WO2017092030A1 - 智能膳食推荐方法、终端及智能膳食推荐云端服务器 - Google Patents

智能膳食推荐方法、终端及智能膳食推荐云端服务器 Download PDF

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Publication number
WO2017092030A1
WO2017092030A1 PCT/CN2015/096405 CN2015096405W WO2017092030A1 WO 2017092030 A1 WO2017092030 A1 WO 2017092030A1 CN 2015096405 W CN2015096405 W CN 2015096405W WO 2017092030 A1 WO2017092030 A1 WO 2017092030A1
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user
recipe
meal recommendation
smart meal
smart
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PCT/CN2015/096405
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English (en)
French (fr)
Inventor
黄翔祺
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内蒙古伊利实业集团股份有限公司
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Priority to PCT/CN2015/096405 priority Critical patent/WO2017092030A1/zh
Publication of WO2017092030A1 publication Critical patent/WO2017092030A1/zh

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q30/00—Commerce

Definitions

  • the invention relates to the field of information automatic push technology, in particular to a method for recommending a corresponding dish/restaurant for different users, in particular to a smart meal recommendation method, a terminal and a smart meal recommendation cloud server.
  • the electronic scale and the food database are generally used for the determination of food calories and nutrients.
  • the user due to different data such as the name, composition, brand, manufacturer, and taste of various foods, the user must perform data search in the database. Finding the corresponding food in a one-by-one way is therefore time consuming.
  • it is not able to help users manage their daily diet, nor can they measure the calories taken by users daily, weekly, or longer, and give warnings of excessive or insufficient intake, so that users can not truly grasp themselves. The diet, therefore, can not improve the habit of eating improperly.
  • the technical problem to be solved by the present invention is to provide a smart meal recommendation method, a terminal, and a smart meal recommendation cloud server, which solves the problem that the prior art cannot propose a meal plan according to the user's personal health condition.
  • a specific embodiment of the present invention provides a smart meal recommendation method, including: acquiring personal health information of a user; locating the geographic location of the user, and uploading the geographic location to the cloud server; acquiring the cloud server according to The recipe of the user-adjacent restaurant determined by the geographical location; screening the recommended recipe display from the recipe based on the personal health information to the user.
  • a smart meal recommendation terminal comprising: a personal information acquisition unit, configured to acquire personal health information of the user; a positioning unit, configured to locate a geographic location of the user, and the geographic location Uploading to the cloud server; the recipe obtaining unit is configured to obtain a recipe of the user surrounding the restaurant determined by the cloud server according to the geographical location; and a screening unit, configured to filter the recommended recipe display from the recipe based on the personal health information to the user .
  • Another embodiment of the present invention further provides a smart meal recommendation method, comprising: receiving a geographic location uploaded by a smart meal recommendation terminal; and determining a recipe of the surrounding restaurant of the user according to the geographic location.
  • Another embodiment of the present invention further provides a smart meal recommendation cloud server, including: a first receiving unit, configured to receive a geographic location uploaded by the smart meal recommendation terminal; and a first recipe determining unit, configured to use the geographic location according to the geographic location Determine the recipes of the restaurants around the user.
  • Another embodiment of the present invention further provides a smart meal recommendation method, including: acquiring personal health information of a user; acquiring a geographic location of the user from the smart meal recommendation terminal; and surrounding the user's surrounding restaurant according to the geographic location a recipe; selecting a recommended recipe from the recipe based on the personal health information; and pushing the recommended recipe to the smart meal recommendation terminal.
  • Another embodiment of the present invention further provides a smart meal recommendation cloud server, comprising: an information acquisition unit, configured to acquire personal health information of the user; and a second receiving unit, configured to acquire a geographic location of the user from the smart meal recommendation terminal a second recipe determining unit, configured for a recipe of the surrounding restaurant of the user according to the geographical location; a recipe screening unit, configured to filter the recommended recipe from the recipe based on the personal health information, and push the recommendation to the smart meal a terminal; a pushing unit, configured to push the recommended recipe to the smart meal recommendation terminal.
  • a smart meal recommendation cloud server comprising: an information acquisition unit, configured to acquire personal health information of the user; and a second receiving unit, configured to acquire a geographic location of the user from the smart meal recommendation terminal a second recipe determining unit, configured for a recipe of the surrounding restaurant of the user according to the geographical location; a recipe screening unit, configured to filter the recommended recipe from the recipe based on the personal health information, and push the recommendation to the smart meal a terminal; a pushing unit, configured to
  • the smart meal recommendation method, the terminal, and the smart meal recommendation cloud server have at least the following advantages or features: the smart meal recommendation terminal is used to locate the geographic location of the user, and the cloud server determines according to the geographic location.
  • the surrounding restaurants and their recipes; the smart meal recommendation terminal screens the restaurants and their recipes with reasonable calories and nutrients from these restaurants and their recipes based on the user's personal health information, and displays these restaurants and their recipes, so that According to the user's personal physical condition, the user is provided with a reasonable meal plan.
  • the present invention can also provide dietary suggestions according to the health needs set by the user, improve the habit of improper eating, and can effectively prevent or reduce the user's high blood fat, high blood pressure, and high Diseases such as blood sugar, while ensuring that users receive appropriate energy and nutrients to meet the needs of the body.
  • Embodiment 1 is a flowchart of Embodiment 1 of a smart meal recommendation method according to a specific embodiment of the present invention
  • Embodiment 2 is a flowchart of Embodiment 2 of a smart meal recommendation method according to an embodiment of the present invention
  • Embodiment 3 is a flowchart of Embodiment 3 of a smart meal recommendation method according to an embodiment of the present invention
  • Embodiment 4 is a flowchart of Embodiment 4 of a smart meal recommendation method according to an embodiment of the present invention
  • FIG. 5 is a block diagram of Embodiment 1 of a smart meal recommendation terminal according to a specific embodiment of the present invention.
  • FIG. 6 is a block diagram of Embodiment 2 of a smart meal recommendation terminal according to an embodiment of the present invention.
  • FIG. 7 is a block diagram of a recommendation unit of a smart meal recommendation terminal according to an embodiment of the present invention.
  • FIG. 8 is another block diagram of a recommendation unit of a smart meal recommendation terminal according to an embodiment of the present invention.
  • Embodiment 9 is a flowchart of Embodiment 5 of a smart meal recommendation method according to an embodiment of the present invention.
  • FIG. 10 is a block diagram of a first embodiment of a smart meal recommendation cloud server according to an embodiment of the present invention.
  • FIG. 11 is a flowchart of Embodiment 6 of a smart meal recommendation method according to an embodiment of the present invention.
  • FIG. 12 is a flowchart of Embodiment 7 of a smart meal recommendation method according to an embodiment of the present invention.
  • FIG. 13 is a flowchart of Embodiment 8 of a smart meal recommendation method according to an embodiment of the present invention.
  • FIG. 14 is a flowchart of Embodiment 9 of a smart meal recommendation method according to an embodiment of the present invention.
  • FIG. 15 is a block diagram of a second embodiment of a smart meal recommendation cloud server according to an embodiment of the present invention.
  • FIG. 16 is a block diagram of a third embodiment of a smart meal recommendation cloud server according to an embodiment of the present invention.
  • FIG. 17 is a block diagram of a recipe screening unit of a smart meal recommendation terminal according to an embodiment of the present invention.
  • FIG. 18 is another block diagram of a recipe screening unit of a smart meal recommendation terminal according to an embodiment of the present invention.
  • FIG. 19 is a schematic diagram of an application interface of an example 1 of a smart meal recommendation system according to an embodiment of the present invention.
  • FIG. 20 is a schematic diagram of an application interface of an example 2 of a smart meal recommendation system according to an embodiment of the present invention.
  • 21 is a schematic diagram of an application interface of an example 3 of a smart meal recommendation system according to an embodiment of the present invention.
  • FIG. 22 is a schematic diagram of an application interface of an example 4 of a smart meal recommendation system according to an embodiment of the present invention.
  • FIG. 1 is a flowchart of Embodiment 1 of a smart meal recommendation method according to an embodiment of the present invention.
  • a smart meal recommendation terminal is used to locate a geographic location where a user is located, and the cloud server determines a user perimeter according to a geographic location.
  • the restaurant and its recipes; the smart meal recommendation terminal selects the restaurants and their recipes with reasonable calories and nutrients from these restaurants and their recipes based on the user's personal health information, and displays these or the restaurant and its recipes.
  • Step 1 Obtain the user's personal health information.
  • the personal health information includes at least one of user vital sign data, meal plan data, historical diet data, and user medical record data.
  • the personal health information can be stored in the user terminal (ie, the smart meal recommendation terminal), or can be stored in the cloud server. The information needs to be input by the user in advance or imported through the desktop computer, and the user can modify the personal health information after logging in to the system.
  • Step 2 Locate the geographic location of the user and upload the geographic location to the cloud server.
  • the location of the smart meal recommendation terminal can be located through a GPS (Global Positioning System) chip built in the smart meal recommendation terminal (or mobile terminal), thereby obtaining the geographical location of the user, and then uploading the geographic location to the cloud server.
  • GPS Global Positioning System
  • Step 3 Obtain a recipe of the surrounding restaurant of the user determined by the cloud server according to the geographical location.
  • the cloud server stores all the restaurant and its recipe information. After the restaurant operator logs in to the cloud server, the restaurant and its restaurant can be uploaded or modified.
  • the recipe information includes the recipe ingredients, the weight of the ingredients, the oil content of the recipe, the salt content of the recipe, the sugar content of the recipe, and the like.
  • the information can be used to determine the calorie and nutrient composition information of the recipe, and the information can also be used to determine the recipe.
  • the information of the degree of pungency, greasyness, etc.; the cloud server can determine the recipe of the surrounding restaurant according to the geographical location, and the smart meal recommendation terminal obtains the recipe of the surrounding restaurant from the cloud server.
  • Step 4 Filter the recommended recipe display from the recipe based on the personal health information to the user. Because each user has different physical characteristics, different health indexes, different eating habits, and different religious beliefs, the demand for calories and nutrients is different. For example, for two healthy users, usually, the calorie needs of large-weight users. Relative to the heat demand of light weight users, of course, also refer to the user's historical diet; for the same user, the calorie planning stage requires less calories than usual; for different people, it is growing body Middle school students have a wider demand for nutrients than adults.
