Food material management method and system

Abstract

The invention provides a food material management method and system. The food material management method comprises the steps that the state information, sent by the storage device, of food materials stored in the storage device is obtained, the storage device actively senses the state of the food materials, an intelligent agent accurately masters the freshness of the food materials through the state information of the food materials, and waste of the food materials due to expiration and deterioration is avoided. Meanwhile, the intelligent agent judges the food materials needing to be processed preferentially according to the freshness of the food materials, generates a menu suitable for the current cooking equipment in combination with equipment information of at least one cooking equipment which is owned by the user and can execute cooking, and actively pushes a recommended menu list to target cooking equipment which executes the target recommended menu; and the user is reminded to reasonably utilize the food materials about to be expired, so that the target cooking equipment executes the corresponding cooking program of the target recommended menu, and effective food material management is realized.

Description

TECHNICAL FIELD

[0001] The present specification relates to the technical field of intelligent household appliances, and in particular to a food material management method and system. BACKGROUND

[0002] With the development of technology, users have higher and higher requirements for the intelligence of household appliances. As a common refrigeration and preservation device in production and life, a refrigerator needs to improve its intelligence.

[0003] Current intelligent devices are mostly in a passive state of executing instructions, and lack effective food material management means.

[0004] For example, in terms of food material management and cooking, users need to manually check and remember the shelf life of food materials in the refrigerator, resulting in a large amount of food materials expiring and deteriorating due to not being eaten in time, and then being discarded, causing resource waste and economic loss, which is difficult to meet user needs.

[0005] Therefore, there is a need for a food material management scheme for intelligent devices. SUMMARY

[0006] To solve the above technical problems, the present specification provides the following technical solutions:

[0007] In a first aspect, a food material management method is provided, the method comprising:

[0008] acquiring state information of food materials stored in a storage device sent by the storage device;

[0009] identifying the freshness of the food materials based on the state information, and determining food materials that need to be processed in priority;

[0010] generating a recommended recipe list containing the food materials that need to be processed in priority and adapted to at least one cooking device owned by a user based on the food materials that need to be processed in priority and device information of the cooking device;

[0011] pushing a target recommended recipe determined based on the recommended recipe list to a target cooking device that executes the target recommended recipe, so that the target cooking device executes a cooking program corresponding to the target recommended recipe.

[0012] In the above scheme, the storage device actively senses the state of the food materials, and the intelligent agent accurately masters the freshness of the food materials through the state information of the food materials, avoiding waste of food materials due to expiration and deterioration. At the same time, the intelligent agent determines the food materials that need to be processed in priority according to the freshness of the food materials, generates a recipe suitable for the current cooking device in combination with the device information of at least one cooking device owned by the user that can execute cooking, and actively pushes the recommended recipe list to remind the user to reasonably use the food materials that will expire, effectively reducing the probability of discarding the food materials that expire.

[0013] In some embodiments, the target recommended recipe is determined by a user interaction unit; and the method further comprises:

[0014] pushing the recommended recipe list to the user interaction unit, so that a user determines a target recommended recipe from the recommended recipe list;

[0015] receiving the target recommended recipe sent by the user interaction unit, so as to adjust a recipe recommendation model for generating the recommended recipe list according to the target recommended recipe.

[0016] In the above scheme, the cooking program of the cooking equipment is determined by the state of the food material in the storage device, forming an intelligent linkage ecological system of storage, management and cooking, breaking the information island between household appliances, realizing the association, interconnection and collaborative work between devices, and improving the intelligent level of household appliances.

[0017] In some embodiments, the user interaction unit is an interaction unit of the cooking equipment or a user terminal.

[0018] In the above scheme, the user interaction unit supports multi-scene cooperation, improving the ease of use and practicality of the intelligent food material management system.

[0019] In some embodiments, after the recommended recipe list is pushed to the user interaction unit, the method further comprises:

[0020] receiving a cancel instruction sent by the user interaction unit, recording the recommended recipe list and the feature parameters of each recommended recipe corresponding to the cancel instruction, so as to adjust a recipe recommendation model for generating the recommended recipe list.

[0021] In the above scheme, by capturing the cancel instruction of the recommended recipe by the user, the recipe recommendation model is dynamically optimized, the user does not like the recipe type is filtered out, the invalid recommendation is reduced, the user screening cost is reduced, and the accuracy of subsequent recommendation is improved.

[0022] In some embodiments, after the target recommended recipe determined based on the recommended recipe list is pushed to the target cooking equipment for executing the target recommended recipe, so that the target cooking equipment executes the corresponding cooking program of the target recommended recipe, the method further comprises:

[0023] obtaining actual cooking data after the target cooking equipment completes the cooking program;

[0024] adjusting a recipe recommendation model for generating the recommended recipe list based on the actual cooking data.

[0025] According to different types of actual cooking data, the recommendation logic is adjusted in a targeted manner, the food material management is more accurate and efficient, the recommended recipes are more in line with user preferences and meet user needs, so as to achieve the effects of reducing waste and improving food material utilization efficiency.

[0026] In some embodiments, the food material management method is applied to the intelligent agent.

[0027] In a second aspect, a food material management method is provided, which is applied to a storage device, and the method comprises:

[0028] Obtaining state information of food materials stored in the storage device;

[0029] Sending the state information to the intelligent agent to enable the intelligent agent to execute the food material management method according to any one of the above.

[0030] In the above scheme, the storage device can actively perceive the state of the food materials stored therein, changing the mode of passive waiting for instructions of the traditional device, actively managing the food materials, and meeting potential needs of the user. Meanwhile, based on the state information fused from multiple source sensors, the accuracy of the intelligent agent in identifying the freshness of the food materials is improved.

[0031] In some embodiments, the storage device comprises a perception module.

[0032] The obtaining of the state information of the food materials stored in the storage device comprises:

[0033] When a triggering condition is met, the state information of the food materials stored in the storage device is obtained through the perception module;

[0034] The triggering condition comprises at least one of the following:

[0035] The current time reaches a preset time period time node;

[0036] In response to a user interaction operation on the storage device;

[0037] The state of the food materials or the environment in the storage device changes dynamically.

[0038] In the above scheme, the setting of the triggering condition enables the perception module to work on demand, which not only ensures the timeliness and accuracy of the state information of the food materials, but also avoids meaningless energy waste, and ensures the real-time performance and energy efficiency balance of data collection.

[0039] In some embodiments, the storage device further comprises a communication module for sending the state information to the intelligent agent.

[0040] In the above scheme, the state information is transmitted efficiently and stably by the communication module, so that the agent can obtain the real-time state information of the food materials in time, and make accurate decisions based on the real-time data.

