Dining analysis method

Abstract

The invention discloses a dining analysis method. The dining analysis method is applied to the intelligent dining system, the intelligent dining system comprises public vessels used for containing meals and a dish taking tool used for clamping the meals, a weighing device is arranged below each public vessel, each public vessel is provided with a reader-writer, the dish taking tool is provided with an electronic tag, and the analysis method comprises the steps that the dish taking tool is bound with a user; when the food taking tool picks food in the public vessel, the reader-writer in the public vessel detects the electronic tag and generates an induction signal corresponding to a user, the weighing device detects the weight change value of the corresponding public vessel, and the background server analyzes the dining condition of the corresponding user based on the induction signal and the weight change value and forms a dining report of the user. And the dining report is fed back to the corresponding user. According to the technical scheme, the nutritional ingredient intake condition of the user can be effectively known, so that the health of the user can be accurately managed through diet.

Description

Technical Field

[0001] The present invention relates to the field of smart catering technology, and in particular to a dining analysis method. Background Art

[0002] As people pay more attention to their health, they are also paying more attention to their diet. However, it is difficult for people to know the details of their meals in a timely manner. This makes it difficult for users to know their nutritional intake and manage their health through diet. Summary of the Invention

[0003] In response to the deficiencies in the prior art, the present invention provides a meal analysis method that can effectively understand the user's nutritional intake, so that the user can accurately manage his or her health through diet.

[0004] The present application provides a dining analysis method, which is applied to a smart dining system. The smart dining system is a shared dining system, comprising a food-picking tool and a public container. The public container is used to hold food, and the food-picking tool is used to pick up food. There are multiple public containers, each of which has a scale disposed below it. The public container is provided with a reader / writer, and the food-picking tool is provided with an electronic tag. The analysis method includes:

[0005] Binding the food-picking tool to the user;

[0006] When the food-picking tool picks up food from the public container, the reader / writer in the public container detects the electronic tag and generates a sensing signal corresponding to the user, and at the same time, the weighing device detects the weight change value of the corresponding public container;

[0007] The sensing signal and the weight change value are provided to a backend server, and the backend server analyzes the dining situation of the corresponding user based on the sensing signal and the weight change value to form a dining report of the user.

[0008] In one aspect, the dining system includes a user locker and a scanner, and a QR code is provided on the surface of the food-picking tool;

[0009] The step of binding the food picking tool to the user includes:

[0010] The scanner is used to scan the QR code of the food-picking tool, and the user locker is used to lock the user;

[0011] A one-to-one binding relationship is established between the food picking tool and the user.

[0012] In one aspect, the user locker is at least one of a camera, a fingerprint reader, and an identification code.

[0013] In one aspect, the step of the backend server analyzing the dining situation of the corresponding user based on the sensing signal and the weight change value includes:

[0014] The backend server receives the sensing signal and determines the corresponding user who performs the food-grabbing action based on the sensing signal;

[0015] When the weight change value is greater than zero, it is determined that the user has picked up the corresponding dish;

[0016] When the weight change value is equal to zero, it is determined that the user has given up picking up the corresponding dish;

[0017] The dining situation of the corresponding user is analyzed based on the weight change value combined with pre-stored dish ingredient information.

[0018] In one aspect, before the step of analyzing the dining situation of the corresponding user based on the sensing signal and the weight change value, the backend server includes:

[0019] The type and weight of ingredients, as well as the type and quantity of added seasonings are obtained, and the ingredient information of each dish is formed in combination with the cooking method, and the ingredient information is stored in the backend server.

[0020] In one aspect, after the step of binding the food picking tool to the user, the following steps are included:

[0021] determining a user identity based on the user locker;

[0022] Based on the user's identity, the user's historical dining history is retrieved, the nutritional intake trend of the user is analyzed, and recommendations are made for the user's current dining dishes.