  • the present invention can further filter the surrounding restaurants and recipes according to the personal needs of the user, and recommend the delicious foods that meet the health needs of the users, and can also target the users daily, weekly or Record the calories and nutrients ingested for a long period of time, warning the excessive or insufficient intake of calories and nutrients, so that users can pay attention to their own bad eating habits and prevent users from obesity, malnutrition, hyperlipidemia due to improper diet.
  • the user's physical data mainly refers to the user's weight, gender, age, and identities (physical workers or mental workers, daily exercise volume, ethnicity, religious beliefs, etc.).
  • the meal plan data mainly refers to whether the user is in the stage of weight loss
  • the historical dietary data mainly involves Information about the user's eating habits, historical diet, and the effect of historical diet on body weight.
  • User medical record data refers to whether the user currently has certain diseases, which may limit the user's diet. For example, diabetics cannot take high-sugar foods. People with heart disease cannot eat foods with high salt content, and people with high blood pressure cannot eat high-calorie foods in large quantities.
  • FIG. 2 is a flowchart of Embodiment 2 of a smart meal recommendation method according to an embodiment of the present invention.
  • the smart meal recommendation terminal needs to calculate the heat and nutrients contained in the recipe, so as to be based on user requirements. Users recommend reasonable recipes.
  • the method further includes:
  • Step 3' Analyze the calories and nutrients contained in the recipe.
  • the recipe information uploaded or imported by the restaurant manager mainly includes the information of the recipe ingredients, the weight of the ingredients, the oil content of the recipe, the salt content of the recipe, the sugar content of the recipe, and the like, and the information of the calorie and nutrient composition of the recipe can be determined through the information. You can determine the spicy and greasy taste of the recipe.
  • the smart meal recommendation terminal obtains the calorie and nutrient composition information of the dish
  • the restaurant and the recipe information can be displayed to the user according to the specific situation of the user, so as to achieve the target and satisfy the user's needs.
  • Embodiment 3 is a flowchart of Embodiment 3 of a method for recommending a smart meal according to a specific embodiment of the present invention.
  • the smart meal recommendation terminal filters the recipes of the surrounding restaurants according to the heat and nutrients of the user, and then Display the filtered recipes to the user.
  • the step of filtering the recommended recipe display to the user from the recipe based on the personal health information includes:
  • Step 41 Calculate the heat and nutrients of the user according to the personal health information.
  • the personal health information includes one or a combination of user vital sign data, meal plan data, historical diet data, or user medical record data.
  • Step 42 Screening the recommended recipe from the recipe according to the calories and nutrients contained in the recipe and the required calories and nutrients.
  • the calories and nutrients contained in the recommended recipes can reach the calorie and nutrients.
  • the recommended calories may be slightly less than the calories of the user's body, if the user is in a long body.
  • the recommended recipe contains slightly more calories than the user's body needs.
  • Step 43 Display the recommended recipe to the user in units of restaurants. If the recipe combination is displayed to the user, it is necessary to ensure that the recipe combination is from the same restaurant; if the package is displayed to the user or a single recipe, there is no such problem.
  • the specific display mode can mark the restaurant and its corresponding recipes on the map, and number the restaurant. The user can intuitively feel the location and distance of the restaurant, and can guide the user to the corresponding restaurant through map navigation, which is convenient to use. The user experience is high; if the user has a strong sense of direction, the user can also be notified by short message, and the user goes to the corresponding restaurant according to the information content, so that the user terminal's traffic is not consumed, and the cost is saved, even if the terminal is configured low.
  • the present invention is applied, and in addition, the present invention is equally applicable to middle-aged and elderly people who do not apply smart terminals, and has a wide application population.
  • the user is shown the recipe containing the corresponding calories and nutrients, so that the user's calorie intake will not be excessive, and there will be no problem of insufficient energy and malnutrition. Good health.
  • Embodiment 4 is a flowchart of Embodiment 4 of a smart meal recommendation method according to an embodiment of the present invention. As shown in FIG. 4, before displaying a recommended recipe to a user, it is necessary to intelligently sort the recommended recipes to be displayed, and further Improve the user experience.
  • the method before the step of displaying the recommended recipe to the user in the restaurant unit, the method further includes the steps of:
  • Step 42' Sort the recommended recipe according to at least one of user preference, restaurant distance, and health demand.
  • the user can pre-set the sorting rules of the recommended recipes.
  • the system also has its own default sorting, the user can modify the sorting, and can adjust the sorting at any time, for example, the first sorting is user preference, and the second sorting is restaurant distance.
  • the third ranking is a health requirement, which satisfies the individual needs of the user and improves the user experience.
  • the system may display multiple groups of recipes to the user at the same time.
  • it is necessary to intelligently sort the plurality of groups of recipes usually grouped and displayed in units of restaurants.
  • the recipes correspond to a restaurant, and multiple recipes can also correspond to the same restaurant.
  • the recommended methods are diverse and simple.
  • FIG. 5 is a block diagram of Embodiment 1 of a smart meal recommendation terminal according to an embodiment of the present invention.
  • the smart meal recommendation terminal is used to locate a geographic location of the user, and the geographic location is uploaded to the cloud server.
  • the cloud server determines the user's surrounding restaurant and its corresponding recipe according to the geographical location; the smart meal recommendation terminal selects the restaurant and the recipe with reasonable calorie and nutrient content from the user's surrounding restaurant and its corresponding recipe based on the user's personal health information, and Display these or this restaurant and its recipes to the user.
  • the smart meal recommendation terminal 100 includes a personal information acquisition unit 10, a positioning unit 20, a recipe acquisition unit 30, and a screening unit 40, wherein the personal information acquisition unit 10 is configured to acquire personal health information of the user.
  • the personal health information may be stored in the cloud server 200 or stored in the smart meal recommendation terminal 100. If the personal health information is stored in the cloud server 200, the user may modify or upload the personal health information, if the personal health information stores the smart meal recommendation In the terminal 100, the user can input or modify personal health information, and the present invention is not limited thereto.
  • the personal health information includes: user vital sign data, meal plan data, historical diet data, and user medical record data; and the positioning unit 20 is configured to locate the user.
  • the recipe obtaining unit 30 is configured to obtain a recipe of the user's surrounding restaurant determined by the cloud server according to the geographic location; and the filtering unit 40 is configured to use the personal health information Recommended dishes in the recipe The spectrum is displayed to the user.
  • the smart meal recommendation terminal 100 further filters the surrounding restaurants and recipes according to the personal needs of the user, displays the delicious foods that meet the user's own health needs, and can also ingest the users daily, weekly or longer.
  • the calories and nutrients are recorded to alert users to excessive or insufficient intake of calories and nutrients, so that users can pay attention to their own bad eating habits and prevent users from obesity, malnutrition, hyperlipidemia, high blood pressure and high risk due to improper diet. Blood sugar and other diseases.
  • the user's vital data is mainly the user's weight, gender, age, identity (physical workers or mental workers, daily exercise volume, ethnicity, religious beliefs, etc.).
  • the meal plan data is mainly whether the user is losing weight.
  • historical dietary data mainly involves information such as the user's eating habits, historical diet, and the effect of historical diet on body weight.
  • the user's medical record data refers to whether the user currently has certain diseases related to diet, which may limit the user's diet, for example. People with diabetes can't eat foods with high sugar content. People with heart disease can't eat foods with high salt content. People with high blood pressure can't eat high-calorie foods in large quantities.
  • the smart meal recommendation terminal 100 may be a dedicated mobile terminal device or a user's smart phone. After the meal recommendation application (ie, mobile phone APP) is installed on the smart phone, the purpose of the present invention is practical, and the present invention is not limited thereto.
  • FIG. 6 is a block diagram of Embodiment 2 of a smart meal recommendation terminal according to an embodiment of the present invention. As shown in FIG. 6 , the smart meal recommendation terminal 100 needs to calculate calories and nutrients contained in the recipe to meet user requirements. The user displays a reasonable recipe.
  • the smart meal recommendation terminal 100 further includes an analysis unit 50, wherein the analysis unit 50 is configured to analyze the heat and nutrients contained in the recipe.
  • the smart meal recommendation terminal 100 obtains the information about the calories and nutrients contained in the dish
  • the restaurant and the recipe information can be displayed to the user in combination with the user's personal health information, so as to achieve the personalized needs of the user.
  • FIG. 7 is a block diagram of a recommendation unit of a smart meal recommendation terminal according to an embodiment of the present invention.
  • the screening unit 40 filters the recipes of the user's surrounding restaurants according to the user's demand for heat and nutrients, and then filters out the recipes.
  • the recipe is displayed to the user for the user to select.
  • the screening unit 40 specifically includes a requirement calculation module 041, a screening module 042, and a display module 043, wherein the requirement calculation module 041 is configured to calculate a heat demand of the user according to the personal health information. And a nutrient component; the screening module 042 is configured to filter the recommended recipe from the recipe according to the heat and nutrients contained in the recipe and the required calories and nutrients; the display module 043 is used for the restaurant unit The recommended recipe is displayed to the user.
  • the screening unit 40 recommends a recipe containing the corresponding calorie and nutrients according to the user's calorie and nutrient requirements, so as to ensure that the user's dietary calorie intake does not appear excessive, and there is no shortage of energy or malnutrition. To keep the user's health in good condition.
  • FIG. 8 is another block diagram of a recommendation unit of a smart meal recommendation terminal according to an embodiment of the present invention.
  • the recommendation unit 40 may further include a sorting module 044, where the sorting module 044 is used.
  • the recommended recipes are sorted according to at least one of user preference, restaurant distance, and health needs.
  • the user can pre-set the sorting rule of the recommended recipe through the smart meal recommendation terminal.
  • the system also has its own default sorting, the user can modify the sorting, and can adjust the sorting at any time, for example, the first sorting is user preference, and the second Sorted into restaurant distance, the third sort is for health needs, to meet the individual needs of users, and to improve user experience.
  • FIG. 9 is a flowchart of Embodiment 5 of a method for recommending a smart meal according to a specific embodiment of the present invention.
  • the smart meal recommendation cloud server receives the geographic location uploaded by the smart meal recommendation terminal, and determines according to the geographic location.
  • the recipes of the restaurants around the users are for the smart meal recommendation terminal.
  • Step S1 Receive the geographical location uploaded by the smart meal recommendation terminal.