[0041] In a third aspect, a food material management system is provided, and the system comprises:

[0042] a storage device configured to obtain state information of food materials stored in the storage device, and send the state information to the agent;

[0043] an agent configured to implement the food material management method according to the first aspect;

[0044] a user terminal configured to receive a recommended recipe list sent by the agent through a product application of the user terminal, display the recommended recipe list, obtain a target recommended recipe confirmed by a user, and feed back the target recommended recipe to the agent, and send the target recommended recipe to a cooking device;

[0045] a cooking device configured to execute a cooking program corresponding to the target recommended recipe.

[0046] In the above scheme, the storage device actively obtains the state information of the food materials stored therein, and the agent identifies the freshness of the food materials based on the state information, approximately grasps the shelf life of the food materials in real time, and generates a recommended recipe based on the determination of the food materials that need to be processed in priority, in combination with the information of the cooking device, the environmental state, and the potential needs of the user, to provide effective eating suggestions for the user, so that the user can accurately and timely grasp the freshness and shelf life of the food materials, and avoid wasting a large amount of food materials due to expiration. In addition, based on the collaborative scheduling mechanism of the agent, the recommended recipe confirmed by the user is synchronized to the cooking device to execute a corresponding cooking program, so as to complete the cooking of the food materials. In this process, through information sharing and collaborative work among intelligent devices, the user does not need to manually search for a recipe and set cooking parameters, and the cooking preparation and execution process are automatically completed, thereby providing the user with a convenient and intelligent cooking experience, effectively reducing the probability of food materials expiring due to not being eaten in time, and thus building an effective food material management scheme.

[0047] In a fourth aspect, a computer program product is provided for implementing the food material management method according to the first aspect.

[0048] In a fifth aspect, a storage device is provided for implementing the food material management method according to the second aspect.

[0049] In a sixth aspect, a computer readable storage medium is provided, and a computer program is stored on the computer readable storage medium, and the program is executed by a processor to implement the food material management method according to the first aspect or the second aspect.

[0050] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this specification. Attached Figure Description

[0051] To more clearly illustrate the technical solutions in the embodiments of this specification or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the embodiments of this specification. For those skilled in the art, other drawings can be obtained based on these drawings.

[0052] Figure 1 This is a flowchart illustrating a food ingredient management method provided in this manual;

[0053] Figure 2 This is another flowchart illustrating a food ingredient management method provided in this manual;

[0054] Figure 3 This is an interactive diagram of a food ingredient management system provided in this manual;

[0055] Figure 4 This is a schematic diagram of a computer-readable storage medium provided in this disclosure;

[0056] Figure 5 This is a schematic diagram of the structure of a computing device provided in this disclosure. Detailed Implementation

[0057] This specification describes several technical solutions with different concepts. Each concept has one or more embodiments, and different concepts can be combined to form more embodiments. Those skilled in the art, after reading this specification, can combine different concepts to obtain new technical solutions, and these new technical solutions should also fall within the scope of this specification.

[0058] The technical solutions of these different concepts will be introduced in turn below. Some concepts may appear in multiple technical solutions of different concepts. For these concepts, this article will explain them when they first appear and will not repeat them in the following text.

[0059] Most current smart devices are in a state of passively executing instructions and lack effective means of food management.

[0060] For example, in terms of food management and cooking, users need to manually check and remember the expiration dates of the food in the refrigerator, resulting in a large amount of food expiring and spoiling due to not being eaten in time, and then being discarded, causing waste of resources and economic losses, which makes it difficult to meet user needs.

[0061] To address the aforementioned technical problems, this manual provides a method for managing food ingredients.

[0062] The storage device actively acquires the status information of the food stored inside. Based on the AI ​​agent, it identifies the freshness of the food according to the status information, which is close to real-time monitoring of the food's shelf life. Based on the determination of the food that needs to be processed first, it generates recommended recipes by combining information from the cooking equipment, environmental conditions, and potential user needs, and provides users with effective eating suggestions. This allows users to accurately and timely grasp the freshness and shelf life of the food, avoiding the waste of a large amount of food due to expiration.

[0063] Furthermore, based on the collaborative scheduling mechanism of AI agents, the recommended recipes confirmed by the user are synchronized to the cooking equipment to execute the corresponding cooking programs, thereby completing the cooking of the ingredients. In this process, through information sharing and collaborative work between intelligent devices, users do not need to manually search for recipes or set cooking parameters; the cooking preparation and execution process is automatically completed, providing users with a convenient and intelligent cooking experience. This effectively reduces the probability of ingredients expiring and spoiling due to not being consumed in time, thus constructing an effective food management solution.

[0064] The following embodiments, in conjunction with the accompanying drawings, illustrate a method for managing food ingredients provided in this specification.

[0065] Figure 1 This is a flowchart illustrating a food ingredient management method according to an exemplary embodiment. The food ingredient management method can be applied to storage devices.

[0066] The storage devices mentioned in this article generally refer to devices that interact with an Internet of Things (IoT) platform. They typically refer to electrical appliances used in various environments, such as homes or office buildings, for various purposes. Specifically, they can be electrical appliances / home appliances with storage functions, such as refrigerators, freezers, smart rice storage containers, and fruit and vegetable preservation cabinets. Furthermore, storage appliances can also be multifunctional appliances that combine the ability to sense the status of various food items and output data.

[0067] The storage device described in this manual has the conventional structure and functions of storage devices currently on the market (such as product casing, power interface, basic equipment functions, etc.), and will not be described in detail here.

[0068] like Figure 1 As shown, the method includes steps 101 and 102.

[0069] In step 101, the status information of the food stored inside the storage device is obtained.

[0070] As an example, the storage device has a built-in sensing module. The sensing module can monitor the status of the food inside the storage device in real time through technologies such as image recognition and sensor detection, so as to report to the intelligent agent for subsequent management of the food.

[0071] The status information of the ingredients includes, but is not limited to, the type, quantity, and shelf life of the ingredients. This information allows users to keep track of the ingredients' condition in a timely manner.

[0072] In some embodiments, the sensing module includes, but is not limited to, an image recognition unit, a weight sensor, an environmental sensor, etc.

[0073] The sensing module is configured to: acquire changes in the surface morphology of food ingredients through an image recognition unit; record the consumption rate through a weight sensor; and acquire environmental data within the storage device through an environmental sensor, as environmental data affects the state of the food ingredients. For example, spinach's shelf life is extended by 1.2 times at 4°C.

[0074] It's understandable that the image recognition unit's camera captures images of the inside of the storage unit, generating images of the food. The intelligent agent then uses image recognition technology to identify the type and quantity of food in the images in real time. For example, it can add close-up shots to perishable foods to capture changes in surface texture—for instance, triggering a spoilage warning when the browning rate of spinach leaf edges exceeds 15%.

[0075] In some cases, ingredients may be obscured, leading to errors in the quantity of ingredients. This can be resolved in the following ways.

