CN110634552A - Recipe pushing method and device based on Internet of things operating system - Google Patents
Recipe pushing method and device based on Internet of things operating system Download PDFInfo
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- CN110634552A CN110634552A CN201910888007.4A CN201910888007A CN110634552A CN 110634552 A CN110634552 A CN 110634552A CN 201910888007 A CN201910888007 A CN 201910888007A CN 110634552 A CN110634552 A CN 110634552A
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Abstract
The invention discloses a recipe pushing method and device based on an Internet of things operating system. The method comprises the following steps: in appointed time period, acquire user's eating habit information through intelligent household equipment, wherein, eating habit information includes at least: information on eaten food materials and cooking information of each eaten food material; generating a target recipe according to the eating habit information of the user, wherein the target recipe at least comprises the following components: the target food material information and target cooking information corresponding to the target food material; the target recipes are pushed to the users, the corresponding recipes are formulated according to the dietary habits of each user for pushing, the technical problem that the recipe recommendation items of intelligent application are single and cannot meet the requirements of different users is solved, and the matching degree of the recipe pushing and the different users is improved.
Description
Technical Field
The invention relates to the technical field of an operating system of the Internet of things, in particular to a recipe pushing method and device based on the operating system of the Internet of things.
Background
In the prior art, intelligent application of a recipe recommendation scheme which can be provided often can only provide food material recommendation matched with a user fitness plan according to the user fitness plan, and the recommendation mode is often single in recommendation items, is not suitable for different users, is not suitable for common users without the fitness plan, and cannot meet daily use requirements of the users.
Aiming at the problem that the recipe recommendation item of intelligent application in the prior art is single and cannot meet the requirements of different users, an effective solution is not provided at present.
Disclosure of Invention
The embodiment of the invention provides a recipe pushing method and device based on an Internet of things operating system, and at least solves the technical problem that a recipe recommendation item applied intelligently is single and cannot meet requirements of different users.
According to an aspect of the embodiment of the invention, a recipe pushing method based on an internet of things operating system is provided, and the method comprises the following steps: in a specified time period, acquiring eating habit information of a user through intelligent household equipment, wherein the eating habit information at least comprises: information on eaten food materials and cooking information of each eaten food material; generating a target recipe according to the eating habit information of the user, wherein the target recipe at least comprises: the target food material information and target cooking information corresponding to the target food material; and pushing the target recipe to the user.
Optionally, the acquiring, by the smart home device, the eating habit information of the user in the specified time period includes: acquiring eaten food material information in a specified time period, wherein the eaten food material information comprises: a time when the eaten food material is placed in an intelligent refrigerator, a time when the eaten food material is taken out of the intelligent refrigerator, a type of the eaten food material, and a quality and/or quantity of the eaten food material; acquiring cooking information of the eaten food material within a specified time period, wherein the cooking information of the eaten food material at least comprises: the type and amount of the eaten food material cooked, the cooking manner of the eaten food material, and the type and amount of seasoning used when the eaten food material is cooked.
Optionally, the generating a target recipe according to the eating habit information of the user includes: acquiring physical state information of the user, wherein the physical state information at least comprises one of the following: body weight, body fat rate, protein content, bone salt content, visceral fat rate; and generating a target recipe according to the eating habit information of the user and the body state information of the user.
Optionally, the generating a target recipe according to the eating habit information of the user and the body state information of the user includes: recording the eating habit information of the user and the body state information of the user in a specified time period; analyzing the eating habit information of the user and the body state information of the user to obtain first target nutrition information which needs to be supplemented by the user; wherein the first target nutritional information comprises: a first target nutrient class, and a supplementation amount corresponding to each of the first target nutrient classes; obtaining a first target recipe corresponding to the first target nutritional information from a database, wherein the first target recipe comprises: first target food material information and cooking information of the first target food material.
Optionally, the generating a target recipe according to the eating habit information of the user and the body state information of the user includes: acquiring target weather information; and generating the target recipe according to the eating habit information of the user, the body state information of the user and the target weather information.
Optionally, the generating the target recipe according to the eating habit information of the user, the body state information of the user, and the target weather information includes: recording eating habit information of the user, body state information of the user and weather information in a specified time period; analyzing the eating habit information of the user, the body state information of the user and the weather information to obtain second target nutrition information which needs to be supplemented by the user; wherein the second target nutritional information comprises: a second target nutritional class, and a supplementation amount corresponding to each of the second target nutritional classes; acquiring a second target recipe corresponding to the second target nutritional information from a database, wherein the second target recipe comprises: second target food material information and cooking information of the second target food material.
Optionally, after the information of the consumed food materials is obtained, the method includes: generating a food material record table according to the eaten food material information, wherein the food material record table is used for recording the time of putting the eaten food material into the intelligent refrigerator and the time of taking the eaten food material out of the intelligent refrigerator, the type, the number and the weight of the eaten food material, the freshness of the eaten food material and the optimal eating time of the eaten food material.
Optionally, after generating the food material record table according to the consumed food material information, the method includes: when any food material placed in the intelligent refrigerator is taken out and is not placed back to the refrigerator after the preset time, deleting the record related to the food material in the food material record table, and sending prompt information, wherein the prompt information is used for prompting that the food material exceeds the optimal eating time.
