Diet plan scheme recommendation method, storage medium and intelligent equipment

Abstract

The invention discloses a diet plan scheme recommendation method, a storage medium and intelligent equipment, and relates to the technical field of smart home, the method comprises the following steps: obtaining user input content, the user input content is multi-modal data including at least one of voice description, health documents, recorded videos, personal photos and input characters, and the user input content is the multi-modal data of at least one of the voice description, the health documents, the recorded videos, the personal photos and the input characters; and analyzing the user input content based on the vertical domain model to obtain user health demand information, generating at least one diet plan scheme according to the user health demand information, and pushing the diet plan scheme to the user side. Thus, the user input information of multiple modes is obtained, and the user input content is analyzed based on the vertical domain model, so that the user health demand information can be obtained more accurately and comprehensively, and then the diet plan scheme is generated. In this way, the diet plan scheme customized for the user can better conform to the diet preference and physical condition of the user, and various personalized requirements of the user for the healthy diet plan scheme can be met.

Description

Technical Field

[0001] The present application relates to the field of smart homes. Specifically, it relates to a method for recommending a diet plan, a storage medium, and a smart device. Background Art

[0002] The application of smart diet in the home is developing rapidly, showing broad market prospects and great development potential. Smart diet, as a new type of catering model, through the integration of intelligent devices and management software, realizes the digital transformation and intelligent upgrade of all links of healthy diet recommendation, and can combine the user's diet preferences, health status and nutritional needs in daily home life to provide functions such as personalized diet suggestions, helping users achieve scientific diet and promoting physical health.

[0003] The realization of smart diet in the current technology requires manual input or linkage with relevant devices to obtain personal or family health information, with high input costs and time-consuming, and there is a certain degree of inaccuracy in the data. Moreover, the diet plan is set according to an existing fixed database. For the same weight loss or diet needs, the set diet plan is too single and cannot be set according to the user's personal needs, with poor flexibility. Finally, each update of the industry's diet plan requires manual update and real-time update of user information to set the diet plan according to user needs. To sum up, the existing technology cannot effectively provide users with diet technology that is updated in real time and meets the personalized needs of users, resulting in a poor user experience. Summary of the Invention

[0004] The present application aims to solve the above technical problems, that is, to solve the problem that the existing technology cannot effectively provide users with diet technology that meets the personalized needs of users and is updated in real time, resulting in a poor user experience.

[0005] In a first aspect, the present application provides a method for recommending smart diet, including:

[0006] Obtain user input content, where the user input content is multimodal data including at least one of voice description, health document, recorded video, personal photo, and input text;

[0007] Analyze the user input content based on a pre-trained vertical domain model to obtain user health requirement information;

[0008] Generate at least one diet plan according to the user health requirement information and push the diet plan to the user side.

[0009] In one technical solution of the above-mentioned dietary plan recommendation method, the user input content includes at least two of voice description, health document, recorded video, personal photo, and input text;

[0010] The obtaining of the user's health requirement information includes:

[0011] Based on the multi-modal capabilities of the vertical domain model, the user input content is processed for information and data fusion to obtain the user's health requirement information;

[0012] Among them, the user's health requirement information includes at least one of user's physical diagnosis information, user's dietary taboos, user's exercise plan, user's required dietary content, and user's work and rest time.

[0013] In one technical solution of the above-mentioned dietary plan recommendation method, the generating of at least one dietary plan according to the user's health requirement information includes:

[0014] According to at least one of the user's physical diagnosis information, user's dietary taboos, user's exercise plan, user's required dietary content, and user's work and rest time, at least one dietary plan is generated, where the dietary plan is a dietary arrangement made according to the user's physical condition and nutritional needs.

[0015] In one technical solution of the above-mentioned dietary plan recommendation method, after the dietary plan is pushed to the user side, the method further includes:

[0016] In response to the user modification instruction received by the user side, new user input content is obtained;

[0017] Combined with the generated dietary plan, the user's health requirement information is updated according to the new user input content;

[0018] Based on the vertical domain model, at least one new dietary plan is regenerated according to the updated user's health requirement information.

