122 results about "Foods types" patented technology

The invention discloses a food material decay prediction method and device, electronic equipment and a storage medium, and the method comprises the steps: determining the food material type of a target food material if it is detected that the target food material is put into a refrigerator, and matching a target sensor set corresponding to the food material type from a preset detection library; controlling each target sensor to carry out data acquisition, and carrying out food material decay detection processing according to the acquired target data to obtain a decay detection result; determining a sensor weight of the target sensor according to the quality parameter and the food material coefficient; performing fusion processing on the putrefaction detection result corresponding to each target sensor and the sensor weight to obtain a comprehensive putrefaction detection result corresponding to the target food material; according to the comprehensive decay detection result and the actual storage temperature of the refrigerator, the remaining storage duration of the target food materials is determined, and the actual storable duration of the food materials placed in the refrigerator can be accurately predicted through dynamic fusion of the detection results of the multiple sensors and combination of the actual storage temperature.

The invention relates to a multi-level food safety risk evaluation method based on clustering and an entropy weight method, and belongs to the technical field of food safety. Firstly, a Mini-batch K-means clustering algorithm is adopted to carry out risk level preliminary division on a sample, and automatic risk identification of mass sampling inspection data is realized. Then, counting risk grade frequencies of different food types according to three levels of province, city and district (county), and constructing a frequency matrix; and then weighting the risk indexes of various foods by using an entropy weight method, calculating comprehensive risk scores of the food types under different levels, and further aggregating to obtain the total risk level of each region. And finally, carrying out final grading on the risk score of each region by adopting a K-Means clustering method, and determining the food safety risk grade of each province, city and district (county). According to the method, multi-level and data-driven accurate evaluation of food safety risks can be realized, a scientific sampling inspection decision basis is provided for supervision departments, supervision efficiency is improved, resource allocation is optimized, and public food safety is guaranteed.

The invention relates to the technical field of food detection, in particular to a GC-IMS-based food freshness detection method, device and equipment, and the method comprises the following steps: obtaining headspace sampling gas of a to-be-detected food sample; according to the type of the to-be-detected food sample, automatically matching preset chromatographic conditions and ion mobility spectrometry conditions from a graded food type database; the headspace sampling gas is injected into GC-IMS, analysis is carried out based on matched chromatographic conditions and ion mobility spectrometry conditions, and a volatile organic compound fingerprint spectrum of the sample is obtained; and extracting preset key feature information from the fingerprint spectrum, and inputting the key feature information into a food freshness evaluation model to obtain a freshness evaluation result of the to-be-detected food sample. Therefore, the problems that in the prior art, detection parameter curing lacks adaptability, key feature analysis is not accurate, and model prediction accuracy is insufficient are solved.

The invention relates to a food water content calculation method and device based on a visual image, equipment and a medium. First, food image data is collected, and first image data is obtained by using a standardized preprocessing technology. Secondly, extracting surface glossiness and texture feature values from the first image data, segmenting the image by using a feature detection algorithm, marking a key region related to the water content, and forming a visual feature set; thirdly, the relevance of all elements in the visual feature set is analyzed, food types are distinguished through a classification rule, feature weight distribution of different types of food is determined, and optimization of feature description is achieved; and finally, based on the optimized feature description, establishing a mapping relation model between the water content and the visual features, substituting a newly input food image into the model, predicting the water content, and outputting a real-time detection result. An efficient and convenient detection means is provided for the fields of food processing, storage and the like, the detection cost is reduced, and the production efficiency and the product quality control capability are improved.

The invention discloses a personalized recipe recommendation system, a recommendation method and an interaction system, and relates to the technical field of diet recommendation, the system comprises a user data collection module, a food image recognition module and a personalized recommendation module, the user data collection module is used for obtaining health data and diet preference data of a user, the health data comprises basic information, health conditions and exercise habits, the basic information comprises regions, the health conditions comprise allergen lists, chronic diseases and diet targets, and the food image recognition module is used for obtaining food photos uploaded by a user, recognizing the food photos to obtain food recognition results and sending the food recognition results to the user. The food identification result comprises a food type corresponding to the food photo, and the personalized recommendation module is used for determining a recommended recipe recommended to the user based on the health data, the diet preference data and the food identification result. By considering more comprehensive influence factors, a more suitable and personalized recipe can be recommended to the user.