According to another aspect of the embodiments of the present invention, there is also provided a recipe pushing device based on an internet of things operating system, including: the first acquisition module is used for acquiring the eating habit information of a user through intelligent household equipment in a specified time period, wherein the eating habit information at least comprises: information on eaten food materials and cooking information of each eaten food material; a generating module, configured to generate a target recipe according to the eating habit information of the user, where the target recipe at least includes: the target food material information and target cooking information corresponding to the target food material; and the pushing module is used for pushing the target recipe to the user.
Optionally, the obtaining module includes: a first obtaining unit, configured to obtain consumed food material information within a specified time period, where the consumed food material information includes: a time when the eaten food material is placed in an intelligent refrigerator, a time when the eaten food material is taken out of the intelligent refrigerator, a type of the eaten food material, and a quality and/or quantity of the eaten food material; a second obtaining unit, configured to obtain, within a specified time period, cooking information of the consumed food material, where the cooking information of the consumed food material at least includes: the type and amount of the eaten food material cooked, the cooking manner of the eaten food material, and the type and amount of seasoning used when the eaten food material is cooked.
Optionally, the generating module includes: a third obtaining unit, configured to obtain body state information of the user, where the body state information includes at least one of: body weight, body fat rate, protein content, bone salt content, visceral fat rate; and the first generating unit is used for generating a target recipe according to the eating habit information of the user and the body state information of the user.
Optionally, the first generating unit includes: the recording subunit is used for recording the eating habit information of the user and the body state information of the user in a specified time period; the analysis subunit is configured to analyze the eating habit information of the user and the body state information of the user to obtain first target nutritional information that the user needs to supplement, where the first target nutritional information includes: a first target nutrient class, and a supplementation amount corresponding to each of the first target nutrient classes; a first generating subunit, configured to obtain a first target recipe corresponding to the first target nutritional information from a database, where the first target recipe includes: first target food material information and cooking information of the first target food material.
Optionally, the first generating unit further includes: the acquisition subunit is used for acquiring target weather information; and the second generation subunit is used for generating the target recipe according to the eating habit information of the user, the body state information of the user and the weather information of the current day.
Optionally, the second generating subunit is further configured to: recording eating habit information of the user, body state information of the user and weather information in a specified time period; analyzing the eating habit information of the user, the body state information of the user and the weather information to obtain second target nutrition information which needs to be supplemented by the user; wherein the second target nutritional information comprises: a second target nutritional class, and a supplementation amount corresponding to each of the second target nutritional classes; acquiring a second target recipe corresponding to the second target nutritional information from a database, wherein the second target recipe comprises: second target food material information and cooking information of the second target food material.
Optionally, the obtaining module includes: a second generating unit, configured to generate a food material record table according to the eaten food material information, where the food material record table is used to record a time for putting the eaten food material into the smart refrigerator and a time for taking the eaten food material out of the smart refrigerator, a type, a number, and a weight of the eaten food material, a freshness of the eaten food material, and an optimal eating time of the eaten food material.
Optionally, the obtaining module further includes: the deleting unit is used for deleting the record related to any food material in the food material record table when any food material placed in the intelligent refrigerator is taken out and is not placed back to the refrigerator after a preset time; and the sending unit is used for sending prompt information, wherein the prompt information is used for prompting that the optimal eating time of any food material is exceeded.
According to another aspect of the embodiments of the present invention, there is also provided a computer-readable storage medium, in which a computer program is stored, where the computer program is configured to execute the above method for determining a suspicious account when the computer program is executed.
According to another aspect of the embodiments of the present invention, there is also provided an electronic device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor executes the method for determining the suspicious account number through the computer program.
In the embodiment of the invention, in a specified time period, the eating habit information of a user is acquired through the intelligent household equipment, wherein the eating habit information at least comprises the following components: information on eaten food materials and cooking information of each eaten food material; generating a target recipe according to the eating habit information of the user, wherein the target recipe at least comprises the following components: the target food material information and target cooking information corresponding to the target food material; the target recipes are pushed to the users, the corresponding recipes are formulated according to the dietary habits of each user for pushing, the technical problem that the recipe recommendation items of intelligent application are single and cannot meet the requirements of different users is solved, and the matching degree of the recipe pushing and the different users is improved.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a schematic diagram of a hardware environment of an alternative recipe pushing method based on an internet of things operating system according to an embodiment of the present invention;
fig. 2 is a flowchart of an alternative recipe pushing method based on an internet of things operating system according to an embodiment of the present invention;
fig. 3 is a block diagram of a recipe pushing system based on an internet of things operating system according to an embodiment of the present invention;
fig. 4 is a flowchart of an alternative recipe pushing method based on an internet of things operating system according to an embodiment of the present invention;
fig. 5 is an alternative structure block diagram of a recipe pushing device based on an internet of things operating system according to an embodiment of the present invention;
fig. 6 is a schematic structural diagram of an alternative electronic device according to an embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the invention described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
The method provided by the first embodiment of the present invention may be executed in a mobile terminal, a computer terminal, or a similar computing device. Taking the mobile terminal as an example, fig. 1 is a block diagram of a hardware structure of the mobile terminal of a recipe pushing method based on an internet of things operating system according to an embodiment of the present invention. As shown in fig. 1, the mobile terminal 10 may include one or more (only one shown in fig. 1) processors 102 (the processor 102 may include, but is not limited to, a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data, and optionally may also include a transmission device 106 for communication functions and an input-output device 108. It will be understood by those skilled in the art that the structure shown in fig. 1 is only an illustration, and does not limit the structure of the mobile terminal. For example, the mobile terminal 10 may also include more or fewer components than shown in FIG. 1, or have a different configuration than shown in FIG. 1.
