Intelligent meal taking system

Abstract

The invention discloses an intelligent meal taking system. The intelligent meal taking system is applied to a user who moves slowly, the intelligent meal taking system comprises a dinner plate recognition module, a man-machine interaction module, an intelligent meal taking execution module and a meal analysis module, and the dinner plate recognition module is used for recognizing the identity of a dinner plate and associating meal taking user information; the man-machine interaction module is used for receiving a dish taking instruction of a user and generating a dish taking instruction; the intelligent food taking execution module is used for completing food taking under the food taking instruction; the meal analysis module is used for collecting meal taking data, analyzing the diet condition of the user and generating a meal report; and the dinner plate identification module, the intelligent meal taking execution module, the man-machine interaction module and the meal analysis module are in communication connection. According to the technical scheme, frequent movement of the dinner plate can be effectively reduced, food spilling is avoided, and potential safety hazards are reduced.

Description

Technical Field

[0001] The present invention relates to the field of smart catering technology, and in particular to a smart meal collection system. Background Art

[0002] Smart cafeterias can improve meal serving efficiency, optimize management, enhance the dining experience, and promote healthy eating. However, for users with limited mobility, especially the elderly, frequently moving plates requires a certain level of coordination and physical strength. Elderly individuals may have reduced physical function and lack arm strength, making it difficult to maintain stability when moving plates. This can easily cause plates to shake and food to spill, resulting in food waste and potentially soiling the floor, posing a safety hazard. Summary of the Invention

[0003] In response to the shortcomings of the existing technology, the present invention provides a smart meal collection system that can effectively reduce the frequent movement of plates, avoid food spillage, and reduce safety hazards.

[0004] This application provides a smart meal collection system, which is applied to users with slow movements and includes:

[0005] A meal tray identification module, which is used to identify the identity of the meal tray and associate it with the user information of the meal pick-up user;

[0006] A human-computer interaction module, which is used to receive a user's instruction to pick up food and generate a pick-up instruction;

[0007] An intelligent meal pickup execution module, which is used to complete the meal pickup under the meal pickup instruction;

[0008] A dining analysis module, which is used to collect meal collection data, analyze user diet and generate dining reports;

[0009] The plate recognition module, the intelligent meal-taking execution module, the human-computer interaction module and the meal analysis module are communicatively connected.

[0010] In one aspect, the intelligent meal pickup execution module includes:

[0011] A robotic arm, the robotic arm being provided with utensils adapted for preparing a variety of dishes;

[0012] A safety protection structure includes a transparent protection barrier, and the transparent protection barrier is arranged within the operating range of the robotic arm.

[0013] In one aspect, the human-computer interaction module includes:

[0014] An interactive interface, wherein the interactive interface is provided with touch buttons;

[0015] A voice interaction unit is used to recognize voice commands.

[0016] In one aspect, the smart meal pickup system includes:

[0017] The account management module is used for user identity binding, account recharge management, and recording and analyzing user dining time, dishes and cost data.

[0018] In one aspect, the meal analysis module includes a weighing unit, which is used to weigh the meal plate and obtain weighing data.

[0019] In one aspect, the dining analysis module further includes a report sharing unit, which is used to push the dining report to associated family members and receive family feedback information.

[0020] In one aspect, the smart meal collection system also includes a system optimization module, which optimizes system functions and adjusts the types, tastes and nutritional combinations of dishes based on meal reports and family feedback.

[0021] In one aspect, the smart meal pickup system also includes an operation management module, which is used to perform inventory warning, meal preparation quantity prediction and operation data analysis based on meal pickup data.

[0022] In one aspect, the smart meal collection system further includes an emergency processing module, which is used to switch to a backup working mode in the event of a failure to provide manual assistance services.

[0023] The beneficial effects of the present invention are as follows: the intelligent meal-taking execution module of the smart meal-taking system will complete the meal-taking under the meal-taking instruction, and the user does not need to frequently move the plate to get the meal by himself, which fundamentally reduces the situation where food is spilled due to unstable movement of the plate, avoids food waste, and reduces the safety hazards caused by the soiling of the ground. The human-computer interaction module receives the user's meal-taking instructions and generates a meal-taking instruction. Compared with the traditional meal-taking method where the user needs to go to the dining table to select the dishes independently, it greatly reduces their body coordination pressure and physical exertion, and reduces the safety risks that may be caused by excessive physical burden. In addition, the dining analysis module collects meal-taking data and analyzes the user's diet, and can also generate a dining report. The dining report helps to understand the dietary preferences and nutritional intake of users with slow movements, thereby providing them with dish selection suggestions that are more in line with their health needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] 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.