The invention relates to the technical field of artificial intelligence application, in particular to a personalized diet suggestion method, system and equipment based on a large language model.The method comprises the steps that meal information input by a user is received, and the meal information comprises food pictures or text descriptions; processing the meal information, and identifying food types and quantity; calculating the nutrient content of the current meal in combination with a nutrient database according to the identified food type and quantity; generating a personalized nutritional demand based on the user basic information and the health condition, and determining a demand gap between the nutritional content of the current meal and the personalized nutritional demand; inputting the nutrient content, the demand difference, the user diet preference data and the medicine and food homology data of the current meal into a large language model, and generating the nutrition evaluation of the current meal and the personalized diet suggestion of the next meal; and feeding back the nutrition evaluation and the personalized diet suggestion to a user through a visual interface. And scientific and reasonable diet of the user can be realized.

The present invention relates to a smart home cooking system using an artificial intelligence device, comprising: at least one cooking utensil provided to cook food ingredients; and the artificial intelligence device that is provided to identify a speech command of a user and control the cooking utensil to cook the food ingredients according to the identified speech command, learns a preferred food of the user and a preferred food type of the user according to a food cooking history of the user, detects, when there is a request of the user, at least one food recipe according to the preferred food of the user or the preferred type of the user from among a pre-stored plurality of recipes, on the basis of a result of the learning, and provides the detected at least one food recipe to the user as a recommended food recipe.

The invention discloses a food frying process online monitoring method and system, and relates to the technical field of food processing monitoring. The method comprises the following steps: transmitting a frequency-adjustable ultrasonic signal to a frying medium, receiving a response signal after the medium acts on food, and filtering; according to the comparison result of the amplitude attenuation rate of the response signal and the threshold value, the ultrasonic emission frequency is dynamically adjusted; performing feature extraction on the preprocessed signal to form a feature vector containing amplitude, frequency and energy features; inputting the feature vector into a judgment model trained by a dynamic frequency sample, and outputting a current frying state; and a control instruction of the frying equipment is generated so as to realize process regulation and control. Through combination of frequency-controlled ultrasonic excitation and acoustic feature extraction, the method can adapt to different grease environments and food types, gives consideration to the signal penetration depth and the signal-to-noise ratio, achieves non-destructive, real-time and quantifiable monitoring of the frying process, and remarkably improves the cooking state recognition precision and monitoring consistency.

The invention relates to a heart failure patient water inflow monitoring system and method based on intelligent water content evaluation, and the system can monitor and evaluate the inflow of a heart failure patient every time through a weight sensor, a three-dimensional camera, a clinical terminal and a nurse station background on a clinical dining carrier. Comprising the food type, the weight and the water content ratio of the current food to be eaten, and the total weight and the total water content of the food eaten this time, and generating a daily in-out report in combination with the sunrise of the heart failure patient. In this way, the daily incoming and outgoing amount of the heart failure patient can be accurately evaluated, specific parameters of the eaten food can be counted in detail and the total water content of the eaten food can be evaluated in detail without tracking and recording of nurses, the subsequent diet balance adjusting strategy is greatly influenced, visual eating data are automatically provided for background doctors, and the efficiency is improved. Doctors can conveniently adjust nursing or rehabilitation and diagnosis and treatment schemes according to the in-out amount of the patient.