The memory 104 may be used to store computer programs, for example, software programs and modules of application software, such as computer programs corresponding to the data information obtaining method in the embodiment of the present invention, and the processor 102 executes various functional applications and data processing by running the computer programs stored in the memory 104, so as to implement the above-mentioned method. The memory 104 may include high speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory located remotely from the processor 102, which may be connected to the mobile terminal 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The transmission device 106 is used for receiving or transmitting data via a network. Specific examples of the network described above may include a wireless network provided by a communication provider of the mobile terminal 10. In one example, the transmission device 106 includes a Network adapter (NIC), which can be connected to other Network devices through a base station so as to communicate with the internet. In one example, the transmission device 106 may be a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
Fig. 2 is a flowchart of a recipe pushing method based on an internet of things operating system according to an embodiment of the present invention. As shown in fig. 2, the method includes:
step S202, acquiring the eating habit information of the user through the intelligent household equipment in a specified time period, wherein the eating habit information at least comprises: information on eaten food materials and cooking information of each eaten food material;
step S204, generating a target recipe according to the eating habit information of the user, wherein the target recipe at least comprises: the target food material information and target cooking information corresponding to the target food material;
and step S206, pushing the target recipe to the user.
It should be noted that the above steps can be implemented on a cloud control platform of the intelligent gateway, the acquisition of the eating habit information of the user can be implemented through the intelligent home devices, and the related intelligent home devices are all connected to the same intelligent gateway through the internet of things, so that information sharing is implemented.
Fig. 3 is a block diagram of a recipe pushing system based on an internet of things operating system according to an embodiment of the present invention. As shown in fig. 3, the user control terminal, the intelligent refrigerator and the intelligent cabinet are all connected to the intelligent gateway.
Optionally, in a specific time, acquiring the eating habit information of the user through the smart home device includes: acquiring the eaten food material information in a specified time period, wherein the eaten food material information comprises: the time when the eaten food materials are put into the intelligent refrigerator, the time when the eaten food materials are taken out of the intelligent refrigerator, the types of the eaten food materials, and the quality and/or quantity of the eaten food materials; acquiring cooking information of the eaten food material within a specified time period, wherein the cooking information of the eaten food material at least comprises: the type and amount of the cooked edible material, the cooking style of the edible material, and the type and amount of seasoning used when the edible material is cooked.
In the process of using the intelligent refrigerator, the intelligent refrigerator can acquire images of food materials put in or taken out by a user through a camera, and the acquired food material images are uploaded to a cloud control platform.
In an implementation mode, cameras can be arranged inside a cabinet door and a cabinet of an intelligent refrigerator, so that the food materials put in or taken out by a user can be subjected to image acquisition through the cameras, and the acquired food material images are uploaded to a cloud control platform.
Meanwhile, the intelligent refrigerator can record the weight of food materials put into the refrigerator by a user through a self-contained weight sensor, and the weight of the food materials and the image of the food materials are uploaded to the cloud control platform together.
In addition, the user also can use the scanning bar code function through installing the intelligent refrigerator control APP on the cell-phone, through the mode that scans two-dimensional code or the bar code on eating the material extranal packing, acquires the relevant information of this edible material, include: the production place, the type, the weight, the brand, the production date, the quality guarantee period and the like, and the obtained related information of the food materials is uploaded to the cloud control platform to be stored.
The intelligent cabinet is used for collecting images of seasonings taken out by a user through a camera arranged on the intelligent cabinet, determining the type of the seasonings used by the user during cooking, determining the cooking habits of the user according to the quality change of the seasonings before and after the seasonings are taken out, and uploading the information to the cloud control platform.
In this scheme, after information determination user that high in the clouds control platform uploaded through intelligent refrigerator takes out some edible materials, can send "batching record" instruction to intelligent cupboard to make intelligent cupboard respond to this instruction, confirm the batching kind that the user took out through the camera, and according to the quality change of this batching before taking out and after putting into, and upload these some information to high in the clouds control platform, so that high in the clouds control platform can confirm that the user is when these edible materials of culinary art according to these some information, the seasoning and the quantity of custom-added.
For example, the cloud control platform determines that the food material taken out by the user is: "tofu" and issued a "ingredients record" command to the intelligent cabinet, which in response to the "ingredients record" command, determines the ingredients taken by the user as "chili paste" by means of the camera and determines the quality variation before and after the chili paste is taken out and put back: 10g to upload these information to high in the clouds control platform, and then high in the clouds control platform can confirm and save the user to eating the culinary art custom of material "bean curd" and do: cooking with chili paste.
The type and quantity of food materials and the type and quantity of seasonings being cooked at present can be obtained through an intelligent gas stove or an integrated stove or a camera of an intelligent range hood, and the embodiment of the invention does not limit the types and the quantities.
Optionally, generating the target recipe according to the eating habit information of the user includes: acquiring physical state information of a user, wherein the physical state information at least comprises one of the following: body weight, body fat rate, protein content, bone salt content, visceral fat rate; and generating a target recipe according to the eating habit information of the user and the body state information of the user.
Optionally, the generating the target recipe according to the eating habit information of the user and the body state information of the user comprises: recording the eating habit information of the user and the body state information of the user in a specified time period; analyzing the eating habit information and the body state information of the user to obtain first target nutrition information which needs to be supplemented by the user; wherein the first target nutritional information comprises: a first target nutrient class, and a supplementation amount corresponding to each first target nutrient class; obtaining a first target recipe corresponding to the first target nutritional information from the database, wherein the first target recipe comprises: the first target food material information and the cooking information of the first target food material.