[0023] In one aspect, after the step of determining the user identity based on the user locker, the method further comprises:

[0024] Based on the user's identity, the user's past medical records are retrieved, and the user's dietary restrictions and suitable dishes are provided. In addition, the user's physical health status is warned based on the current dining situation.

[0025] In one aspect, the smart dining system further includes a personal container, and a scale is provided below the personal container;

[0026] The steps to generate a user's dining report include:

[0027] After the user finishes eating, weighing the remaining food in the user's personal container;

[0028] The amount of food remaining in individual dishes was analyzed by taking photos to determine the ratio of the amount of food to the amount of food;

[0029] The composition of the remaining meal is calculated based on the meal proportion and the weight of the remaining meal, and the composition of the remaining meal is deducted from the meal report.

[0030] In one aspect, the smart dining system further includes serving chopsticks, which are provided with electronic tags;

[0031] When the serving chopsticks are used to pick up food, the dish to be picked up is determined based on the electronic tag of the serving chopsticks and the reader / writer of the serving vessel;

[0032] The recipient of the food to be picked up by the serving chopsticks is determined based on the weight change of the personal utensil.

[0033] In one aspect, after the step of feeding back the dining report to the corresponding user, the method further includes:

[0034] An evaluation option is provided on the dining report, and the user scores each dish based on the evaluation option, thereby improving the dish.

[0035] The beneficial effects of the present invention are reflected in: binding the food-picking tool to the user, establishing a one-to-one correspondence between the user and the food-picking tool. Thus, when the food-picking tool picks up food from a shared container, the reader / writer in the shared container detects the electronic tag and generates a sensing signal corresponding to the user. After measuring the weight change of the shared container, the specific dish picked up by the user can be determined. Based on the sensing signal and weight change, the backend server analyzes the user's dining habits and generates a dining report. The user can use this report to understand their nutritional intake and accurately manage their health through diet. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly describes the drawings required for the specific embodiments or the description of the prior art. Similar elements or parts are generally identified by similar reference numerals throughout the drawings. Elements or parts in the drawings are not necessarily drawn to scale.

[0037] Figure 1 A schematic diagram of the steps of the analysis method for the smart dining system in this application;

[0038] Figure 2 This is a schematic diagram of the steps for binding a food-picking tool to a user in the analysis method of the smart dining system of this application;

[0039] Figure 3 This is a schematic diagram of the steps for analyzing the dining situation of a corresponding user in the analysis method of the smart dining system of this application;

[0040] Figure 4 This is a schematic diagram of the steps for obtaining ingredient information of dishes in the analysis method of the smart dining system of this application;

[0041] Figure 5 This is a schematic diagram of the steps for recommending dishes for a user's current meal in the analysis method of the smart dining system of this application;

[0042] Figure 6 This is a schematic diagram of the steps for providing early warning of a user's health status in the analysis method of the smart dining system in this application;

[0043] Figure 7 A schematic diagram of the steps for forming a user's dining report in the analysis method of the smart dining system of this application;

[0044] Figure 8 A schematic diagram of the steps for determining the use of serving chopsticks to pick up food in the analysis method of the smart dining system of this application;

[0045] Figure 9 This is a schematic diagram of the steps for scoring each dish in the analysis method of the smart dining system in this application;

[0046] Figure 10 This is a schematic diagram of the desktop structure of the smart dining system applied for.

[0047] Description of the accompanying drawings: 100, desktop; 101, personal utensils; 102, public utensils. DETAILED DESCRIPTION

[0048] The following embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are therefore only examples and are not intended to limit the scope of protection of the present invention.

[0049] It should be noted that, unless otherwise specified, the technical or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the present invention belongs.