  • the smart meal recommendation terminal can use its own GPS positioning chip to locate the geographical location where the user is located (for example, latitude and longitude information), and the smart meal recommendation cloud server receives the geographical location uploaded by the smart meal recommendation terminal.
  • Step S2 determining the recipe of the surrounding restaurant of the user according to the geographical location.
  • the smart meal recommendation cloud server determines the restaurant near the geographical location and its corresponding recipe information from its stored restaurant and recipe information.
  • the smart meal recommendation cloud server determines the recipe of the surrounding restaurant according to the geographic location provided by the smart meal recommendation terminal, and the restaurant manager can log in to the system to modify or upload the restaurant and its recipe information.
  • FIG. 10 is a block diagram of a first embodiment of a smart meal recommendation cloud server according to an embodiment of the present invention.
  • the smart meal recommendation cloud server 200 stores all restaurants and recipe information therein, and the restaurant By logging in to the cloud server 200, the camper can upload or modify the recipe information.
  • the recipe information includes recipe ingredients, ingredient weight, oil content of the recipe, salt content of the recipe, sugar content of the recipe, etc., and the information can determine the calories and nutrition of the recipe.
  • Ingredient information through which information can also be used to determine the spicyness and greasyness of the recipe.
  • the smart meal recommendation cloud server 200 can also use the crawler technology to selectively capture the recipe information in the restaurant menu database according to the established crawling target, without requiring the restaurant operator to upload or update the restaurant and its corresponding recipe information, which is convenient and quick. .
  • the cloud server 200 includes a first receiving unit 210 and a first recipe determining unit 220, wherein the first receiving unit 210 is configured to receive a geographic location uploaded by the smart meal recommendation terminal.
  • the first recipe determining unit 220 is configured to determine a recipe of the surrounding restaurant of the user according to the geographical location.
  • the recipe information includes information such as recipe ingredients, ingredient weight, oil content of the recipe, salt content of the recipe, and sugar content of the recipe. The information can be used to determine the calorie and nutrient composition information of the recipe.
  • all the restaurants and their recipe information are stored in the cloud server 200.
  • the restaurant operator can upload or modify the recipe information by logging in to the cloud server 200, and the cloud server 200 integrates the restaurants and their recipe information, and calculates the recipe.
  • FIG. 11 is a flowchart of Embodiment 6 of a smart meal recommendation method according to an embodiment of the present invention.
  • the smart meal recommendation cloud server obtains personal health information and a geographical location, and determines a user surrounding restaurant according to the geographic location. And corresponding recipe information, and further screening the surrounding restaurants and corresponding recipe information according to personal health information, and pushing the filtered restaurant and recipe information to the smart meal recommendation terminal.
  • Step 11 Obtain the personal health information of the user. If the personal health information is stored in the smart meal recommendation terminal, the smart meal recommendation cloud server may obtain personal health information from the smart meal recommendation terminal; if the person health information is stored in the smart meal recommendation cloud server, it may be directly called from the storage unit; or The user directly inputs or imports personal health information to the smart meal recommendation cloud server, and the present invention is not limited thereto.
  • the personal health information includes at least one of user vital sign data, meal plan data, historical diet data, and user medical record data.
  • Step 12 Obtain the geographic location of the user from the smart meal recommendation terminal. Smart Meal Recommends the cloud server to obtain the user's geographic location from the smart meal recommendation terminal
  • Step 13 The recipe of the surrounding restaurant of the user determined according to the geographical location.
  • the smart meal recommends the recipe of the surrounding restaurant of the user determined by the cloud server according to the geographical location.
  • Step 14 Screening the recommended recipe from the recipe based on the personal health information.
  • the smart meal recommendation cloud server further filters the surrounding restaurants and their recipes, and filters out the restaurants and recipes tailored to the users to maintain or improve the user's physical health.
  • Step 15 Push the recommended recipe to the smart meal recommendation terminal.
  • the smart meal recommendation cloud server pushes the further filtered recipes to the corresponding users.
  • the present invention can further filter the surrounding restaurants and recipes according to the personal needs of the user, recommend the delicious foods that meet the health needs of the users, and can also take in the calories taken by the users daily, weekly or longer.
  • Nutritional components are recorded to alert users to excessive or insufficient intake of calories and nutrients, so that users can pay attention to their own bad eating habits and prevent users from obesity, malnutrition, hyperlipemia, hypertension, hyperglycemia and other diseases due to improper diet. .
  • FIG. 12 is a flowchart of Embodiment 7 of a smart meal recommendation method according to an embodiment of the present invention.
  • the smart meal recommendation cloud server analyzes the heat and nutrients contained in the recipe, and reduces the smart meal recommendation terminal.
  • the amount of data processing improves the execution efficiency of the present invention and further improves user satisfaction.
  • the method further includes:
  • Step 13' Analyze the calories and nutrients contained in the recipe.
  • FIG. 13 is a flowchart of Embodiment 8 of a method for recommending a smart meal according to a specific embodiment of the present invention.
  • the smart meal recommendation cloud server filters the recipe of the surrounding restaurant according to the user's demand for heat and nutrition.
  • the step of selecting the recommended recipe from the recipe based on the personal health information includes:
  • Step 141 Calculate the heat and nutrient components of the user according to the personal health information.
  • Step 142 Screening the recommended recipe from the recipe according to the heat and nutrients contained in the recipe and the required calories and nutrients.
  • the user's demand calorie and nutrient components are calculated on the smart meal recommendation cloud server side, and the recipe is further screened according to the heat and nutrients contained in the recipe and the required calories and nutrients, which can be reduced.
  • the amount of data processing on the smart meal recommendation terminal side improves the execution efficiency of the present invention, reduces the configuration requirements of the smart meal recommendation terminal, and further improves user satisfaction.
  • FIG. 14 is a flowchart of Embodiment 9 of a smart meal recommendation method according to an embodiment of the present invention, as shown in FIG. 14 , according to the heat and nutrients contained in the recipe and the required calories and nutrition After the ingredients are filtered out from the recipes, the recommended recipes can be intelligently sorted, and the user can get the recommended recipes at a glance to improve the user experience.
  • the method further comprises:
  • Step 143 Sort the recommended recipe according to at least one of user preference, restaurant distance, and health demand.
  • FIG. 15 is a block diagram of a second embodiment of a smart meal recommendation cloud server according to an embodiment of the present invention.
  • the smart meal recommendation cloud server obtains personal health information and a geographic location, and determines a user perimeter according to the geographic location.
  • the restaurant and its corresponding recipe information further filter the surrounding restaurants and corresponding recipe information according to the personal health information, and push the filtered restaurant and recipe information to the smart meal recommendation terminal.
  • the specific embodiment of the present invention includes an information obtaining unit 201, a second receiving unit 202, a second recipe determining unit 203, a recipe screening unit 204, and a pushing unit 205, wherein the information acquiring unit 201 is configured to acquire personal health information of the user, and the individual The health information includes: user vitals data, meal plan data, historical diet data, and user medical record data, etc.; the second receiving unit 202 is configured to acquire the geographic location of the user from the smart meal recommendation terminal; and the second recipe determining unit 203 is configured to a recipe for the geographically determined user's surrounding restaurant; the recipe screening unit 204 is configured to filter the recommended recipe from the recipe based on the personal health information; and the pushing unit 205 is configured to push the recommended recipe to the smart meal recommendation terminal.
  • the information acquiring unit 201 is configured to acquire personal health information of the user, and the individual The health information includes: user vitals data, meal plan data, historical diet data, and user medical record data, etc.; the second receiving unit 202 is configured to acquire the
  • FIG. 16 is a block diagram of a third embodiment of a smart meal recommendation cloud server according to a specific embodiment of the present invention.
  • the smart meal recommendation cloud server 200 further includes a second analysis unit 206, wherein the The second analyzing unit 206 is configured to analyze the heat and nutrients contained in the recipe.
  • FIG. 17 is a block diagram of a recipe screening unit of a smart meal recommendation terminal according to an embodiment of the present invention. As shown in FIG. 17, the recipe screening unit 204 further includes:
  • the requirement calculation module 2041 is configured to calculate the user's required calories and nutrients according to the personal health information.
  • the screening module 2042 is configured to screen the recommended recipe from the recipe according to the heat and nutrients contained in the recipe and the required calories and nutrients.
  • FIG. 18 is another block diagram of a recipe screening unit of a smart meal recommendation terminal according to an embodiment of the present invention. As shown in FIG. 18, the recipe screening unit 204 further includes:
  • the sorting module 2043 is configured to sort the recommended recipe according to at least one of user preference, restaurant distance, and health demand.
  • the smart meal recommendation system includes a plurality of smart meal recommendation terminals 100 and a cloud server connected to the smart meal recommendation terminal 100, as shown in FIG. 200, of which
  • the smart meal recommendation terminal 100 includes a personal information acquisition unit 10, a positioning unit 20, a recipe acquisition unit 30, and a screening unit 40.
  • the personal information acquisition unit 10 is configured to acquire personal health information of the user, and the personal health information can be stored in the cloud.
  • the server 200 can also be stored in the smart meal recommendation terminal 100; the positioning unit 20 is configured to locate the geographic location of the user, and upload the geographic location to the cloud server; the recipe acquisition unit 30 is configured to acquire the cloud server according to the geographic location.
  • the location determining the recipe of the user's surrounding restaurant; the screening unit 40 is configured to filter the recommended recipe display from the recipe based on the personal health information to the user.
  • the cloud server 200 includes a first receiving unit 210 and a first recipe determining unit 220, wherein the first receiving unit 210 is configured to receive a geographic location uploaded by the smart meal recommendation terminal.
  • the first recipe determining unit 220 is configured to determine a recipe of the surrounding restaurant of the user according to the geographical location.
  • the personal health information, the restaurant, and the recipe information are stored in the cloud server 200, which can save the storage capacity of the smart meal recommendation terminal 100.
  • the recipe recommendation operation mainly occurs in the smart meal recommendation terminal 100, and the smart meal recommendation terminal is utilized. 100 locating the geographic location of the user, so that the restaurant surrounding the user and the corresponding recipe information are retrieved in the cloud server 200, and the smart meal recommendation terminal 100 compares the calorie and nutrients required by the user with the calories and nutrients included in the recipe. Thereby, the recipe to be recommended is screened, and the smart meal recommendation terminal 100 intelligently sorts the recipes to be recommended and then displays them to the user.
