CN109299070A - A kind of vegetable boiling method and system based on big data - Google Patents
A kind of vegetable boiling method and system based on big data Download PDFInfo
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- CN109299070A CN109299070A CN201811050937.4A CN201811050937A CN109299070A CN 109299070 A CN109299070 A CN 109299070A CN 201811050937 A CN201811050937 A CN 201811050937A CN 109299070 A CN109299070 A CN 109299070A
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- 238000009835 boiling Methods 0.000 title claims abstract description 243
- 235000013311 vegetables Nutrition 0.000 title claims abstract description 199
- 238000000034 method Methods 0.000 title claims abstract description 27
- 235000013305 food Nutrition 0.000 claims abstract description 39
- 239000000463 material Substances 0.000 claims abstract description 39
- 238000010411 cooking Methods 0.000 claims abstract description 15
- 230000007613 environmental effect Effects 0.000 claims abstract description 13
- 238000013500 data storage Methods 0.000 claims description 2
- 238000013480 data collection Methods 0.000 abstract description 3
- 230000000694 effects Effects 0.000 abstract description 3
- 230000029087 digestion Effects 0.000 description 4
- 238000010025 steaming Methods 0.000 description 4
- 230000009286 beneficial effect Effects 0.000 description 2
- 230000007812 deficiency Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
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Abstract
The invention discloses a kind of vegetable boiling method and system based on big data, carry out multiple vegetable boiling respectively to multiple tracks vegetable, every dish product generate a boiling data after completing boiling, by numerous boiling data collections into database as basic data, in vegetable boiling to be carried out, obtain the menu name and assessment factor of vegetable to be produced, it is identical with the menu name of vegetable to be produced that menu name is found out in the database, assess the approximate several boiling data of assessment factor of factor and vegetable to be produced, vegetable is selected in several boiling data found out score a highest boiling data and obtain the boiling durations of this boiling data, a length of vegetable scoring highest boiling duration for making the vegetable when boiling, a length of best boiling duration when the boiling, the acquisition of best boiling duration considers food materials spy Sign data and environmental data, best boiling duration can make vegetable cooking effect more preferable.
Description
Technical field
The present invention relates to big data technical fields, more particularly, to a kind of vegetable boiling method based on big data and are
System.
Background technique
Vegetable boiling is a kind of common cooking method, usually by the time of manual control vegetable boiling, manual control dish
Product boiling the degree of automation is not high, and special messenger guard is needed to prevent steaming or the time that has not been cooked or heated long enough.Existing automation boiling solves manually
The problem of boiling labor intensive, does not need special messenger and manages boiling, multiple groups menu is arranged, when corresponding boiling is arranged in each vegetable
Between, after user inputs menu name and vegetable food materials are put into steam box, the steaming of default digestion time can be carried out to vegetable automatically
It boils.
But the corresponding digestion time of the existing each vegetable of automatic boiling method is fixed, and ring at that time is not accounted for
The characteristic of border factor (such as ambient humidity, environment temperature, ambient pressure) or food materials, and environmental factor, the feature of food materials
Data be on vegetable digestion time it is influential, can to carry out boiling according to the digestion time that go out vegetable bad.
Summary of the invention
It is an object of the invention to overcome above-mentioned technical deficiency, proposes a kind of vegetable boiling method based on big data and be
System, solves above-mentioned technical problem in the prior art.
To reach above-mentioned technical purpose, technical solution of the present invention provides a kind of vegetable boiling method based on big data,
Include:
S1, multiple vegetable boiling is carried out respectively to multiple tracks vegetable, every dish product generate a boiling number after completing boiling
According to, by the boiling data of generation storage to database, a boiling data include the menu name of the secondary vegetable boiling, assessment because
Number, vegetable scoring, boiling duration, assessment factor include the food materials characteristic and/or environmental data of the secondary vegetable boiling；
S2, the menu name for obtaining vegetable to be produced and assessment factor, find out menu name and wait make in the database
The menu name for making vegetable is identical, the assessment factor and vegetable to be produced approximate several boiling data of assessment factor, is looking into
Vegetable is selected in several boiling data found out score a highest boiling data and obtain the boilings of this boiling data
Duration；
S3, to vegetable to be produced carry out S2 acquisition boiling duration boiling.