For example, if the body state information of the user shows that the fat content in the body of the user is high and the protein content is low, a recipe with high protein and low fat, such as egg white, beef, chicken breast, green leaf vegetables and the like, can be recommended to the user, and simultaneously, the favorite cooking method of the user is recommended according to the eating habits of the user.
Optionally, the generating the target recipe according to the eating habit information of the user and the body state information of the user comprises: acquiring target weather information; and generating a target recipe according to the eating habit information of the user, the body state information of the user and the target weather information.
Optionally, generating the target recipe according to the eating habit information of the user, the body state information of the user, and the target weather information includes: recording eating habit information of a user, body state information of the user and weather information in a specified time period; analyzing the eating habit information of the user, the body state information of the user and the weather information to obtain second target nutrition information which needs to be supplemented by the user; wherein the second target nutritional information comprises: a second target nutritional class, and a supplementation amount corresponding to each of the second target nutritional classes; acquiring a second target recipe corresponding to the second target nutritional information from a database, wherein the second target recipe comprises: second target food material information and cooking information of the second target food material.
For example, in autumn when the weather is dry, some recipes for moistening the lung can be recommended, and meanwhile, recipes which meet the physical requirements and the dietary preferences of the user are recommended to the user in consideration of the physical state and the dietary habits of the user. Some warm-tonifying recipes such as mutton soup can be recommended when the temperature is low in winter, but if uric acid in the body of a user is high, food with relatively high purine is avoided, and the mutton soup is a fault of high purine, so that certain avoidance is needed.
Optionally, after the information of the consumed food material is obtained, the method includes: and generating a food material recording table according to the eaten food material information, wherein the food material recording table is used for recording the time of putting the eaten food material into the intelligent refrigerator and the time of taking the eaten food material out of the intelligent refrigerator, the type, the number and the weight of the eaten food material, the freshness of the eaten food material and the optimal eating time of the eaten food material.
Optionally, after generating the food material record table according to the consumed food material information, the method includes: when any food material placed in the intelligent refrigerator is taken out and is not placed back to the refrigerator after the preset time, the record related to any food material in the food material record table is deleted, and prompt information is sent, wherein the prompt information is used for prompting that the optimal eating time of any food material is exceeded.
According to the information recommendation method based on the Internet of things operating system, on one hand, when a user uses the intelligent refrigerator, the intelligent refrigerator can identify food materials put in or taken out by the user through a camera of the intelligent refrigerator, and upload the types and the putting time of the food materials to a cloud control platform; the cloud control platform classifies the food materials (vegetables, fruits, meats, eggs and the like) according to the food material types uploaded by the intelligent refrigerator, and counts the food material types used or bought by the user in a preset counting period, so as to determine the eating habits and recent recipe composition of the user according to the counting result; on one hand, the cloud control platform can also send a data acquisition instruction to the intelligent cabinet, so that the intelligent cabinet can record the usage amount of the seasoning used by the user during each cooking and upload the usage amount to the cloud control platform for storage, and the server can determine the cooking habit of the user according to the data; on the other hand, the cloud control platform can acquire the current weather condition through a weather APP or an intelligent door and window system, and acquire body data of the user through an intelligent body fat scale; and finally, the cloud control platform can recommend the food materials of the current day (or a period of time in the future) to the user according to the eating habits of the user and according to the weather conditions, cooking habits, body data and the latest recipe composition. Adopt the scheme that this application provided, through the collection of intelligent refrigerator and intelligent cupboard to user's edible material and seasoning, high in the clouds control platform can be accurate acquire user's eating habits and culinary art custom to can acquire the nearest recipe constitution of user, refer to weather data and the user health data that acquire simultaneously, can guarantee to eat when recommending to the user, both accord with user's eating habits, can satisfy daily nutrition demand again, and accord with user health needs, be favorable to that the user is healthy. In addition, linkage between the intelligent household devices and intelligent degree of the intelligent household are greatly improved.
In order to further understand the technical solution of the embodiment of the present invention, the following description is made with reference to fig. 4. Fig. 4 is a flowchart of a recipe pushing method based on an internet of things operating system according to an embodiment of the present invention. As shown in fig. 4, the method includes:
In an implementation mode, cameras can be arranged inside a cabinet door and a cabinet of an intelligent refrigerator, so that the food materials put in or taken out by a user can be subjected to image acquisition through the cameras, and the acquired food material images are uploaded to a cloud control platform.
Meanwhile, the intelligent refrigerator can record the weight of food materials put into the refrigerator by a user through a self-contained weight sensor, and the weight of the food materials and the image of the food materials are uploaded to the cloud control platform together.
In addition, the user also can use the scanning bar code function through installing the intelligent refrigerator control APP on the cell-phone, through the mode that scans two-dimensional code or the bar code on eating the material extranal packing, acquires the relevant information of this edible material, include: the production place, the type, the weight, the brand, the production date, the shelf life and the like, and the obtained food material related information is uploaded to a cloud control platform (equivalent to an intelligent gateway) to be stored.
Generally, the outer package of the food material is often written with information related to the brand, the type and the like of the food material, and the cloud control platform can determine the brand and the type of the product by performing image recognition on the collected food material images, and then search the information related to the food material on the network according to the brand, the type and the collected food material images. For example, through image recognition, the cloud control platform determines that the food material put into the intelligent refrigerator is: three-component pure milk.
