CN109493156A - Vegetable recommended method and device based on workout data - Google Patents
Vegetable recommended method and device based on workout data Download PDFInfo
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- CN109493156A CN109493156A CN201811079653.8A CN201811079653A CN109493156A CN 109493156 A CN109493156 A CN 109493156A CN 201811079653 A CN201811079653 A CN 201811079653A CN 109493156 A CN109493156 A CN 109493156A
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- vegetable
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- heat density
- heat
- workout data
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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
- G06Q30/06—Buying, selling or leasing transactions
- G06Q30/0601—Electronic shopping [e-shopping]
- G06Q30/0631—Item recommendations
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
Abstract
The vegetable recommended method based on workout data that this application discloses a kind of, comprising: workout data of the acquisition user in gymnasium；Determine user in the exercise intensity of the gymnasium according to the workout data；Based on the mapping relations matrix of user's exercise intensity and heat density under at least one physiological characteristic dimension, the exercise intensity corresponding target heat density in the mapping relations matrix is determined；Target is obtained to have dinner the dish information of food and drink shops in geographical coverage area locating for position；It is screened and the matched vegetable of target heat density at least one food and drink shops in the geographical coverage area according to the dish information.The vegetable recommended method based on workout data carries out the heat of exercise consumption supplemented with user much sooner and precisely, promote sport and body-building industry with catering industry merging on line, while also improving the consumption experience and user's viscosity of user.
Description
Technical field
This application involves Internet technical fields, and in particular to a kind of vegetable recommended method based on workout data.This Shen
Please it is related to a kind of vegetable recommendation apparatus and a kind of electronic equipment based on workout data simultaneously.
Background technique
With the rapid development of the technologies such as Internet of Things, big data, various technologies relevant to Internet of Things, big data have been goed deep into
Different social sectors are applied to, with user's life, the quickening of work rhythm, the psychological pressure faced and body pressure
Also increasing, user to gymnasium participates in body-building and has become common exercise and pressure delivery mode, and user is in sanitation park or square
While performed physical exercise, it is also necessary to pass through the body kept fit of making rational planning for diet control of dietary structure.
A kind of vegetable collocation recommended method based on institute's calorific requirement that the prior art (CN105844357A) provides, comprising:
Calorie calculation step need to be supplemented: according to user it is daily needed for basis heat and the heat of consumption needed for this day for obtaining in advance
Amount, calculates the heat of the user required supplement when having dinner；Step is formulated in vegetable combination: right according to each vegetable institute
The calorie value and vegetable combined method answered formulate multiple alternative vegetable combinations of active user；Vegetable group screening step to one's taste
It is rapid: multiple vegetable groups are generated in the alternative vegetable combination according to the consumer behavior and taste hobby of user in systems
Conjunction scheme；Vegetable combined recommendation step: according to the sequence of the vegetable assembled scheme, recommend best vegetable combination for user.
The vegetable based on institute's calorific requirement that the prior art provides is arranged in pairs or groups recommended method, when carrying out vegetable collocation and recommending, is
The heat that user requires supplementation with is extrapolated according to the historical data of the heat consumed in the past, to be according to the heat extrapolated
User recommends vegetable matched combined, however, this method can not be that user recommends dish according to the heat that user currently consumes in real time
Product in time can not targetedly supplement the heat of user's consumption, be haveed the defects that certain.
Summary of the invention
The application provides a kind of vegetable recommended method based on workout data, to solve defect of the existing technology.This
Apply while being related to a kind of vegetable recommendation apparatus and a kind of electronic equipment based on workout data.
The application provides a kind of vegetable recommended method based on workout data, comprising: acquisition user is in the strong of gymnasium
Body data；Determine user in the exercise intensity of the gymnasium according to the workout data；Based on user at least one life
The mapping relations matrix for managing exercise intensity and heat density under characteristic dimension, determines the exercise intensity in the mapping relations square
Corresponding target heat density in battle array；Target is obtained to have dinner the dish information of food and drink shops in geographical coverage area locating for position；
It is screened and the target heat density at least one food and drink shops in the geographical coverage area according to the dish information
Matched vegetable.
Optionally, the vegetable recommended method based on workout data, comprising: it is pre- that vegetable is generated based on the vegetable filtered out
About order.
Optionally, the exercise intensity and the mapping relations matrix of heat density and user have unique corresponding relation, institute
State fortune of the mapping relations matrix of exercise intensity and heat density based on the physiological characteristic of user and user in historical time section
Fatigue resistance and the heat density for consuming vegetable determine；Wherein, the heat density of the vegetable, the heat that can be provided according to vegetable
Amount and the quality and/or volume of vegetable determine.
Optionally, the physiological characteristic dimension is provided with corresponding priority；Wherein, the physiological characteristic, including
It is at least one of following: height, weight, body fat rate, blood pressure, blood lipid, blood glucose, body temperature.
Optionally, the mapping based on user exercise intensity and heat density under at least one physiological characteristic dimension is closed
It is matrix, determines the exercise intensity corresponding target heat density in the mapping relations matrix, comprising: search the fortune
Corresponding heat is close in exercise intensity and the mapping relations matrix of heat density under each physiological characteristic dimension of user for fatigue resistance
Degree；According to physiological characteristic dimension priority in descending order to the heat density under each physiological characteristic dimension found into
Row sequence；Select the heat density under the physiological characteristic dimension of highest priority as the target heat density.
Optionally, the workout data is acquired by the infrared collecting device for being set to carpet in the gymnasium and is obtained,
Correspondingly, described determine user in the exercise intensity of the gymnasium according to the workout data, comprising: according to the body-building
The sport and body-building type and run duration for including in data calculate user in the gymnasium in conjunction with the physiological characteristic of user
Each period heat consumption；Heat consumption according to user in each period determines user in the foundation motion of each period
Intensity；It is weighted in time dimension according to the foundation motion intensity, by the foundation motion intensity in time dimension
Exercise intensity of the weighted average as user in the gymnasium.