The present invention also provides a kind of vegetable decoction system based on big data, comprising:
Data acquisition module: carrying out multiple vegetable boiling to multiple tracks vegetable respectively, and every dish product generate after completing boiling
One boiling data stores the boiling data of generation to database, and a boiling data include the vegetable of the secondary vegetable boiling
Title, assessment factor, vegetable scoring, boiling duration, assessment factor include the food materials characteristic and/or ring of the secondary vegetable boiling
Border data；
Optimal boiling duration obtains module: obtaining the menu name and assessment factor of vegetable to be produced, looks into the database
If the assessment factor for finding out menu name identical with the menu name of vegetable to be produced, assessment factor and vegetable to be produced is approximate
Dry boiling data are selected the highest boiling data of vegetable scoring and are obtained in several boiling data found out and are somebody's turn to do
The boiling duration of boiling data；
Boiling execution module: the steaming that optimal boiling duration obtains the boiling duration that module obtains is carried out to vegetable to be produced
It boils.
Compared with prior art, the beneficial effect comprise that carrying out multiple vegetable boiling respectively to multiple tracks vegetable, often
One vegetable generates a boiling data after completing boiling, by numerous boiling data collections into database based on number
According to, in vegetable boiling to be carried out, obtain vegetable to be produced menu name and assessment factor, find out vegetable in the database
Title is identical with the menu name of vegetable to be produced, assesses factor and the approximate several boilings of the assessment factor of vegetable to be produced
Data select the highest boiling data of vegetable scoring in several boiling data found out and obtain this boiling number
According to boiling duration, when boiling, a length of vegetable for making the vegetable scored highest boiling duration, and when boiling is a length of best
Boiling duration, the acquisition of best boiling duration consider food materials characteristic (scoring of food materials tough degree for cooking, food materials temperature) and ring
Border data (ambient humidity, environment temperature, ambient pressure), best boiling duration can make vegetable cooking effect more preferable.
Detailed description of the invention
Fig. 1 is a kind of vegetable boiling method flow chart based on big data provided by the invention；
Fig. 2 is a kind of vegetable decoction system structural block diagram based on big data provided by the invention.
In attached drawing: 1, the vegetable decoction system based on big data, 11, data acquisition module, 12, the acquisition of optimal boiling duration
Module, 13, boiling execution module.
Specific embodiment
In order to make the objectives, technical solutions, and advantages of the present invention clearer, with reference to the accompanying drawings and embodiments, right
The present invention is further elaborated.It should be appreciated that the specific embodiments described herein are merely illustrative of the present invention, and
It is not used in the restriction present invention.
The present invention provides a kind of vegetable boiling method based on big data, comprising:
S1, multiple vegetable boiling is carried out respectively to multiple tracks vegetable, every dish product generate a boiling number after completing boiling
According to, by the boiling data of generation storage to database, a boiling data include the menu name of the secondary vegetable boiling, assessment because
Number, vegetable scoring, boiling duration, assessment factor include the food materials characteristic and/or environmental data of the secondary vegetable boiling；
S2, the menu name for obtaining vegetable to be produced and assessment factor, find out menu name and wait make in the database
The menu name for making vegetable is identical, the assessment factor and vegetable to be produced approximate several boiling data of assessment factor, is looking into
Vegetable is selected in several boiling data found out score a highest boiling data and obtain the boilings of this boiling data
Duration；
S3, to vegetable to be produced carry out S2 acquisition boiling duration boiling.
Vegetable boiling method of the present invention based on big data carries out multiple dish to multiple tracks vegetable in step S1 respectively
Product boiling, every dish product generate a boiling data after completing boiling, by the boiling data storage of generation to database；When into
After the multiple vegetable boiling of row, a large amount of boiling data of generation will be stored into database, be subsequent wait make as basic data
The boiling operation for making vegetable provides big data and supports.When a vegetable carries out the boiling of boiling duration under assessment factor at that time
Afterwards, it is manually scored the vegetable boiling result, the result of scoring is vegetable scoring, and vegetable scoring can measure the vegetable and work as
When assessment factor under boiling duration it is whether suitable, when vegetable score it is higher, illustrate that the boiling duration is more suitable；
Wherein, assessment factor includes the food materials characteristic and/or environmental data of the secondary vegetable boiling, food materials characteristic
Including the scoring of food materials tough degree for cooking, food materials temperature, environmental data includes ambient humidity, environment temperature, the ring for carrying out vegetable boiling
Border air pressure；Assess the scoring of food materials tough degree for cooking, food materials temperature, the ambient humidity, environment temperature, ambient pressure that factor includes
It can influence the boiling result of vegetable.