[0019] In one technical solution of the above-mentioned dietary plan recommendation method, after the dietary plan is pushed to the user side, the method further includes:

[0020] According to the preset period, the dietary plan is updated regularly, and the preset period is a time period set in advance for regularly updating the dietary plan.

[0021] In one technical solution of the above-mentioned dietary plan recommendation method, the regular update of the dietary plan includes:

[0022] For each of the preset cycles, obtain the current user input content in real time and determine whether the user input content has changed;

[0023] If it has changed, based on the vertical domain model, update the user's health requirement information according to the current user input content;

[0024] Adjust the diet plan according to the updated user health requirement information to obtain an updated diet plan;

[0025] If it has not changed, update the diet plan according to the existing user health requirement information.

[0026] In a technical solution of the above diet plan recommendation method, the obtaining of the user input content in multimodal format includes:

[0027] Obtain the user's voice description through the microphone device of the user terminal, where the voice description is used to describe at least one of the user's weight, height, gender, diet preference, and diet taboos; and / or,

[0028] Obtain the health documents uploaded by the user, where the health documents include at least one of the user's physical examination reports, imaging reports, and hospital test reports; and / or,

[0029] Obtain the recorded video or personal photos of the user, where the personal photos include at least one of full-body photos, half-body photos, and partial photos; and / or,

[0030] Display an information collection form to the user through the display device of the user terminal to obtain the input text of the user, where the input text is the text input by the user when filling in the information collection form according to their own health conditions.

[0031] In a technical solution of the above diet plan recommendation method, the generating of at least one diet plan according to the user health requirement information includes:

[0032] Based on the associated database, generate a user health analysis report according to the user health requirement information, where the user health analysis report includes at least one diet plan;

[0033] The associated database includes at least one of a medical database, an ingredient database, a health preservation database, and a diet database;

[0034] Pushing the diet plan to the user terminal includes:

[0035] Perform readability typesetting on the user health analysis report and perform visual display through the user terminal.

[0036] In a second aspect, a computer-readable storage medium is provided, in which a program is stored, and the program is adapted to be loaded and run by a processor to execute the diet plan recommendation method described in any one of the technical solutions of the above diet plan recommendation method.

[0037] In a third aspect, an intelligent device is provided, which includes at least one processor and at least one memory. The memory is adapted to store multiple computer programs, and the computer programs are adapted to be loaded and run by the processor to execute the diet plan recommendation method described in any one of the technical solutions of the above diet plan recommendation method.

[0038] One or more of the above technical solutions of the present application have at least one or more of the following beneficial effects:

[0039] In the case of adopting the above technical solution, the present application provides a diet plan recommendation method, including: obtaining user input content, where the user input content is multimodal data including at least one of voice description, health document, recorded video, personal photo, and input text; analyzing the user input content based on a pre-trained vertical domain model to obtain user health requirement information; generating at least one diet plan based on the user health requirement information, and pushing the diet plan to the user terminal. Through the above configuration method, the present application can obtain multi-modal user input information, and comprehensively analyze the multi-modal user input content based on the multi-modal capabilities of the vertical domain model, and can more accurately and comprehensively analyze and obtain user health requirement information, and then generate at least one diet plan based on the user health requirement information and push it to the user terminal for display to the user. In this way, the generated diet plan can better conform to the user's dietary preferences and physical conditions, realizing customized for the user, and can meet various personalized needs of the user for a healthy diet plan.

[0040] Secondly, the user can also change the existing diet plan at any time by inputting a user interaction instruction on the user terminal to add new user input content, which can more closely match the user's demand changes to generate or update the diet plan, improving the flexibility of the diet plan and meeting the user's diet plan customization needs in different application scenarios. Finally, the diet plan can be updated regularly through a preset period, without manual data update, and combined with the real-time data capture ability of the vertical domain model to realize the regular update of the diet plan, which can provide the user with a rich variety of diet plans, ensure the timeliness and accuracy of the diet plan, and enhance the user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The accompanying drawings here are incorporated into the specification and form a part of this specification, showing embodiments consistent with this application, and are used together with the specification to explain the principles of this application.