Optionally, the target that obtains is had dinner the dish information of food and drink shops in geographical coverage area locating for position, comprising:
Determine the food and drink shops that the target is had dinner in geographical coverage area locating for position；The food and drink door is extracted from vegetable database
The dish information of vegetable in shop；It include the caloric information of the vegetable in the dish information.
Optionally, described to be screened at least one food and drink shops in the geographical coverage area according to the dish information
With the matched vegetable of target heat density, comprising: at least one food and drink shops in the geographical coverage area, execute
Following operation: the quality and/or volume of the heat and vegetable that can be provided according to the vegetable for including in the dish information, meter
Calculate the heat density of vegetable；From both the heat density of food and drink shops screening vegetable and the target heat density difference
Absolute value be less than setting heat density threshold value vegetable, as with the matched vegetable of the mark heat density.
Optionally, described that vegetable reservation order is generated based on the vegetable filtered out, comprising: to be wrapped according in the workout data
The amount of exercise and run duration contained calculates user's total amount of heat consumed by the sanitation park or square under the current dining period；According to sieve
The caloric information for including in the dish information of vegetable is selected, the total amount of heat of vegetable is filtered out described in calculating；It is filtered out described in judgement
Whether the total amount of heat of vegetable is more than or equal to user's total amount of heat consumed by the sanitation park or square under the current dining period, if
It is to be filtered to the vegetable for filtering out vegetable type coincidence in vegetable；Vegetable is consumed in historical time section to user
Clustering is carried out, the dining preference of user is obtained；It is rejected in vegetable after filtration unmatched with the dining preference of user
Vegetable.
Optionally, if whether the total amount of heat for filtering out vegetable described in the judgement was more than or equal under the current dining period
User's judging result of total amount of heat sub-step consumed by the sanitation park or square be it is no, perform the following operations: in the geographic region
The heat density matched vegetable adjacent with the target heat density numerical value screens at least one food and drink shops within the scope of domain, and
The vegetable is added in the vegetable of screening and reserves order；Also, preferential screening is adjacent with the target heat density numerical value and counts
Value is greater than the matched vegetable of heat density of the target heat density.
Optionally, target geographical coverage area locating for position of having dinner includes: that the target is had dinner quotient locating for position
Enclose range of nodes.
The application also provides a kind of vegetable recommendation apparatus based on workout data, comprising:
Workout data acquisition unit, for acquiring user in the workout data of gymnasium；
Exercise intensity determination unit, for determining that movement of the user in the gymnasium is strong according to the workout data
Degree；
Target heat density determination unit, for being based on user exercise intensity and heat under at least one physiological characteristic dimension
The mapping relations matrix of metric density determines the exercise intensity corresponding target heat density in the mapping relations matrix；
Dish information acquiring unit is had dinner the vegetable of food and drink shops in geographical coverage area locating for position for obtaining target
Information；
Vegetable screening unit, for according to the dish information in the geographical coverage area at least one food and drink shops
Middle screening and the matched vegetable of target heat density.
Optionally, the vegetable recommendation apparatus based on workout data, comprising:
Vegetable reserves order generation unit, for generating vegetable reservation order based on the vegetable filtered out.
Optionally, the exercise intensity and the mapping relations matrix of heat density and user have unique corresponding relation, institute
State fortune of the mapping relations matrix of exercise intensity and heat density based on the physiological characteristic of user and user in historical time section
Fatigue resistance and the heat density for consuming vegetable determine；Wherein, the heat density of the vegetable, the heat that can be provided according to vegetable
Amount and the quality and/or volume of vegetable determine.
Optionally, the physiological characteristic dimension is provided with corresponding priority；Wherein, the physiological characteristic, including
It is at least one of following: height, weight, body fat rate, blood pressure, blood lipid, blood glucose, body temperature.
Optionally, the target heat density determination unit, comprising:
Heat density searches subelement, moves by force under each physiological characteristic dimension of user for searching the exercise intensity
It spends and corresponding heat density in the mapping relations matrix of heat density；
Heat density sorting subunit, for priority according to physiological characteristic dimension in descending order to finding
Heat density under each physiological characteristic dimension is ranked up；
Target heat density selects subelement, and the heat density under the physiological characteristic dimension for selecting highest priority is made
For the target heat density.
Optionally, the workout data is acquired by the infrared collecting device for being set to carpet in the gymnasium and is obtained,
Correspondingly, the exercise intensity determination unit, comprising:
Heat consumption computation subunit, when for according to the sport and body-building type and movement for including in the workout data
Between, the heat consumption of each period of the user in the gymnasium is calculated in conjunction with the physiological characteristic of user；
Foundation motion intensity determines subelement, determines user when each for the heat consumption according to user in each period
Between section foundation motion intensity；
Foundation motion intensity weighted subelement, for being weighted in time dimension according to the foundation motion intensity,
Using the foundation motion intensity time dimension exercise intensity of the weighted average as user in the gymnasium.
Optionally, the dish information acquiring unit, comprising:
Food and drink shops determines subelement, the food and drink door having dinner in geographical coverage area locating for position for determining the target
Shop；
Dish information extracts subelement, for believing from the vegetable for extracting vegetable in the food and drink shops in vegetable database
Breath；It include the caloric information of the vegetable in the dish information.
Optionally, the vegetable screening unit, comprising:
Heat density computation subunit, heat for can be provided according to the vegetable for including in the dish information and
The quality and/or volume of vegetable, calculate the heat density of vegetable；
Matching screening subelement, for the heat density and the target heat density from food and drink shops screening vegetable
The absolute value of the two difference be less than setting heat density threshold value vegetable, as with the matched vegetable of the mark heat density；And
And at least one food and drink shops in the geographical coverage area, the heat density computation subunit and described are run
With screening subelement.