  • the thermal and nutrient composition comparison, and the smart sorting of the recipes may also be processed by the cloud server 200, as shown in FIG.
  • the smart meal recommendation system includes a plurality of smart meal recommendation terminals 100 and a cloud server connected to the smart meal recommendation terminal 100, as shown in FIG. 200, of which
  • the smart meal recommendation terminal 100 includes a second positioning unit 101 and a display unit 102, where
  • the second positioning unit 101 is configured to locate a geographic location of the user; the display unit 102 is configured to display the recommended recipe pushed by the cloud server 200 on the smart meal recommendation terminal 100.
  • the cloud server 200 includes an information obtaining unit 201, a second receiving unit 202, a second recipe determining unit 203, a recipe screening unit 204, and a pushing unit 205.
  • the information acquiring unit 201 is configured to acquire personal health information of the user, and personal health.
  • the information includes: user vitals data, meal plan data, historical diet data, and user medical record data, etc.;
  • the second receiving unit 202 is configured to acquire the geographic location of the user from the smart meal recommendation terminal;
  • the second recipe determining unit 203 is configured to use the geographic a recipe for the location-determined user's surrounding restaurant;
  • the recipe screening unit 204 is configured to filter the recommended recipe from the recipe based on the personal health information;
  • the pushing unit 205 is configured to push the recommended recipe to the smart meal recommendation terminal.
  • the cloud server 200 may further include: a restaurant crawler unit for capturing a recipe in the restaurant menu database; and a login unit for providing the smart meal recommendation terminal with a port for logging in to the cloud server; storing A unit for storing personal health information and recipes for users.
  • the smart meal recommendation terminal 100 is a mobile phone
  • the cloud server 200 is a server
  • a plurality of mobile phones are connected to the server
  • the smart meal recommendation application (mobile phone APP) is installed on the mobile phone, and the user logs in to the application through the client login port.
  • the recipe in the hall menu database is stored in the storage unit.
  • the restaurant manager is required to install the smart meal recommendation application on the mobile phone, and the restaurant manager can upload or register the application through the server. Modify the restaurant and recipe information in the storage unit.
  • the application When the user goes out to eat, the application is opened, the mobile phone automatically locates the geographical location information of the user, and the application acquires the geographical location information of the user, and the application requests the server to provide the restaurant and recipe information near the geographical location based on the geographical location information.
  • the application analyzes the calorie and nutrient information of the recipe, and combines the calorie and nutrient information required by the user to display the corresponding restaurant and recipe.
  • User A's personal health information is (male, Han, no religion, 25 years old, weight 70 kg, height 180 cm, no meal plan, history per meal)
  • the calorie intake is 2,500 calories and the body is healthy.
  • User B's personal health information is (female, Han, Vietnamese, 30, weight 60 kg, height 160 cm, losing weight, history of calorie intake is 2,200 calories, body Health)
  • User C's personal health information is (male, Hui, 50 years old, weight 80 kg, height 176 cm, heart disease rehabilitation period, historical calorie intake 2700 calories, cholecystitis patients), three user mobile phones
  • the smart meal recommendation application is installed on the top, as shown in the application interface shown in FIG.
  • the user can use the “manual input location” button to locate the recipe near the input location according to the geographical location input by the user.
  • the “automatic positioning” button is based on Location positioning machine where to find restaurants surrounding the case. After users A, B, and C log in to the smart meal recommendation system, they input their own personal health information, and the mobile phones respectively locate the geographic locations of users A, B, and C. Since users A, B, and C work in the same company, the geographic location the same.
  • the mobile phone transmits the geographic location to the cloud server through the mobile communication network (the mobile phones of the users A, B, and C are connected to the same cloud server), and the cloud server delivers the restaurant and the recipe near the geographic location to the users A and B, respectively.
  • C's mobile phone User A's mobile phone calculates the calories contained in the recipe in the background. Because User A is healthy and has no meal plan, and there is no special eating habit, therefore, according to User A's intake of 2,500 calories per meal.
  • a total of six meal options for three restaurants are displayed to User A (Restaurant 1: Beef Rice + Coke (2500 calories), or Egg Noodle + Meatloaf (2450 calories)
  • Restaurant 2 fish-flavored pork + rice + egg-flower soup (2550 calories), or gong bang chicken rice bowl + mung bean porridge (2550 calories);
  • restaurant 3 mutton foam + meat plus glutinous rice (2600 calories) ), or ⁇ + ⁇ (2400 calories)
  • the user can click on the “Details” button in the figure to view the ingredients, nutrients, lightness, spicyness, salt content and grain content of the recommended recipes. Information.
  • User B's mobile phone also calculates the calories contained in the recipe in the background. Since User B is a Buddhist, it cannot recommend leek to it, and because it is losing weight, the calories recommended to it should be slightly less than the calories before weight loss, such as As shown in Figure 21, a total of six meal options for three restaurants are displayed to User B (Restaurant 1: Plain Fried Rice + Coke (2100 calories), or Plain + Hand Cake (2000 calories); Restaurant 4: Cool Skin + Biscuits (1800 calories), or potato + rice (1900 calories); Restaurant 5: Chongqing noodles + soy milk (1950 calories), or noodles + fruit salad (1800 calories)), the user clicks on the details
  • the button can be used to view the ingredients, nutrients, lightness, spicyness, salt content, and grain content of the recommended recipes.
  • User C's mobile phone also calculates the calories contained in the recipe in the background. Since user C is a Hui family, it should recommend a halal restaurant to it, and because it is dealing with a heart disease rehabilitation period, the recommended salt and food content of the recipe is recommended. Should be low, and nutrition should be more comprehensive, while taking into account the body is fatter, try to recommend that the calories of the recipe is lower than the historical diet calories, and because it is a cholecystitis patient, the cholesterol content in the recipe should be low, as shown in Figure 22.
  • the user can also place an order directly by the smart meal recommendation system, and the user can directly dine after the store arrives, saving the user waiting time.
  • the smart meal recommendation system also navigates the user to go to the meal.
  • the invention provides a smart meal recommendation method and system, a terminal and a cloud server, which can obtain the restaurant and its recipe information around the user by locating the geographical location information of the user; and filter the restaurant and its recipe based on the user's personal health information.
  • the restaurant and its recipes with reasonable calorie and nutrient content, and recommend/display one or more restaurants and their recipes to the user, the invention can propose a reasonable meal plan according to the user's personal physical condition, and can also be based on the health set by the user.
  • the need to provide dietary advice to improve the user's eating habits can effectively prevent or reduce the user's high blood fat, high blood pressure, high blood sugar and other diet-related diseases, while ensuring that users consume energy and nutrients that meet the body's functional needs.
  • the invention can help the user to manage the daily diet, and can prompt the user to take excessive calorie or insufficient calorie intake daily, weekly or long-term, so that the user really grasps his or her own eating condition and urges the user to improve eating habits.
  • the invention can recommend the restaurant and its recipes for the out-of-home eating ethnic group and consumer preferences.
  • the invention can utilize the Internet crawler technology to automatically compare the restaurant dishes with the recipe database, and the nutrient composition and heat range provided are helpful for the user to refer to and record.
  • the present invention can provide various recommendation methods according to different ages and locations of the user according to the age, identity, and sub-health status (eg, according to past experience and preferences, distance, comprehensive selection (shake), etc.).
  • an embodiment of the present invention may also be a program code for executing the above program executed in a Digital Signal Processor (DSP).
  • DSP Digital Signal Processor
  • the invention may also relate to various functions performed by a computer processor, digital signal processor, microprocessor or Field Programmable Gate Array (FPGA).
  • the above described processor may be configured to perform specific tasks in accordance with the present invention, which are accomplished by executing machine readable software code or firmware code that defines a particular method disclosed herein.
  • Software code or firmware code can be developed into different programming languages and different formats or forms. Software code can also be compiled for different target platforms. However, different code patterns, types, and languages of software code and other types of configuration code for performing tasks in accordance with the present invention do not depart from the spirit and scope of the present invention.

