task corresponding to the target cooking menu is executed.

5. The cooking menu recommendation method according to claim 4, characterized in that: The performing a cooking task corresponding to the target cooking menu according to the target cooking menu and the food storage information includes: Extracting cooking ingredient information from the target cooking menu to obtain cooking ingredient information; If the cooking ingredient information and the ingredient storage information meet the preset cooking ingredient conditions, the cooking task corresponding to the target cooking menu is executed.

6. The cooking menu recommendation method according to claim 5, characterized in that: After extracting the cooking ingredient information from the target cooking menu and obtaining the cooking ingredient information, the method further includes: If the cooking ingredient information and the ingredient storage information do not meet the preset cooking ingredient conditions, determining ingredient difference information of the cooking ingredient information and the ingredient storage information; Generate purchased ingredient data according to the ingredient difference information; Ingredients are purchased through a preset purchasing platform and purchasing ingredient data, order information is generated, and the order information is sent to the target device.

7. The cooking menu recommendation method according to claim 1, characterized in that: The step of executing the cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area also includes: According to the current cooking mode, extracting each serving time in the preset cooking menu and the food material data and / or seasoning data corresponding to each serving time; The cooking task corresponding to the preset cooking menu is executed according to the delivery time, the food storage information and the food data and / or seasoning data corresponding to each delivery time.

8. A cooking menu recommendation device, characterized in that: The cooking menu recommendation device comprises: A response module, configured to send a trigger message of the scheduled cooking to a target device in response to the scheduled cooking operation; A receiving module, used for receiving feedback information returned by the target device according to the trigger information; an identification module, configured to execute a cooking task corresponding to the preset cooking menu according to the preset cooking menu and the food storage information of the preset food storage area when identifying that the feedback information is execution information; An execution module is used to obtain commuting data of the target device when recognizing that the feedback information is adjustment information, and execute the cooking task corresponding to the preset cooking menu according to the commuting data, the preset cooking menu and the food storage information.

9. An intelligent cooking machine, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the cooking menu recommendation method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the cooking menu recommendation method according to any one of claims 1 to 7 are implemented.

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