In addition, it should be noted here that, when the user selects to use the intelligent refrigerator control APP to actively input the food material information, the cloud control platform can acquire the relevant information of the food material in a bar code scanning manner, so that when the user puts the food material into the intelligent refrigerator, the intelligent refrigerator can upload the acquired food material image to the cloud control platform, so that the cloud control platform can judge whether the relevant information of the food material is stored through image recognition, and when the cloud server stores the relevant information of the food material, the cloud control platform cannot continue to search the relevant information of the food material.
And aiming at the scene that the user purchases food materials through the shopping APP, the cloud control platform can acquire the shopping order of the food materials under the account from the shopping APP client side or the server through the shopping APP registered by the user, and further determine and store the related information of the newly purchased food materials of the user according to the order information.
In addition, it should be noted that, when the user takes out the food material from the intelligent refrigerator, the intelligent refrigerator uploads the taken-out food material to the cloud control platform, so that the cloud control platform records the taking-out date in the food material record table corresponding to the food material. When the food material is taken out and exceeds a preset time threshold (for example, 24 hours, in the scheme, different time thresholds are set for different food materials, for convenience of description, the time thresholds set for different food materials are hereinafter referred to as "the longest storage time outside the refrigerator") and the food materials are not put back into the intelligent refrigerator, a record corresponding to the food material is deleted in the food material record table, and meanwhile, a prompt is sent to a user to inform the user that the time for taking out the refrigerator by the food material is long, and if the time is not consumed, the user is advised to discard the food material, so that the food material which is possibly deteriorated due to the fact that the user takes out the refrigerator for a.
And the cloud control platform can create a consumed food material record table in the database, record the food material which is taken out from the intelligent refrigerator by the user and is not put back in the consumed food material record table, determine the taking-out date of the food material recorded in the food material record table as the consumption date of the food material, record the consumption date of the food material and the weight of the food material obtained by executing the steps 1-2 in the consumed food material record table, and delete the record corresponding to the food material from the food material record table.
For example, by executing step 1 and step 2, the cloud control platform creates a "food material record table" shown in table 1 below.
TABLE 1 food material recording table
| Food material | Type (B) | Species of | Date of storage | Status of state | Date of taking out |
| Food material a | Dairy product | Milk | Number 6 month 10 2019 | Taking out | Number 6 month 12 2019 |
| Food material b | Vegetable product | Spinach | Number 6 month 11 2019 | Storage of | - |
| Food material c | Fruit | Peach (Chinese character) | Number 6 month 12 2019 | Taking out | Number 6 month 14 of 2019 |
The state in the record table indicates whether the food material is currently stored in the intelligent refrigerator, the state "take-out" indicates that the food material is currently taken out by a user and is not in the intelligent refrigerator, and the cloud control platform can take out the date of the food material collected by the intelligent refrigerator as the date of the food material taken out for the food material in the state "take-out". And for the food materials in the state of storage, the taking-out date is not recorded.
As noted in table 1 above, assume that the "longest storage time period outside the refrigerator" preset for milk is: 24 hours, the current date is No. 6/14, and the cloud control platform determines that the food material a taking time exceeds the "longest storage time outside the refrigerator" according to the taking date recorded in the food material record table, so that the cloud control platform can record the food material a and the consumption time of the food material a in the "consumed food material record table" shown in the following table 2, and delete the relevant record of the food material a in the table 1.
Table 2 consumed food material recording table
| Food material | Type (B) | Species of | Date of consumption | Weight (g) |
| Food material a | Dairy product | Milk | Number 6 month 12 2019 | 100g |
| Food material d | Vegetable product | Amaranthus mangostanus L.var.amaranth | Number 6 month 10 2019 | 500g |
| Food material e | Fruit | Watermelon | Number 6 month 9 2019 | 500g |
In this scheme, the cloud control platform may count the types and weights of the food materials consumed by the user in a preset time period (for example, 7 days) according to the consumed food material record table.
For example, the cloud control platform determines that the statistics of the consumed food materials in the past week (7 days) of the user are as follows: meat: 800g, vegetables: 900g, fruit: 600g, dairy product: 400 g.
The cloud control platform can acquire the theoretical normal diet food material composition ratio of the user (or the normal diet food material composition ratio of the user recommended by a nutrition expert) through the internet, for example, on the premise of guaranteeing the nutrition balance, the theoretical normal diet food material composition ratio of the user is as follows: meat: vegetable: fruit: the dairy product is 2:2:1:1, that is, the ratio of the food material types ingested by the user in a certain time period (for example, 1 day, 1 week, 1 month, etc.) should satisfy the above-mentioned ratio requirement.
Supposing that the cloud control platform determines that the theoretical normal diet and food material composition proportion of the user is as follows: meat: vegetable: fruit: the dairy product is 2:2:1:1, and the user is determined to have a diet food material composition in the past week (7 days) by performing step 3: meat: 800g, vegetables: 900g, fruit: 600g, dairy product: 400g, the cloud control platform may determine that the food material composition of the user in the future one week (7 days) is: meat: 800g, vegetables: 700g, fruit: 200g of dairy product: 400g, further ensuring that the composition ratio of the food materials in the diet of the user in two weeks reaches: meat: vegetable: fruit: dairy product 2:2:1: 1.