[0076] One approach is to acquire a sequence of multiple images, including the state information of the ingredients, for subsequent redundancy checks. This involves analyzing and comparing the multiple images to determine the final quantity of the ingredients.

[0077] Another approach is to use data from weight sensors to help determine the quantity of food. For example, when the food is eggs, weight sensors located in the egg storage area can record the weight of all eggs in real time. Since the weight of a single egg generally falls within a certain range, the total number of eggs can be estimated.

[0078] In some embodiments, food data, equipment data, and environmental data within the storage device are identified, and the status information of the food is determined based on the equipment data and environmental equipment.

[0079] For example, temperature and humidity sensors continuously monitor the microenvironment of the storage space. When the temperature in the refrigerator fluctuates by more than ±2°C (such as rising from 4°C to 6°C), the equivalent shelf life of fresh food is automatically shortened—fresh milk is reduced by 12 hours from its original shelf life.

[0080] By integrating multi-source sensors, more accurate information on the status of ingredients can be obtained, transforming the status of ingredients from an abstract concept into a quantitative indicator, thus providing a data foundation for determining the ingredients that need to be prioritized for processing.

[0081] In some embodiments, obtaining the status information of the food stored inside the storage device includes:

[0082] When the triggering condition is met, the sensing module obtains the status information of the food stored inside the storage device.

[0083] The triggering condition includes at least one of the following:

[0084] The current time has reached a preset time periodic node;

[0085] Respond to user interaction with the storage device;

[0086] The internal food or environmental conditions of the storage device undergo dynamic changes.

[0087] Preset time periods are fixed times set by the user or the system, such as 8 AM, 12 AM, every 6 hours, or 8 AM every Monday. Different food storage characteristics may correspond to different periods. For example, fresh food changes rapidly, so the period can be set to 4-6 hours; frequent monitoring allows for timely assessment of freshness. Dried goods change slowly, so the period can be set to 14 hours, allowing for monitoring of food status while reducing unnecessary scanning.

[0088] After setting the periodic time nodes, the sensing module will start working when the actual time reaches the set time node: the camera captures images of the food, and the sensors collect information such as temperature and weight, without user intervention. For example, it can automatically scan the refrigerator every evening at 8 pm to update the remaining shelf life and quantity of all food items. This avoids food waste due to untimely updates caused by long periods of inactivity.

[0089] The aforementioned triggering condition is an active detection mechanism that triggers the sensing module to work at fixed intervals to ensure the regular updating of status information.

[0090] The food detection mechanism during user interaction with the storage device is an instant response mechanism that collects information synchronously while the user interacts with the storage device, ensuring that the information is updated immediately upon operation.

[0091] As an example, user interaction refers to the act of a user touching or notifying a storage device. When the storage device is a refrigerator, the interaction includes, but is not limited to, the user opening the refrigerator door, pulling out drawers, remotely viewing the device via a product application on a user terminal associated with the refrigerator, and inputting commands on the refrigerator's touchscreen.

[0092] When an interaction occurs, the sensing module immediately initiates a short-term scan. For example, when a user opens the refrigerator door to retrieve food, the door magnetic sensor triggers the camera to capture an image of the refrigerator's internal storage space and simultaneously updates the status information of the food in the storage space to the intelligent agent for food status analysis and management.

[0093] By using the above triggering conditions, the impact of user behavior on the status of ingredients can be captured in real time, ensuring that the information is updated synchronously with the actual situation.

[0094] On the other hand, when an interactive operation occurs, the sensing module immediately starts a short-term scan to record information such as the quantity and storage time of the ingredients. This information can provide feedback on the shelf life of the ingredients and help estimate the freshness of the ingredients by observing changes in their surface morphology.

[0095] The storage device detects dynamic changes in the food or environmental conditions inside the storage unit using sensors in real time. Once a change exceeding a preset threshold (such as a temperature fluctuation exceeding 2°C) is detected, a targeted scan is immediately initiated. This prevents food spoilage due to uncontrolled environmental conditions and reduces ineffective scans of normal conditions.

[0096] In some embodiments, the sensing module detects the status information of the food in the storage device in real time.

[0097] The above-mentioned triggering conditions allow the sensing module to work on demand, ensuring both the timeliness and accuracy of food status information and avoiding meaningless energy waste. The three triggering conditions form a complementary information collection mechanism, ensuring a balance between real-time data collection and energy efficiency.

[0098] In step 102, the status information is sent to the intelligent agent.

[0099] The storage device also includes a communication module for sending the status information to the intelligent agent. The intelligent agent can proactively recommend recipes based on the condition of the ingredients, the environmental conditions, and the user's potential needs, thereby achieving the optimal solution for ingredient management and cooking, improving ingredient utilization and user experience.

[0100] The communication module efficiently and stably transmits status information, enabling intelligent agents to make accurate decisions based on real-time data obtained from the ingredients.

[0101] Through the above embodiments, the storage device can proactively sense the status of the food stored inside, changing the traditional mode of passively waiting for instructions and actively managing the food to meet potential user needs. Simultaneously, based on the status information fusion of multi-source sensor data, the accuracy of the intelligent agent in identifying the freshness of the food is improved.

[0102] Figure 2 This is another flowchart illustrating a food management method according to an exemplary embodiment of this specification. The food management method provided in the following embodiments can be applied to intelligent agents.

[0103] The intelligent agent described in this specification refers to a digital software program created using artificial intelligence technology that possesses autonomous learning, decision-making, and execution capabilities. At least one intelligent agent is created within the intelligent agent platform, with different intelligent agents implementing different intelligent devices and functions.

[0104] As an example, the intelligent agent may be, but is not limited to, a local processor deployed on a user terminal, a computing unit built into a storage device, a cloud server, etc.

[0105] The food ingredient management method includes steps 201 to 204:

[0106] Step 201: Obtain the status information of the food stored inside the storage device sent by the storage device.

[0107] It receives food status information, equipment information, and environmental data sent by the communication module of the storage device, providing complete and accurate raw data for subsequent processing.

[0108] In some cases, the agent preprocesses the received state information to ensure data reliability before generating recipes based on the valid data. This preprocessing can be, but is not limited to, data cleaning to remove outliers; it can also include structured storage, creating a file linking state information, collection time, and other relevant data for later application.

[0109] Step 202: Based on the status information, identify the freshness of the ingredients and determine the ingredients that need to be processed first.

[0110] The intelligent agent supports the parsing of multi-format data, such as numerical data from sensors, image data from image recognition, and text data input by humans, and verifies the freshness of ingredients through cross-validation of multi-dimensional data.