Optionally, the vegetable reserves order generation unit, comprising:
Body-building total amount of heat computation subunit, for according to the amount of exercise and run duration for including in the workout data, meter
Calculate user's total amount of heat consumed by the sanitation park or square under the current dining period；
Vegetable total amount of heat computation subunit, for counting according to the caloric information for including in the dish information of vegetable is filtered out
The total amount of heat of vegetable is filtered out described in calculation；
Judgment sub-unit, for judging whether the total amount of heat for filtering out vegetable is more than or equal to the current dining period
Lower user's total amount of heat consumed by the sanitation park or square, if so, operation the first vegetable filtering subelement, clustering subelement and
Second vegetable filters subelement；Wherein, first vegetable filters subelement, for filtering out vegetable type in vegetable to described
The vegetable of coincidence is filtered；
The clustering subelement carries out clustering for consuming vegetable in historical time section to user, obtains
The dining preference of user；
Second vegetable filters subelement, mismatches for rejecting in vegetable after filtration with the dining preference of user
Vegetable.
Optionally, if the judging result of judgment sub-unit output is no, operation postsearch screening subelement；It is described secondary
Subelement is screened, at least one food and drink shops screening in the geographical coverage area and the target heat density numerical value
The matched vegetable of adjacent heat density, and the vegetable is added in the vegetable of screening and reserves order；Also, preferential screening and institute
It states that target heat density numerical value is adjacent and numerical value is greater than the matched vegetable of heat density of the target heat density.
The application also provides a kind of electronic equipment, comprising: memory and processor；The memory is for storing computer
Executable instruction, the processor are used to execute the computer executable instructions: body-building number of the acquisition user in gymnasium
According to；Determine user in the exercise intensity of the gymnasium according to the workout data；Based on user at least one physiology spy
The mapping relations matrix for levying exercise intensity and heat density under dimension, determines the exercise intensity in the mapping relations matrix
Corresponding target heat density；Target is obtained to have dinner the dish information of food and drink shops in geographical coverage area locating for position；According to
Screening matches the dish information with the target heat density at least one food and drink shops in the geographical coverage area
Vegetable.
The vegetable recommended method based on workout data provided by the present application, comprising: user is in gymnasium for acquisition
Workout data；Determine user in the exercise intensity of the gymnasium according to the workout data；Based on user at least one
The mapping relations matrix of exercise intensity and heat density under physiological characteristic dimension, determines the exercise intensity in the mapping relations
Corresponding target heat density in matrix；Target is obtained to have dinner the vegetable letter of food and drink shops in geographical coverage area locating for position
Breath；It is screened at least one food and drink shops in the geographical coverage area according to the dish information close with the target heat
Spend matched vegetable.
The vegetable recommended method based on workout data provided by the present application is carried out by acquisition user in gymnasium
The workout data that motion exercise generates is analyzed and processed workout data and obtains user in gymnasium progress sport and body-building forging
The exercise intensity of refining, and according to the mapping relations matrix of user's exercise intensity and heat density under physiological characteristic dimension, it determines
User carries out sport and body-building and tempers the heat density of vegetable required supplementation with, to have dinner geographic area model locating for position from target
Wei Nei food and drink shops filter out with the matched vegetable of the heat density, vegetable reserve order by way of to user recommend sieve
Vegetable is selected, to carry out the heat of exercise consumption supplemented with user much sooner and precisely, can not only promote to move
Exercise industry merging on line with catering industry, while also improving the consumption experience and user's viscosity of user.
Detailed description of the invention
Attached drawing 1 is a kind of process flow diagram of vegetable recommended method embodiment based on workout data provided by the present application；
Attached drawing 2 is a kind of schematic diagram of vegetable recommendation apparatus embodiment based on workout data provided by the present application；
Attached drawing 3 is the schematic diagram of a kind of electronic equipment provided by the present application.
Specific embodiment
Many details are explained in the following description in order to fully understand the application.But the application can be with
Much it is different from other modes described herein to implement, those skilled in the art can be without prejudice to the application intension the case where
Under do similar popularization, therefore the application is not limited by following public specific implementation.
The application provides a kind of vegetable recommended method based on workout data, and the application also provides a kind of based on workout data
Vegetable recommendation apparatus and a kind of electronic equipment.It is carried out one by one below in conjunction with the attached drawing of embodiment provided by the present application
It is described in detail, and each step of method is illustrated.
A kind of vegetable recommended method embodiment based on workout data provided by the present application is as follows:
Referring to attached drawing 1, it illustrates a kind of vegetable recommended method embodiments based on workout data provided by the present application
Process flow diagram.
Step S101, workout data of the acquisition user in gymnasium.
Under the fast-developing overall situation of new retail, service for life class, which is widely used, to be used by a user, and service for life is passed through
The recommendation of class, user would know that essential information, service evaluation, the shops's environmental evaluation etc. of the related all kinds of shops of life, and can make
It is paid with the service for life class application.Especially sport and body-building, KTV, bar, food and drink, hotel, Entertainment, beauty,
The characteristics of industries such as massage, this kind of industry is that consumption number of times are more frequent, therefore, for this kind of industry, how to pass through life
The online service function that service class application provides preferably services user, becomes the key for promoting user oriented service, for example, fortune
Dynamic body-building accepts extensively for user, and user can be more using the progress of various body-building equipments in residence or the gymnasium of profession
The body building of sample, and being widely used with Internet of Things, the identification between user and body-building equipment have become with information collection
To be necessary, but the workout data of user is not counted accurately and network analysis, can not effectively utilize workout data.
The vegetable recommended method based on workout data provided by the embodiments of the present application, it is real based on the application of service for life class
It is existing, in specific implementation process, the workout data generated by acquiring user in gymnasium sport and body-building, and it is based on service for life
Class application realize to collected workout data carry out analytical calculation, thus according to analysis result user gymnasium into
The exercise intensity that row sport and body-building is taken exercise carries out the heat that sport and body-building tempers consumption for user, needs to be supplemented in time,
And the exercise intensity for carrying out sport and body-building exercise according to user is needed to supplement the vegetable of suitable heat density, so that user be made to exist
Carrying out supplement vegetable after sport and body-building is taken exercise much sooner, effectively, can not only promote sport and body-building industry and catering industry
Fusion on line, while the consumption experience that user applies in service for life class can be also improved, it is answered to improve service for life class
User's viscosity.
