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A dietary nutrition analysis method based on face recognition self-service dining system

A technology of face recognition and nutrition analysis, applied in the field of artificial intelligence, can solve problems such as inability to obtain accurate data, inability to obtain nutritional content, and inability to control diet, etc., to achieve clean payment methods, avoid direct transactions of cash or credit cards, and improve health horizontal effect

Active Publication Date: 2022-05-17
SHANDONG SYNTHESIS ELECTRONICS TECH
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  • Abstract
  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0013] With the strengthening of people’s awareness of health management, facing so many unhealthy eating habits and uncontrollable diets, people want to know whether their nutrition is balanced. At present, there is no suitable tool to calculate it, because the types of food contained in each dish are too large. It is not easy to calculate, it is impossible to obtain accurate data, and it is impossible to know how many nutrients are ingested

Method used

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  • A dietary nutrition analysis method based on face recognition self-service dining system
  • A dietary nutrition analysis method based on face recognition self-service dining system
  • A dietary nutrition analysis method based on face recognition self-service dining system

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Embodiment Construction

[0069] A specific embodiment of the present invention will be described in detail below in conjunction with the accompanying drawings, but it should be understood that the protection scope of the present invention is not limited by the specific embodiment.

[0070] Such as figure 1 Shown, the present invention comprises the following steps:

[0071] Step 1: Data storage of nutritional information of dishes, Step 2: Setting and saving of personal data information of dining users, Step 3: Registration of dining users’ faces, binding of face recognition and payment accounts during meals, Step 4: Self-service meal pick-up on demand, Accurate measurement, step 5: senseless payment: the system automatically deducts the fee according to the weighed weight * fixed unit price of the dish in the payment account bound to the face registration, step 6: nutritional analysis.

[0072] Described step one concrete steps are as follows:

[0073] Step 11: Save all the nutritional components o...

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Abstract

The invention discloses a diet nutrition analysis method based on a face recognition self-service dining system, which comprises the following steps: step 1: data storage of nutritional component information of dishes; step 2: setting and saving personal data information of dining users; step 3: dining users Face registration, face recognition and payment account binding when dining; Step 4: Self-service meal pick-up on demand, accurate measurement; Step 5: Non-inductive payment: The system automatically uses the weighted amount in the payment account bound to face registration The fixed unit price of the weight * dishes will be deducted; Step 6: Nutritional analysis. The perfect meal ordering system and the non-inductive payment of face recognition technology make the payment method cleaner and more efficient, avoiding direct transactions in cash or swiping cards. The billing desk of the meal ordering system automatically weighs and measures in grams, and the server pushes nutritional analysis through big data calculations, reminding people in real time whether their intake is balanced and reasonable, and sending people dietary health guidance and advice through WeChat.

Description

technical field [0001] The invention relates to the field of artificial intelligence, in particular to a method for analyzing diet and nutrition based on a face recognition self-service dining system. Background technique [0002] In order to actively promote the "Internet + nutrition and health" service and promote the application of big data, and drive the development of the information technology industry oriented by nutrition and health, at the same time, the health data of Chinese teenagers is not optimistic: 80% of students have poor breakfast nutrition, and the incidence of anemia in adolescence Up to 38%, the incidence of fatty liver among obese children in the country is 40%-50%. The current survey by the Chinese Academy of Preventive Medicine shows that the protein intake of nearly 270 million school students in China is only 65% ​​of the standard amount, the calcium, iron, and zinc are seriously deficient, and the vitamin intake is only 15% of the standard amount....

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G16H20/60G06Q20/40
CPCG16H20/60G06Q20/40145
Inventor 谭雪欣马文英王卫中许辰郭恩英肖贺韩永青王占鹏刘佳
Owner SHANDONG SYNTHESIS ELECTRONICS TECH
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