[0111] The multi-dimensional factors include, but are not limited to, time, environment, and morphology. The edible time of the food is determined by combining the initial storage time and shelf life. If the edible time is less than the set priority processing time, the food is determined to be a priority processing food. Furthermore, abnormal storage temperature and humidity will affect the storage time of the food; therefore, the estimated edible time is shortened accordingly, and the decision on whether the food should be a priority processing food is based on the shortened time.

[0112] In some embodiments, after analyzing the freshness of ingredients to determine those requiring priority processing, the intelligent agent sorts them according to their urgency, forming a priority list to precisely identify the ingredients that most urgently need priority processing. For example, priorities can be differentiated based on the edibility time of the ingredients, with the priority list including three levels of ingredients requiring priority processing. Level 1 includes ingredients that need to be processed within 24 hours, including those nearing their expiration date or slightly spoiled; Level 2 includes ingredients that need to be processed within 3 days, including those whose freshness has decreased but have not spoiled and those in small quantities; and Level 3 includes ingredients that can be processed routinely, including those with good freshness but which should be prioritized for pairing according to user preferences.

[0113] By monitoring the status of ingredients in real time and using a priority model to accurately identify ingredients nearing their expiration date, not only can waste of expired ingredients be reduced, but user eating preferences can also be met.

[0114] Step 203: Based on the ingredients that need to be prioritized and the equipment information of at least one cooking device owned by the user, generate a list of recommended recipes that includes the ingredients that need to be prioritized and is compatible with the cooking device.

[0115] The intelligent agent generates recommended recipes that the cooking equipment can execute based on the ingredients that need to be processed first and the equipment information of the cooking equipment, so that the ingredients and equipment are accurately matched, and the cooking equipment can automatically set the cooking program according to the recommended recipe, thereby improving cooking efficiency.

[0116] The user's information on at least one cooking device includes, but is not limited to, the device type (e.g., oven, air fryer, rice cooker), brand and model (different brands and models of cooking devices are associated with different smart functions), device function parameters (e.g., supported cooking methods, temperature range, capacity), and usage status (e.g., whether it is being used or is malfunctioning). The user selects a target cooking device from this information that can perform the cooking and is compatible with the ingredients requiring priority processing. The target cooking device can be one or more.

[0117] In some embodiments, the device information of the cooking equipment is obtained in the following ways.

[0118] When a recommended recipe needs to be generated, the intelligent agent establishes a connection with the cooking equipment and obtains the equipment information of at least one cooking device currently owned by the user in real time.

[0119] Alternatively, the agent can pre-store equipment information for the user's cooking appliances and directly access it when a recommended recipe needs to be generated. In some cases, the pre-stored equipment information in the agent is updated in real time to ensure reliability, and the recommended recipes generated based on this information can be executed.

[0120] In other words, the recommended recipes generated by the intelligent agent simultaneously meet two conditions: ingredient compatibility and device compatibility. Multiple recommended recipes are then arranged in a specific order to create a list for the user to select and confirm. This specific order may, but is not limited to, prioritizing the urgency of food preparation, cooking time, and user preferences, with the optimal option displayed at the top.

[0121] In some embodiments, when the intelligent agent identifies an ingredient that needs to be prioritized, it combines the device information of the user's cooking equipment to filter recommended recipes from a preset recipe database that contain the ingredient that needs to be prioritized and are compatible with the user's existing cooking equipment, and pushes them to the user's terminal.

[0122] It is understandable that a recipe database can be created based on standard recipes set according to nutritional rules, or based on users' historical cooking records, or based on recipes set according to user profiles.

[0123] In some embodiments, when the agent identifies ingredients that need to be prioritized, it generates a list of recommended recipes by combining the device information of the user's cooking equipment and historical cooking records.

[0124] Through the above embodiments, the intelligent agent generates a list of recommended recipes based on information about ingredients and cooking equipment, proactively pushes suggested recipes, reminds users to make reasonable use of ingredients that are about to expire, and effectively reduces the probability of expired ingredients being discarded.

[0125] In some embodiments, the agent creates a device collaboration scheme for the recommended recipes. The device collaboration scheme includes the cooking method and cooking parameters of each recommended recipe in the corresponding cooking device, so that the subsequent cooking device can automatically set the cooking program according to the recommended recipe, thereby improving cooking efficiency.

[0126] Step 204: Push the target recommended recipe determined based on the recommended recipe list to the target cooking device that executes the target recommended recipe, so that the target cooking device executes the corresponding cooking program of the target recommended recipe.

[0127] Determine the target recommended recipe from at least one of the recommended recipes in the recommended recipe list.

[0128] The user clicks on one or more recipes from the recommended recipe list, and the AI ​​agent identifies them as target recommended recipes. Alternatively, without user interaction, the AI ​​agent automatically selects a certain number of target recommended recipes based on factors such as shortest cooking time, equipment idle status, and highest ingredient utilization.

[0129] In some embodiments, the target recommended recipe is determined through a user interaction unit; the method further includes:

[0130] The recommended recipe list is pushed to the user interaction unit so that the user can select a target recommended recipe from the recommended recipe list;

[0131] Receive the target recommended recipe sent by the user interaction unit.

[0132] Furthermore, the intelligent agent receives the target recommended recipe sent by the user interaction unit, and adjusts the recipe recommendation model that generates the recommended recipe list according to the target recommended recipe.

[0133] A user interaction unit is a unit that provides a user interface, allowing users to select a desired recipe from a list of recommended recipes. It may be, but is not limited to, the interaction unit of a cooking device or a user terminal.

[0134] When the user interaction unit is a user terminal, the user terminal provides a user interface. The user terminal receives a list of recommended recipes sent by the intelligent agent and displays the list through the user interface, where the user can confirm the recipes. The user terminal also acquires the target recommended recipe input by the user and automatically synchronizes the recipe information of the target recommended recipe to the intelligent cooking device via a communication network.

[0135] During this process, each recommended recipe in the recommended recipe list has a corresponding recipe identifier. Once the user selects a target recommended recipe, the recipe identifier corresponding to the target recommended recipe is sent to the intelligent agent, so that the intelligent agent can determine the target recommended recipe corresponding to the recipe identifier and push the target recommended recipe to the target cooking device, so that the target cooking device can execute the corresponding cooking program of the target recommended recipe.

[0136] When the user interaction unit is the interaction unit of the cooking equipment, the cooking equipment provides a user interface to display a list of recommended recipes. The user selects a target recommended recipe in the user interface of the cooking equipment.

[0137] The user interaction unit supports multi-scenario collaboration. Even when cooking equipment is offline or malfunctioning, users can still select recipes through the terminal. Simultaneously, the terminal can link with other services, forming a more complete closed loop of lifestyle services. When users are in the kitchen, they can directly make selections on the cooking equipment without frequently switching terminals, improving operational efficiency. Users can flexibly choose based on their own situation (such as whether they have enough time or are in the kitchen), satisfying the need for refined decision-making while simplifying the cooking process, ultimately enhancing the usability and practicality of the intelligent food management system.