Abstract

本发明提供了一种智能膳食推荐方法、终端及智能膳食推荐云端服务器，其中，智能膳食推荐方法具体包括：获取用户的个人健康信息；定位用户的地理位置，并将所述地理位置上传给云端服务器；获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。本发明可以根据用户的个人身体状况需求向用户推荐合适的餐厅及其对应菜谱，也可以根据用户设定的健康需求向用户提供膳食建议，改善用户饮食不当的习惯，预防与饮食有关疾病的发生。

Description

智能膳食推荐方法、终端及智能膳食推荐云端服务器 技术领域
本发明涉及信息自动推送技术领域，尤其涉及针对不同用户推荐相应菜肴/餐厅的方法，具体来说就是一种智能膳食推荐方法、终端及智能膳食推荐云端服务器。
背景技术
近年来，随着人们生活水平的不断提高以及生活节奏的不断加快，与饮食有关的健康问题日益显现，甚至导致许多国人因饮食不当而产生与饮食相关的疾病，特别是高血脂、高血压、高血糖等富裕病，无形中增多不少，这些疾病又成为动脉硬化和心脏血管疾病的主要诱因。合理安排饮食是预防及治疗常见“三高问题”的最佳法宝，预防及治疗“三高问题”就是要精准控制食品所包含的脂肪及热量。
现有技术中通常使用电子称与食品数据库进行食物热量与营养素的测定，但是，由于各种食物的名称、成份、品牌、厂商，以及口味等数据不同，用户进行数据搜寻时，必须在数据库中以逐笔查找的方式寻找相应的食品，因此操作上相当费时。而且当外出用餐时，更无法帮助用户管理日常饮食，也无法针对用户每日、每周，或更长时间摄取的热量进行测定，并给出摄取过量或不足的警示，使得用户无法真实掌握自己饮食状况，因此，也无法改善自己饮食不当的习惯。
因此，本领域技术人员亟待研发一种膳食推荐方法，能够针对用户的个人身体健康状况向用户推荐菜肴/餐厅，从而避免饮食过量或者营养不良的问题，并实现预防与饮食有关的疾病的目的。
发明内容
有鉴于此，本发明要解决的技术问题在于提供一种智能膳食推荐方法、终端及智能膳食推荐云端服务器，解决了现有技术中无法根据用户个人健康状况提出膳食规划的问题。
为了解决上述技术问题，本发明的具体实施方式提供一种智能膳食推荐方法，包括：获取用户的个人健康信息；定位用户的地理位置，并将所述地理位置上传给云端服务器；获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。
本发明的另一具体实施方式还提供一种智能膳食推荐终端，包括：个人信息获取单元，用于获取用户的个人健康信息；定位单元，用于定位用户的地理位置，并将所述地理位置上传给云端服务器；菜谱获取单元，用于获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；筛选单元，用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。
本发明的另一具体实施方式还提供一种智能膳食推荐方法，包括：接收智能膳食推荐终端上传的地理位置；根据所述地理位置确定用户周边餐厅的菜谱。
本发明的另一具体实施方式还提供一种智能膳食推荐云端服务器，包括：第一接收单元，用于接收智能膳食推荐终端上传的地理位置；第一菜谱确定单元，用于根据所述地理位置确定用户周边餐厅的菜谱。
本发明的另一具体实施方式还提供一种智能膳食推荐方法，包括：获取用户的个人健康信息；从智能膳食推荐终端获取用户的地理位置；根据所述地理位置确定的用户周边餐厅 的菜谱；基于所述个人健康信息从所述菜谱中筛选出推荐菜谱；将所述推荐菜谱推送给智能膳食推荐终端。
本发明的另一具体实施方式还提供一种智能膳食推荐云端服务器，包括：信息获取单元，用于获取用户的个人健康信息；第二接收单元，用于从智能膳食推荐终端获取用户的地理位置；第二菜谱确定单元，用于根据所述地理位置确定的用户周边餐厅的菜谱；菜谱筛选单元，用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱，并推送给智能膳食推荐终端；推送单元，用于将所述推荐菜谱推送给智能膳食推荐终端。
由以上本申请具体实施方式提供的技术方案可知，智能膳食推荐方法、终端及智能膳食推荐云端服务器至少具有以下优点或者特点：利用智能膳食推荐终端定位用户所在的地理位置，云端服务器根据地理位置确定用户周边餐厅及其菜谱；智能膳食推荐终端基于用户的个人健康信息从这些餐厅及其菜谱之中筛选出热量及营养成份合理的餐厅及其菜谱，并将这些餐厅及其菜谱显示出来，从而可以根据用户个人身体状况向用户提供合理的膳食规划，另外本发明也可以根据用户设定的健康需求提供膳食建议，改善用户饮食不当的习惯，可以有效预防或减轻用户的高血脂、高血压、高血糖等疾病，同时保证用户摄取满足身体机能需要的适当能量及营养成份。
应了解的是，上述一般描述及以下具体实施方式仅为示例性及阐释性的，其并不能限制本发明所欲主张的范围。
附图说明
下面的所附附图是本发明的说明书的一部分，其绘示了本发明的示例实施例，所附附图与说明书的描述一起用来说明本发明的原理。
图1为本发明具体实施方式提供的一种智能膳食推荐方法的实施例一的流程图；
图2为本发明具体实施方式提供的一种智能膳食推荐方法的实施例二的流程图；
图3为本发明具体实施方式提供的一种智能膳食推荐方法的实施例三的流程图；
图4为本发明具体实施方式提供的一种智能膳食推荐方法的实施例四的流程图；
图5为本发明具体实施方式提供的一种智能膳食推荐终端的实施例一的框图；
图6为本发明具体实施方式提供的一种智能膳食推荐终端的实施例二的框图；
图7为本发明具体实施方式提供的一种智能膳食推荐终端的推荐单元的框图；
图8为本发明具体实施方式提供的一种智能膳食推荐终端的推荐单元的另一框图；
图9为本发明具体实施方式提供的一种智能膳食推荐方法的实施例五的流程图；
图10为本发明具体实施方式提供的一种智能膳食推荐云端服务器的具体实施例一的框图；
图11为本发明具体实施方式提供的一种智能膳食推荐方法的实施例六的流程图；
图12为本发明具体实施方式提供的一种智能膳食推荐方法的实施例七的流程图；
图13为本发明具体实施方式提供的一种智能膳食推荐方法的实施例八的流程图；
图14为本发明具体实施方式提供的一种智能膳食推荐方法的实施例九的流程图；
图15为本发明具体实施方式提供的一种智能膳食推荐云端服务器的具体实施例二的框图；
图16为本发明具体实施方式提供的一种智能膳食推荐云端服务器的具体实施例三的框图；
图17为本发明具体实施方式提供的一种智能膳食推荐终端的菜谱筛选单元的框图；
图18为本发明具体实施方式提供的一种智能膳食推荐终端的菜谱筛选单元的另一框图；
图19为本发明具体实施方式提供的一种智能膳食推荐系统的示例一的应用界面示意图；
图20为本发明具体实施方式提供的一种智能膳食推荐系统的示例二的应用界面示意图；
图21为本发明具体实施方式提供的一种智能膳食推荐系统的示例三的应用界面示意图；
图22为本发明具体实施方式提供的一种智能膳食推荐系统的示例四的应用界面示意图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚明白，下面将以附图及详细叙述清楚说明本发明所揭示内容的精神，任何所属技术领域技术人员在了解本发明内容的实施例后，当可由本发明内容所教示的技术，加以改变及修饰，其并不脱离本发明内容的精神与范围。
本发明的示意性实施例及其说明用于解释本发明，但并不作为对本发明的限定。另外，在附图及实施方式中所使用相同或类似标号的元件/构件是用来代表相同或类似部分。
关于本文中所使用的“第一”、“第二”、…等，并非特别指称次序或顺位的意思，也非用以限定本发明，其仅为了区别以相同技术用语描述的元件或操作。
关于本文中所使用的方向用语，例如：上、下、左、右、前或后等，仅是参考附图的方向。因此，使用的方向用语是用来说明并非用来限制本创作。
关于本文中所使用的“包含”、“包括”、“具有”、“含有”等等，均为开放性的用语，即意指包含但不限于。
关于本文中所使用的“及/或”，包括所述事物的任一或全部组合。
关于本文中所使用的用语“大致”、“约”等，用以修饰任何可以微变化的数量或误差，但这些微变化或误差并不会改变其本质。一般而言，此类用语所修饰的微变化或误差的范围在部分实施例中可为20％，在部分实施例中可为10％，在部分实施例中可为5％或是其他数值。本领域技术人员应当了解，前述提及的数值可依实际需求而调整，并不以此为限。
某些用以描述本申请的用词将于下或在此说明书的别处讨论，以提供本领域技术人员在有关本申请的描述上额外的引导。
图1为本发明具体实施方式提供的一种智能膳食推荐方法的实施例一的流程图，如图1所示，利用智能膳食推荐终端定位用户所在的地理位置，云端服务器根据地理位置确定用户周边餐厅及其菜谱；智能膳食推荐终端基于用户的个人健康信息从这些餐厅及其菜谱之中筛选出热量及营养成份合理的餐厅及其菜谱，并将这些或这个餐厅及其菜谱显示出来。
该附图具体实施方式包括：
步骤1：获取用户的个人健康信息。个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据和用户病历数据中的至少一种。个人健康信息可以存储在用户终端(即智能膳食推荐终端)中，也可以存储在云端服务器中，这些信息需要用户事先输入或者通过台式计算机导入，并且用户登录系统后可以修改个人健康信息。
步骤2：定位用户的地理位置，并将所述地理位置上传给云端服务器。可以通过智能膳食推荐终端(或者移动终端)内置的GPS(全球定位系统)芯片定位智能膳食推荐终端的位置，从而获得用户所在的地理位置，再将地理位置上传给云端服务器。
步骤3：获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱。云端服务器中存储有所有餐厅及其菜谱信息，餐厅经营者登录云端服务器后可以上传或者修改餐厅及其 对应的菜谱信息，菜谱信息包括菜谱配料、配料重量、菜谱含油量、菜谱含盐量、菜谱含糖量等信息，通过这些信息可以确定菜谱的热量及营养成份信息，通过这些信息还可以确定菜谱的麻辣程度、油腻程度等信息；云端服务器可以根据所述地理位置确定出用户周边餐厅的菜谱，智能膳食推荐终端从云端服务器获得其周边餐厅的菜谱。
步骤4：基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。由于每个用户的体质特征不同、健康指数不同、饮食习惯、宗教信仰不同，因此对热量及营养成份的需求也不同，例如，对于两个健康的用户，通常情况下，大体重用户需求的热量相对于体重轻用户需求的热量多，当然也要参考用户的历史饮食量；对于同一个用户而言，减肥计划阶段需求的热量比平时需求的热量要少；对于不同人群而言，正在长身体的中学生对营养成份的需求比成年人更加广泛。