The invention discloses a diet management system for diabetic patients, which relates to the technical field of intelligent diet management and is technically characterized by comprising a data acquisition module, a nutrition analysis and suggestion generation module, a blood glucose prediction module, a feedback learning module, a personalized strategy recommendation module, an excitation and verification module and a communication module, the system automatically collects health and diet data of a user through a camera, a body fat scale, a glucometer and wearable equipment, identifies food types and estimates components by using a convolutional neural network, and realizes automatic calculation of energy and nutritional ingredients. The food-blood glucose response model constructed on the basis of individual historical data can predict postprandial blood glucose changes, sensitivity coefficients are dynamically updated through a regression correction mechanism, individualized blood glucose prediction is achieved, the system further generates intake suggestions through a component back-calculation method, and the intake suggestions and the intake suggestions are given to a user. And the result is visually displayed on the terminal in the form of a blood glucose curve and an energy distribution diagram, and real-time diet guidance is provided.

The embodiment of the invention discloses a multi-modal fusion food recognition large model construction and application method and system, and the method comprises the steps: obtaining a multi-modal training data set, carrying out the combined training of multi-modal training data in the multi-modal training data set, and obtaining a multi-modal fusion food recognition large model; obtaining multi-modal data of food to be identified; performing feature extraction and fusion on the multi-modal data through a multi-modal fusion food identification large model to obtain corresponding fusion feature information; and based on the fusion feature information, utilizing a multi-modal fusion food identification large model to carry out food type identification and nutritional ingredient analysis, and outputting an identification result and a nutrition suggestion. According to the embodiment of the invention, the method achieves the recognition of the to-be-recognized food based on the multi-modal data of the to-be-recognized food through the powerful learning and reasoning capabilities of a large model, achieves the more accurate and comprehensive recognition of the food, and improves the recognition accuracy and reliability of the food.

The present application relates to a terminal device for blood sugar management during pregnancy and its cloud server, the terminal device collects physiological data and blood sugar data of a target user including the gestation period, the cloud server obtains a plurality of blood sugar data of reference users from a plurality of terminal devices and forms an overall reference data set in a manner associated with gestational age, the cloud server calculates basic statistical indicators for each group in the overall reference data set, combines the specific percentile position of the user's blood sugar data in its own group distribution, judges the current blood sugar state of the user by comparing the user's blood sugar data with the preset healthy blood sugar range, and generates a graded diet suggestion accordingly, the diet suggestion optimizes the diet structure of the target user by selecting food categories with different GI values; the terminal device receives and visually displays personalized diet suggestions matching the blood sugar status of the target user to the target user.

Containers for facilitating adherence to dietary plans are provided, along with related systems and methods. A locking mechanism secures an access panel moveable between an opened position and a closed position in the closed position. A controller receives user input regarding desired caloric intake amount for a time period and regarding a type or types of foodstuff stored at the container, and weight readings from at least one weight sensor. The controller determines a caloric value of removed foodstuffs from the containers from the weight readings and the type or types of foodstuff indicated in the user input, and operates the locking mechanism to secure the access panel in the closed position where the caloric value of the removed foodstuffs for the time period exceeds the desired caloric intake amount for the time period.

A bird feeder device is provided. The device is comprised of a housing with generally parallel side walls, a rear wall, a top wall, and a bottom wall, with at least one tail brace wall on the bottom wall allowing birds to brace their tail while feeding. The housing has a front opening for bird access to food placed inside, safeguarded by a removable screen insert that can be introduced through an opening in the top wall, covering the front opening to regulate access based on food type. Additionally, the housing incorporates at least one fastener for suspending the device at an angle conducive to gravity-fed food movement towards the front opening, with design considerations such as a top wall overhang and the suspended angle of the device that aim to deter larger birds from feeding and support smaller birds.

The application discloses a method for determining food type of an electric pressure cooker and related components, and relates to the technical field of home appliance control. First, a heating module is controlled to work at a first preset working power. When the pressure in the electric pressure cooker reaches a preset pressure range, the heating control module stops working and the number of pressure signal actions is increased by one, so that the food type is determined based on the number of pressure signal actions subsequently. When the working time of the electric pressure cooker does not reach a preset detection time, the heating module is continuously controlled to repeat the above steps until the working time reaches the preset detection time. The food type of the food to be cooked is determined by the number of pressure signal actions of the electric pressure cooker within the preset detection time, so that the cooking mode corresponding to the food type is adjusted, and problems such as cooking failure affecting the user experience are avoided.