[0138] In other embodiments, the user adjusts each recommended recipe in the recommended recipe list, and determines the adjusted recommended recipe as the target recommended recipe. The user can adjust the recommended recipe according to cooking preferences, ingredient quantities, and other needs. For example, if the user prefers soft and tender food, they can set corresponding cooking time, cooking power, and other parameters.

[0139] According to the communication protocol of the target cooking device, the digital instructions of the adjusted recommended recipe are transmitted to the intelligent cooking device. After receiving the instructions, the cooking device automatically calls the corresponding program to cook.

[0140] Through the above embodiments, the cooking program of the cooking equipment is determined by the state of the food in the storage device, forming an intelligent interconnected ecosystem of storage, management, and cooking. This breaks down information silos between home appliances, enables interconnection and collaborative work between various devices, and improves the intelligence level of home appliances.

[0141] After the user confirms the target recommended recipe, the user's preference is recorded as a historical cooking record for the next generation of recommended recipe list, thereby optimizing the recipe recommendation model and improving the accuracy of recipe recommendations.

[0142] In some embodiments, after pushing the recommended recipe list to the user interaction unit, the method further includes:

[0143] The system receives a cancellation command sent by the user interaction unit, records the recommended recipe list corresponding to the cancellation command and the feature parameters of each recommended recipe, and adjusts the recipe recommendation model that generates the recommended recipe list.

[0144] When a user receives a list of recommended recipes in the interaction unit (terminal / cooking device), if the user sends a cancellation command (which may be to cancel the entire list or to cancel a few recommended recipes in the list), the agent receives the cancellation command and parses the specific object corresponding to the cancellation command. The specific object is the list of recommended recipes or one or more recommended recipes.

[0145] From the list of canceled recommended recipes and the recommended recipes themselves, key feature parameters are extracted. These key feature parameters include, but are not limited to, recipe type, cooking method, flavor, ingredient type, and ingredient quantity. These parameters are then associated with user identity (to ensure individualized optimization), time, and context information and stored in a negative sample library for model training. Sample data in the negative sample library is used to trigger iterative updates to the recommendation model. In some cases, when a certain number of negative samples accumulate (such as a single user canceling the same type of recipe three times consecutively, or the cancellation rate for a certain type of recipe exceeding 30% among all users), iterative updates to the recommendation model are triggered.

[0146] In this embodiment, by capturing the user's cancellation command for recommended recipes, the recipe recommendation model can be dynamically optimized, filtering out recipe types that the user does not like, reducing invalid recommendations, lowering the user's screening cost, and improving the accuracy of subsequent recommendations.

[0147] In some embodiments, the method of pushing a target recommended recipe determined based on the recommended recipe list to a target cooking device that executes the target recommended recipe, so that the target cooking device executes the cooking program corresponding to the target recommended recipe, further includes:

[0148] Based on the target recommended recipe and the equipment information of the target cooking equipment, generate cooking parameters adapted to the target cooking equipment;

[0149] The target recommended recipe and the corresponding cooking parameters are synchronously sent to the target cooking device so that the target cooking device executes the cooking program corresponding to the target recommended recipe.

[0150] Before pushing a recommended recipe to the target cooking device, the cloud-based intelligent agent generates cooking parameters based on the cooking steps of the recipe and the performance parameters of the cooking device (such as a maximum power of 2000W). These cooking parameters include, but are not limited to, temperature, time, and power values.

[0151] The target recommended recipe is then packaged and bundled with control commands, and simultaneously sent to the target cooking device via a communication network. Upon receiving the command, the target cooking device skips the semantic parsing step and directly reads the cooking parameters, which serve as physical control commands that can directly drive the device to execute the cooking program.

[0152] Cooking parameters are generated in the cloud and simultaneously sent to the cooking equipment along with the target recommended recipe. This allows users to complete the cooking preparation and execution process automatically without having to manually search for recipes or set cooking equipment parameters.

[0153] In some embodiments, after pushing the target recommended recipe determined based on the recommended recipe list to the target cooking device that executes the target recommended recipe, so that the target cooking device executes the corresponding cooking program of the target recommended recipe, the method further includes:

[0154] Obtain the actual cooking data after the target cooking device completes the cooking process;

[0155] Based on the actual cooking data, the recipe recommendation model for generating the recommended recipe list is adjusted.

[0156] Actual cooking data includes the cooking execution results and the actual cooking parameters during the cooking process. These actual cooking parameters include those obtained through user intervention during the cooking process, where the cooking equipment executes the cooking program based on the target recommended recipe. For example, if the user manually adjusts the cooking parameters or program on the equipment, changing the recommended cooking temperature from 180℃ for 40 minutes to 200℃ for 30 minutes, or if the user repeatedly skips the blanching step when cooking meat, the cooking equipment will record the actual operational parameters and send them to the intelligent agent.

[0157] Actual cooking data reflects user preferences and needs. Therefore, the recipe recommendation model that generates the recommended recipe list is adjusted based on actual cooking data. Continuing with the example of adjusting cooking temperature, when recommending similar recipes later, the model automatically generates adaptation parameters by increasing the temperature by 11% and decreasing the time by 25%, and prioritizes recommending recipes that support these parameter adjustments. For another example, based on steps skipped by the user, the agent prioritizes displaying recipes that do not include skipped steps when recommending recipes later.

[0158] In some embodiments, the cooking success rate of a target recommended recipe is fed back through the cooking execution results. Recipes with a success rate below a certain value will have their recommendation level lowered in subsequent recommendations. In other cases, based on the feedback from the cooking execution results, the recipe recommendation model is optimized. When recommending recipes in subsequent instances, the current cooking method, cooking procedure, cooking parameters, and other relevant data affecting the cooking execution results of the target recommended recipe are adjusted to ensure the suitability and reliability of the recipes recommended by the agent for the user.

[0159] In this embodiment, the recommendation logic is adjusted according to different types of actual cooking data to make ingredient management more accurate and efficient, and the recommended recipes are more in line with user preferences and meet user needs, thereby reducing waste and improving the efficiency of ingredient utilization.

[0160] Through the above embodiments, the storage device actively senses the state of the food, and the intelligent agent accurately grasps the freshness of the food based on its state information, preventing waste due to spoilage. Simultaneously, the intelligent agent determines the foods requiring priority processing based on their freshness, and, combined with information about at least one cooking device owned by the user capable of performing cooking, generates recipes suitable for the current cooking device. It then proactively pushes a list of recommended recipes to the user, reminding them to make reasonable use of soon-to-expire food and effectively reducing the probability of food being discarded due to expiration.

[0161] This specification also provides a computer program product, including an intelligent agent that, when executed by a processor, implements the food management method described above.