[0042] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the following will briefly introduce the accompanying drawings required for use in the description of the embodiments or the prior art. Obviously, for those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0043] Figure 1 It is a schematic diagram of the main steps of a diet plan recommendation method according to an embodiment of this application;

[0044] Figure 2 It is a schematic diagram of the main steps of obtaining user input content in a multimodal format in an embodiment of this application;

[0045] Figure 3 It is a schematic diagram of the main steps of a diet plan recommendation method in an embodiment of this application;

[0046] Figure 4 It is a schematic diagram of the hardware environment composed of the device side 102 and the cloud side 104 according to an embodiment of this application. Detailed implementation manners

[0047] To enable those skilled in the art of this technology to better understand the solutions of this application, the following will clearly and completely describe the technical solutions in the embodiments of this application in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are only a part of the embodiments of this application, rather than all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative efforts should fall within the scope of protection of this application.

[0048] It should be noted that the terms "first", "second", etc. in the specification, claims and the above accompanying drawings of this application are used to distinguish similar objects, and do not necessarily need to describe a specific order or sequence. It should be understood that such used data can be interchanged under appropriate circumstances so that the embodiments of this application described here can be implemented in an order other than those illustrated or described here. In addition, the terms "include" and "have" and any variations thereof are intended to cover non-exclusive inclusion. For example, a process, method, system, product or device including a series of steps or units does not necessarily have to be limited to those clearly listed steps or units, but may include other steps or units not clearly listed or inherent to these processes, methods, products or devices.

[0049] According to one aspect of the embodiments of the present application, a method for recommending a diet plan is provided. Refer to the appendix Figure 1 , Figure 1 is a schematic flowchart of the main steps of the method for recommending a diet plan according to an embodiment of the present application. As Figure 1 shown, the method for recommending a diet plan includes steps S101 - S103:

[0050] Step S101: Obtain user input content.

[0051] In this embodiment, the diet plan refers to a set of scientific and healthy diet arrangements formulated according to personal health conditions, nutritional needs, and living habits. The diet arrangements usually can include the food combinations for three meals a day, the amount of calories and nutrients ingested per meal or per day, as well as information such as diet and rest time, etc.

[0052] Among them, the user input content is multimodal data including at least one type of data such as voice description, health document, recorded video, personal photo, and input text. In some other implementation manners, user data stored in the devices connected to the smart home system can also be automatically collected as the user input content. For example, the user data can include data such as user weight, body fat percentage, blood sugar, or blood pressure.

[0053] In one implementation manner, refer to the appendix Figure 2 , Figure 2 is a schematic flowchart of the main steps for obtaining user input content in multimodal format in an embodiment of the present application. As Figure 2 shown, step S101 can include at least one of the following steps:

[0054] Step S1011: Obtain the voice description of the user through the microphone device of the user terminal.

[0055] Among them, the voice description can be used to describe at least one piece of information such as the user's weight, height, gender, diet preference, and diet taboos.

[0056] In this implementation manner, the user terminal can be a client in the smart home, such as a remote control program software installed on a mobile device, a smart home platform, a smart wearable device, a smart TV, and other terminals.

[0057] In one implementation manner, the voice of the user can be collected through the microphone device, and natural language processing technology can be used to convert the voice into text and analyze the voice content information, extract information such as the user's weight, height, gender, diet preference, and diet taboos, and generate the final voice description.

[0058] Step S1012: Obtain the health document uploaded by the user.

[0059] Among them, the health documents include at least one of the user's physical examination reports, imaging reports, and hospital test reports.

[0060] In one implementation, the user can directly upload the health documents to the cloud server through the network medium on the mobile user terminal, so that the cloud server can input the health documents into the vertical domain model.

[0061] Step S1013: Obtain the user's recorded video or personal photo.

[0062] Among them, the personal photo can be an image used to obtain the user's status, and can include at least one of a full-body photo, a half-body photo, and a partial photo. The recorded video can be an image used to obtain the user's current appearance and physical behavior, and can include the user's exercise video or the user's full-body video, etc.

[0063] In one implementation, the human body features in the video can be analyzed through video analysis technology to infer information such as the health status and exercise habits of the user terminal.

[0064] Step S1014: Display an information collection form to the user through the display device of the user terminal to obtain the user's input text.