[0025] Figure 1 This is a schematic diagram of the structure of the smart dining system for this application;

[0026] Figure 2 This is a schematic diagram of the layout of the smart dining system for this application.

[0027] Description of the drawings: 100, plate recognition module; 200, human-computer interaction module; 300, intelligent meal collection execution module; 400, meal analysis module; 500, account management module; 600, system optimization module; 700, operation management module; 800, emergency response module. DETAILED DESCRIPTION

[0028] 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.

[0029] 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.

[0030] like Figure 1 As shown, the present application provides a smart meal collection system, which is applied to users with slow movements, such as the elderly. The smart meal collection system includes: a plate recognition module 100, a human-computer interaction module 200, an intelligent meal collection execution module 300 and a meal analysis module 400.

[0031] The tray recognition module 100 is used to identify the tray and associate it with the user who picked it up. It uses advanced recognition technologies, such as RFID (Radio Frequency Identification) or QR code recognition. The tray is fitted with a corresponding RFID tag or printed with a QR code. When the tray is brought close to the recognition device, the device emits a specific signal (for RFID) or scans the QR code, thereby obtaining the tray's unique identification information.

[0032] The plate recognition module 100 associates the identified plate identity with the user information pre-stored in the system. This user information includes the user's name, age, health status, dietary preferences, and account information. Through this association, the smart meal collection system provides accurate user identification and relevant data foundation for subsequent operations such as meal collection, payment, and meal analysis. For example, when a slow-moving elderly person presents a plate for recognition, the system immediately identifies the individual and can provide personalized service based on their health status and dietary preferences.

[0033] The human-computer interaction module 200 is used to receive user instructions to pick up dishes and generate instructions for picking up dishes. This module provides users with limited mobility with a variety of convenient interaction methods for issuing pickup instructions. For example, it is equipped with a large, high-contrast touchscreen display that displays detailed information such as dish images, names, prices, and nutritional information. Users can select their desired dishes by simply touching the on-screen menu. Furthermore, considering that users with limited mobility may have difficulty manipulating dishes with their hands, a voice interaction function is also provided, allowing users to issue pickup instructions by clearly speaking the dish name.

[0034] After receiving the user's order instructions, the human-computer interaction module 200 processes and interprets them, converting them into order instructions that the system can understand and execute. These instructions contain detailed information about the dish selected by the user, such as the dish number and quantity, and send them to the intelligent order execution module 300 to execute the specific order operation.

[0035] The intelligent meal retrieval execution module 300 is used to complete the retrieval of dishes according to the retrieval instructions. The intelligent meal retrieval execution module 300 maintains a communication connection with the human-computer interaction module 200 and receives the retrieval instructions sent by the human-computer interaction module 200 in real time. Once the instructions are received, the intelligent meal retrieval execution module 300 immediately interprets and processes the instructions to determine the location and quantity of the dishes to be retrieved.

[0036] The intelligent meal retrieval execution module 300 is typically equipped with an advanced robotic arm or other automated meal retrieval equipment. The robotic arm possesses high-precision motion control capabilities, accurately moving to the corresponding dish storage location according to the retrieval instructions, taking the dishes in the prescribed quantity and manner, and placing them on the identified plates. The meal retrieval process also considers the needs of slower users, such as maintaining a moderate operating speed to avoid spilling food due to excessive movement.

[0037] The dining analysis module 400 is used to collect meal pickup data, analyze the user's dietary habits, and generate dining reports. The module collects various data related to the user's meal pickup, including the name, quantity, weight, and pickup time of the dish selected. This data is derived from the plate recognition module 100, the human-computer interaction module 200, and the intelligent meal pickup execution module 300, and is transmitted and aggregated via the system's internal communication network.

[0038] The meal analysis module 400 conducts in-depth analysis of the collected meal collection data. It combines this with information pre-entered by the user regarding health status and dietary preferences to assess whether the user's diet is balanced and their nutritional intake is appropriate. For example, it analyzes the user's intake of calories, protein, fat, carbohydrates, vitamins, and other nutrients for each meal to determine whether it meets their physical needs. For users with slower movements, it also pays special attention to factors such as food texture and digestibility.