[0162] As an example, intelligent agents can be deployed, but are not limited to, on public cloud servers, home edge computing gateways, product applications on user terminals, and embedded chips in storage devices.

[0163] This manual also provides a food ingredient management system. Figure 3 This is an interactive diagram of a food ingredient management system provided in this manual.

[0164] The food management system includes: storage devices, cooking equipment, and an intelligent agent for implementing the food management method.

[0165] The storage device acquires the status information of the food stored inside the storage device; and sends the status information to the intelligent agent.

[0166] The intelligent agent acquires the status information of the food stored inside the storage device from the storage device; identifies the freshness of the food based on the status information, and determines the food that needs to be processed first; generates a list of recommended recipes that includes the food that needs to be processed first and is compatible with the cooking device based on the device information of the food that needs to be processed first and the user owns at least one cooking device; and pushes the target recommended recipe determined based on the recommended recipe list to the target cooking device that executes the target recommended recipe.

[0167] The target cooking device executes the cooking procedure corresponding to the target recommended recipe.

[0168] The cooking equipment mentioned in this article generally refers to kitchen appliances used in home or other environments (such as office buildings) for various purposes. Specifically, it can be cooking appliances / household appliances with a certain cooking function, such as electric pressure cookers, electric frying pans, blenders, juicers, and stir-fry machines. In addition, cooking appliances can also be multifunctional cooking appliances with various cooking functions.

[0169] The cooking equipment described in this manual has the conventional structure and functions of smart devices currently on the market (such as product casing, power interface, basic device functions, etc.), and will not be described in detail here.

[0170] The intelligent agents described in this article may include, but are not limited to, local processors deployed on user terminals, built-in computing units in storage devices, cloud servers, intelligent agent platforms, cooking equipment, etc.

[0171] In the process of pushing the target recommended recipe determined based on the recommended recipe list to the target cooking device that executes the target recommended recipe, the interaction of the user interaction unit in the food ingredient management system is involved. The user interaction unit receives information, displays the recommended recipe list, and transmits user instructions to complete the interaction between the user, the intelligent agent, and the cooking device in the food ingredient management system.

[0172] As an example, the user interaction unit includes the interaction unit of the cooking equipment or the user terminal.

[0173] When the user interaction unit is a user terminal, the food management system further includes a user terminal, used to receive a list of recommended recipes sent by the intelligent agent through the product application of the user terminal; also used to display the list of recommended recipes; and also used to obtain a target recommended recipe determined by the user and send the target recommended recipe to the intelligent agent. Specific embodiments are as follows.

[0174] Based on the above-described food management system, this description provides an embodiment of a food management method applicable to user terminal product applications.

[0175] The food ingredient management method includes the following steps 301 to 303.

[0176] Step 301: Receive a list of recommended recipes sent by the intelligent agent. The list of recommended recipes is generated by the intelligent agent based on the status information of the ingredients stored in the storage device, the freshness of the ingredients, the determination of the ingredients that need to be processed first, and the device information of at least one cooking device owned by the user. The list includes at least one recommended recipe that is compatible with the cooking device.

[0177] Step 302: Display the recommended recipe list;

[0178] Step 303: Obtain the target recommended recipe input by the user, and push the target recommended recipe to the target cooking device so that the target cooking device executes the corresponding cooking program of the target recommended recipe.

[0179] In some embodiments, the target recommended recipe has a recipe identifier. After the user terminal determines the target recommended recipe, the recipe identifier corresponding to the target recommended recipe is sent to the intelligent agent, so that the intelligent agent can determine the target recommended recipe corresponding to the recipe identifier. Subsequently, the intelligent agent pushes the target recommended recipe to the target cooking device, so that the target cooking device executes the cooking program corresponding to the target recommended recipe.

[0180] Product applications are typically installed on the user's terminal operating system. Applications can be client programs (such as apps installed on a mobile phone) or lightweight applications (such as web applications, Android quick apps, etc.). Lightweight applications can be understood as lightweight programs that do not require downloading a client application.

[0181] As an example, a user can manually open the product application installed on their terminal's operating system. Specifically, if the product client program is installed on the user's terminal, the user will typically open it manually. If the product application is not installed, the user can choose to manually download and install the product client program, or manually open the product's lightweight application.

[0182] When the intelligent agent interacts with the user terminal's product application via the network, it receives a list of recommended recipes sent by the intelligent agent. Based on the user's preferences and needs for the recommended recipes, the user selects the recommended recipe they need to use in the product application as the target recommended recipe.

[0183] In this example, the product application interface displays all recommended recipes in the recommended recipe list. Each recommended recipe is accompanied by descriptions including, but not limited to, basic recipe information, recommendation criteria (freshness of ingredients, shelf life, compatible cooking equipment, etc.), and cooking parameters. Users can determine the target recommended recipe by referring to the accompanying descriptions of each recommended recipe.

[0184] In some embodiments, obtaining the target recommended recipe input by the user includes:

[0185] A confirmation operation was detected for at least one recommended recipe in the recommended recipe list;

[0186] In response to the confirmation operation, the recommended recipe corresponding to the confirmation operation is determined as the target recommended recipe.

[0187] In one scenario, a user may directly select a specific recommended recipe from the list of recommended recipes as their target recipe.

[0188] In this scenario, the user's confirmation process for recommended recipes within the product application varies depending on the user interaction unit settings. For operations performed on the product application interface, these can include, but are not limited to, touch controls, voice commands, and gestures, providing feedback on the user's selection. For operations performed on user interaction units with physical buttons, these can include, but are not limited to, knob operations, up / down button operations, and confirmation button operations.

[0189] After the user fully confirms the operation, the user interaction unit quickly responds and locks the target recommended recipe. At the same time, it retrieves the recipe identifier corresponding to the recipe and binds the confirmation operation with the recipe identifier. This ensures that when the confirmation is sent to the agent later, the agent can accurately locate the recipe selected by the user and avoid errors caused by relying on potentially duplicate recipe names.

[0190] In other embodiments, obtaining the target recommended recipe input by the user includes:

[0191] An adjustment operation was detected for at least one recommended recipe in the recommended recipe list;

[0192] In response to the adjustment operation, the parameter adjustment interface of the recommended recipe that was interacted with is displayed;

[0193] Receive and record the adjustment information input by the user through the parameter adjustment interface, and generate the adjusted recommended recipe;

[0194] In response to the user's confirmation of the adjusted recommended recipe, the adjusted recommended recipe is determined as the target recommended recipe.

[0195] In another scenario, the recommended recipes in the recommended recipe list may not fully meet the user's needs, and the user needs to adjust the recommended recipes to use the adjusted recipes as the target recommended recipes.