参见图1，相较于现有技术，本发明能够根据用户的个人需求对用户周边餐厅及菜谱进一步筛选，给用户推荐符合自身健康需求的美味佳肴，还可以针对用户每日、每周或更长时期内摄取的热量及营养成份进行记录，对用户热量及营养成份摄取过量或不足进行警示，使用户关注自身的不良饮食习惯，防止用户由于饮食不当产生肥胖症、营养不良症、高血脂、高血压、高血糖等疾病。用户体征数据主要是指用户体重、性别、年龄、身份(体力劳动者还是脑力劳动者，每天运动量、民族、宗教信仰等)，膳食计划数据主要是指用户是否处于减肥阶段，历史饮食数据主要涉及用户饮食习惯、历史饮食量、历史饮食量对体重的影响等信息，用户病历数据是指用户目前是否有某些疾病，可能会限定用户的饮食，例如，糖尿病人不能摄取含糖量高的食物，心脏病人不能摄取含盐量高的食品，高血压人群不能大量食用高热量食品。
图2为本发明具体实施方式提供的一种智能膳食推荐方法的实施例二的流程图，如图2所示，智能膳食推荐终端需要计算菜谱所含的热量及营养成份，以便根据用户需求向用户推荐合理的菜谱。
在该附图具体实施方式中，获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱步骤之后还包括：
步骤3’：分析所述菜谱所含的热量及营养成份。餐厅管理者上传或者导入的菜谱信息主要包括菜谱配料、配料重量、菜谱含油量、菜谱含盐量、菜谱含糖量等信息，通过这些信息可以确定菜谱的热量及营养成份信息，通过这些信息还可以确定菜谱的麻辣程度、油腻程度等信息。
参见图2，智能膳食推荐终端获得菜肴的热量及营养成份信息后，才可以结合用户的具体情况向用户显示餐厅及菜谱信息，做到有的放矢，满足用户的需求。
图3为本发明具体实施方式提供的一种智能膳食推荐方法的实施例三的流程图，如图3所示，智能膳食推荐终端根据用户的需求热量及营养成份筛选用户周边餐厅的菜谱，再将筛选出来的菜谱显示给用户。
在该附图具体实施方式中，基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户的步骤，具体包括：
步骤41：根据所述个人健康信息计算出用户的需求热量及营养成份。个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据或用户病历数据中的一种或组合。
步骤42：根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱。通常情况下，推荐菜谱所含的热量及营养成份达到需求热量及营养成份即可，但是，如果用户处于减肥阶段，推荐菜谱所含的热量可以略小于用户身体需求的热量，如果用户处于长身体的青春期阶段，推荐菜谱所含的热量可以略大于用户身体需求的热量。
步骤43：以餐厅为单位将所述推荐菜谱显示给用户。如果向用户显示的是菜谱组合，要保证菜谱组合来自同一家餐厅；如果向用户显示的是套餐或者单一菜谱，则不存在这样的问题。具体显示方式，可以在地图上标注餐厅及其对应的菜谱，并对餐厅进行编号，用户可以直观地感受到餐厅的位置及距离，并可以通过地图导航引导用户前往相应的餐厅就餐，使用方便，用户体验度高；如果用户方向感较强，也可以通过短信息的方式通知用户，用户根据信息内容前往相应餐厅就餐，这样不消耗用户终端的流量，节省费用，即便是配置低的终端也可以应用本发明，此外，对于不会应用智能终端的中老年人同样适用本发明，应用人群广泛。
参见图3，根据用户的热量及营养成份需求，向用户显示含有对应热量及营养成份的菜谱，保证用户热量摄取即不会出现过量，也不会出现能量不足、营养不良的问题，保持用户的身体健康状况良好。
图4为本发明具体实施方式提供的一种智能膳食推荐方法的实施例四的流程图，如图4所示，在向用户显示推荐菜谱之前，需要对将要显示的推荐菜谱进行智能排序，进一步提高用户体验。
在该附图具体实施方式中，以餐厅为单位将所述推荐菜谱显示给用户的步骤之前，还包括步骤：
步骤42’：按照用户喜好、餐厅距离、健康需求中的至少一种对所述推荐菜谱进行排序。用户可以预先设定推荐菜谱的排序规则，当然如果用户不设置，系统也有自己默认的排序，用户可以修改排序，并且可以随时调整排序，例如第一排序为用户喜好，第二排序为餐厅距离，第三排序为健康需求，满足用户的个性化需求，提高用户体验度。
参见图4，实际应用过程中，系统可能同时向用户显示多组菜谱，为了让用户能够快速发现让自己满意的菜谱，需要对多组菜谱进行智能排序，通常以餐厅为单位进行分组显示，一组菜谱对应一个餐厅，多组菜谱也可以对应同一家餐厅，推荐方式多样，简单方便。
图5为本发明具体实施方式提供的一种智能膳食推荐终端的实施例一的框图，如图5所示，利用智能膳食推荐终端定位用户所在的地理位置，并将地理位置上传给云端服务器，云端服务器根据地理位置确定获得用户周边餐厅及其对应的菜谱；智能膳食推荐终端基于用户的个人健康信息从用户周边餐厅及其对应菜谱之中筛选出热量及营养成份合理的餐厅及其菜谱，并将这些或这个餐厅及其菜谱显示给用户。
在该附图具体实施方式中，智能膳食推荐终端100包括个人信息获取单元10、定位单元20、菜谱获取单元30、筛选单元40，其中，个人信息获取单元10用于获取用户的个人健康信息，个人健康信息可以存储在云端服务器200中，也可以存储在智能膳食推荐终端100中，如果个人健康信息存储在云端服务器200中，用户可以修改或者上传个人健康信息，如果个人健康信息存储智能膳食推荐终端100中，用户可以输入或者修改个人健康信息，本发明不以此为限，个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据和用户病历数据等；定位单元20用于定位用户的地理位置，并将所述地理位置上传给云端服务器；菜谱获取单元30用于获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；筛选单元40用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。
参见图5，智能膳食推荐终端100根据用户的个人需求对用户周边餐厅及菜谱进一步筛选，向用户显示符合用户自身健康需求的美味佳肴，还可以针对用户每日、每周或更长时期内摄取的热量及营养成份进行记录，对用户热量及营养成份摄取过量或不足进行警示，使用户关注自身的不良饮食习惯，防止用户由于饮食不当产生肥胖症、营养不良症、高血脂、高血压、高血糖等疾病。用户体征数据主要是用户体重、性别、年龄、身份(体力劳动者还是脑力劳动者，每天运动量、民族、宗教信仰等)，膳食计划数据主要是用户是否处于减肥 阶段，历史饮食数据主要涉及用户饮食习惯、历史饮食量、历史饮食量对体重的影响等信息，用户病历数据是指用户目前是否有与饮食有关的某些疾病，可能会限定用户的饮食，例如，糖尿病人不能摄取含糖量高的食物，心脏病人不能摄取含盐量高的食品，高血压人群不能大量食用高热量食品。智能膳食推荐终端100可以是专门的移动终端设备，也可以是用户的智能手机，在智能手机上安装膳食推荐应用程序(即手机APP)后实用本发明的目的，本发明不以此为限。
图6为本发明具体实施方式提供的一种智能膳食推荐终端的实施例二的框图，如图6所示，智能膳食推荐终端100需要计算菜谱所含的热量及营养成份，以便针对用户需求向用户显示合理的菜谱。
在该附图具体实施方式中，该智能膳食推荐终端100还包括分析单元50，其中，分析单元50用于分析所述菜谱所含的热量及营养成份。
参见图6，智能膳食推荐终端100获得菜肴包含的热量及营养成份信息后，可以结合用户的个人健康信息向用户显示餐厅及菜谱信息，做到有的放矢，满足用户的个性化需求。
图7为本发明具体实施方式提供的一种智能膳食推荐终端的推荐单元的框图，如图7所示，筛选单元40根据用户的需求热量及营养成份筛选用户周边餐厅的菜谱，再将筛选出来的菜谱显示给用户，供用户选择。
在该附图具体实施方式中，所述筛选单元40具体包括需求计算模块041、筛选模块042、显示模块043，其中，需求计算模块041，用于根据所述个人健康信息计算出用户的需求热量及营养成份；筛选模块042用于根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱；显示模块043用于以餐厅为单位将所述推荐菜谱显示给用户。
参见图7，筛选单元40根据用户的热量及营养成份需求，向用户推荐含有对应热量及营养成份的菜谱，保证用户饮食热量摄取即不会出现过量，也不会出现能量不足、营养不良的现象，保持用户的身体健康状况良好。
图8为本发明具体实施方式提供的一种智能膳食推荐终端的推荐单元的另一框图，如图8所示，所述推荐单元40还可以包括排序模块044，其中，所述排序模块044用于按照用户喜好、餐厅距离、健康需求中的至少一种对所述推荐菜谱进行排序。用户可以通过智能膳食推荐终端预先设定推荐菜谱的排序规则，当然如果用户不设置，系统也有自己默认的排序，用户可以修改排序，并且可以随时调整排序，例如第一排序为用户喜好，第二排序为餐厅距离，第三排序为健康需求，满足用户的个性化需求，提高用户体验度。
图9为本发明具体实施方式提供的一种智能膳食推荐方法的实施例五的流程图，如图9所示，智能膳食推荐云端服务器接收智能膳食推荐终端上传的地理位置，并根据地理位置确定用户周边餐厅的菜谱，以供智能膳食推荐终端调取。
该附图具体实施方式包括步骤：
步骤S1：接收智能膳食推荐终端上传的地理位置。智能膳食推荐终端可以利用自身的GPS定位芯片定位出用户所处的地理位置(例如经纬度信息)，智能膳食推荐云端服务器接收智能膳食推荐终端上传的地理位置。
步骤S2：根据所述地理位置确定用户周边餐厅的菜谱。智能膳食推荐云端服务器从自身的存储的餐厅及菜谱信息中确定出该地理位置附近的餐厅及其对应的菜谱信息。
参见图8，智能膳食推荐云端服务器根据智能膳食推荐终端提供的地理位置确定用户周边餐厅的菜谱，餐厅管理者可以登录系统后修改或者上传自己经营的餐厅及其菜谱信息。
图10为本发明具体实施方式提供的一种智能膳食推荐云端服务器的具体实施例一的框图，如图10所示，智能膳食推荐云端服务器200内存储有所有餐厅及其菜谱信息，餐厅经 营者通过登录云端服务器200可以上传或者修改其菜谱信息，菜谱信息包括菜谱配料、配料重量、菜谱含油量、菜谱含盐量、菜谱含糖量等信息，通过这些信息可以确定菜谱的热量及营养成份信息，通过这些信息还可以确定菜谱的麻辣程度、油腻程度等信息。此外，智能膳食推荐云端服务器200还可以利用爬虫技术根据既定的抓取目标，有选择地抓取餐厅菜单数据库中的菜谱信息，不需要餐厅经营者上传或者更新餐厅及其对应菜谱信息，方便快捷。
在该附图具体实施方式中，所述云端服务器200包括第一接收单元210、第一菜谱确定单元220，其中，第一接收单元210用于接收智能膳食推荐终端上传的地理位置。第一菜谱确定单元220用于根据所述地理位置确定用户周边餐厅的菜谱。菜谱信息包括菜谱配料、配料重量、菜谱含油量、菜谱含盐量、菜谱含糖量等信息，通过这些信息可以确定菜谱的热量及营养成份信息。
