9 results about "Food purchasing" patented technology

The invention belongs to the technical field of food additive detection, and particularly relates to a food additive detection method based on artificial intelligence, which comprises the following steps: S1, shooting a package ingredient table to obtain a package ingredient table photo; s2, transmitting the shot photo to a cloud for AI identification, and extracting additive names and dosage data on the photo; s3, establishing a food additive early warning database according to WHO, EFSA and GB2760 international and domestic authoritative databases; s4, the extracted additive data is compared with data in a food additive early warning database, and related information output and early warning are carried out. People can rapidly and conveniently know the risk levels, effects and potential influences on health of various additives in the food purchasing process; therefore, people are helped to purchase and select food, and body health and safety are guaranteed.

The invention discloses a fresh food distribution method and system. Receiving fresh food purchase order information generated by the client; extracting article information and address information from the purchase order information of the target fresh food; based on the article information and the logistics address information, determining a fresh food distribution priority, a distribution mode and a distribution path; and determining delivery order information according to the fresh food delivery priority, the delivery mode and the delivery path. According to the invention, the information of the fresh food and the address information of the customer are determined based on the purchase information of the customer, and the type, the refreshing time and the storage condition of the food are determined according to the food information, so that the packaging mode and the delivery priority of the food are intelligently determined, and the delivery path is reasonably generated in combination with the address information. According to the method, the food which is most easy to expire is intelligently and preferentially distributed, so that the freshness of the food after distribution is ensured, the reasonability of food distribution and the safety of the food are effectively ensured, and the user experience is greatly improved.

To provide a system.SOLUTION: A system includes: means for coordinating with shopping information and merchandise information of supermarkets; means for proposing a recipe according to a price, calories, and a stock status; and means for referring to food material purchase history of a user, and for proposing a recipe based on the specific calories and budget.SELECTED DRAWING: Figure 1

A home appliance control method and an electronic device for performing the method can be provided. Particularly, a food purchasing method and a refrigerator for performing the method can be provided, the method comprising the operations of: acquiring a food list including a plurality of food items required to be purchased for a refrigerator; selecting the plurality of food items to be purchased from the food list; determining a plurality of candidate purchasing locations on the basis of the plurality of selected food items, a plurality of pre-collected user preference conditions, and priorities among the plurality of user preference conditions; and displaying the plurality of candidate purchasing locations according to the priorities.

We provide the system. [Solution] A device for inputting user preference information and recording said preference information, A device for selecting suitable food based on the aforementioned preference information, In order to collect supplementary information regarding the selected food, a device that works in conjunction with other devices is used. A device that presents the selected food and supplementary information to the user, A device for completing the procedure for purchasing the aforementioned food, A device that reflects the user's past history and presents food and beverage combinations, A system that includes this.

A system for dietary adjustment based on individual eating habits, the system comprising at least one processor, according to an embodiment of the disclosed invention: is configured to receive purchased food list data including information on the types and amounts of purchased foods purchased by a user and information on an expected consumption period which is a food purchasing cycle planned and preset by the user; and on the basis of the purchased food list data, the information on the expected consumption period, and eating habit information of the user, may generate at least one of information on the type and amount of a user-customized recommended food for purchase, which needs to be additionally purchased, and information on the type and amount of a consumption-deferred food, which needs to be left uneaten until the next food purchasing time.

An advanced food storing, dispensing, and packaging system, including the use of computing and communications technology to both monitor and improve quality of food. The storing and dispensing system can also integrate with better packaging. Such a system and technology is used to create a better way to acquire and control food quality, whether delivered or not, raw or cooked, that is fresher when monitored, whether it waits to be delivered for immediate consumption or is acquired raw or in bulk and stored in a home pantry. This technology can be further leveraged to enable patrons to access and transact a food purchase without waiting in a checkout line including food that is not required to be specially packaged in order to be recognized by video analytics.

This invention discloses a consumer behavior-driven carbon credit conversion method and application system. By collecting purchase data of near-expiry food, the system calculates emission reductions by category carbon reduction coefficient multiplied by measurement, and maps these reductions to carbon credits in real time (1kg CO₂e = 10 credits, error ≤5%), and connects to a third-party carbon trading platform. This solves the problems of coarse calculations and poor real-time performance in existing methods, and can accurately incentivize users to engage in green consumption. It is suitable for carbon credit scenarios on community O2O platforms.

Nutrient prediction systems and methods can include systems and methods of training and testing machine-learning models and food purchase data collection and analysis. For example, a food purchase data collection and analysis system, under the control of at least one processor, can include a purchase data collection device to collect food purchase data at a point of sale of a food basket including information regarding food items purchased and location of the food purchase, an analysis server including a machine-learning model predicting nutrient availability based on the food purchase data, and a network for transmitting the food purchase data from the purchase data collection device to the analysis server for analysis using the machine-learning model.