[0039] Based on the analysis results, the meal analysis module 400 generates a detailed meal report. This report includes the user's dietary profile, nutritional intake analysis, and health recommendations. These reports can be presented in intuitive charts and textual descriptions for easy review by the user and relevant personnel. The system can also send meal reports to the user and their family members via text messages, emails, or mobile applications, allowing them to keep abreast of the user's dietary status and make appropriate adjustments and arrangements.

[0040] The plate recognition module 100 , the intelligent meal-taking execution module 300 , the human-computer interaction module 200 and the meal analysis module 400 are communicatively connected.

[0041] The intelligent meal-picking execution module 300 of the smart meal-picking system will complete the meal-picking under the meal-picking instruction. Users do not need to frequently move the plates to get the meals, which fundamentally reduces the situation where food is spilled due to unstable movement of the plates, avoids food waste, and reduces the safety hazards caused by dirty floors. The human-computer interaction module 200 receives the user's meal-picking instructions and generates meal-picking instructions. Compared with the traditional meal-picking method where users need to go to the dining table to select dishes independently, it greatly reduces their body coordination pressure and physical exertion, and reduces the safety risks that may be caused by excessive physical burden. In addition, the dining analysis module 400 collects meal-picking data and analyzes the user's diet, and can also generate a dining report. The dining report helps to understand the dietary preferences and nutritional intake of users with slow movements, thereby providing them with dish selection suggestions that are more in line with their health needs.

[0042] In one embodiment of the present application, the intelligent meal collection execution module 300 includes: a robotic arm and a safety protection structure.

[0043] The robotic arm is equipped with utensils suitable for a variety of dishes; the utensils on the robotic arm are specially designed according to the characteristics of different dishes. For example, for block-shaped dishes such as braised pork and potato cubes, a gripper with a non-slip design may be used to ensure that the dishes do not slip during the grasping process; and for soup dishes, a long-handled soup spoon will be equipped, and the depth and curvature of the soup spoon are carefully designed to accurately scoop out the right amount of soup without spilling the soup. For loose dishes such as vegetable salads, a wide spatula-like tool may be used to pick them up, meeting the needs of different dishes and ensuring the efficiency and hygiene of the food collection process.

[0044] The safety protection structure includes a transparent protective barrier, which is set within the operating range of the robotic arm. The role of the transparent protective barrier of the safety protection structure: The transparent protective barrier is set within the operating range of the robotic arm and has multiple functions. From a safety perspective, it can prevent the robotic arm from causing harm to surrounding personnel due to unexpected situations during operation, and act as a physical barrier. At the same time, the transparent material does not prevent the user from observing the meal-taking operation process of the robotic arm. The user can clearly see how the dishes are taken by the robotic arm and placed on the plate, which increases the transparency and visibility of the meal-taking process. In addition, the protective barrier can also prevent pollutants such as dust and droplets from entering the operating area of ​​the robotic arm, ensure the hygiene of the dishes, avoid external factors from interfering with the meal-taking process, and ensure the safety, hygiene and stability of the entire meal-taking process.

[0045] In one embodiment of the present application, the human-computer interaction module 200 includes: an interaction interface and a voice interaction unit.

[0046] The interactive interface is equipped with touch buttons; the design of the touch buttons of the interactive interface fully takes into account the characteristics of users with slow movements. Touch buttons are usually larger in size, which is convenient for users to click and operate, and reduces accidental touches caused by hand tremors or inaccurate operations. At the same time, the layout of the buttons is simple and clear, and is reasonably divided according to the category of dishes, functional modules, etc. For example, different types of food buttons such as staple foods, dishes, and soups are arranged separately, so that users can quickly find the dishes they want to choose. In addition, the touch buttons also have an obvious feedback mechanism. When the user clicks the button, the button will have feedback such as color change, vibration or sound prompts to let the user confirm that the operation has been received by the system.

[0047] The voice interaction unit is used to recognize voice commands. Voice interaction unit: The voice interaction unit greatly facilitates slow-moving users who have difficulty operating their hands or have poor eyesight. Users only need to speak clear voice commands, such as "I want a serving of Kung Pao Chicken" or "Give me a bowl of rice", and the voice interaction unit can use advanced voice recognition technology to convert the voice into command information that the system can understand. The unit has a high recognition accuracy rate and can adapt to different accents and speaking speeds. Even if the speaker speaks slowly or with a local accent, it can accurately recognize commands. At the same time, the voice interaction unit also supports multiple rounds of dialogue, and users can supplement or modify commands at any time. For example, first say "I want a serving of vegetables" and then add "broccoli", and the system can accurately understand and execute them.