In a kind of preferred embodiment provided by the embodiments of the present application, the carpet setting infrared collecting in gymnasium is filled
It sets, infrared collecting device is arranged by carpet to acquire the workout data of user, user is often moved to the (running of a certain body-building equipment
Machine, barbell, rowing machine, elects device etc. at Spinning) where region, can detect user in the run duration in the region,
And user in the region is carried in static resting state or exercise state, and by infrared collecting device and user
Smart machine (such as smart phone, Intelligent bracelet, smartwatch mobile terminal) get through, infrared collecting device is collected
Workout data is sent to smart machine one end of user's carrying；The smart machine of user's carrying and user are in service for life class application
Account binding, so that the upload of applying workout data to service for life class is realized, by service for life class using according to upload
Workout data carry out further data processing.
Step S102 determines user in the exercise intensity of the gymnasium according to the workout data.
The user got according to above-mentioned steps S101 carries out the workout data of exercise generation in gymnasium, determines
User carries out the exercise intensity of exercise in gymnasium, in a kind of preferred embodiment provided by the embodiments of the present application, root
According to the sport and body-building type and run duration for including in above-mentioned collected workout data, in conjunction with the physiological characteristic meter of user itself
It calculates user and carries out heat consumed by exercise (in general, and body-building equipment in each body-building equipment region of gymnasium
The heat of the exercise movement consumption of adaptation is often related to physiological characteristics such as the weight of user itself, weight, therefore can
According to the relevant physiologicals feature such as the weight of itself, weight, for example do the heat of a push-up movement consumption are as follows: w=g*m (body
Weight) * h (personal forearm)), calculating user, (that is: user carries out exercise institute in each body-building equipment in each period
The corresponding period) heat consumption determine user in the foundation motion intensity of each period, and in time dimension to described
Foundation motion intensity is weighted, for example is weighted according to the duration of each period to corresponding foundation motion intensity, finally
Using foundation motion intensity time dimension exercise intensity of the weighted average as user in gymnasium.
Step S103, the mapping relations based on user's exercise intensity and heat density under at least one physiological characteristic dimension
Matrix determines the exercise intensity corresponding target heat density in the mapping relations matrix.
Preferably, the physiological characteristic, including at least one of following: height, weight, body fat rate, blood pressure, blood lipid, blood glucose,
Body temperature.Correspondingly, the physiological characteristic dimension is the dimension referred to where each physiological characteristic, for example, height dimension, weight dimension
Deng；Further, the physiological characteristic dimension is additionally provided with corresponding priority, the purpose that priority is set be can be
User provides more accurate and personalized analysis.For example, the body fat rate of certain user is higher, which carries out the mesh of exercise
Be then during being analyzed user for body-building data to carry out vegetable recommendation, to be paid the utmost attention to reduce body fat rate
This factor of body fat rate enables the user to preferably reach the fitness goals for reducing body fat rate.
The application be around recommend suitable vegetable for the user after gymnasium carries out exercise so that its
This core idea of the heat of exercise consumption is supplemented, the mapping of exercise intensity and heat density described in the embodiment of the present application is closed
It is matrix, refers to that describing the user for a user carries out the different motion intensity of exercise, and each fortune in gymnasium
The heat density for the vegetable that fatigue resistance requires supplementation with.Why the mapping relations matrix of exercise intensity and heat density is set, is
In order to improve the efficiency of user's additional heat after exercise, for example, the high-intensitive forging that user carries out in gymnasium
Refining, after the exercise, if the lower food of additional heat density, may require supplementation with a large amount of group foods could meet body
It needs, or even will appear user and add to and can not receive the degree of feed and meet body not yet to the needs of heat, be based on this,
For different exercise intensities, the vegetable that different heat densities are arranged is supplemented for user.
For example, the high intensity exertions that user X is carried out in gymnasium, then can supplement beef, the flesh of fish to recommended user X
The vegetable of this kind of high heat；But if the low intensive exercise (Yoga is jogged) that user X is carried out in gymnasium, then
This kind of vegetables low in calories of water fruits and vegetables can be supplemented to recommended user X.
Since the purpose that user carries out exercise is not quite similar, a part of user is to lose weight, and there are also parts
User is to increase flesh lipid-loweringing, and there may also be the users for other fitness goals, therefore, can be for different user setting not
Same strategy.Preferably, the exercise intensity and the mapping relations matrix of heat density and user have unique corresponding relation,
That is: the exercise intensity of the user and the mapping relations matrix of heat density, the exercise intensity are respectively set for each user
With the mapping relations matrix of heat density based on exercise intensity in historical time section of the physiological characteristic of user and user and
The heat density for consuming vegetable determines；Wherein, the heat density of the vegetable, the heat and vegetable that can be provided according to vegetable
Quality and/or volume determine (in practical application, heat, quality and/or the volume of vegetable can be by providing the food and drink door of the vegetable
Shop is provided).
For example, the exercise intensity of user X and the mapping relations matrix of heat density are as shown in the table under weight dimension:
In upper table, the heat density of vegetable is in turn divided into first to fourth totally 4 heat density sections from low to high, uses
The exercise intensity of family X is in turn divided into level-one to level Four totally 4 exercise intensity sections from low to high.The current weight of user X
For 60kg, the target of body-building is weight-reducing, due to the weight of user X be it is continually changing, when user's X weight is more than 60kg,
Gymnasium carries out the exercise of more violent three-level exercise intensity, the vegetable that can be supplemented after body-building be heat density compared with
The vegetable of small (heat density is in the first heat density section (c1/J~c2/J))；Similar, when user's X weight is 55kg
When, the exercise of second degree of motion intensity is carried out in gymnasium, the vegetable that can be supplemented after body-building is the smaller (heat of heat density
Metric density is in the first heat density section (c1/J~c2/J)) vegetable.