Vegetable boiling method of the present invention based on big data obtains the assessment factor of vegetable to be produced in step S2
Method specifically:
The assessment factor of vegetable to be produced, which can according to need, freely to be configured, specifically, depending on the user's operation or
Default setting selects the food materials tough degree for cooking of vegetable to be produced to score, food materials temperature, ambient humidity, environment temperature, ambient pressure
In it is one or more as assessment factors.
Vegetable boiling method of the present invention based on big data finds out menu name in step S2 in the database
The approximate several boiling data of the assessment factor of, assessment factor identical with the menu name of vegetable to be produced and vegetable to be produced
Method specifically:
Find out identical first data acquisition system of menu name of menu name and vegetable to be produced in the database, first
Data acquisition system include several boiling data, found out in the first data acquisition system assessment factor and vegetable to be produced assessment because
The approximate the second data set of number, the second data set include several boiling data, each boiling data in the second data set
Menu name is identical with the menu name of vegetable to be produced, the assessment factor of assessment factor and vegetable to be produced is approximate.
Vegetable boiling method of the present invention based on big data finds out in step S2 in the first data acquisition system and comments
Estimate the method for the assessment approximate the second data set of factor of factor and vegetable to be produced specifically:
Compare the assessment factor of boiling data in the first data acquisition system, the assessment factor of vegetable to be produced, in the first data
The numerical value of numerical value and the corresponding assessment factor of vegetable to be produced that assessment factor is found out in set differs within a preset range
Several boiling data, the boiling data composition the second data set found out.
Vegetable boiling method of the present invention based on big data in step S2, obtains the vegetable name of vegetable to be produced
Claim and assessment factor, find out in the database menu name it is identical with the menu name of vegetable to be produced, assessment factor and to
The approximate several boiling data of assessment factor for making vegetable, select vegetable scoring in several boiling data found out
A highest boiling data and the boiling duration for obtaining this boiling data, principle are as follows:
Difference assessment factors same vegetables best boiling duration be it is different, have a large amount of boiling number in database
According to finding out menu name with the menu name of vegetable to be produced identical, assessment factor and vegetable to be produced in the database
The approximate several boiling data of factor are assessed, the assessment factor in these boiling data is approximate, but with difference when boiling,
And scoring is different because boiling duration difference leads to vegetable, it will under the conditions of assessment factor is approximate using unitary variant principle
Assessment factor is seen as identical, chooses vegetable and scores and a highest boiling data and obtains the boiling durations of this boiling data,
Best boiling duration of a length of vegetable under the assessment factor when boiling of acquisition, carries out best boiling duration to the vegetable
Boiling will keep the boiling result of vegetable best.
The present invention also provides a kind of vegetable decoction system 1 based on big data, comprising:
Data acquisition module 11: carrying out multiple vegetable boiling to multiple tracks vegetable respectively, and every dish product produce after completing boiling
A raw boiling data, the boiling data of generation are stored to database, a boiling data include the dish of the secondary vegetable boiling
The name of an article claims, assesses factor, vegetable scoring, boiling duration, assessment factor include the secondary vegetable boiling food materials characteristic and/or
Environmental data；
Optimal boiling duration obtains module 12: obtaining the menu name and assessment factor of vegetable to be produced, in the database
The assessment factor for finding out menu name identical with the menu name of vegetable to be produced, assessment factor and vegetable to be produced is approximate
Several boiling data are selected the highest boiling data of vegetable scoring and are obtained in several boiling data found out
The boiling duration of this boiling data；
Boiling execution module 13: the steaming that optimal boiling duration obtains the boiling duration that module obtains is carried out to vegetable to be produced
It boils.