In this scheme, after information determination user that high in the clouds control platform uploaded through intelligent refrigerator takes out some edible materials, can send "batching record" instruction to intelligent cupboard to make intelligent cupboard respond to this instruction, confirm the batching kind that the user took out through the camera, and according to the quality change of this batching before taking out and after putting into, and upload these some information to high in the clouds control platform, so that high in the clouds control platform can confirm that the user is when these edible materials of culinary art according to these some information, the seasoning and the quantity of custom-added.
For example, the cloud control platform determines that the food material taken out by the user is: "tofu" and issued a "ingredients record" command to the intelligent cabinet, which in response to the "ingredients record" command, determines the ingredients taken by the user as "chili paste" by means of the camera and determines the quality variation before and after the chili paste is taken out and put back: 10g to upload these information to high in the clouds control platform, and then high in the clouds control platform can confirm and save the user to eating the culinary art custom of material "bean curd" and do: cooking with chili paste.
And 406, the cloud control platform acquires weather information from the weather APP.
It should be noted here that, the cloud control platform can acquire weather information through the weather APP, and can also acquire a current weather condition through the sensor of the smart door/window.
In addition, in this scheme, high in the clouds control platform can constitute recommendation cycle according to diet edible material, obtains the weather information in appointed date range from weather APP department. For example, if the cloud control platform recommends a future seven-day diet food material composition to the user every seven days, in this case, the cloud control platform may obtain a future seven-day weather condition from the weather APP every seven days; and assuming that the cloud control platform recommends the diet food material composition for the next day to the user every day, under such a condition, the cloud control platform needs to acquire the weather condition for the next day from the weather APP every day.
Specifically, the cloud control platform stores preset food material recommendation rules, such as may include:
rule a: the temperature is more than or equal to 32 ℃, and food materials which do not contain hot peppers in a habitual cooking mode are recommended;
rule b: the temperature is less than 0 ℃, and food materials containing pepper in a habitual cooking mode are recommended;
rule c: snowfall, recommended food material spareribs … …, and so on.
In this scheme, the cloud control platform may determine the recommended food material type and recommended times within a period of time in the future according to the dietary food material composition determined by performing step 4. And the cloud control platform can determine food materials meeting recommendation rules in the suggested food material categories according to the obtained weather conditions and the preset food material recommendation rules, and sends the determined food materials to the intelligent refrigerator and the user terminal so as to recommend the food materials to the user through the intelligent refrigerator and the mobile terminal.
For example, the cloud control platform determines that the food materials for eating on the next day are meat, vegetables and soy products, and determines that the weather conditions on the next day are: the temperature is-5 ℃, and when snow falls, the cloud control platform can determine to recommend food materials according to preset food material recommendation rules: bean curd and spareribs, determining a vegetable (such as shallot) from food materials which are frequently matched with the bean curd or the spareribs by a user according to cooking habits of the user, and pushing the determined food materials to the user.
It should be noted that, for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present invention is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the invention. Further, those skilled in the art should also appreciate that the embodiments described in the specification are preferred embodiments and that the acts and modules referred to are not necessarily required by the invention.
Through the above description of the embodiments, those skilled in the art can clearly understand that the method according to the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but the former is a better implementation mode in many cases. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (e.g., ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal device (e.g., a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
According to another aspect of the embodiment of the invention, a recipe pushing device based on an internet of things operating system is further provided, wherein the recipe pushing device is used for implementing the recipe pushing method based on the internet of things operating system. Fig. 5 is an alternative structural block diagram of a recipe pushing device based on an internet of things operating system according to an embodiment of the present invention, and as shown in fig. 5, the device includes:
a first obtaining module 502, configured to obtain, by the smart home device, eating habit information of a user in a specified time period, where the eating habit information at least includes: information on eaten food materials and cooking information of each eaten food material;
a generating module 504, configured to generate a target recipe according to the eating habit information of the user, where the target recipe at least includes: the target food material information and target cooking information corresponding to the target food material;
a pushing module 506, configured to push the target recipe to the user.
Optionally, the obtaining module includes: the first obtaining unit is used for obtaining food material information placed inside the intelligent refrigerator within a specified time period, wherein the food material information at least comprises: the time for placing the food materials into the intelligent refrigerator, the types of the food materials, the time for taking the food materials out of the intelligent refrigerator, and the volume and/or the number of the food materials; a second obtaining unit, configured to obtain cooking information of the food material in a specified time period, where the cooking information at least includes: the type and the number of the food materials to be cooked, the cooking mode of the food materials, and the type and the amount of seasonings to be used when the food materials are cooked.
Optionally, the obtaining module includes: a first obtaining unit, configured to obtain consumed food material information within a specified time period, where the consumed food material information includes: a time when the eaten food material is placed in an intelligent refrigerator, a time when the eaten food material is taken out of the intelligent refrigerator, a type of the eaten food material, and a quality and/or quantity of the eaten food material; a second obtaining unit, configured to obtain, within a specified time period, cooking information of the consumed food material, where the cooking information of the consumed food material at least includes: the type and amount of the eaten food material cooked, the cooking manner of the eaten food material, and the type and amount of seasoning used when the eaten food material is cooked.
Optionally, the generating module includes: a third obtaining unit, configured to obtain body state information of the user, where the body state information includes at least one of: body weight, body fat rate, protein content, bone salt content, visceral fat rate; and the first generating unit is used for generating a target recipe according to the eating habit information of the user and the body state information of the user.