[0050] like Figure 1 and Figure 10As shown, the present application provides a dining analysis method, which is applied to a smart dining system. The smart dining system is a shared dining system. Simply put, shared dining means that everyone shares the dishes. For example, when dining at a round table, the dishes are placed on the round table and everyone shares the dishes. The smart dining system includes a food-picking tool and a public container 102. The public container 102 is used to hold the food, and the food-picking tool is used to pick up the food. The public container can be a bowl or plate, and the food-picking tool includes a knife, fork, chopsticks, and spoon. There are multiple public containers 102, each of which is provided with a scale below. The public container 102 is provided with a reader / writer, which can be embedded in the outer periphery of the public container 102. To ensure power supply, a battery can be provided at the bottom of the public container 102 to power the reader / writer. The food-picking tool is provided with an electronic tag. The electronic tag can be embedded in the end of the food-picking tool that contacts the food, and a battery is provided at the other end. The other end of the food-picking tool is usually also the end held by the user, and the electronic tag is connected via the battery. Analytical methods include:

[0051] Step S10, bind the food picking tool to the user; in this way, a corresponding relationship between the food picking tool and the user can be established, so that the food picking tool used by the user can be known, thereby ensuring the accuracy of the analysis data.

[0052] In step S20, when the food-picking tool picks up food from the shared container 102, the reader / writer in the shared container 102 detects the electronic tag and generates a sensing signal corresponding to the user. Simultaneously, the scale detects the weight change of the shared container 102. As the food-picking tool approaches the shared container 102, the reader / writer reads the signal from the electronic tag and determines the direction in which the user is picking up the food. Once the scale detects the weight change of the shared container 102, the user has completed the food-picking process.

[0053] In step S30, the sensing signal and weight change value are provided to a backend server. The backend server analyzes the user's dining habits based on the sensing signal and weight change value, generating a dining report. The weight change value can be used to determine the quantity of food consumed by the user and, in turn, analyze the nutritional composition of the food consumed. The dining report can be provided to the user via a mini-program or text message.

[0054] In this embodiment, the food-picking tool is bound to the user, establishing a one-to-one correspondence between the user and the food-picking tool. Thus, when the food-picking tool picks up food from the common vessel 102, the reader / writer in the common vessel 102 detects the electronic tag and generates a sensing signal corresponding to the user. By measuring the weight change of the common vessel 102, the reader / writer can determine which dish the user has picked up. Based on the sensing signal and weight change, the backend server analyzes the user's dining habits and generates a dining report. This report allows users to understand their nutritional intake and accurately manage their health through diet.

[0055] In addition, the technical solution of this application can track individual food-picking behavior through inductive detection between the electronic tag and the reader / writer, thereby accurately determining the dishes consumed by the user. In addition, a display panel can be set up on the desktop to display the user's dining status in real time, enabling dynamic nutritional analysis.

[0056] The following further explains the workings between the electronic tag and the reader / writer in this application. The electronic tag can be an active RFID (radio frequency identification) tag, powered by a built-in micro battery, which can actively transmit signals and has a long communication range (typically 1-10 meters), making it suitable for dynamic food retrieval scenarios. The electronic tag chip stores a unique ID (such as an encrypted code).

[0057] An electronic tag can be embedded in the gripping end of a food-picking tool (such as the tip of a chopstick), ensuring close proximity to a reader / writer on a shared container. A button battery is placed in the gripping end, connected to the tag chip via a microcircuit, ensuring continuous power. When a user picks up food, the electronic tag is activated by the reader's radio frequency field and transmits the user's binding data, ensuring rapid response and strong anti-interference capabilities.

[0058] The reader is embedded in the outer edge of the public utensil and adopts a directional antenna design, focusing on the food-picking area above the utensil to avoid misreading signals from other directions. It has a built-in anti-collision algorithm (such as time division multiple access TDMA) to support simultaneous reading of multiple tags to avoid signal conflicts when multiple people are picking up food. The reader is powered by a rechargeable lithium battery at the bottom of the public utensil and transmits data to the backend server in real time via Wi-Fi or Bluetooth. When the food-picking tool enters the reader's sensing range (about 10cm), the reader captures the electronic tag ID and generates a sensing signal; the scale is simultaneously triggered to record the weight change of the public utensil, and the two data are linked and uploaded to the server. The reader antenna adopts a circular polarization design to reduce the reflection interference of metal utensils on the radio frequency signal; the electronic tag chip is embedded in electromagnetic shielding material to prevent the high temperature or humidity in the cooking environment from affecting the signal stability.