[0065] Among them, the input text is the text input by the user on the user terminal according to their own health condition.

[0066] In this implementation, the information collection form can be used to collect information such as the user's physical data, eating habits, and dietary taboos. Therefore, the input text can include information such as personal physical condition, weight, height, gender, taste preference, and dietary taboos.

[0067] In other implementations, it is also possible to directly obtain the user's input text through the text input box in the user terminal without using the information collection form, which does not affect the normal implementation of this implementation.

[0068] Step S102: Analyze the user input content based on the pre-trained vertical domain model to obtain the user's health requirement information.

[0069] In this embodiment, the vertical domain model refers to a large language model trained and optimized in a specific field or industry. Among them, usually a general large model can be used as the basic model, combined with the domain knowledge of a specific field or industry (in this embodiment, the domain knowledge can be dietary data such as dietary taboos, eating tastes, and healthy cooking knowledge), and the final vertical domain model is obtained after training and optimization. Due to its ability to provide more professional and accurate answers to problems in a specific field, the vertical domain model has stronger practicality in the application scenario of providing dietary technical solutions for users.

[0070] In one embodiment, the vertical domain model can be a large artificial intelligence model (AI large model). Among them, the large artificial intelligence model refers to a deep learning model with huge parameters and complex structures, which is usually used to process large-scale data and generate highly accurate predictions and results.

[0071] In one embodiment, an initial AI large model can be constructed based on the architecture of the Transformer Model first; then, a large amount of high-quality recipe data, the nutritional value of different food combinations in the nutrition database, the impact of different cooking forms on the taste of ingredients, and food calories and other data are obtained as training data to train the initial AI large model. In this way, the algorithm model of the AI large model will, based on machine learning and deep learning technologies, through the analysis of the training data, learn how to calculate the daily required calories according to the user's weight and height, and recommend corresponding ingredients and cooking methods according to the user's health status and taste preferences; finally, the model is dynamically adjusted and optimized continuously according to the user's diet plan history records and feedback to obtain the final AI large model.

[0072] In one embodiment, the user input content can be multi-modal data, that is, the user input content needs to include at least two of voice description, health documents, recorded videos, personal photos, and input text.

[0073] In this embodiment, obtaining the user's health requirement information may include:

[0074] Step S1021: Based on the multi-modal capabilities of the vertical domain model, perform information processing and data fusion on the user input content to obtain the user's health requirement information.

[0075] Among them, the user's health requirement information includes at least one of the user's physical diagnosis information, the user's diet taboos, the user's exercise plan, the user's required diet content, and the user's work and rest time.

[0076] In one embodiment, performing information processing and data fusion on the user input content may include: synchronously performing data processing and information analysis on text, images, videos, and voices, and fusing the processing and analysis results of text, images, videos, and voices to obtain the user's health requirement information.

[0077] In this embodiment, information fusion can be performed at multiple levels, including the feature level, the model level, and the decision level. In this way, fusing the user input content of multiple modalities such as images, voices, and texts can improve the understanding and processing capabilities of the AI large model, enabling it to more accurately extract the user's health requirement information and customize a diet plan for the user.

[0078] Step S103: Generate at least one diet plan according to the user's health requirement information and push the diet plan to the user terminal.

[0079] In this embodiment, the user's health requirement information includes one or more of the user's physical diagnosis information, user's diet taboos, user's exercise plan, user's required diet content, and user's work and rest time.

[0080] In one embodiment, step S103 may further include:

[0081] Step S1031: Generate at least one diet plan according to at least one of the user's physical diagnosis information, user's diet taboos, user's exercise plan, user's required diet content, and user's work and rest time.

[0082] Wherein, the diet plan is a diet arrangement made according to the user's physical condition and nutritional needs.

[0083] In one embodiment, generating at least one diet plan according to the user's health requirement information may include:

[0084] Based on the associated database, generate a user health analysis report according to the user's health requirement information, and the user health analysis report includes at least one diet plan.

[0085] In this embodiment, the associated database includes at least one of a medical database, an ingredient database, a health preservation database, and a diet database.