After above-mentioned steps S102 determines the exercise intensity that user for body-building place carries out exercise, here, according to described
Exercise intensity corresponding target heat density in mapping relations matrix, a kind of preferred embodiment provided by the embodiments of the present application
In, for the mapping relations matrix of user's exercise intensity and heat density under each physiological characteristic dimension, the fortune is searched respectively
Corresponding heat is close in exercise intensity and the mapping relations matrix of heat density under each physiological characteristic dimension of user for fatigue resistance
Degree, then according to the priority of each physiological characteristic dimension of user, according to physiological characteristic dimension priority in descending order
Heat density under each physiological characteristic dimension found is ranked up, the physiological characteristic dimension of highest priority is finally selected
Under heat density as the target heat density.
Step S104 obtains target and has dinner the dish information of food and drink shops in geographical coverage area locating for position.
Target described in the embodiment of the present application is had dinner geographical coverage area locating for position, and preferably feeling the pulse with the finger-tip mark is had dinner locating for position
Commercial circle range of nodes, specifically, the commercial circle node refers to each region for obtaining after consumption dimension carries out region division
Representative node, specifically, the division of commercial circle node is divided in combination with both geographic area and consumption temperature, such as root
According to the electronic map data that map quotient provides, geographic area is divided by function as different zones first, such as residential quarter,
School, park, market, road etc., according to the region with commercial consumption attribute obtained after above-mentioned division, such as market, road
Shops, shops of residential quarter side of trackside etc. carry out further market area partition to the region obtained after above-mentioned division, such as
Market in city is divided into a commercial circle node, the city street Nei Moutiao is divided into a commercial circle node, or by city
The a piece of region division in area is that (Pekinese international trade region or three regions Li Tun are respectively divided into a commercial circle to a commercial circle node
Node).
In the specific implementation, the target of user position of having dinner can actively be set in service for life class application by user
It sets, the position that is presently according to user, user can also be applied to carry out exercise in the past by service for life class and had dinner position,
And the movement track that user is daily, show that the user relatively high position of possibility of having dinner is had dinner as target by analyzing prediction
Position.
Preferably, it obtains target to have dinner the dish information of food and drink shops in commercial circle range of nodes locating for position, comprising: determine
The target is had dinner the food and drink shops in commercial circle range of nodes locating for position；From being extracted in vegetable database in the food and drink shops
The dish information of vegetable；It include the caloric information of the vegetable in the dish information.
Step S105, according to the dish information in the geographical coverage area at least one food and drink shops screening with
The matched vegetable of target heat density.
In a kind of preferred embodiment provided by the embodiments of the present application, according to the dish information in the commercial circle node model
Screening and the matched vegetable of target heat density at least one interior food and drink shops are enclosed, is specifically realized in the following way:
For at least one food and drink shops in the commercial circle range of nodes, perform the following operations:
The quality and/or volume of the heat and vegetable that can be provided according to the vegetable for including in the dish information, meter
Calculate the heat density of vegetable；From both the heat density of food and drink shops screening vegetable and the target heat density difference
Absolute value be less than setting heat density threshold value vegetable, as with the matched vegetable of the mark heat density.
Above-mentioned steps S105 is filtered out and the target heat density in the food and drink shops in the commercial circle range of nodes
Matched vegetable, that is, after filtering out the vegetable to be recommended to user, it is preferred that be also based on the vegetable filtered out and generate dish
Product reserve order, can also carry out a key to the vegetable reservation order of generation depending on the user's operation and place an order.
It is above-mentioned that vegetable reservation is generated based on the vegetable filtered out in a kind of preferred embodiment provided by the embodiments of the present application
Order, comprising: according to the amount of exercise and run duration for including in the workout data, calculate current (the dining period in dining period
Refer to the time that user currently eats after the time and exercise once eaten before gymnasium carries out exercise
Time interval between the two) under user's total amount of heat consumed by sanitation park or square；It is wrapped according in the dish information for filtering out vegetable
The caloric information contained filters out the total amount of heat of vegetable described in calculating；The total amount of heat that vegetable is filtered out described in judgement whether be greater than or
Person is equal to user's total amount of heat consumed by sanitation park or square under the current dining period；
1) if so, being filtered to the vegetable that vegetable type is overlapped in vegetable is filtered out, and to user in historical time
Consumption vegetable carries out clustering in section, obtains the dining preference of user, finally rejects in vegetable after filtration with user's
The dining unmatched vegetable of preference；
2) if it is not, it is preferred that at least one food and drink shops screens and the target heat density in the commercial circle range of nodes
The matched vegetable of the adjacent heat density of numerical value, and the vegetable is added in the vegetable of screening and reserves order；Also, preferential screening
Adjacent and numerical value is greater than the matched vegetable of heat density of the target heat density with the target heat density numerical value, if
The matched vegetable of heat density that adjacent and numerical value is greater than the target heat density with the target heat density numerical value is added
After vegetable reserves order, the total amount of heat of vegetable is still less than user's total amount of heat consumed by sanitation park or square in vegetable reservation order,
Then further screen the heat density that and numerical value adjacent with the target heat density numerical value is less than the target heat density
The vegetable matched is added vegetable and reserves order.
In conclusion the vegetable recommended method based on workout data provided by the present application, by acquisition user strong
Body place carries out the workout data of motion exercise generation, is analyzed and processed to workout data and obtains user in gymnasium progress
The exercise intensity that sport and body-building is taken exercise, and according to the mapping relations of user's exercise intensity and heat density under physiological characteristic dimension
Matrix determines that user carries out the heat density that sport and body-building tempers the vegetable required supplementation with, to have dinner locating for position from target
In the range of nodes of commercial circle food and drink shops filter out with the matched vegetable of the heat density, vegetable reserve order by way of to
User recommends to filter out vegetable, so that the heat of exercise consumption is carried out supplemented with user much sooner and precisely, it can not only
Enough promote sport and body-building industry with catering industry merging on line, while also improving the consumption experience of user and user glues
Degree.