Vegetable decoction system 1 of the present invention based on big data, the food materials characteristic in data acquisition module 11
Including the scoring of food materials tough degree for cooking, food materials temperature, environmental data includes ambient humidity, environment temperature, the ring for carrying out vegetable boiling
Border air pressure.
Vegetable decoction system 1 of the present invention based on big data, optimal boiling duration obtain module 12 and are used for basis
The operation of user or default setting select the food materials tough degree for cooking of vegetable to be produced to score, food materials temperature, ambient humidity, environment temperature
It is one or more as assessment factor in degree, ambient pressure.
Vegetable decoction system 1 of the present invention based on big data, optimal boiling duration obtain module 12 and are used in number
According to identical first data acquisition system of the menu name for finding out menu name and vegetable to be produced in library, the first data acquisition system includes
Several boiling data, and the assessment factor that finds out in the first data acquisition system assessment factor and vegetable to be produced approximate the
Two data acquisition systems, the second data set include several boiling data, the menu name of each boiling data in the second data set
The assessment factor of, assessment factor identical with the menu name of vegetable to be produced and vegetable to be produced is approximate.
Vegetable decoction system 1 of the present invention based on big data, optimal boiling duration obtain module 12 for comparing
The assessment factor of the assessment factor, vegetable to be produced of boiling data, finds out in the first data acquisition system in first data acquisition system
Several boiling data of the numerical value difference of the numerical value and the corresponding assessment factor of vegetable to be produced of assessing factor within a preset range,
The boiling data composition the second data set found out.
Compared with prior art, the beneficial effect comprise that carrying out multiple vegetable boiling respectively to multiple tracks vegetable, often
One vegetable generates a boiling data after completing boiling, by numerous boiling data collections into database based on number
According to, in vegetable boiling to be carried out, obtain vegetable to be produced menu name and assessment factor, find out vegetable in the database
Title is identical with the menu name of vegetable to be produced, assesses factor and the approximate several boilings of the assessment factor of vegetable to be produced
Data select the highest boiling data of vegetable scoring in several boiling data found out and obtain this boiling number
According to boiling duration, when boiling, a length of vegetable for making the vegetable scored highest boiling duration, and when boiling is a length of best
Boiling duration, the acquisition of best boiling duration consider food materials characteristic (scoring of food materials tough degree for cooking, food materials temperature) and ring
Border data (ambient humidity, environment temperature, ambient pressure), best boiling duration can make vegetable cooking effect more preferable.
The above described specific embodiments of the present invention are not intended to limit the scope of the present invention..Any basis
Any other various changes and modifications that technical concept of the invention is made should be included in the guarantor of the claims in the present invention
It protects in range.
Claims (10)
1. a kind of vegetable boiling method based on big data characterized by comprising
S1, multiple vegetable boiling is carried out respectively to multiple tracks vegetable, every dish product generate a boiling data after completing boiling, will
The boiling data storage generated to database, a boiling data include the menu name of the secondary vegetable boiling, assessment because
Number, vegetable scoring, boiling duration, the assessment factor include the food materials characteristic and/or environmental data of the secondary vegetable boiling；
S2, the menu name and the assessment factor for obtaining vegetable to be produced, find out in the database menu name and
The menu name of vegetable to be produced is identical, assesses factor and the approximate several boiling data of the assessment factor of vegetable to be produced,
Vegetable is selected in several boiling data found out score a highest boiling data and obtain this boiling data
Boiling duration；
S3, the vegetable to be produced is carried out S2 acquisition boiling duration boiling.
2. the vegetable boiling method based on big data as described in claim 1, which is characterized in that the food materials in step S1
Characteristic include food materials tough degree for cooking scoring, food materials temperature, the environmental data include carry out vegetable boiling ambient humidity,
Environment temperature, ambient pressure.
3. the vegetable boiling method based on big data as claimed in claim 2, which is characterized in that obtained in step S2 to be produced
The method of the assessment factor of vegetable specifically:
Depending on the user's operation or default setting select the food materials tough degree for cooking of vegetable to be produced to score, food materials temperature, environmental wet
It is degree, environment temperature, one or more as assessment factors in ambient pressure.