参见图10，云端服务器200内存储有所有餐厅及其菜谱信息，餐厅经营者通过登录云端服务器200可以上传或者修改其菜谱信息，云端服务器200对这些餐厅及其菜谱信息进行整合，并计算出菜谱对应的热量及营养成份信息，供智能膳食推荐终端100检索查找；此外，智能膳食推荐云端服务器200还可以利用爬虫技术根据既定的抓取目标，有选择地抓取餐厅菜单数据库中的菜谱信息，不需要餐厅经营者上传或者更新餐厅及其对应菜谱信息，方便快捷。
图11为本发明具体实施方式提供的一种智能膳食推荐方法的实施例六的流程图，如图11所示，智能膳食推荐云端服务器获取个人健康信息和地理位置，根据地理位置确定用户周边餐厅及其对应菜谱信息，再根据个人健康信息对用户周边餐厅及对应菜谱信息做进一步筛选，并将筛选出来的餐厅及菜谱信息推送给智能膳食推荐终端。
该附图具体实施方式包括步骤：
步骤11：获取用户的个人健康信息。如果个人健康信息存储在智能膳食推荐终端中，智能膳食推荐云端服务器可以从智能膳食推荐终端获取个人健康信息；如果人健康信息存储在智能膳食推荐云端服务器中，可以直接从存储单位中调用；或者用户直接向智能膳食推荐云端服务器输入或者导入个人健康信息，本发明不以此为限。个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据和用户病历数据中的至少一种。
步骤12：从智能膳食推荐终端获取用户的地理位置。智能膳食推荐云端服务器从智能膳食推荐终端获取用户的地理位置
步骤13：根据所述地理位置确定的用户周边餐厅的菜谱。智能膳食推荐云端服务器根据所述地理位置确定的用户周边餐厅的菜谱。
步骤14：基于所述个人健康信息从所述菜谱中筛选出推荐菜谱。智能膳食推荐云端服务器对用户周边餐厅及其菜谱做进一步筛选，筛选出针对用户个人量身定制的餐厅及菜谱，保持或改善用户的身体健康状况。
步骤15：将所述推荐菜谱推送给智能膳食推荐终端。智能膳食推荐云端服务器将进一步筛选出来的菜谱推送给对应用户。
参见图11，本发明能够根据用户的个人需求对用户周边餐厅及菜谱进一步筛选，给用户推荐符合自身健康需求的美味佳肴，还可以针对用户每日、每周或更长时期内摄取的热量及营养成份进行记录，对用户热量及营养成份摄取过量或不足进行警示，使用户关注自身的不良饮食习惯，防止用户由于饮食不当产生肥胖症、营养不良症、高血脂、高血压、高血糖等疾病。
图12为本发明具体实施方式提供的一种智能膳食推荐方法的实施例七的流程图，如图12所示，智能膳食推荐云端服务器分析菜谱所含的热量及营养成份，减少智能膳食推荐终端的数据处理量，提高本发明的执行效率，进一步提高用户满意度。
在该附图具体实施方式中，根据所述地理位置确定的用户周边餐厅的菜谱步骤之后，该方法还包括：
步骤13’：分析所述菜谱所含的热量及营养成份。
图13为本发明具体实施方式提供的一种智能膳食推荐方法的实施例八的流程图，如图13所示，智能膳食推荐云端服务器根据用户的需求热量及营养成份筛选用户周边餐厅的菜谱。
在该附图具体实施方式中，基于所述个人健康信息从所述菜谱中筛选出推荐菜谱的步骤，具体包括：
步骤141：根据所述个人健康信息计算出用户的需求热量及营养成份。
步骤142：根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱。
参见图13，在智能膳食推荐云端服务器侧计算出用户的需求热量及营养成份，并根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份对菜谱进一步筛选，能够减少智能膳食推荐终端侧的数据处理量，提高本发明的执行效率，降低了智能膳食推荐终端的配置要求，进一步提高用户满意度。
图14为本发明具体实施方式提供的一种智能膳食推荐方法的实施例九的流程图，如图14所示，根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱之后，可以对推荐菜谱进行智能排序，用户可以一目了然获得心仪的推荐菜谱，提高用户体验度。
在该附图具体实施方式中，根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱步骤之后，还包括：
步骤143：按照用户喜好、餐厅距离、健康需求中的至少一种对所述推荐菜谱进行排序。
图15为本发明具体实施方式提供的一种智能膳食推荐云端服务器的具体实施例二的框图，如图15所示，智能膳食推荐云端服务器获取个人健康信息和地理位置，根据地理位置确定用户周边餐厅及其对应菜谱信息，再根据个人健康信息对用户周边餐厅及对应菜谱信息做进一步筛选，并将筛选出来的餐厅及菜谱信息推送给智能膳食推荐终端。
该附图具体实施方式包括信息获取单元201、第二接收单元202、第二菜谱确定单元203、菜谱筛选单元204、推送单元205，其中，信息获取单元201用于获取用户的个人健康信息，个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据和用户病历数据等；第二接收单元202用于从智能膳食推荐终端获取用户的地理位置；第二菜谱确定单元203用于根据所述地理位置确定的用户周边餐厅的菜谱；菜谱筛选单元204用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱；推送单元205用于将所述推荐菜谱推送给智能膳食推荐终端。
图16为本发明具体实施方式提供的一种智能膳食推荐云端服务器的具体实施例三的框图，如图16所示，智能膳食推荐云端服务器200还包括第二分析单元206，其中，所述第二分析单元206用于分析所述菜谱所含的热量及营养成份。
图17为本发明具体实施方式提供的一种智能膳食推荐终端的菜谱筛选单元的框图，如图17所示，所述菜谱筛选单元204进一步包括：
需求计算模块2041，用于根据所述个人健康信息计算出用户的需求热量及营养成份。
筛选模块2042，用于根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱。
图18为本发明具体实施方式提供的一种智能膳食推荐终端的菜谱筛选单元的另一框图，如图18所示，所述菜谱筛选单元204还包括：
排序模块2043，用于按照用户喜好、餐厅距离、健康需求中的至少一种对所述推荐菜谱进行排序。
本发明的一具体实施方式还提供的一种智能膳食推荐系统，如图10所示，所述智能膳食推荐系统包括多个智能膳食推荐终端100和与所述智能膳食推荐终端100连接的云端服务器200，其中，
所述智能膳食推荐终端100包括个人信息获取单元10、定位单元20、菜谱获取单元30、筛选单元40，其中，个人信息获取单元10用于获取用户的个人健康信息，个人健康信息可以存储在云端服务器200中，也可以存储在智能膳食推荐终端100中；定位单元20用于定位用户的地理位置，并将所述地理位置上传给云端服务器；菜谱获取单元30用于获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；筛选单元40用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。
所述云端服务器200包括第一接收单元210、第一菜谱确定单元220，其中，第一接收单元210用于接收智能膳食推荐终端上传的地理位置。第一菜谱确定单元220用于根据所述地理位置确定用户周边餐厅的菜谱。
本具体实施例中，个人健康信息及餐厅、菜谱信息存储于云端服务器200中，可以节省智能膳食推荐终端100的存储容量，菜谱推荐运算主要发生在智能膳食推荐终端100中，利用智能膳食推荐终端100定位用户的地理位置，从而在云端服务器200中检索出用户周边的餐厅及其对应的菜谱信息，智能膳食推荐终端100通过比对用户需求热量及营养成份，与菜谱包括的热量及营养成份，从而筛选出欲推荐的菜谱，智能膳食推荐终端100并对欲推荐的菜谱进行智能排序，然后显示给用户。
本发明的其它实施例中，为了减轻智能膳食推荐终端100的处理压力，热量及营养成份比对，以及菜谱的智能排序也可以交由云端服务器200处理，如图15所示。
本发明的一具体实施方式还提供的一种智能膳食推荐系统，如图15所示，所述智能膳食推荐系统包括多个智能膳食推荐终端100和与所述智能膳食推荐终端100连接的云端服务器200，其中，
所述智能膳食推荐终端100包括第二定位单元101、显示单元102，其中，
所述第二定位单元101用于定位用户的地理位置；所述显示单元102用于在智能膳食推荐终端100上显示云端服务器200推送的所述推荐菜谱。
所述云端服务器200包括信息获取单元201、第二接收单元202、第二菜谱确定单元203、菜谱筛选单元204、推送单元205，其中，信息获取单元201用于获取用户的个人健康信息，个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据和用户病历数据等；第二接收单元202用于从智能膳食推荐终端获取用户的地理位置；第二菜谱确定单元203用于根据所述地理位置确定的用户周边餐厅的菜谱；菜谱筛选单元204用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱；推送单元205用于将所述推荐菜谱推送给智能膳食推荐终端。
在本发明的其它具体实施方式中，云端服务器200还可以包括：餐厅爬虫单元，用于抓取餐厅菜单数据库中的菜谱；登录单元，用于向智能膳食推荐终端提供登录云端服务器的端口；存储单元，用于存储用户的个人健康信息和菜谱。
为了便于说明，假定智能膳食推荐终端100为手机，云端服务器200为服务器，多部手机与该服务器连接，手机上装有智能膳食推荐应用程序(手机APP)，用户通过客户端登录口登录应用程序后，可以修改或者上传存储单元中的个人健康信息，餐厅爬虫单元抓取餐 厅菜单数据库中的菜谱，存储在存储单元中，当然，如果不利用餐厅爬虫单元，那么需要餐厅管理者在手机也安装智能膳食推荐应用程序，通过服务端登录应用程序，餐厅管理者可以上传或者修改存储单元中的餐厅及菜谱信息。当用户外出用餐时，打开应用程序，手机自动定位用户的地理位置信息，应用程序获取用户所处的地理位置信息，应用程序基于该地理位置信息向服务器要求提供该地理位置附近的餐厅及菜谱信息，应用程序分析菜谱的热量及营养成份信息，并结合用户需求的热量及营养成份信息，向用户显示相应的餐厅及菜谱。