[0048] In one embodiment of the present application, the smart meal pickup system includes: an account management module 500, which is used for user identity binding, account recharge management, and recording and analyzing user dining time, dishes and cost data. The account management module 500 supports multiple identity binding methods, such as common ID card recognition, face recognition, social security card binding, etc. Taking ID card recognition as an example, the user only needs to place the ID card on the designated recognition device, and the system can quickly read the identity information and establish an association with the system account; face recognition uses the camera to collect the user's facial features for identification and binding. This multi-mode binding not only facilitates users with slow movements, but also ensures the accuracy and security of identity authentication, preventing others from impersonating others to pick up meals. At the same time, after binding the identity, the system can associate the user's health records, dietary taboos and other information.

[0049] To meet the needs of diverse users, the account management module 500 also provides a variety of top-up channels. Online, it supports convenient payment methods such as WeChat and Alipay, allowing users to easily top up their accounts from their phones at home. Offline, top-up locations are also available, offering cash and card options for those unfamiliar with online transactions. For users with limited mobility, remote top-up can be performed by family members. The system updates account balances in real time, ensuring users are always aware of their account status and preventing meal pickup delays due to insufficient balances.

[0050] Furthermore, the account management module 500 records in detail each user's meal time, selected dishes, and cost data. By analyzing meal times, users' dining habits can be understood, such as whether they have fixed meal times. This helps the cafeteria rationally arrange meal preparation and service times. Analysis of selected dishes can help understand users' taste preferences and nutritional intake. For example, if a user frequently chooses high-sugar dishes, the system can subsequently provide healthy eating reminders or recommend low-sugar dishes. Cost data analysis can assist the cafeteria in formulating reasonable pricing strategies and help users understand their dining consumption, achieving consumer transparency.

[0051] In one embodiment of the present application, the dining analysis module 400 includes a weighing unit, which is used to weigh the plate and obtain weighing data. High-precision weighing: The weighing unit is equipped with a high-precision weighing sensor, which can accurately sense subtle changes in the weight of the plate and strictly control the weighing error within an extremely small range, for example, it can achieve a high precision of ±0.1 grams. Both the weight of the plate itself and the weight change after adding different dishes can be accurately measured. When the plate is placed on the weighing unit, the weighing sensor will start working immediately and collect the weight data of the plate in real time. In addition, these data will be promptly transmitted to the processing system of the dining analysis module 400 for subsequent rapid analysis and processing.

[0052] The weight data obtained by the weighing unit, combined with the system's pre-stored calorie information for each dish, can accurately calculate the weight of each dish the user has chosen and the corresponding calorie intake. For example, if a user chooses a portion of braised pork and the weighing unit measures its weight at 200 grams, the system can calculate the user's calorie intake based on the preset calorie data per 100 grams of braised pork.

[0053] By recording the weight of each user's meal plate over a long period of time, we can analyze their dietary patterns, such as the time intervals between meals and the amount of food consumed at each meal. We can also further understand their dietary preferences. For example, some users frequently choose heavier vegetable dishes, indicating a preference for vegetarianism; while others frequently choose high-calorie, high-fat meat dishes, reflecting their different dietary preferences.

[0054] Based on the nutritional intake calculated from the weighing data, the meal analysis module 400 can provide personalized health recommendations based on the user's health status and nutritional needs. For example, if a user has a chronic history of excessive salt intake, the system will remind them to reduce their choices of high-salt dishes and recommend low-salt and healthy options. For users who need to control their weight, the system can provide reasonable dietary adjustment suggestions based on their caloric intake.

[0055] In one embodiment of the present application, the meal analysis module 400 also includes a report sharing unit, which is used to push meal reports to associated family members and receive family feedback information. The report sharing unit regularly pushes the meal reports generated by the meal analysis module 400 to associated family members. These reports are detailed, covering information such as the user's dish selection, food intake, and nutritional intake analysis for each meal, and are presented in intuitive charts and concise text descriptions, such as a bar chart showing the daily intake comparison of various nutrients. Family members receive reports through mobile phone applications, text messages, or emails, and can keep abreast of the dietary habits of family members who are slow in action. For example, if the elderly have been eating insufficient vegetables for a long time, family members can communicate with the elderly in a timely manner based on the report, encourage them to increase their vegetable intake, or contact the cafeteria staff to adjust the meal combination for the elderly.