[0086] Among them, the medical database may include data such as drug data, disease data, diagnosis data, and medical history materials, etc.; the ingredient database may contain information such as the name, ingredients, nutritional components, cooking methods, applicable populations, and usage precautions of ingredients; the health preservation database may contain data such as the nutritional components and health benefits of different foods, the formula and its health benefits of medicated diets, and diet health advice data, etc.; the diet database may contain data such as the nutritional component data of foods, applicable meal types (such as breakfast, lunch, dinner), and calorie intake, etc.

[0087] In this embodiment, the user health analysis report can be automatically generated by the AI large model connected to the associated database according to the user's health requirement information.

[0088] In one embodiment, pushing the diet plan to the user terminal may include:

[0089] Perform readability typesetting on the user health analysis report and perform visual display through the user terminal.

[0090] In this embodiment, the user health analysis report may include a summary of the user's current physical condition, dietary taboos, exercise plan, diet plan, and other health-related suggestions.

[0091] In one embodiment, after step S103, the method may further include:

[0092] Step S1041: In response to a user modification instruction received by the user terminal, obtain the newly added user input content;

[0093] Step S1042: Combine the generated diet plan and update the user's health requirement information according to the newly added user input content;

[0094] Step S1043: Based on the vertical domain model, regenerate at least one new diet plan according to the updated user health requirement information.

[0095] In this embodiment, the user can view the final user health analysis report on the user terminal, modify the user input content at any time according to their own needs, thereby changing the user health requirement information, and correspondingly changing the user health analysis report and the diet plan in the user health analysis report.

[0096] In one embodiment, the user can also preset a time to regularly update the diet plan pushed to the user terminal.

[0097] In this embodiment, after the diet plan is pushed to the user terminal, the method further includes: regularly updating the diet plan according to a preset cycle.

[0098] In this embodiment, the preset cycle is a time cycle preset for regularly updating the diet plan.

[0099] In one embodiment, regularly updating the diet plan may specifically include:

[0100] Step S1051: For each preset cycle, obtain the current user input content in real time and determine whether the user input content has changed. If it has changed, go to steps S1053 - S1054; if it has not changed, go to step S1052.

[0101] Step S1052: Update the diet plan according to the existing user health requirement information.

[0102] Step S1053: If it has changed, update the user health requirement information based on the vertical domain model according to the current user input content.

[0103] Step S1054: Adjust the diet plan according to the updated user health requirement information to obtain the updated diet plan.

[0104] In this embodiment, the vertical domain model can also be associated with a network engine to search for the latest healthy diet data, so as to realize the timely update of the diet plan, thereby ensuring that the diet plan is more scientific and more in line with the current seasonal climate, and improving the timeliness of the diet plan.

[0105] In one embodiment, reference can be made to the appendix Figure 3 , Figure 3 which is a schematic diagram of the main steps of a diet plan recommendation method according to an embodiment of the present application. As Figure 3 shown, the diet plan recommendation method may include steps S201 - S206:

[0106] Step S201: Receive the user input content through the device end, and enter step S202 after the reception operation is completed.

[0107] In this embodiment, the user input content may include text descriptions, personal pictures, video information, audio information, as well as personal physical examination reports, test sheets, and other medical imaging reports, such as X - ray films. Among them, the text description may include information such as personal physical condition, weight, height, gender, taste preferences, and diet taboos. The video information may include information such as a full - body display of the personal body, personal physical condition, height, gender, taste preferences, and diet taboos. The audio information may include information such as personal physical condition, weight, height, gender, taste preferences, and diet taboos.

[0108] In this embodiment, the device end can be various smart devices in the smart home, and execute specific diet plan recommendation functions or tasks through various programs or software installed or saved on it.

[0109] Step S202: Upload the user input content received by the device end to the cloud, so that the cloud executes step S203.

[0110] In one embodiment, the device end and the cloud can be communicatively connected to realize data transmission between the device and the cloud.

[0111] In this embodiment, the cloud can be the cloud server of the smart home, that is, a smart home system based on cloud computing, which is a server used to realize remote control, efficient data processing, and interconnection and interoperability between smart devices.

[0112] Step S203: Input the user input content into the AI large - model, so that the AI large - model executes step S204.