[0059] like Figure 2 As shown, in one embodiment of the present application, the dining system includes a user locker and a scanner, and a QR code is provided on the surface of the food picking tool.

[0060] The steps to bind the food pickup tool to the user include:

[0061] In step S110, a scanner is used to scan the QR code of the food-picking tool, and the user locker locks the user; for example, a QR code is set on the end of the food-picking tool held by the user, and a scanner is set at the user's seat position. The scanner can be embedded in the table 100. The user locker can also be embedded in the table 100 or protrude slightly from the table 100. The user locker can lock the relationship between the user and the seat position.

[0062] Step S120: Establish a one-to-one binding relationship between the food pickup tool and the user. Using the scanner, the food pickup tool is compared to the seated location, and using the user locker, the user is compared to the seated location. This completes a one-to-one binding relationship between the food pickup tool and the user. This allows users to determine which food pickup tool they are using based on their seated location.

[0063] In addition, if the food picking tool has not completed the scanning action, a prompt sound can be issued when the food picking operation is performed to remind the user to complete the scanning of the food picking tool.

[0064] In one embodiment of the present application, the user locker is at least one of a camera, a fingerprint reader, and an identification code. The camera can automatically capture a photo after the user is seated to lock the user's identity. The fingerprint reader requires the user to manually press and identify the user to complete the lock. The user can also complete the lock by scanning the identification code with a mobile phone. After the identification code is completed, it is also convenient to send the dining report directly to the mobile phone.

[0065] like Figure 3 As shown, in one embodiment of the present application, the backend server analyzes the dining situation of the corresponding user based on the sensing signal and the weight change value, including:

[0066] In step S310, the backend server receives the sensing signal and determines the corresponding user who is performing the food picking action based on the sensing signal; the sensing signals generated by each electronic tag and the same reader are different. After the electronic tag of the food picking tool triggers the generation of the sensing signal, the corresponding relationship between the food picking tool and the user can be used to determine which user is picking up the food.

[0067] In step S311, if the weight change value is greater than zero, it is determined that the user has picked up the corresponding dish; if the weight change value is still greater than zero, it indicates that the dish has been picked up. In addition, to reflect the amount of food the user has taken in real time, the scale can display the weight change in real time. The user can know the weight of the dish picked up by the displayed weight change.

[0068] Step S312: When the weight change value is equal to zero, it is determined that the user has given up picking up the corresponding dish. This means that the dish picking tool has reached out to the corresponding dish but has not been picked up. In this case, it can be determined that the user's intake of the dish is zero.

[0069] Step S320 analyzes the user's dining experience based on the weight change and pre-stored dish ingredient data. This dish ingredient data is pre-stored on the backend server and can display nutritional information per unit weight, such as calories per gram, protein, water, trace elements, and sodium. This calculation can be used to determine the nutritional information consumed during the meal.

[0070] like Figure 4 As shown, in one embodiment of the present application, before the step of analyzing the dining situation of the corresponding user based on the sensing signal and the weight change value, the backend server includes:

[0071] Step S01, obtain the type and weight of ingredients, as well as the type and quantity of added seasonings, combine them with the cooking method to form the ingredient information of each dish, and save the ingredient information in the background server.

[0072] In this application, automatic cooking equipment can be used. Each cooking process of the automatic cooking equipment is basically automated. When cooking, the types and weights of the added ingredients, as well as the types and quantities of the added seasonings are basically predetermined. After cooking is completed, the ingredient information can be saved in the background server for subsequent calls.