A micro puree machine including a drive motor coupled to a drive shaft via at least one gear. The drive motor is arranged to rotate a drive shaft and blade assembly. A position motor is operable to change a position of the drive shaft via rotation of the position. A user interface is arranged to: i) receive a user input to select a first routine associated with processing a first food type, and ii) display a status of the processing of the first food type while the first routine is running. A controller is arranged to: i) receive the user input selecting the first routine and retrieve the configuration data associated with the first routine, ii) control operations of the drive motor based on the configuration data associated with the first routine, and iii) control operations of the position motor based on the configuration data associated with the first routine.

The application relates to the technical field of multi-modal data processing, and discloses a food nutrition ingredient content intelligent evaluation method, system, terminal and storage medium based on a multi-modal large model, the method comprising the following steps: obtaining multi-modal data and performing pretreatment to obtain target multi-modal data; adopting a pre-trained multi-modal large model to perform feature extraction, feature alignment and feature fusion on the target multi-modal data to obtain multi-modal fusion features; when a new food type appears, updating parameters of an intermediate deep learning model through an incremental learning and memory enhancement mechanism to obtain a target deep learning model; and inputting the multi-modal fusion features into the target deep learning model to output a nutrition ingredient content evaluation result. Through the multi-modal large model and the continuous learning algorithm, high-precision dynamic evaluation of food nutrition ingredients is realized, the emergence of new food types can be adapted to, and high-precision evaluation of old food types can be maintained.

The invention provides an intelligent dinner plate based on multispectral thermal imaging fusion, and belongs to the technical field of intelligent dinner plates. The multi-mode sensing module collects physical and chemical information of food in the dinner plate; the edge calculation and main control module executes real-time data processing at an equipment end; the lightweight food identification and segmentation model is used for identifying food types based on multispectral image data and segmenting areas of the food; the multi-sensor data fusion algorithm is used for fusing the food types, the area proportion information and the total weight, estimating the initial weight of each kind of food based on a pre-trained density factor, and outputting a structured list containing the food types and the initial weights; the cloud nutrition calculation engine receives the structured list and the related hyperspectral feature data, and queries and identifies standard nutritional ingredients of the food from a nutrition database; and calibrating the initial weight by using the hyperspectral characteristic data, and calculating and summarizing the total nutritional ingredients and total calorie of the whole meal based on the calibrated weight and the finely-adjusted nutritional ingredients.

The present invention provides an apparatus and method for cooking food in a pressurized steam oven, wherein the food is steam cooked in a first stage and grilled in a next stage. The method automatically identifies the time of the first stage (slow) cooking and the time of the second stage (fast) cooking based on the type, size, temperature and 3d image of the food. The slow cooking stops when the food reaches the critical temperature by an amount determined by various parameters and then starts the quick cooking of frying and baking. The slow cooking method may be a pressurized steam cooking method. The method automatically reduces the time of slow cooking so that the internal temperature of the food does not prematurely reach the critical temperature. The method helps to avoid overcooking of food during the grilling phase.

The invention discloses a nutrition regulation and control method based on natural feeding habits of dogs and cats and a matched composition, and belongs to the technical field of pet food. The method comprises the following steps: S1, determining original hunting habits of dogs and cats, and obtaining food types, food sources and food structure data of the dogs and cats in a natural state; s2, based on the original hunting habit data, designing and providing a periodic food composition composed of a plurality of different formulas; s3, feeding different formulas in the periodic food composition in turn according to a predetermined sequence to realize diverse diet; s4, evaluating the influence of the periodic food composition on gastrointestinal health indexes and allergy occurrence probability of dogs and cats through principal component analysis and logistic regression analysis models; and S5, dynamically adjusting the formula or feeding sequence of the periodic food combination according to the evaluation result of the S4. Natural hunting diversity is simulated through periodic food combination, and the problems of nutrition imbalance, intestinal flora imbalance and the like caused by long-term single diet are solved.

