CN109711272A - Crops intelligent management method, system, electronic equipment and storage medium - Google Patents
Crops intelligent management method, system, electronic equipment and storage medium Download PDFInfo
- Publication number
- CN109711272A CN109711272A CN201811475067.5A CN201811475067A CN109711272A CN 109711272 A CN109711272 A CN 109711272A CN 201811475067 A CN201811475067 A CN 201811475067A CN 109711272 A CN109711272 A CN 109711272A
- Authority
- CN
- China
- Prior art keywords
- crops
- crop area
- data
- setting
- sensor
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Landscapes
- Fertilizing (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
- Catching Or Destruction (AREA)
Abstract
The embodiment of the invention discloses crops intelligent management method, system, electronic equipment and storage mediums, the present invention relates to field of artificial intelligence, wherein, the described method includes: being based on preset Machine Vision Recognition model, according to environmental data and image data, the crops and various weeds of each kind in setting crop area are identified, corresponding recognition result is obtained；According to recognition result and the influence factor factor associated with recognition result, the corresponding fertilizer of intelligent sprinkling and the first drug are carried out by crops of at least one first sprayer to each kind of setting crop area.The solution of the present invention, it can accomplish: intelligent management is carried out to the crops of each kind in setting crop area, that is: intelligent to spray corresponding fertilizer and drug, targetedly spray corresponding fertilizer and drug, not only increase the plantation efficiency of plantation crops, the yield of crops is also improved, man power and material has been saved.
Description
Technical field
The present embodiments relate to field of artificial intelligence, and in particular to crops intelligent management method, system, electricity
Sub- equipment and storage medium.
Background technique
Bread is the staff of life, basis of the agricultural product as national economy, and unquestionable obtains the attention of countries in the world.
Nowadays, peasant's aging is serious, whose the following kind ground is urgent problem.The main force that rural area is tilled the land at present
It should be after 60,70, the old man of many births fifties also is continuing to be engaged in farm work.After 80s kind of ground it is few.Peasant is mostly agriculture
It is busy to go home to till the land, it is over and makes money to manual labour in city, few professional peasants truly.
Although mechanization is universal, due to having a large population and a few land, in addition soil disperses, causing cannot completely large-scale machine
Tool, some places or semi-mechanization.
The structure of agricultural production is unreasonable, plant it is single, be essentially all 1 year 2 season crops, winter wheat, summer corn.
Agricultural product security meets a severe test.It is well known that the agricultural of China Today faces lot of challenges, such as chemical fertilizer agriculture
Medicine abuse, pollution of estuary, crop straw burning bring atmosphere pollution etc..
Traditional agriculture technology means fall behind, and will cause liquid manure, the pesticide wasting of resources, not only cost high benefit is low, can also make
Polluted at soil, matrix, product quality cannot get effective guarantee, industrialized agriculture by be the future of agriculture development mainstream.
For planting the crops in farmland or greenhouse, how to accomplish targetedly to spray corresponding fertilizer and medicine
Object is technical problem to be solved.
Summary of the invention
For this purpose, the embodiment of the present invention provides crops intelligent management method, system, electronic equipment and storage medium, with
It solves not accomplishing targetedly to spray corresponding fertilizer for planting the crops in farmland or greenhouse in the prior art
And the problem of drug.
To achieve the goals above, embodiments of the present invention provide the following technical solutions:
In the first aspect of embodiments of the present invention, crops intelligent management method is provided, comprising: based on pre-
If machine learning model, the picture number arrived according to the collected environmental data of data acquisition device and image acquisition device
According to the environmental data and described image data of record setting crop area, wherein the data acquisition device at least wraps
It includes the solar panel for being set to the setting crop area and is set at least one described for setting crop area
Sensor；Based on preset Machine Vision Recognition model, according to the environmental data and described image data, to the setting agriculture
The crops and various weeds of each kind in crop area are identified, corresponding recognition result is obtained；According to the knowledge
Other result and the influence factor factor associated with the recognition result, by least one first sprayer to the setting agriculture
The crops of each kind of crop area carry out intelligent spraying corresponding fertilizer and the first drug, wherein influence factor because
Attached bag includes the corresponding first influence factor factor of environmental forecasting result and the corresponding second influence factor factor of production forecast result.
In another embodiment of the invention, the method also includes: it is collected described according at least one sensor
The image data that environmental data and image acquisition device arrive is based on preset synoptic model, to the setting crops area
The agricultural planting environment in domain is predicted, corresponding environmental forecasting result is obtained.
In another embodiment of the invention, the method also includes: be based on preset crop yield prediction model, root
According to the environmental data and described image data, the crop yield of the setting crop area is predicted, phase is obtained
The production forecast result answered.