[0113] In this embodiment, the AI large - model is a specific vertical domain model in the above - mentioned embodiment.

[0114] In this embodiment, the AI large model can be a text generation deep learning model (Generative Pre-Trained Transformer, GPT model). The GPT model is a deep learning model trained based on Internet data. It can generate coherent and natural text through pre-training and fine-tuning of model parameters, and is widely used in the field of natural language processing.

[0115] In one embodiment, the user input content can be input into the AI large model through an Application Programming Interface (API interface).

[0116] Step S204: The AI large model performs multimodal processing on the user input content and returns the processing result to the cloud, so that the cloud executes step S205.

[0117] In one embodiment, the AI large model can process and fuse multimodal user input content, and combine knowledge food ingredients, medical, health, and health preservation databases across the network to output corresponding diet plan solutions.

[0118] In one embodiment, as Figure 3 shown, the processing result of the AI large model can include a summary of the user's current situation, dietary taboos, diet plans, exercise plans, and other suggestions. Among them, the summary of the current situation can include information such as the user's height and weight, blood conditions, whether there are latent diseases, whether they are obese, whether there are current diseases, how to treat the diseases, what to pay attention to, and how to relieve them; dietary taboos can include the foods suitable for the user, the foods not suitable for the user, suitable food combinations, and prohibited food combinations; diet plans can include the update cycle of each diet plan, what the diet content of breakfast / lunch / dinner is, and how long the diet ratio cycle of each meal is, etc.; exercise plans can include the exercise items suitable for the user, the appropriate exercise duration, and video tutorials of the exercise items; other suggestions can include information such as the user's drinking water or rest time and other health suggestions.

[0119] Step S205: The cloud obtains the output report of the AI large model and transmits the output report to the device side, so that the device side executes step S206.

[0120] In this embodiment, the AI large model can summarize the user's current situation summary, dietary taboos, diet plans, exercise plans, and other suggestions output, and form an output report to output to the cloud.

[0121] Step S206: Format the output report into readable information and push it to the user.

[0122] In this embodiment, the cloud can transmit the output report to the device end through the communication network, and the device end formats the output report to form a readability report for visual display.

[0123] Therefore, users can obtain automatically generated diet plans by inputting information in different modes. The operation is simple and can be used by various groups of people and various industries, such as the medical industry, fitness industry, consulting industry or housekeeping industry, etc., with a wide range of application scenarios.

[0124] In one implementation, the user can also add new user input content according to his / her own changing needs. Figure 3 As shown, after step S206, the method may further include steps S207 to S209:

[0125] Step S207: Receive and add the user's new demand information through the device end.

[0126] In this embodiment, the user can add new user input content, which will be acquired and analyzed by the device to obtain the user's new demand information. The user can also directly modify the current status summary in the visualized readability report and upload the modified content directly to the cloud. The user can also use other methods to input their own new demand information, which will not affect the normal implementation of the embodiments of the present application.

[0127] Step S208: New user requirements are formed in combination with the output report, and the new user requirements are saved to the cloud, so that the cloud executes step S209.

[0128] In this embodiment, the output report can be an existing output report saved in the cloud or the device. In some other embodiments, new user needs can be formed by the device or the cloud, which does not affect the normal implementation of the embodiment of the present application.

[0129] Step S209: The cloud inputs the user demand into the GPT big model and outputs a new report.

[0130] In one implementation, the user may also set an update cycle to regularly update the output report and regenerate the diet plan in the report to ensure the timeliness and accuracy of the diet plan.

[0131] In one embodiment, the above-mentioned diet plan recommendation method can be widely used in smart home (Smart Home), smart home, smart home device ecology, smart residential (Intelligence House) ecology and other whole-house intelligent digital control application scenarios.

[0132] Optionally, the above-mentioned dietary plan recommendation method can be applied toFigure 4 In the hardware environment composed of the device side 102 and the cloud side 104 as shown. As Figure 4 shown, the cloud side 104 is connected to the device side 102 through a network, and can be used to provide services (such as application services, etc.) for the terminal or the client installed on the terminal. A database can be set up on the server or independently of the server to provide data storage services for the cloud side 104. Cloud computing and / or edge computing services can be configured on the server or independently of the server to provide data operation services for the cloud side 104.