This technology provides a way to simplify the selection of colorants and their amounts. [Solution] The food image provision system 1 includes a storage unit 11 that stores data D2 for displaying food images of colored foods using coloring agents, food image information D1 that associates the coloring agent added to the colored food with the amount of coloring agent added, a receiving unit 12 that can receive a specification of at least one of the following: food type, food shape, color classification of the coloring agent, coloring agent, and amount added, and an output unit 13 that can provide at least one food image corresponding to the specification received by the receiving unit 12. The output unit 13 is capable of performing the following processes: providing a first food image associated with the coloring agent and amount added, and providing a second food image that has the same food shape as the first food image associated with the coloring agent and amount added.

The embodiment of the application provides an ohmic heating equipment control method and device, electronic equipment and a storage medium, which determine a heating rate database in a normal working state of ohmic heating equipment; determine the food type of food in the ohmic heating equipment in response to a starting operation of the ohmic heating equipment; then determine a first heating rate when the ohmic heating equipment heats the food, and acquire a second heating rate corresponding to the same food type in the heating rate database; further judge whether the ohmic heating equipment has an electrode pollution phenomenon according to the first heating rate and the second heating rate; if it is determined that the ohmic heating equipment has the electrode pollution phenomenon, the user is informed of a cleaning mode of the ohmic heating equipment. Real-time monitoring and early identification of the electrode pollution state of the ohmic heating equipment are realized, the long-term operation efficiency of the ohmic heating equipment is improved, the service life of the equipment and the heating effect of the food are improved, and the maintenance cost of the equipment is reduced.

A micro puree machine including a drive motor coupled to a drive shaft via at least one gear. The drive motor is arranged to rotate a drive shaft and blade assembly. A position motor is operable to change a position of the drive shaft via rotation of the position. A user interface is arranged to: i) receive a user input to select a first routine associated with processing a first food type, and ii) display a status of the processing of the first food type while the first routine is running. A controller is arranged to: i) receive the user input selecting the first routine and retrieve the configuration data associated with the first routine, ii) control operations of the drive motor based on the configuration data associated with the first routine, and iii) control operations of the position motor based on the configuration data associated with the first routine.

The invention relates to the technical field of temperature measurement based on a food type self-adaptive temperature measurement strategy, and discloses a temperature measurement method and device based on the food type self-adaptive temperature measurement strategy and a medium. The temperature measurement process can adapt to the heat conduction characteristics of different foods, the pertinence of temperature acquisition is improved, the adaptive optimization of the temperature measurement strategy is realized by acquiring detection data of each probe and dynamically adjusting the weight of the probe according to the detection data, the system can accurately reflect the change of the internal temperature gradient, and finally, the real-time temperature is subjected to weighted fusion, so that the accuracy of temperature measurement is improved. And the measured temperature of the food to be subjected to temperature measurement is obtained. The method has the beneficial effects that the problems that a traditional temperature measurement method is inaccurate in measurement, cannot reflect the gradient, depends on manual operation and the like are effectively solved, and the temperature measurement precision, the operation convenience and the final cooking quality stability of the intelligent cooking equipment are remarkably improved.

The invention relates to a cooking equipment control method and device, equipment and a storage medium, and the method comprises the steps: determining a target cooking space and a target cooking temperature of a to-be-cooked food material according to a target food material parameter of the to-be-cooked food material; the target food material parameters comprise one or more of the following: a target food material type, a target food material weight, a target food material area and a target food material volume; determining the position of a partition plate according to the target cooking space; and the first heating assembly and the second heating assembly are controlled, and the to-be-cooked food materials are heated according to the target cooking temperature.