[0073] like Figure 5 As shown, in one embodiment of the present application, after the step of binding the food picking tool to the user, the following steps are included:

[0074] Step S40, determining the user identity based on the user locker; after confirming the user identity, it can be checked whether the user is dining for the first time or has dined there before.

[0075] In step S50, based on the user's identity, the user's dining history is retrieved, nutritional trends in the user's intake are analyzed, and recommendations for the user's current meal are made. For example, an AI model can be used to retrieve the user's dining history and, if the user's sodium intake is excessive or dietary fiber is insufficient, the AI model can provide recommendations for the user's current meal. The AI model can also be continuously updated to recommend more scientific meal combinations.

[0076] like Figure 6 As shown, in one embodiment of the present application, after the step of determining the user identity based on the user locker, the method further includes:

[0077] Step S60: Based on the user's identity, the user's past medical records are retrieved, and the user's dietary restrictions and suitable dishes are provided. The user's health status is also warned based on their current dining habits. The backend server can be connected to the hospital's management system, or the user can proactively provide past medical records to the backend server. Through artificial intelligence analysis, the user's dining habits can be better guided. If the user is overly picky about food and ignores dietary restrictions, a warning or alert can be issued. For example, if the user has high blood lipids, they can reduce their intake of greasy foods, and if they have high blood pressure, they can reduce their salt intake.

[0078] like Figure 7 As shown, in one embodiment of the present application, the smart dining system also includes a personal utensil 101, and a scale is provided under the personal utensil 101; for example, the table top 100 is circular, the personal utensil 101 is provided on the outer circle of the table top 100, and the public utensil 102 is provided on the inner circle of the table top. The public utensil 102 can be rotated on the table top 100 to ensure that each user can get close to the food.

[0079] The steps to generate a user's dining report include:

[0080] Step S301, after the user finishes eating, the weight of the remaining food in the user's personal container 101 is weighed; the user may sometimes have leftover food, and this part needs to be deducted when generating a meal report.

[0081] In step S302, the ratio of the amount of rice and the amount of vegetables remaining in the personal container 101 is analyzed by taking photos. For example, the camera of the user's locker can be fully utilized to take photos, and the ratio of the amount of rice and the amount of vegetables remaining can be obtained through image analysis.

[0082] Step S303: Combine the meal proportion and the weight of the remaining meal to calculate the composition of the remaining meal, and deduct the composition of the remaining meal from the meal report. This can make the meal report more accurate and more able to truly reflect the dining situation.

[0083] like Figure 8 As shown, in one embodiment of the present application, the smart dining system further includes serving chopsticks, which are provided with electronic tags; the serving chopsticks are usually used to pick up food for others. The serving chopsticks are usually not bound to the user.

[0084] Step S70, when using public chopsticks to pick up food, the dish to be picked up is determined based on the electronic tag of the public chopsticks and the reader-writer sensing of the public utensil 102; anyone can use the public chopsticks, and after the public chopsticks trigger the sensing of the reader-writer, the specific dish to be picked up can be known.

[0085] Step S80: Determine the target of the dish to be served by the serving chopsticks in combination with the weight change of the personal vessel 101. If the weight of a person's personal vessel 101 changes, the specific target of the dish to be served by the serving chopsticks can be determined.

[0086] In order to improve the accuracy of the judgment, a reader / writer can also be set around the personal utensil 101. The signals sensed by the reader / writer of the public utensil 102 and the personal utensil 101, which are the objects of the public chopsticks, can be compared with each other. If it is determined that they are all sensed by the public chopsticks, the object of the public chopsticks for taking food can be further determined.

[0087] like Figure 9 As shown, in one embodiment of the present application, after the step of feeding back the dining report to the corresponding user, the following steps are included:

[0088] Step S90: The meal report provides a rating option, allowing users to rate each dish based on the ratings and improve the dish. This can also improve the cooking process, creating dishes that better suit the user's taste. Through the meal report, users can learn about the ingredients of each dish, including main and auxiliary ingredients such as oil, salt, sauce, vinegar, and sugar, as well as the food safety reports of these ingredients and conduct food traceability.