4. the vegetable boiling method based on big data as described in claim 1, which is characterized in that in step S2 in the database
The assessment factor for finding out menu name identical with the menu name of vegetable to be produced, assessment factor and vegetable to be produced is approximate
The method of several boiling data specifically:
Find out identical first data acquisition system of menu name of menu name and vegetable to be produced in the database, described first
Data acquisition system includes several boiling data, finds out in first data acquisition system assessment factor and vegetable to be produced is commented
Estimate the approximate the second data set of factor, the second data set includes several boiling data, the second data set
In each boiling data menu name it is identical with the menu name of vegetable to be produced, assessment factor and vegetable to be produced assessment because
Number is approximate.
5. the vegetable boiling method based on big data as claimed in claim 4, which is characterized in that in the first data in step S2
The method of the assessment approximate the second data set of factor of assessment factor and vegetable to be produced is found out in set specifically:
Compare the assessment factor of boiling data in first data acquisition system, the assessment factor of vegetable to be produced, described first
The numerical value of numerical value and the corresponding assessment factor of vegetable to be produced that assessment factor is found out in data acquisition system is differed in preset range
Interior several boiling data, the boiling data found out form the second data set.
6. a kind of vegetable decoction system based on big data characterized by comprising
Data acquisition module: carrying out multiple vegetable boiling to multiple tracks vegetable respectively, and every dish product generate one after completing boiling
Boiling data store the boiling data of generation to database, and the boiling data include the secondary vegetable boiling
Menu name, assessment factor, vegetable scoring, boiling duration, the assessment factor include the food materials characteristic of the secondary vegetable boiling
According to and/or environmental data；
Optimal boiling duration obtains module: for obtaining the menu name and assessment factor of vegetable to be produced, looking into the database
If the assessment factor for finding out menu name identical with the menu name of vegetable to be produced, assessment factor and vegetable to be produced is approximate
Dry boiling data are selected the highest boiling data of vegetable scoring and are obtained in several boiling data found out and are somebody's turn to do
The boiling duration of boiling data；
Boiling execution module: boiling duration that module obtains is obtained for carrying out optimal boiling duration to the vegetable to be produced
Boiling.
7. the vegetable decoction system based on big data as claimed in claim 6, which is characterized in that in the data acquisition module
The food materials characteristic include food materials tough degree for cooking scoring, food materials temperature, the environmental data include carry out vegetable boiling
Ambient humidity, environment temperature, ambient pressure.
8. the vegetable decoction system based on big data as claimed in claim 7, which is characterized in that the optimal boiling duration obtains
Modulus block for depending on the user's operation or default setting select the food materials tough degree for cooking of vegetable to be produced to score, food materials temperature,
It is ambient humidity, environment temperature, one or more as assessment factors in ambient pressure.
9. the vegetable decoction system based on big data as claimed in claim 6, which is characterized in that the optimal boiling duration obtains
Modulus block is used to find out identical first data acquisition system of menu name of menu name and vegetable to be produced, institute in the database
Stating the first data acquisition system includes several boiling data, and finds out in first data acquisition system assessment factor and to be produced
The approximate the second data set of assessment factor of vegetable, the second data set include several boiling data, described second
The menu name of each boiling data is identical with the menu name of vegetable to be produced in data acquisition system, assesses factor and vegetable to be produced
Assessment factor it is approximate.
10. the vegetable decoction system based on big data as claimed in claim 9, which is characterized in that the optimal boiling duration
Assessment factor of the module for the assessment factor, vegetable to be produced of boiling data in first data acquisition system is obtained,
The numerical value of assessment factor and the numerical value difference of the corresponding assessment factor of vegetable to be produced are found out in first data acquisition system default
Several boiling data in range, the boiling data found out form the second data set.
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| CN201811050937.4A CN109299070B (en) | 2018-09-10 | 2018-09-10 | Dish cooking method and system based on big data |
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| CN110794704A (en) * | 2019-11-28 | 2020-02-14 | 广东美的厨房电器制造有限公司 | Method for determining cooking parameters, cooking device and computer storage medium |
| CN114617282A (en) * | 2022-04-25 | 2022-06-14 | 华中科技大学 | A quality improvement-oriented tobacco leaf curing process optimization method, system and terminal |
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| CN109299070B (en) | 2021-05-11 |
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