[0133] The above network can include but is not limited to at least one of the following: wired network, wireless network. The above wired network can include but is not limited to at least one of the following: wide area network, metropolitan area network, local area network. The above wireless network can include but is not limited to at least one of the following: WIFI (Wireless Fidelity), Bluetooth. The device side 102 is not limited to being a PC, mobile phone, tablet computer, smart refrigerator, smart oven, smart stove, smart projection device, smart TV, smart audio and video, smart speaker, smart kitchen and bathroom device, smart air purification device, smart steam box, smart microwave oven, smart kitchen water heater, smart purifier, smart water dispenser, smart door lock, etc.

[0134] Through the above configuration method, the present application can obtain multi-modal user input information and comprehensively analyze the multi-modal user input content based on the multi-modal capabilities of the vertical domain model, and can more accurately and comprehensively analyze and obtain the user's health needs information. Then, at least one diet plan is generated according to the user's health needs information and pushed to the user side for display to the user. In this way, the generated diet plan can better conform to the user's diet preferences and physical conditions, customize the diet plan for the user, and can meet the various personalized needs of the user for a healthy diet plan.

[0135] Secondly, the user can also change the existing diet plan at any time by inputting a user interaction instruction on the user side and adding new user input content, which can generate or update the diet plan more in line with the user's demand changes, improve the flexibility of the diet plan, and meet the user's diet plan customization needs in different application scenarios. Finally, the diet plan can be updated regularly through a preset period, without manual data update, and the real-time data capture ability of the vertical domain model is combined to realize the regular update of the diet plan, which can provide rich and diverse diet plans for the user, ensure the timeliness and accuracy of the diet plan, and enhance the user experience.

[0136] It should be noted that although the above embodiments describe the various steps in a specific order, those skilled in the art can understand that, in order to achieve the effects of the present application, it is not necessary for different steps to be executed in such an order. They can be executed simultaneously (in parallel) or in other orders, and these variations are all within the protection scope of the present application.

[0137] Those skilled in the art can understand that all or part of the processes in the method of the above-described embodiment of the present application can also be completed by instructing relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-described method embodiments can be implemented. Among them, the computer program includes computer program code, and the computer program code can be in the form of source code, object code, executable file or some intermediate form, etc. The computer-readable storage medium can include: any entity or device, medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electrical carrier signal, telecommunication signal, and software distribution medium that can carry the computer program code.

[0138] On the other hand, the present application also provides an intelligent device. In an embodiment of the intelligent device according to the present application, the intelligent device may include a memory and a processor. A computer program is stored in the memory, and the processor is configured to execute the diet plan recommendation method in the above-described diet plan recommendation method embodiment of the method through the computer program.

[0139] Furthermore, the present application also provides a computer-readable storage medium. In an embodiment of the computer-readable storage medium according to the present application, the computer-readable storage medium can be configured to store a program for executing the diet plan recommendation method in the intelligent device of the above-described method embodiment. The program can be loaded and run by a processor to implement the diet plan recommendation method in the above-described intelligent device. For the sake of convenience of description, only the parts related to the embodiments of the present application are shown. For the specific technical details not disclosed, please refer to the method part of the embodiments of the present application. The computer-readable storage medium can be a memory device formed by various electronic devices. Optionally, the computer-readable storage medium in the embodiments of the present application is a non-transitory computer-readable storage medium.

[0140] Furthermore, it should be understood that since the setting of each module is only for explaining the functional units of the device of the present application, the corresponding physical devices of these modules can be the processor itself, or a part of the software in the processor, a part of the hardware, or a part of the combination of software and hardware. Therefore, the number of each module in the figure is only illustrative.

[0141] Those skilled in the art can understand that the various modules in the device can be adaptively split or combined. Such splitting or combining of specific modules does not cause the technical solution to deviate from the principle of the present application. Therefore, the technical solutions after splitting or combining will all fall within the protection scope of the present application.

[0142] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as within the protection scope of the present application.