A kind of vegetable recommendation apparatus embodiment based on workout data provided by the present application is as follows:
In the above-described embodiment, a kind of vegetable recommended method based on workout data is provided, it is corresponding, this
Application additionally provides a kind of vegetable recommendation apparatus based on workout data, is illustrated with reference to the accompanying drawing.Reference attached drawing 2,
Show a kind of schematic diagram of vegetable recommendation apparatus embodiment based on workout data provided by the present application.Due to Installation practice
It is substantially similar to embodiment of the method, so describing fairly simple, relevant part refers to the embodiment of the method for above-mentioned offer
Corresponding explanation.Installation practice described below is only schematical.
The application provides a kind of vegetable recommendation apparatus based on workout data, comprising:
Workout data acquisition unit 201, for acquiring user in the workout data of gymnasium；
Exercise intensity determination unit 202, for determining user in the movement of the gymnasium according to the workout data
Intensity；
Target heat density determination unit 203, for being based on user's exercise intensity under at least one physiological characteristic dimension
With the mapping relations matrix of heat density, determine that the exercise intensity corresponding target heat in the mapping relations matrix is close
Degree；
Dish information acquiring unit 204 is had dinner food and drink shops in geographical coverage area locating for position for obtaining target
Dish information；
Vegetable screening unit 205 is used at least one food and drink in the geographical coverage area according to the dish information
Screening and the matched vegetable of target heat density in shops.
Optionally, the vegetable recommendation apparatus based on workout data, comprising:
Vegetable reserves order generation unit, for generating vegetable reservation order based on the vegetable filtered out.
Optionally, the exercise intensity and the mapping relations matrix of heat density and user have unique corresponding relation, institute
State fortune of the mapping relations matrix of exercise intensity and heat density based on the physiological characteristic of user and user in historical time section
Fatigue resistance and the heat density for consuming vegetable determine；Wherein, the heat density of the vegetable, the heat that can be provided according to vegetable
Amount and the quality and/or volume of vegetable determine.
Optionally, the physiological characteristic dimension is provided with corresponding priority；Wherein, the physiological characteristic, including
It is at least one of following: height, weight, body fat rate, blood pressure, blood lipid, blood glucose, body temperature.
Optionally, the target heat density determination unit 203, comprising:
Heat density searches subelement, moves by force under each physiological characteristic dimension of user for searching the exercise intensity
It spends and corresponding heat density in the mapping relations matrix of heat density；
Heat density sorting subunit, for priority according to physiological characteristic dimension in descending order to finding
Heat density under each physiological characteristic dimension is ranked up；
Target heat density selects subelement, and the heat density under the physiological characteristic dimension for selecting highest priority is made
For the target heat density.
Optionally, the workout data is acquired by the infrared collecting device for being set to carpet in the gymnasium and is obtained,
Correspondingly, the exercise intensity determination unit 202, comprising:
Heat consumption computation subunit, when for according to the sport and body-building type and movement for including in the workout data
Between, the heat consumption of each period of the user in the gymnasium is calculated in conjunction with the physiological characteristic of user；
Foundation motion intensity determines subelement, determines user when each for the heat consumption according to user in each period
Between section foundation motion intensity；
Foundation motion intensity weighted subelement, for being weighted in time dimension according to the foundation motion intensity,
Using the foundation motion intensity time dimension exercise intensity of the weighted average as user in the gymnasium.
Optionally, the dish information acquiring unit 204, comprising:
Food and drink shops determines subelement, the food and drink door having dinner in geographical coverage area locating for position for determining the target
Shop；
Dish information extracts subelement, for believing from the vegetable for extracting vegetable in the food and drink shops in vegetable database
Breath；It include the caloric information of the vegetable in the dish information.
Optionally, the vegetable screening unit 205, comprising:
Heat density computation subunit, heat for can be provided according to the vegetable for including in the dish information and
The quality and/or volume of vegetable, calculate the heat density of vegetable；
Matching screening subelement, for the heat density and the target heat density from food and drink shops screening vegetable
The absolute value of the two difference be less than setting heat density threshold value vegetable, as with the matched vegetable of the mark heat density；And
And at least one food and drink shops in the geographical coverage area, the heat density computation subunit and described are run
With screening subelement.
Optionally, the vegetable reserves order generation unit, comprising:
Body-building total amount of heat computation subunit, for according to the amount of exercise and run duration for including in the workout data, meter
Calculate user's total amount of heat consumed by the sanitation park or square under the current dining period；
Vegetable total amount of heat computation subunit, for counting according to the caloric information for including in the dish information of vegetable is filtered out
The total amount of heat of vegetable is filtered out described in calculation；
Judgment sub-unit, for judging whether the total amount of heat for filtering out vegetable is more than or equal to the current dining period
Lower user's total amount of heat consumed by the sanitation park or square, if so, operation the first vegetable filtering subelement, clustering subelement and
Second vegetable filters subelement；Wherein, first vegetable filters subelement, for filtering out vegetable type in vegetable to described
The vegetable of coincidence is filtered；
The clustering subelement carries out clustering for consuming vegetable in historical time section to user, obtains
The dining preference of user；
Second vegetable filters subelement, mismatches for rejecting in vegetable after filtration with the dining preference of user
Vegetable.
Optionally, if the judging result of judgment sub-unit output is no, operation postsearch screening subelement；It is described secondary
Subelement is screened, at least one food and drink shops screening in the geographical coverage area and the target heat density numerical value
The matched vegetable of adjacent heat density, and the vegetable is added in the vegetable of screening and reserves order；Also, preferential screening and institute
It states that target heat density numerical value is adjacent and numerical value is greater than the matched vegetable of heat density of the target heat density.