According to the daily diet nutrition analysis method based on the wireless weighing record, the intelligent nutrition scale can collect the food weight and conduct peeling calculation, and the net diet weight is accurately obtained. Through peeling calculation, weight interference of non-food parts such as containers can be eliminated, it is ensured that data uploaded to a cloud analysis background is the real food weight, and a foundation is laid for follow-up accurate nutrition analysis. The cloud analysis background can record the data in time and bind the data with the user ID, so that the diet data of each user can be independently stored and managed, and subsequent personalized nutrition analysis and health management for the user are facilitated. After the cloud analysis background records the data, a nutrition analysis notice or a food type selection input notice is sent to the user terminal in time. The timely notification mechanism can improve the participation degree and the response speed of the user, and ensures that the whole nutrition analysis process is efficiently carried out. The user can quickly log in the cloud analysis background to perform subsequent operation according to the notification, and waiting time is shortened.

The invention discloses an intelligent food water content monitoring dinner plate, and relates to the field of health management, and the dinner plate comprises a plurality of food storage areas, a total weight display unit and a total water content display unit; the food storage areas comprise a staple food area, a vegetable area and an other food area, each food storage area comprises a plurality of food type selection buttons and a weight monitoring module, and the total weight display unit is used for calculating and displaying the total weight of food according to a weight measurement value of the weight monitoring module of each food storage area; and the total water content display unit is used for calculating and displaying the total water content of the food according to the food type selection information of the food type selection button of each food storage area and the weight measurement value of the weight monitoring module. According to the dinner plate, the dynamic water content of various kinds of food is accurately calculated through weight monitoring, food type selection and water content parameter mapping, the measurement accuracy is improved, the total amount display module provides diet overview, and nursing management is facilitated.

The present application relates to the field of refrigerator control technology, and in particular to a control method, system, refrigerator control panel, and product for a refrigerator control panel. The method includes: upon receiving a refrigerator door opening signal, identifying the type of food the user wants to place; obtaining the temperature distribution in the refrigerator, determining a recommended placement area based on the food type and temperature distribution, displaying the recommended placement area to the user, and recording the placement time of the current food; obtaining the placement time and food type of each food in the refrigerator, determining the optimal storage deadline for each food based on the placement time and food type of each food; determining whether there is food deterioration in the refrigerator; and issuing a warning signal when any food in the refrigerator reaches the corresponding optimal storage deadline, or when it is determined that there is food deterioration in the refrigerator. The present application can effectively extend the shelf life of food and reduce food waste.

The invention provides a food risk prediction method, and the method comprises the steps: inputting to-be-predicted data into a food risk prediction model for risk prediction, and obtaining a first risk prediction result, the food risk prediction model being obtained through training according to a sample training data set; obtaining a historical data set, and merging the first risk prediction result with the historical data set to obtain a new training data set; training a food risk prediction model through the new data set to obtain a trained food risk prediction model; and performing risk prediction on the target data through the trained food risk prediction model to obtain a risk prediction result of the target data. According to the method, the problems of difficulty in data acquisition, transnational regulation complexity and high evaluation difficulty caused by diversified food types in an imported food risk reasoning algorithm model can be solved, and potential food safety risk identification and evaluation can be effectively improved, so that the overall supervision efficiency is improved.

The invention discloses a conveyor line intelligent detection method and system based on machine vision, and relates to the field of product detection.The method comprises the steps that running speed information and food type information of a conveyor line are obtained; food image information of a target area of the conveying line is obtained; the running speed information, the food type information and the food image information are input into a food defect detection model to obtain food defect information, and the food defect detection model fuses the food image information, the running speed information and the food type information and combines shape coding and attention enhancement to obtain the food defect information. Therefore, various food defect identification and scores can be obtained. According to the method, the adaptability, the precision and the practicability of the intelligent detection system of the food conveying line are remarkably improved by fusing technologies such as multi-modal perception, structural modeling and attention enhancement.