Optionally, the first generating unit includes: the recording subunit is used for recording the eating habit information of the user and the body state information of the user in a specified time period; the analysis subunit is configured to analyze the eating habit information of the user and the body state information of the user to obtain first target nutritional information that the user needs to supplement, where the first target nutritional information includes: a first target nutrient class, and a supplementation amount corresponding to each of the first target nutrient classes; a first generating subunit, configured to obtain a first target recipe corresponding to the first target nutritional information from a database, where the first target recipe includes: first target food material information and cooking information of the first target food material.
Optionally, the first generating unit further includes: the acquisition subunit is used for acquiring target weather information; and the second generation subunit is used for generating the target recipe according to the eating habit information of the user, the body state information of the user and the weather information of the current day.
Optionally, the second generating subunit is further configured to: recording eating habit information of the user, body state information of the user and weather information in a specified time period; analyzing the eating habit information of the user, the body state information of the user and the weather information to obtain second target nutrition information which needs to be supplemented by the user; wherein the second target nutritional information comprises: a second target nutritional class, and a supplementation amount corresponding to each of the second target nutritional classes; acquiring a second target recipe corresponding to the second target nutritional information from a database, wherein the second target recipe comprises: second target food material information and cooking information of the second target food material.
Optionally, the obtaining module includes: a second generating unit, configured to generate a food material record table according to the eaten food material information, where the food material record table is used to record a time for putting the eaten food material into the smart refrigerator and a time for taking the eaten food material out of the smart refrigerator, a type, a number, and a weight of the eaten food material, a freshness of the eaten food material, and an optimal eating time of the eaten food material.
Optionally, the obtaining module further includes: the deleting unit is used for deleting the record related to any food material in the food material record table when any food material placed in the intelligent refrigerator is taken out and is not placed back to the refrigerator after a preset time; and the sending unit is used for sending prompt information, wherein the prompt information is used for prompting that the optimal eating time of any food material is exceeded.
According to another aspect of the embodiment of the invention, an electronic device for implementing the recipe pushing method based on the internet of things operating system is further provided. As shown in fig. 6, the electronic device comprises a memory 1002 and a processor 1004, the memory 1002 having stored therein a computer program, the processor 1004 being arranged to execute the steps of any of the method embodiments described above by means of the computer program.
Optionally, in this embodiment, the electronic apparatus may be located in at least one network device of a plurality of network devices of a computer network.
Optionally, in this embodiment, the processor may be configured to execute the following steps by a computer program:
s1, acquiring the eating habit information of the user through the intelligent household equipment in a specified time period, wherein the eating habit information at least comprises: information on eaten food materials and cooking information of each eaten food material;
s2, generating a target recipe according to the eating habit information of the user, wherein the target recipe at least comprises: the target food material information and target cooking information corresponding to the target food material;
and S3, pushing the target recipe to the user.
Alternatively, it can be understood by those skilled in the art that the structure shown in fig. 6 is only an illustration, and the electronic device may also be a terminal device such as a smart phone (e.g., an Android phone, an iOS phone, etc.), a tablet computer, a palm computer, a Mobile Internet Device (MID), a PAD, and the like. Fig. 6 is a diagram illustrating a structure of the electronic device. For example, the electronic device may also include more or fewer components (e.g., network interfaces, etc.) than shown in FIG. 6, or have a different configuration than shown in FIG. 6.
The memory 1002 may be configured to store software programs and modules, such as program instructions/modules corresponding to the recipe pushing method and apparatus based on the internet of things operating system in the embodiment of the present invention, and the processor 1004 executes various functional applications and data processing by running the software programs and modules stored in the memory 1002, that is, the recipe pushing method based on the internet of things operating system is implemented. The memory 1002 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 1002 may further include memory located remotely from the processor 1004, which may be connected to the terminal over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof. The memory 1002 may be specifically, but not limited to, configured to store program steps of a recipe pushing method based on an internet of things operating system. As an example, as shown in fig. 6, the memory 1002 may include, but is not limited to, the first obtaining module 502, the generating module 504, and the pushing module 506 in the recipe pushing apparatus based on the internet of things operating system. In addition, other module units in the device for determining a suspicious account may also be included, but are not limited to this, and are not described in this example again.
Optionally, the above-mentioned transmission device 1006 is used for receiving or sending data via a network. Examples of the network may include a wired network and a wireless network. In one example, the transmission device 1006 includes a Network adapter (NIC) that can be connected to a router via a Network cable and other Network devices so as to communicate with the internet or a local area Network. In one example, the transmission device 1006 is a Radio Frequency (RF) module, which is used for communicating with the internet in a wireless manner.
In addition, the electronic device further includes: the display 1008 is used for displaying alarm pushing of suspicious accounts; and a connection bus 1010 for connecting the respective module parts in the above-described electronic apparatus.
Embodiments of the present invention also provide a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the above method embodiments when executed.
Alternatively, in the present embodiment, the storage medium may be configured to store a computer program for executing the steps of:
s1, acquiring the eating habit information of the user through the intelligent household equipment in a specified time period, wherein the eating habit information at least comprises: information on eaten food materials and cooking information of each eaten food material;
s2, generating a target recipe according to the eating habit information of the user, wherein the target recipe at least comprises: the target food material information and target cooking information corresponding to the target food material;
and S3, pushing the target recipe to the user.
Optionally, the storage medium is further configured to store a computer program for executing the steps included in the method in the foregoing embodiment, which is not described in detail in this embodiment.