[0056] After receiving the report, family members can provide feedback to the system through the report sharing unit. This feedback can include special dietary requirements for the elderly, such as food allergies, in which case the family can instruct the cafeteria to avoid serving the relevant dishes. It can also include suggestions for the cafeteria's services, such as requesting the addition of dishes that are more suitable for the elderly. After receiving this feedback, the system passes it on to the appropriate modules. The operations management module 700 adjusts the menu accordingly, and the system optimization module 600 uses this feedback to improve system functionality, better meet the needs of users with mobility impairments, and enhance the overall dining experience.

[0057] In one embodiment of the present application, the smart meal retrieval system also includes a system optimization module 600. The system optimization module 600 optimizes system functions and adjusts the types, tastes, and nutritional combinations of dishes based on meal reports and family feedback. The meal report contains a large amount of data about the user's meal retrieval behavior and dietary preferences. By analyzing this data, the system optimization module 600 can discover functional deficiencies in the system. If the report shows that some users take a long time to operate the human-computer interaction module 200, it may mean that the interactive interface is not simple and easy to understand. The system optimization module 600 will redesign the interactive interface, simplify the operation process, increase the size of the touch buttons, and adjust the button layout so that users with slow movements can complete the meal retrieval operation more conveniently and quickly. In addition, if the meal analysis module 400 reports that certain dishes are frequently taken, but the robotic arm is slow in taking meals, the system optimization module 600 will optimize the robotic arm's program to improve its meal retrieval efficiency.

[0058] Family members, who are closely connected to users with slow movements, provide feedback that directly reflects their actual needs. When a family member suggests that an elderly person needs soft, easily digestible dishes due to physical reasons, the system optimization module 600 communicates this request to the operations management module 700 and kitchen staff, prompting the canteen to add dishes such as pumpkin puree and tofu soup. If multiple family members report that certain dishes are unpopular with the elderly, the system optimization module 600 will consider reducing or replacing these dishes to make the menu more suitable for the user's taste and dietary needs.

[0059] In one embodiment of the present application, the smart meal pickup system also includes an operation management module 700, which is used to perform inventory warnings, meal preparation quantity forecasts and operation data analysis based on meal pickup data. The operation management module 700 collects and analyzes the consumption of various dishes in the meal pickup data in real time. The system sets an inventory warning line for each ingredient in advance. Once the inventory of ingredients corresponding to a certain dish is lower than the warning line, the inventory warning function will be activated. It will promptly send an alarm to the canteen purchasing staff through system pop-ups, text messages or internal communication software, reminding them to purchase and replenish ingredients as soon as possible. For example, when the system detects that the rice inventory is only enough to supply two days of consumption, and the set warning line is three days of consumption, it will trigger an inventory warning to ensure that the canteen will not affect the normal supply of meals due to food shortages, especially to ensure that slow-moving users can get the meals they need on time.

[0060] The operations management module 700 can also leverage big data analysis and prediction algorithms to accurately predict the amount of food to be prepared for each meal, taking into account historical meal pickup data, the current time period, seasonal factors, special holidays, and other information. By analyzing the number of people picking up meals and their dish preferences during different time periods from Monday to Friday, combined with factors such as the weather conditions and whether there are special events, the module predicts the demand for various dishes. For example, demand for hot soup dishes may increase in cold weather. Based on the prediction results, cafeteria staff can prepare the appropriate amount of ingredients in advance, avoiding food waste due to over-preparation or insufficient preparation that prevents slow-moving users from picking up their desired dishes.

[0061] Operations Management Module 700 conducts multi-dimensional analysis of meal pickup data, including user traffic analysis, consumption trend analysis, and dish popularity analysis. By analyzing user traffic in different time periods, it rationally arranges cafeteria staff's working hours and the number of open windows, improving service efficiency and reducing wait times for slow-moving users. It also studies consumption trends to understand user acceptance of dish prices in different seasons and time periods, providing a basis for the cafeteria to formulate reasonable pricing strategies. Analyzing dish popularity to identify which dishes are popular with users and which need improvement or elimination helps optimize the menu structure, improve the overall service quality of the cafeteria, and better meet the dining needs of slow-moving users.