[0089] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A dining analysis method, characterized in that: The dining analysis method is applied to a smart dining system. The smart dining system is a shared dining system. The smart dining system includes a food-picking tool and a public container. The public container is used to hold food, and the food-picking tool is used to pick up food. There are multiple public containers, each of which is provided with a scale, a reader, and a writer. The food-picking tool is provided with an electronic tag. The analysis method includes: Binding the food-picking tool to the user; When the food-picking tool picks up food from the public container, the reader / writer in the public container detects the electronic tag and generates a sensing signal corresponding to the user, and at the same time, the weighing device detects the weight change value of the corresponding public container; The sensing signal and the weight change value are provided to a backend server, and the backend server analyzes the dining situation of the corresponding user based on the sensing signal and the weight change value, forms a dining report of the user, and feeds back the dining report to the corresponding user.

2. The analysis method according to claim 1, characterized in that The dining system includes a user locker and a scanner, and the surface of the food-picking tool is provided with a QR code; The step of binding the food picking tool to the user includes: The scanner is used to scan the QR code of the food-picking tool, and the user locker is used to lock the user; A one-to-one binding relationship is established between the food picking tool and the user.

3. The analysis method according to claim 2, characterized in that The user locker is at least one of a camera, a fingerprint identifier and an identification code.

4. The analysis method according to claim 1, characterized in that The step of the backend server analyzing the dining situation of the corresponding user based on the sensing signal and the weight change value includes: The backend server receives the sensing signal and determines the corresponding user who performs the food-grabbing action based on the sensing signal; When the weight change value is greater than zero, it is determined that the user has picked up the corresponding dish; When the weight change value is equal to zero, it is determined that the user has given up picking up the corresponding dish; The dining situation of the corresponding user is analyzed based on the weight change value combined with pre-stored dish ingredient information.

5. The analysis method according to claim 4, characterized in that Before the step of analyzing the dining situation of the corresponding user based on the sensing signal and the weight change value, the backend server includes: The type and weight of ingredients, as well as the type and quantity of added seasonings are obtained, and the ingredient information of each dish is formed in combination with the cooking method, and the ingredient information is stored in the backend server.

6. The analysis method according to claim 2, characterized in that After the step of binding the food picking tool to the user, the method includes: determining a user identity based on the user locker; Based on the user's identity, the user's historical dining history is retrieved, the nutritional intake trend of the user is analyzed, and recommendations are made for the user's current dining dishes.

7. The analysis method according to claim 2, characterized in that After the step of determining the user identity based on the user locker, the method further includes: Based on the user's identity, the user's past medical records are retrieved, and the user's dietary restrictions and suitable dishes are provided. In addition, the user's physical health status is warned based on the current dining situation.

8. The analysis method according to claim 1, characterized in that The smart dining system further includes a personal container, and a scale is provided below the personal container; The steps to generate a user's dining report include: After the user finishes eating, weighing the remaining food in the user's personal container; The amount of food remaining in individual dishes was analyzed by taking photos to determine the ratio of the amount of food to the amount of food; The composition of the remaining meal is calculated based on the meal proportion and the weight of the remaining meal, and the composition of the remaining meal is deducted from the meal report.

9. The analysis method according to claim 8, characterized in that The smart dining system also includes serving chopsticks, which are provided with electronic tags; When the serving chopsticks are used to pick up food, the dish to be picked up is determined based on the electronic tag of the serving chopsticks and the reader / writer of the serving vessel; The recipient of the food to be picked up by the serving chopsticks is determined based on the weight change of the personal utensil.

10. The analysis method according to claim 1, characterized in that After the step of feeding back the dining report to the corresponding user, the method includes: An evaluation option is provided on the dining report, and the user scores each dish based on the evaluation option, thereby improving the dish.

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