[0143] So far, the technical solutions of the present application have been described in conjunction with the preferred embodiments shown in the drawings. However, those skilled in the art can easily understand that the protection scope of the present application is obviously not limited to these specific embodiments. Without departing from the principle of the present application, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will all fall within the protection scope of the present application.

[0144] The above are only the preferred embodiments of the present application. It should be noted that for those of ordinary skill in the art, without departing from the principle of the present application, several improvements and refinements can be made, and these improvements and refinements should also be regarded as within the protection scope of the present application.

Claims

1. A method for recommending a diet plan, characterized in that: include: Acquiring user input content, wherein the user input content is multimodal data including at least one of voice description, health document, recorded video, personal photo and input text; Analyze the user input content based on the pre-trained vertical domain model to obtain user health demand information; At least one diet plan is generated according to the user health demand information, and the diet plan is pushed to the user terminal.

2. The method for recommending a dietary plan according to claim 1, wherein: The user input content includes at least two of voice description, health documents, recorded videos, personal photos and input text; The obtaining of the user health demand information includes: Based on the multimodal capability of the vertical domain model, information processing and data fusion are performed on the user input content to obtain user health demand information; The user health demand information includes at least one of the user's physical diagnosis information, the user's dietary taboos, the user's exercise plan, the user's required dietary content and the user's work and rest schedule.

3. The method for recommending a dietary plan according to claim 2, wherein: Generating at least one diet plan according to the user health demand information includes: At least one diet plan is generated based on at least one of the user's physical diagnosis information, the user's dietary taboos, the user's exercise plan, the user's required dietary content and the user's work and rest schedule, wherein the diet plan is a diet arrangement formulated according to the user's physical condition and nutritional needs.

4. The method for recommending a dietary plan according to claim 1, wherein: After pushing the diet plan to the user terminal, the method further includes: In response to the user modification instruction received by the user terminal, acquiring newly added user input content; In combination with the generated diet plan, the user health demand information is updated according to the newly added user input content; Based on the vertical domain model, at least one new diet plan is regenerated according to the updated user health needs information.

5. The method for recommending a dietary plan according to claim 1, wherein: After pushing the diet plan to the user terminal, the method further includes: The diet plan is updated regularly according to the preset period, wherein the preset period is a pre-set time period for regularly updating the diet plan.

6. The method for recommending a dietary plan according to claim 5, characterized in that: The regularly updating diet plan includes: For each of the preset cycles, obtaining the current user input content in real time and determining whether the user input content has changed; If a change occurs, based on the vertical domain model, the user health demand information is updated according to the current user input content; Adjust the diet plan according to the updated user health demand information to obtain an updated diet plan; If no change occurs, the diet plan is updated according to the existing user health needs information.

7. The method for recommending a dietary plan according to claim 1, wherein: The obtaining of user input content in a multimodal format includes: Acquiring a voice description of the user through a microphone device at the user end, wherein the voice description is used to describe at least one of the user's weight, height, gender, dietary preference and dietary taboos; and / or, Obtaining the health document uploaded by the user, wherein the health document includes at least one of the user's physical examination report, imaging report, and hospital laboratory test report; and / or, Acquiring a recorded video or personal photo of the user, wherein the personal photo includes at least one of a full-body photo, a half-body photo, and a partial photo; and / or, The information collection form is displayed to the user through the display screen device of the user terminal to obtain the input text of the user, and the input text is the text entered by the user when filling in the information collection form according to his / her own health condition.

8. The method for recommending a dietary plan according to claim 1, wherein: Generating at least one diet plan according to the user health demand information includes: Based on the associated database, generating a user health analysis report according to the user health demand information, the user health analysis report including at least one diet plan; The associated database includes at least one of a medical database, a food material database, a health database and a diet database; Pushing the diet plan to the user terminal includes: The user health analysis report is formatted for readability and displayed visually through the user terminal.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium includes a stored program, wherein the program, when executed, executes the method for recommending a dietary plan according to any one of claims 1 to 8.

10. A smart device, comprising a memory and a processor, characterized in that: A computer program is stored in the memory, and the processor is configured to execute the method for recommending a dietary plan according to any one of claims 1 to 8 through the computer program.

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