假定同在X公司上班的用户A、用户B和用户C，用户A的个人健康信息为(男，汉族，无宗教信仰，25岁，体重70千克，身高180厘米，无膳食计划，历史每顿摄入热量为2500卡路里，身体健康)，用户B的个人健康信息为(女，汉族，佛教徒，30，体重60千克，身高160厘米，正在减肥，历史每顿摄入热量为2200卡路里，身体健康)，用户C的个人健康信息为(男，回族，50岁，体重80千克，身高176厘米，心脏病康复期，历史每顿摄入热量为2700卡路里，胆囊炎患者)，三个用户手机上均装有智能膳食推荐应用程序，如图19所示的应用界面，用户通过“手动输入位置”按钮，可以不用定位，根据用户输入的地理位置，向用户推荐输入位置附近的菜谱，这样方便用户正在前往某地用餐的情况，可以先考查下目的地的餐厅情况，给用户预留更加思考时间，“自动定位”按钮是根据手机所在的位置定位，查找周边餐厅的情形。用户A、B、C登录智能膳食推荐系统后，各自输入自己的个人健康信息，手机各自定位用户A、B、C的地理位置，由于用户A、B、C在同一家公司就职，因此地理位置相同。手机通过移动通信网络将地理位置上传给云端服务器(用户A、B、C的手机连接同一个云端服务器)，云端服务器将该地理位置附近的所述餐厅及菜谱分别下发到用户A、B、C的手机中，用户A的手机在后台计算菜谱所含的热量，由于用户A身体健康，而且没有膳食规划，而且也没有特殊的饮食习惯，因此，按照用户A每顿摄入2500卡路里热量来搭配饮食即可，如图20所示，共向用户A显示了三个餐厅的六种膳食选项(餐厅一：牛肉饭+可乐(2500卡路里热量)，或者鸡蛋面+肉饼(2450卡路里热量)；餐厅二：鱼香肉丝+米饭+蛋花汤(2550卡路里热量)，或者宫爆鸡丁盖饭+绿豆粥(2550卡路里热量)；餐厅三：羊肉泡馍+肉加馍(2600卡路里热量)，或者臊子面+烧饼(2400卡路里热量))，用户点击图中“详情”按钮可以查看推荐菜谱的配料、营养成份、清淡程度、麻辣程度、含盐量、含粮量等信息。
用户B的手机同样在后台计算菜谱所含的热量，由于用户B为佛教徒，不能向其推荐荤菜，同时由于其正在减肥，因此向其推荐的菜谱的热量应当略小于减肥前的热量，如图21所示，共向用户B显示了三个餐厅的六种膳食选项(餐厅一：素炒饭+可乐(2100卡路里热量)，或者素面+手抓饼(2000卡路里热量)；餐厅四：凉皮+烧饼(1800卡路里热量)，或者土豆丝+米饭(1900卡路里热量)；餐厅五：重庆小面+豆浆(1950卡路里热量)，或者刀削面+水果沙拉(1800卡路里热量))，用户点击图中“详情”按钮可以查看推荐菜谱的配料、营养成份、清淡程度、麻辣程度、含盐量、含粮量等信息。
用户C的手机同样在后台计算菜谱所含的热量，由于用户C为回族，应向其推荐清真餐厅，同时由于其正在处理心脏病康复期，因此向其推荐的菜谱的含盐食和含油量应当低，而且营养要全面些，同时考虑到其身体较胖，尽量推荐菜谱的热量比历史饮食热量低点，同时由于其是胆囊炎患者，因此菜谱中的胆固醇含量应当低，如图22所示，共向用户C显示了二个餐厅的四种膳食选项(餐厅六：羊肉砂锅+米饭(2650卡路里热量，清淡)，或者牛肉面+豆浆(2700卡路里热量，清淡)；餐厅七：牛肉烩菜+米饭(2500卡路里热量，清淡)，或者小鸡炖蘑菇+葱花饼(2700卡路里热量，清淡))，用户点击图中“详情”按钮可以查看推荐菜谱的配料、营养成份、清淡程度、麻辣程度、含盐量、含粮量等信息。
除此之外，用户还可以直接智能膳食推荐系统下单，待用户到店后直接用餐，节省了用户等待时间，同时用户选择相应菜谱后，智能膳食推荐系统还会导航用户前去就餐。
本发明提供一种智能膳食推荐方法及系统、终端、云端服务器，通过定位用户所在的地理位置信息，获得用户周边的餐厅及其菜谱信息；基于用户的个人健康信息从这些餐厅及其菜谱中筛选出热量及营养成份合理的餐厅及其菜谱，并将一个或多个餐厅及其菜谱推荐/显示给用户，本发明可以根据用户个人身体状况提出合理的膳食规划，也可以根据用户设定的健康需求提供膳食建议，改善用户饮食不当的习惯，可以有效预防或减轻用户的高血脂、高血压、高血糖等与饮食有关的疾病，同时保证用户摄取满足身体机能需求的能量及营养成份。
本发明至少还具有以下有益效果：
1、本发明可以帮助用户管理日常饮食，并可以针对使用者每日、每周或长期摄取过量热量或摄取不足热量进行警示，使得用户确实掌握自身的饮食状况，督促用户改善饮食习惯。
2、本发明可以针对外出饮食族群及消费者喜好进行餐厅及其菜谱推荐。
3、本发明可以利用互连网爬虫技术，自动将餐厅菜肴与菜谱数据库进行比对，提供的营养成份与热量范围有助于使用者参考与记录。
4、本发明可以针对使用者年龄、身份、亚健康状况，依照不同时间段及地点，推出多种推荐方式(如：依照过去经验与偏好、距离、综合评选(摇一摇)等)。
上述的本发明实施例可在各种硬件、软件编码或两者组合中进行实施。例如，本发明的实施例也可为在数据信号处理器(Digital Signal Processor，DSP)中执行的执行上述程序的程序代码。本发明也可涉及计算机处理器、数字信号处理器、微处理器或现场可编程门阵列(Field Programmable Gate Array，FPGA)执行的多种功能。可根据本发明配置上述处理器执行特定任务，其通过执行定义了本发明揭示的特定方法的机器可读软件代码或固件代码来完成。可将软件代码或固件代码发展为不同的程序语言与不同的格式或形式。也可为了不同的目标平台编译软件代码。然而，根据本发明执行任务的软件代码与其他类型配置代码的不同代码样式、类型与语言不脱离本发明的精神与范围。
以上所述仅为本发明示意性的具体实施方式，在不脱离本发明的构思和原则的前提下，任何本领域的技术人员所做出的等同变化与修改，均应属于本发明保护的范围。

Claims (14)

  1. 一种智能膳食推荐方法，其特征在于，该方法包括：
    获取用户的个人健康信息；
    定位用户的地理位置，并将所述地理位置上传给云端服务器；
    获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；以及
    基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。
  2. 如权利要求1所述的智能膳食推荐方法，其特征在于，所述个人健康信息包括：用户体征数据、膳食计划数据、历史饮食数据或用户病历数据中的一种或组合。
  3. 如权利要求1所述的智能膳食推荐方法，其特征在于，获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱步骤之后，该方法还包括：
    分析所述菜谱所含的热量及营养成份。
  4. 如权利要求3所述的智能膳食推荐方法，其特征在于，基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户的步骤，具体包括：
    根据所述个人健康信息计算出用户的需求热量及营养成份；
    根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱；以及
    以餐厅为单位将所述推荐菜谱显示给用户。
  5. 如权利要求4所述的智能膳食推荐方法，其特征在于，以餐厅为单位将所述推荐菜谱显示给用户的步骤之前，按照用户喜好、餐厅距离、健康需求中的至少一种对所述推荐菜谱进行排序。
  6. 一种智能膳食推荐终端，其特征在于，该智能膳食推荐终端包括：
    个人信息获取单元，用于获取用户的个人健康信息；
    定位单元，用于定位用户的地理位置，并将所述地理位置上传给云端服务器；
    菜谱获取单元，用于获取云端服务器根据所述地理位置确定的用户周边餐厅的菜谱；以及
    筛选单元，用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱显示给用户。
  7. 如权利要求6所述的智能膳食推荐终端，其特征在于，该智能膳食推荐终端还包括：
    分析单元，用于分析所述菜谱所含的热量及营养成份。
  8. 如权利要求7所述的智能膳食推荐终端，其特征在于，所述筛选单元具体包括：
    需求计算模块，用于根据所述个人健康信息计算出用户的需求热量及营养成份；
    筛选模块，用于根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱；以及
    显示模块，用于以餐厅为单位将所述推荐菜谱显示给用户。
  9. 一种智能膳食推荐方法，其特征在于，该方法包括：
    接收智能膳食推荐终端上传的地理位置；以及
    根据所述地理位置确定用户周边餐厅的菜谱。
  10. 一种智能膳食推荐云端服务器，其特征在于，该智能膳食推荐云端服务器包括：
    第一接收单元，用于接收智能膳食推荐终端上传的地理位置；以及
    第一菜谱确定单元，用于根据所述地理位置确定用户周边餐厅的菜谱。
  11. 一种智能膳食推荐方法，其特征在于，该方法包括：
    获取用户的个人健康信息；
    从智能膳食推荐终端获取用户的地理位置；
    根据所述地理位置确定的用户周边餐厅的菜谱；
    基于所述个人健康信息从所述菜谱中筛选出推荐菜谱；以及
    将所述推荐菜谱推送给智能膳食推荐终端。
  12. 如权利要求11所述的智能膳食推荐方法，其特征在于，根据所述地理位置确定的用户周边餐厅的菜谱步骤之后，该方法还包括：
    分析所述菜谱所含的热量及营养成份。
  13. 如权利要求12所述的智能膳食推荐方法，其特征在于，基于所述个人健康信息从所述菜谱中筛选出推荐菜谱，并推送给智能膳食推荐终端的步骤，具体包括：
    根据所述个人健康信息计算出用户的需求热量及营养成份；
    根据所述菜谱所含的所述热量及营养成份和所述需求热量及营养成份从所述菜谱中筛选出推荐菜谱；以及
    以餐厅为单位将所述推荐菜谱推送给智能膳食推荐终端。
  14. 一种智能膳食推荐云端服务器，其特征在于，该智能膳食推荐云端服务器包括：
    信息获取单元，用于获取用户的个人健康信息；
    第二接收单元，用于从智能膳食推荐终端获取用户的地理位置；
    第二菜谱确定单元，用于根据所述地理位置确定的用户周边餐厅的菜谱；
    菜谱筛选单元，用于基于所述个人健康信息从所述菜谱中筛选出推荐菜谱；以及
    推送单元，用于将所述推荐菜谱推送给智能膳食推荐终端。
PCT/CN2015/096405 2015-12-04 2015-12-04 智能膳食推荐方法、终端及智能膳食推荐云端服务器 WO2017092030A1 (zh)

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CN111695026A (zh) * 2019-03-13 2020-09-22 青岛海尔电冰箱有限公司 用于冰箱的推荐菜谱的方法和装置
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CN113126506A (zh) * 2019-12-30 2021-07-16 佛山市云米电器科技有限公司 家电设备控制方法、控制设备及计算机可读存储介质
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