[0062] In one embodiment of the present application, the smart meal retrieval system further includes an emergency processing module 800, which is used to switch to a backup working mode in the event of a fault to provide manual assistance services. The emergency processing module 800 will continuously monitor the various parts of the smart meal retrieval system, such as the plate recognition module 100, the human-computer interaction module 200, the intelligent meal retrieval execution module 300, etc. in real time. Once a module failure is detected, such as a mechanical arm failure that prevents normal meal retrieval, or a failure of the touch button of the human-computer interaction module 200, the emergency processing module 800 will respond quickly and start the backup working mode in a very short time to ensure that the meal retrieval service is not interrupted.

[0063] The backup working mode is a set of alternative operating solutions specially designed to deal with system failures. If the robotic arm of the intelligent meal collection execution module 300 fails, the backup mode may switch to manual meal collection mode, and the cafeteria staff will use traditional tools to prepare meals for users according to their order requirements. If the plate recognition module 100 fails, the staff can manually enter the user information to associate the meal collection user and ensure the continuity of the meal collection process. This rapid switching of the backup mode can minimize the impact of system failures on slow-moving users' meal collection.

[0064] While operating in standby mode, the emergency handling module 800 will promptly notify cafeteria staff to provide manual assistance to users. Staff will proactively assist slow users in completing the meal collection process, such as assisting them in operating the human-computer interaction module 200, patiently inquiring about their dish needs, assisting them in placing their orders, and guiding them to a seat and rest while waiting to collect their food, ensuring they receive convenient and attentive service even during the system outage. Furthermore, staff will maintain order on-site, answer user questions, and prevent chaos caused by the outage, thereby ensuring the normal operation of the entire cafeteria.

[0065] See Figure 2 The image shows the dining area and food pickup area of ​​the cafeteria. The food pickup area is at the top of the image, and the dining area is at the bottom. The dining area has neatly arranged tables and chairs for diners to eat. A checkout machine is located in the center of the food pickup area. This machine serves as a human-computer interaction module, and users can be seen ordering and selecting dishes in the image. The food pickup area is equipped with eight smart weighing stations, which serve as weighing units. A robotic arm removes dishes from these weighing stations and places them on trays, enabling automated food pickup.

[0066] 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 smart meal collection system, characterized in that: The smart meal collection system is applied to users with slow movements, and includes: A meal tray identification module, which is used to identify the identity of the meal tray and associate it with the user information of the meal pick-up user; A human-computer interaction module, which is used to receive a user's instruction to pick up food and generate a pick-up instruction; An intelligent meal pickup execution module, which is used to complete the meal pickup under the meal pickup instruction; A dining analysis module, which is used to collect meal collection data, analyze user diet and generate dining reports; The plate recognition module, the intelligent meal-taking execution module, the human-computer interaction module and the meal analysis module are communicatively connected.

2. The smart meal collection system according to claim 1, characterized in that: The intelligent meal collection execution module includes: A robotic arm, the robotic arm being provided with utensils adapted for preparing a variety of dishes; A safety protection structure includes a transparent protection barrier, and the transparent protection barrier is arranged within the operating range of the robotic arm.

3. The smart meal collection system according to claim 1, characterized in that: The human-computer interaction module includes: An interactive interface, wherein the interactive interface is provided with touch buttons; A voice interaction unit is used to recognize voice commands.

4. The smart meal collection system according to claim 1, characterized in that: The smart meal collection system includes: The account management module is used for user identity binding, account recharge management, and recording and analyzing user dining time, dishes and cost data.

5. The smart meal collection system according to claim 1, characterized in that: The dining analysis module includes a weighing unit, which is used to weigh the meal plate and obtain weighing data.

6. The intelligent meal collection system according to claim 5, characterized in that: The dining analysis module further includes a report sharing unit, which is used to push the dining report to the associated family members and receive feedback information from the family members.

7. The intelligent meal collection system according to claim 6, characterized in that: The smart meal collection system also includes a system optimization module, which optimizes system functions and adjusts the types, tastes and nutritional combinations of dishes based on meal reports and family feedback.

8. The intelligent meal collection system according to claim 1, characterized in that: The smart meal pickup system also includes an operations management module, which is used to perform inventory warnings, meal preparation quantity predictions, and operations data analysis based on meal pickup data.

9. The intelligent meal collection system according to claim 1, characterized in that: The smart meal collection system also includes an emergency processing module, which is used to switch to a backup working mode in the event of a failure to provide manual assistance services.

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