Alternatively, in this embodiment, a person skilled in the art may understand that all or part of the steps in the methods of the foregoing embodiments may be implemented by a program instructing hardware associated with the terminal device, where the program may be stored in a computer-readable storage medium, and the storage medium may include: flash disks, Read-Only memories (ROMs), Random Access Memories (RAMs), magnetic or optical disks, and the like.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
The integrated unit in the above embodiments, if implemented in the form of a software functional unit and sold or used as a separate product, may be stored in the above computer-readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or a part of or all or part of the technical solution contributing to the prior art may be embodied in the form of a software product stored in a storage medium, and including instructions for causing one or more computer devices (which may be personal computers, servers, network devices, or the like) to execute all or part of the steps of the method described in the embodiments of the present application.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the several embodiments provided in the present application, it should be understood that the disclosed client may be implemented in other manners. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one type of division of logical functions, and there may be other divisions when actually implemented, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (11)
1. A recipe pushing method based on an Internet of things operating system is characterized by comprising the following steps:
in a specified time period, acquiring eating habit information of a user through intelligent household equipment, wherein the eating habit information comprises: information on eaten food materials and cooking information of each eaten food material;
generating a target recipe according to the eating habit information of the user, wherein the target recipe comprises: the target food material information and target cooking information corresponding to the target food material;
and pushing the target recipe to the user.
2. The method according to claim 1, wherein the acquiring, by the smart home device, the eating habit information of the user in the specified time period comprises:
acquiring eaten food material information in a specified time period, wherein the eaten food material information comprises: a time when the eaten food material is placed in an intelligent refrigerator, a time when the eaten food material is taken out of the intelligent refrigerator, a type of the eaten food material, and a quality and/or quantity of the eaten food material;
acquiring cooking information of the eaten food material within a specified time period, wherein the cooking information of the eaten food material at least comprises: the type and amount of the eaten food material cooked, the cooking manner of the eaten food material, and the type and amount of seasoning used when the eaten food material is cooked.
3. The method according to claim 1 or 2, wherein generating a target recipe from the user's eating habit information comprises:
acquiring physical state information of the user, wherein the physical state information at least comprises one of the following: body weight, body fat rate, protein content, bone salt content, visceral fat rate;
and generating a target recipe according to the eating habit information of the user and the body state information of the user.
4. The method of claim 3, wherein generating a target recipe based on the user's eating habits information and the user's physical state information comprises:
recording the eating habit information of the user and the body state information of the user in a specified time period;
analyzing the eating habit information of the user and the body state information of the user to obtain first target nutrition information which needs to be supplemented by the user, wherein the first target nutrition information comprises: a first target nutrient class, and a supplementation amount corresponding to each of the first target nutrient classes;
obtaining a first target recipe corresponding to the first target nutritional information from a database, wherein the first target recipe comprises: first target food material information and cooking information of the first target food material.
5. The method of claim 3, wherein generating a target recipe based on the user's eating habits information and the user's physical state information comprises:
acquiring target weather information;
and generating the target recipe according to the eating habit information of the user, the body state information of the user and the target weather information.
6. The method of claim 5, wherein generating the target recipe from the user's eating habits information, the user's physical state information, and the target weather information comprises:
recording eating habit information of the user, body state information of the user and weather information in a specified time period;
analyzing the eating habit information of the user, the body state information of the user and the weather information to obtain second target nutrition information which needs to be supplemented by the user; wherein the second target nutritional information comprises: a second target nutritional class, and a supplementation amount corresponding to each of the second target nutritional classes;
acquiring a second target recipe corresponding to the second target nutritional information from a database, wherein the second target recipe comprises: second target food material information and cooking information of the second target food material.
7. The method of claim 2, wherein after the obtaining of the consumed food material information, the method comprises:
generating a food material record table according to the eaten food material information, wherein the food material record table is used for recording the time of putting the eaten food material into the intelligent refrigerator and the time of taking the eaten food material out of the intelligent refrigerator, the type, the number and the weight of the eaten food material, the freshness of the eaten food material and the optimal eating time of the eaten food material.
8. The method of claim 7, wherein after generating a food material record table according to the consumed food material information, the method comprises:
when any food material placed in the intelligent refrigerator is taken out and is not placed back to the refrigerator after the preset time, deleting the record related to the food material in the food material record table, and sending prompt information, wherein the prompt information is used for prompting that the food material exceeds the optimal eating time.
9. The utility model provides a diet pusher based on thing networking operating system which characterized in that includes:
the acquisition module is used for acquiring the eating habit information of a user through the intelligent household equipment in a specified time period, wherein the eating habit information at least comprises: information on eaten food materials and cooking information of each eaten food material;
a generating module, configured to generate a target recipe according to the eating habit information of the user, where the target recipe at least includes: the target food material information and target cooking information corresponding to the target food material;
and the pushing module is used for pushing the target recipe to the user.
10. A computer-readable storage medium comprising a stored program, wherein the program when executed performs the method of any of claims 1 to 8.
11. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to execute the method of any of claims 1 to 8 by means of the computer program.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111402996A (en) * | 2020-03-19 | 2020-07-10 | 珠海格力电器股份有限公司 | Diet recipe recommendation method and system and storage medium |
| CN111459054A (en) * | 2020-04-14 | 2020-07-28 | 珠海格力电器股份有限公司 | Recipe pushing method, equipment, storage medium and kitchen appliance |
| CN111639261A (en) * | 2020-05-27 | 2020-09-08 | 合肥美的电冰箱有限公司 | Message pushing method, system, electronic equipment and storage medium |
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Application publication date: 20191231 |