[0196] In this case, when an adjustment operation is detected, the interactive unit will display a dedicated parameter adjustment interface. The content of the parameter adjustment interface includes, but is not limited to, ingredient parameters, flavor parameters, cooking parameters, quantity parameters, etc.

[0197] Different user interaction units support different operation methods. When operating on the product application interface, which includes adjustment / edit / modification options, recipe adjustments can be made through touch, voice, or gesture operations. When operating on user interaction units with physical buttons, the recipe can be selected using a knob / button, and then the physical button for adjustment can be pressed. Recipe adjustments can also be made using the device's existing physical buttons.

[0198] After the user completes the parameter adjustment on the interface, the user interaction unit needs to accurately record the adjustment information and generate a personalized version of the target recommended recipe to ensure that the modified content can be recognized and executed by the system. Understandably, the adjusted parameters need to be compatible with the user's cooking equipment to avoid cooking failures due to parameters exceeding limits.

[0199] The system will assign a new temporary identifier to the adjusted recipe (e.g., the original identifier "RC001" becomes "RC001-1") and associate it with the original recipe information and adjustment records to ensure that the intelligent agent can recognize that the target recommended recipe is a version modified from the recommended recipe after receiving it.

[0200] Once the user is satisfied with the adjusted recipe, they can confirm the target recommended recipe by clicking the confirmation button.

[0201] The target recommended recipes obtained after user adjustments reflect the user's preferences and can be used to optimize subsequent recommendations. For example, if a user cancels a step in the sugar-adding process of a recommended recipe, the agent will default to not adding sugar when recommending similar recipes in the future.

[0202] This process allows users to personalize recipe parameters based on their own needs, making the recommended recipes more suitable for their actual cooking habits, taste preferences, or scenario requirements, in addition to the recommendations from the intelligent agent.

[0203] Through the above process, after the user selects the target recommended recipe, the target recommended recipe is sent to the intelligent agent (this can be done by sending the recipe identifier corresponding to the target recommended recipe to the intelligent agent so that the intelligent agent can determine the target recommended recipe based on the recipe identifier), so that the intelligent agent can send the corresponding target recommended recipe information to the target cooking device.

[0204] In some cases, the recipe identifier is also associated with the cooking device that executes the recommended recipe. Therefore, the user terminal sends the recipe identifier of the target recommended recipe to the intelligent agent. After receiving it, the intelligent agent can directly locate the cooking device that needs to be pushed to, thereby improving cooking efficiency.

[0205] In some embodiments, after displaying the recommended recipe list, the method further includes:

[0206] In response to the user's cancellation operation on the recommended recipe list, a cancellation command is generated;

[0207] The cancellation command is sent to the agent so that the agent records the list of recommended recipes corresponding to the cancellation command and the feature parameters of each recommended recipe, so as to adjust the recipe recommendation model that generates the list of recommended recipes.

[0208] When a user is dissatisfied with the recommended recipe list, they will initiate a cancellation action. The interaction unit needs to accurately identify this action and generate a corresponding cancellation command. After generating the cancellation command, the interaction unit sends the command through a communication method matched with the agent, ensuring that the agent can fully receive and understand the user's negative intent.

[0209] After receiving a cancellation command, the agent analyzes the recommended list and the feature parameters of the recipes within it to optimize the model, avoiding types of recipes the user dislikes in the next recommendation. For the entire food management system, reducing invalid recommendations means users are more likely to choose and prioritize the use of ingredients, achieving the goal of reducing waste and increasing efficiency.

[0210] In other embodiments, when the user interaction unit is the interaction unit of a cooking device, the cooking device is configured with the same complete functions as the aforementioned product application or includes targeted functions for interaction between the product application and the intelligent agent. The specific settings can be configured according to actual needs, and may be, but are not limited to, based on factors such as manufacturing costs, interaction efficiency, and implementation methods. In this case, the cooking device provides an interface displaying a list of recommended recipes, with each recommended recipe accompanied by a recipe description. The user selects a target recommended recipe based on the descriptions of each recommended recipe in the list.

[0211] Specifically, the interaction unit of the cooking equipment receives and displays the recommended recipe list; based on the recommended recipe list, it obtains the target recommended recipe input by the user.

[0212] As an example, in a scheme where the user confirms the recipe, similar to using the product application on the user's terminal as the user interaction unit, the method of obtaining the target recommended recipe input by the user includes the following two methods.

[0213] One approach is that if a user finds a recipe suitable for the current recommendation, the user can directly select a specific recipe from the list of recommended recipes as their target recipe.

[0214] In this case, obtaining the target recommended recipe input by the user includes: the cooking device detecting a confirmation operation for at least one recommended recipe in the recommended recipe list; and in response to the confirmation operation, determining that the recommended recipe corresponding to the confirmation operation is the target recommended recipe.

[0215] Another approach is that if the recommended recipes in the recommended recipe list cannot fully meet the user's needs, the user needs to adjust the recommended recipes to use as the target recommended recipes.

[0216] In this case, obtaining the target recommended recipe input by the user includes: the cooking device detecting an adjustment operation for at least one recommended recipe in the recommended recipe list; in response to the adjustment operation, displaying a parameter adjustment interface for the interacted recommended recipe; receiving and recording the adjustment information input by the user through the parameter adjustment interface, and generating an adjusted recommended recipe; and in response to the user's confirmation operation on the adjusted recommended recipe, determining the adjusted recommended recipe as the target recommended recipe.

[0217] In this way, when the smart agent interacts with the cooking equipment over the network, the user can select the desired recommended recipe in the product application according to their own needs.

[0218] The cooking equipment used for user confirmation can be selected based on actual needs, including but not limited to cooking equipment that is closest to the user, adapted to the best recommended recipe, has the same complete functions as the above-mentioned product applications, or includes targeted functions for interaction between the product applications and the intelligent agent, and is easy to operate.

[0219] In this embodiment, the user confirms the target recommended recipe on the cooking device. By selecting the target recommended recipe and obtaining cooking information on the cooking device, not only is information association and collaborative work established between the storage device, the intelligent agent and the cooking device, improving the efficiency of food management, but also the problem of discarding expired and uneaten food is solved.

[0220] After determining the target recommended recipe, the intelligent agent sends the corresponding cooking parameters, cooking program, and other information to the cooking device based on the recipe identifier of the selected target recommended recipe. The cooking device acquires the target recommended recipe; based on the information of the target recommended recipe and the device information, it sets the corresponding cooking program; and executes the cooking program.

[0221] Before executing the cooking program, the method further includes: detecting an interactive operation on at least one cooking parameter button in the cooking device; in response to the interactive operation, adjusting the current cooking program based on information of the cooking parameters corresponding to the interactive operation; and executing the adjusted cooking program.