Optionally, target geographical coverage area locating for position of having dinner includes: that the target is had dinner quotient locating for position
Enclose range of nodes.
A kind of electronic equipment embodiment provided by the present application is as follows:
In the above-described embodiment, a kind of vegetable recommended method based on workout data is provided, in addition, the application also mentions
The electronic equipment for having supplied a kind of vegetable recommended method for realizing described based on workout data, is said with reference to the accompanying drawing
It is bright.Referring to attached drawing 3, it illustrates the schematic diagrames of a kind of electronic equipment provided in this embodiment.The electronics provided by the present application
Apparatus embodiments describe fairly simple, and the vegetable based on workout data that relevant part refers to above-mentioned offer is recommended
The corresponding explanation of embodiment of the method.Embodiment described below is only schematical.
The application provides a kind of electronic equipment, comprising: memory 301 and processor 302；The memory 301 is for depositing
Store up computer executable instructions, the processor 302 is for executing following computer executable instructions: user is in sanitation park or square for acquisition
Workout data；Determine user in the exercise intensity of the gymnasium according to the workout data；Based on user at least
The mapping relations matrix of exercise intensity and heat density under one physiological characteristic dimension, determines the exercise intensity in the mapping
Corresponding target heat density in relational matrix；Target is obtained to have dinner the vegetable of food and drink shops in geographical coverage area locating for position
Information；It is screened and the target heat at least one food and drink shops in the geographical coverage area according to the dish information
The vegetable of density matching.
Optionally, the processor 302 is also used to execute following computer executable instructions: raw based on the vegetable filtered out
Order is reserved at vegetable.
Optionally, the exercise intensity and the mapping relations matrix of heat density and user have unique corresponding relation, institute
State fortune of the mapping relations matrix of exercise intensity and heat density based on the physiological characteristic of user and user in historical time section
Fatigue resistance and the heat density for consuming vegetable determine；Wherein, the heat density of the vegetable, the heat that can be provided according to vegetable
Amount and the quality and/or volume of vegetable determine.
Optionally, the physiological characteristic dimension is provided with corresponding priority；Wherein, the physiological characteristic, including
It is at least one of following: height, weight, body fat rate, blood pressure, blood lipid, blood glucose, body temperature.
Optionally, the mapping based on user exercise intensity and heat density under at least one physiological characteristic dimension is closed
It is matrix, determines the exercise intensity corresponding target heat density in the mapping relations matrix, comprising: search the fortune
Corresponding heat is close in exercise intensity and the mapping relations matrix of heat density under each physiological characteristic dimension of user for fatigue resistance
Degree；According to physiological characteristic dimension priority in descending order to the heat density under each physiological characteristic dimension found into
Row sequence；Select the heat density under the physiological characteristic dimension of highest priority as the target heat density.
Optionally, the workout data is acquired by the infrared collecting device for being set to carpet in the gymnasium and is obtained,
Correspondingly, described determine user in the exercise intensity of the gymnasium according to the workout data, comprising: according to the body-building
The sport and body-building type and run duration for including in data calculate user in the gymnasium in conjunction with the physiological characteristic of user
Each period heat consumption；Heat consumption according to user in each period determines user in the foundation motion of each period
Intensity；It is weighted in time dimension according to the foundation motion intensity, by the foundation motion intensity in time dimension
Exercise intensity of the weighted average as user in the gymnasium.
Optionally, the target that obtains is had dinner the dish information of food and drink shops in geographical coverage area locating for position, comprising:
Determine the food and drink shops that the target is had dinner in geographical coverage area locating for position；The food and drink door is extracted from vegetable database
The dish information of vegetable in shop；It include the caloric information of the vegetable in the dish information.
Optionally, described to be screened at least one food and drink shops in the geographical coverage area according to the dish information
With the matched vegetable of target heat density, comprising: at least one food and drink shops in the geographical coverage area, execute
Following operation:
The quality and/or volume of the heat and vegetable that can be provided according to the vegetable for including in the dish information, meter
Calculate the heat density of vegetable；From both the heat density of food and drink shops screening vegetable and the target heat density difference
Absolute value be less than setting heat density threshold value vegetable, as with the matched vegetable of the mark heat density.
It is optionally, described that vegetable reservation order is generated based on the vegetable filtered out, comprising:
According to the amount of exercise and run duration for including in the workout data, user is described under the calculating current dining period
Total amount of heat consumed by sanitation park or square；According to the caloric information for including in the dish information for filtering out vegetable, filtered out described in calculating
The total amount of heat of vegetable；Whether the total amount of heat that vegetable is filtered out described in judgement is more than or equal under the current dining period user in institute
Total amount of heat consumed by sanitation park or square is stated, if so, being filtered to the vegetable for filtering out vegetable type coincidence in vegetable；To with
Family consumes vegetable in historical time section and carries out clustering, obtains the dining preference of user；It is rejected in vegetable after filtration
With the unmatched vegetable of dining preference of user.
Optionally, if whether the total amount of heat for filtering out vegetable described in the judgement was more than or equal under the current dining period
User's total amount of heat consumed by the sanitation park or square instruction implementing result be it is no, perform the following operations: in the geographic area
The heat density matched vegetable adjacent with the target heat density numerical value screens at least one food and drink shops in range, and will
The vegetable of screening is added the vegetable and reserves order；Also, preferentially screen and numerical value adjacent with the target heat density numerical value
Greater than the matched vegetable of heat density of the target heat density.
Optionally, target geographical coverage area locating for position of having dinner includes: that the target is had dinner quotient locating for position
Enclose range of nodes.
Although the application is disclosed as above with preferred embodiment, it is not for limiting the application, any this field skill
Art personnel are not departing from spirit and scope, can make possible variation and modification, therefore the guarantor of the application
Shield range should be subject to the range that the claim of this application defined.