[0222] Specifically, when cooking-related information does not match the user's needs, the user can temporarily adjust the parameters by directly operating the device's parameter buttons before the cooking equipment executes the program. Upon detecting this interaction, the cooking equipment will immediately update and modify the preset cooking program to ensure that the adjusted parameters match the user's expectations. Figure 1 The cooking process must be consistent with the equipment's operating logic. After the cooking equipment completes parameter adjustments, the modified cooking program is executed to ensure that the final cooking result meets the user's real-time expectations.

[0223] Of course, users can still modify relevant parameters while the cooking device is executing its program, and the device will continue from the current point. Simultaneously, the device will record the adjusted parameters as actual cooking data and synchronize it to the intelligent agent to optimize future recipe recommendations.

[0224] Through the above embodiments, information association and collaborative work are established between the storage device and the cooking equipment. The target recommended recipe is pushed to the target cooking equipment that is compatible with it. The equipment can automatically execute the corresponding cooking program according to the target recommended recipe to complete the cooking. In this process, the user does not need to manually search for recipes and set cooking parameters, which improves cooking efficiency and provides users with a convenient and intelligent cooking experience.

[0225] This specification also discloses a storage device for implementing the food management method described above.

[0226] Figure 4 This is a schematic diagram of a computer-readable storage medium 140 provided in this disclosure, on which a computer program is stored, which, when executed by a processor, implements the method of any embodiment of this disclosure.

[0227] This disclosure also provides a computing device, including a memory and a processor; the memory is used to store computer instructions that can be executed on the processor, and the processor is used to implement the methods of any embodiment of this disclosure when executing the computer instructions.

[0228] Figure 5 This is a schematic diagram of the structure of a computing device provided in this disclosure, such as... Figure 5 As shown, the computing device 15 may include, but is not limited to: a processor 151, a memory 152, and a bus 153 connecting different system components (including the memory 152 and the processor 151).

[0229] The memory 152 stores computer instructions that can be executed by the processor 151, enabling the processor 151 to perform the training method of the aesthetic image generation model according to any embodiment of this disclosure. The memory 152 may include a random access memory unit (RAM) 1521, a cache memory unit (Cache) 1522, and / or a read-only memory unit (ROM) 1523. The memory 152 may also include a program tool 1525 having a set of program modules 1524, including but not limited to: an operating system, one or more application programs, other program modules, and program data. One or more combinations of these program modules may include an implementation of a network environment.

[0230] Bus 153 may include, for example, a data bus, an address bus, and a control bus. The computing device 15 can also communicate with external devices 155 via I / O interface 154, such as a keyboard or a Bluetooth device. The computing device 15 can also communicate with one or more networks via network adapter 156, such as a local area network (LAN), a wide area network (WAN), or a public network. As shown in the figure, the network adapter 156 can also communicate with other modules of the computing device 15 via bus 153.

[0231] Furthermore, although the operations of the methods disclosed herein are described in a specific order in the accompanying drawings, this does not require or imply that these operations must be performed in that specific order, or that all of the operations shown must be performed to achieve the desired result. Additionally or alternatively, certain steps may be omitted, multiple steps may be combined into one step, and / or one step may be broken down into multiple steps.

[0232] While the spirit and principles of this disclosure have been described with reference to several specific embodiments, it should be understood that this disclosure is not limited to the disclosed specific embodiments, and the division of aspects does not imply that features in these aspects cannot be combined for benefit; such division is merely for convenience of expression. This disclosure is intended to cover various modifications and equivalent arrangements included within the spirit and scope of the appended claims.

Claims

1. A method for managing food ingredients, characterized in that, The method includes: Obtain the status information of the food stored inside the storage device sent by the storage device; Based on the status information, the freshness of the ingredients is identified, and the ingredients that need to be processed first are determined. Based on the ingredients that need to be prioritized and the equipment information of at least one cooking device owned by the user, a list of recommended recipes is generated that includes the ingredients that need to be prioritized and is compatible with the cooking device. The target recommended recipe determined based on the recommended recipe list is pushed to the target cooking device that executes the target recommended recipe, so that the target cooking device executes the corresponding cooking program of the target recommended recipe.

2. The food ingredient management method as described in claim 1, characterized in that, The target recommended recipe is determined through a user interaction unit; the method further includes: The recommended recipe list is pushed to the user interaction unit so that the user can select a target recommended recipe from the recommended recipe list; The system receives the target recommended recipe sent by the user interaction unit, and adjusts the recipe recommendation model that generates the recommended recipe list based on the target recommended recipe.

3. The food ingredient management method as described in claim 2, characterized in that, The user interaction unit is the interaction unit or user terminal of the cooking equipment.

4. The food ingredient management method as described in claim 2, characterized in that, After pushing the recommended recipe list to the user interaction unit, the method further includes: The system receives a cancellation command sent by the user interaction unit, records the recommended recipe list corresponding to the cancellation command and the feature parameters of each recommended recipe, and adjusts the recipe recommendation model that generates the recommended recipe list.

5. The food ingredient management method as described in claim 1, characterized in that, After pushing the target recommended recipe determined based on the recommended recipe list to the target cooking device that executes the target recommended recipe, so that the target cooking device executes the corresponding cooking program of the target recommended recipe, the method further includes: Obtain the actual cooking data after the target cooking device completes the cooking process; Based on the actual cooking data, the recipe recommendation model for generating the recommended recipe list is adjusted.

6. The food ingredient management method as described in claim 1, characterized in that, Applied to intelligent agents.

7. A method for managing food ingredients, characterized in that, Applied to a storage device, the method includes: Obtain the status information of the food stored inside the storage device; The status information is sent to the intelligent agent so that the intelligent agent can execute the food management method as described in any one of claims 1 to 5.

8. The food ingredient management method as described in claim 7, characterized in that, The storage device includes a sensing module; The process of obtaining the status information of the food stored inside the storage device includes: When the triggering condition is met, the sensing module obtains the status information of the food stored inside the storage device. The triggering condition includes at least one of the following: The current time has reached a preset time periodic node; Respond to user interaction with the storage device; The internal food or environmental conditions of the storage device undergo dynamic changes.

9. The food ingredient management method as described in claim 7, characterized in that, The storage device also includes a communication module for sending the status information to the intelligent agent.

10. A food ingredient management system, characterized in that, The system includes: A storage device is used to acquire the status information of the food stored inside the storage device and send the status information to the intelligent agent. An intelligent agent is used to implement the food management method as described in any one of claims 1 to 5; The user terminal is used to receive a list of recommended recipes sent by the intelligent agent through the product application of the user terminal; it is also used to display the list of recommended recipes; it is also used to obtain the target recommended recipe confirmed by the user and feed it back to the intelligent agent, and at the same time send the target recommended recipe to the cooking device. A cooking device for executing the cooking procedure corresponding to the target recommended recipe.

Images