In a typical configuration, calculating equipment includes that one or more processors, input/output interface, network connect
Mouth and memory.
Memory may include the non-volatile memory in computer-readable medium, random access memory (RAM) and/or
The forms such as Nonvolatile memory, such as read-only memory (ROM) or flash memory (flash RAM).Memory is computer-readable medium
Example.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include non-temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It will be understood by those skilled in the art that embodiments herein can provide as method, system or computer program product.
Therefore, complete hardware embodiment, complete software embodiment or embodiment combining software and hardware aspects can be used in the application
Form.It is deposited moreover, the application can be used to can be used in the computer that one or more wherein includes computer usable program code
The shape for the computer program product implemented on storage media (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.)
Formula.
Claims (10)
1. a kind of vegetable recommended method based on workout data characterized by comprising
User is acquired in the workout data of gymnasium；
Determine user in the exercise intensity of the gymnasium according to the workout data；
Based on the mapping relations matrix of user's exercise intensity and heat density under at least one physiological characteristic dimension, determine described in
Exercise intensity corresponding target heat density in the mapping relations matrix；
Target is obtained to have dinner the dish information of food and drink shops in geographical coverage area locating for position；
It is screened and the target heat at least one food and drink shops in the geographical coverage area according to the dish information
The vegetable of density matching.
2. the vegetable recommended method according to claim 1 based on workout data characterized by comprising
Vegetable reservation order is generated based on the vegetable filtered out.
3. the vegetable recommended method according to claim 2 based on workout data, which is characterized in that the exercise intensity with
The mapping relations matrix of heat density and user have unique corresponding relation, the mapping relations of the exercise intensity and heat density
The heat density of the exercise intensity and consumption vegetable of physiological characteristic and user of the matrix based on user in historical time section is true
It is fixed；
Wherein, the heat density of the vegetable, the quality and/or volume of the heat and vegetable that can be provided according to vegetable are true
It is fixed.
4. the vegetable recommended method according to claim 3 based on workout data, which is characterized in that the physiological characteristic dimension
Degree is provided with corresponding priority；
Wherein, the physiological characteristic, including at least one of following: height, weight, body fat rate, blood pressure, blood lipid, blood glucose, body temperature.
5. the vegetable recommended method according to claim 4 based on workout data, which is characterized in that described to be existed based on user
The mapping relations matrix of exercise intensity and heat density under at least one physiological characteristic dimension, determines the exercise intensity described
Corresponding target heat density in mapping relations matrix, comprising:
Search the mapping relations matrix of exercise intensity exercise intensity and heat density under each physiological characteristic dimension of user
In corresponding heat density；
According to the priority of physiological characteristic dimension in descending order to the heat density under each physiological characteristic dimension found
It is ranked up；
Select the heat density under the physiological characteristic dimension of highest priority as the target heat density.
6. according to claim 1 to the vegetable recommended method described in 5 any one based on workout data, which is characterized in that institute
It states workout data and acquisition is acquired by the infrared collecting device for being set to carpet in the gymnasium, correspondingly, described according to institute
Stating workout data determines user in the exercise intensity of the gymnasium, comprising:
According to the sport and body-building type and run duration for including in the workout data, user is calculated in conjunction with the physiological characteristic of user
The heat consumption of each period in the gymnasium；
Heat consumption according to user in each period determines user in the foundation motion intensity of each period；
It is weighted in time dimension according to the foundation motion intensity, by the foundation motion intensity adding in time dimension
Exercise intensity of the weight average value as user in the gymnasium.
7. according to claim 1 to the vegetable recommended method described in 5 any one based on workout data, which is characterized in that institute
It states and obtains target and have dinner the dish information of food and drink shops in geographical coverage area locating for position, comprising:
Determine the food and drink shops that the target is had dinner in geographical coverage area locating for position；
From the dish information for extracting vegetable in the food and drink shops in vegetable database；It include the vegetable in the dish information
Caloric information.
8. the vegetable recommended method according to claim 7 based on workout data, which is characterized in that described according to the dish
Product information is screened at least one food and drink shops in the geographical coverage area and the matched vegetable of target heat density,
Include:
For at least one food and drink shops in the geographical coverage area, perform the following operations:
The quality and/or volume of the heat and vegetable that can be provided according to the vegetable for including in the dish information calculate dish
The heat density of product；
From the absolute value of the heat density of food and drink shops screening vegetable and both target heat densities difference less than setting
The vegetable for determining heat density threshold value, as with the matched vegetable of the mark heat density.
9. a kind of vegetable recommendation apparatus based on workout data characterized by comprising
Workout data acquisition unit, for acquiring user in the workout data of gymnasium；
Exercise intensity determination unit, for determining user in the exercise intensity of the gymnasium according to the workout data；
Target heat density determination unit, for close based on user exercise intensity and heat under at least one physiological characteristic dimension
The mapping relations matrix of degree determines the exercise intensity corresponding target heat density in the mapping relations matrix；
Dish information acquiring unit is had dinner the vegetable letter of food and drink shops in geographical coverage area locating for position for obtaining target
Breath；
Vegetable screening unit, for being sieved at least one food and drink shops in the geographical coverage area according to the dish information
Choosing and the matched vegetable of target heat density.
10. a kind of electronic equipment characterized by comprising
Memory and processor；
The memory is for storing computer executable instructions, and for executing, the computer is executable to be referred to the processor
It enables:
User is acquired in the workout data of gymnasium；
Determine user in the exercise intensity of the gymnasium according to the workout data；
Based on the mapping relations matrix of user's exercise intensity and heat density under at least one physiological characteristic dimension, determine described in
Exercise intensity corresponding target heat density in the mapping relations matrix；
Target is obtained to have dinner the dish information of food and drink shops in geographical coverage area locating for position；
It is screened and the target heat at least one food and drink shops in the geographical coverage area according to the dish information
The vegetable of density matching.
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