In another embodiment of the invention, the method also includes: based on it is preset first sprinkling model, according to described
Recognition result carries out intelligent sprinkling phase by various weeds of at least one second sprayer to the setting crop area
The second drug answered, wherein at least one image collecting device for being used to acquire corresponding image data is fixed on corresponding the
On two sprayers.
In another embodiment of the invention, the method also includes: according to the recognition result, according to preset second
Model is sprayed, carries out intelligence by crops of at least one first sprayer to each kind of the setting crop area
Change and spray corresponding fertilizer and the first drug, wherein at least one is used to acquire the image collecting device of corresponding image data
It is fixed on corresponding first sprayer.
In yet another embodiment of the present invention, the sensor includes first sensor, second sensor, third sensing
Device and the 4th sensor, the first sensor are used to measure the items associated with soil in the setting crop area
Soil data；The second sensor for measure the setting plant be implanted with it is associated with surrounding air in crop area
Air themperature data；The 3rd sensor for measure the setting plant be implanted with it is related to surrounding air in crop area
The air-conditioning humidity data of connection；4th sensor is used to measure the light data that the setting kind is implanted in crop area.
In yet another embodiment of the present invention, described image acquisition device is included at least with the next item down: being equipped with first
The satellite image acquisition device of camera, the unmanned plane image collecting device for being equipped with second camera and be equipped with third camera shooting
The filming apparatus of head, wherein the collected described image data of described image acquisition device are for showing the setting crops
The maturity of the crops of each kind in region.
In the second aspect of embodiments of the present invention, crops intellectualized management system, the system packet are provided
Include: data record unit is based on preset machine learning model, according to the collected environmental data of data acquisition device and image
Acquisition device acquired image data, the environmental data and described image data of record setting crop area, wherein
The data acquisition device includes at least the solar panel for being set to the setting crop area and is set to described set
Determine at least one sensor of crop area；Recognition unit is based on preset Machine Vision Recognition model, according to the data
The environmental data and described image data of recording unit records, the agriculture to each kind in the setting crop area
Crop and various weeds are identified, corresponding recognition result is obtained；Spray unit, the institute identified according to the recognition unit
Recognition result and the influence factor factor associated with the recognition result are stated, is set by least one first sprayer to described
The crops for determining each kind of crop area carry out the corresponding fertilizer of intelligent sprinkling and the first drug, wherein the shadow
Ringing Factors includes that the corresponding first influence factor factor of environmental forecasting result and production forecast result corresponding second influence
Factors.
In the third aspect of embodiments of the present invention, a kind of electronic equipment is provided, the electronic equipment includes depositing
Reservoir and processor, the processor and the memory complete mutual communication by bus；The memory is stored with
The program instruction that can be executed by the processor, the processor call described program instruction to be able to carry out side as described above
Method.
In the fourth aspect of embodiments of the present invention, a kind of computer readable storage medium is provided, is stored thereon
There is the step of computer program, the computer program realizes any of the above-described the method when being executed by processor.
Embodiment according to the present invention, the embodiment of the invention provides crops intelligent management methods, system, electronics
Equipment and storage medium have the advantages that the crops to each kind in setting crop area carry out intelligent pipe
Reason, it may be assumed that corresponding fertilizer and drug are sprayed in intelligence, targetedly spray corresponding fertilizer and drug, not only increase plantation
The plantation efficiency of crops also improves the yield of crops, has saved man power and material.
Detailed description of the invention
It, below will be to embodiment party in order to illustrate more clearly of embodiments of the present invention or technical solution in the prior art
Formula or attached drawing needed to be used in the description of the prior art are briefly described.It should be evident that the accompanying drawings in the following description is only
It is merely exemplary, it for those of ordinary skill in the art, without creative efforts, can also basis
The attached drawing of offer, which is extended, obtains other implementation attached drawings.
Fig. 1 is the flow diagram for the crops intelligent management method that one embodiment of the invention provides；
Fig. 2 is the structural schematic diagram for the crops intellectualized management system that another embodiment of the present invention provides.
In figure: 201- data record unit；202- recognition unit；203- spray unit.
Specific embodiment
Embodiments of the present invention are illustrated by particular specific embodiment below, those skilled in the art can be by this explanation
Content disclosed by book is understood other advantages and efficacy of the present invention easily, it is clear that described embodiment is the present invention one
Section Example, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall within the protection scope of the present invention.
Embodiment 1
Embodiment according to the present invention 1 provides crops intelligent management method, as shown in Figure 1, implementing for the present invention
The flow diagram for the crops intelligent management method that example 1 provides.This method at least includes the following steps:
S101 is based on preset machine learning model, is adopted according to the collected environmental data of data acquisition device and image
Acquisition means acquired image data, the environmental data and image data of record setting crop area, wherein data acquisition dress
Set including at least the solar panel for being set to setting crop area and be set at least one of setting crop area
Sensor；
It should be noted that preset machine learning model in this step is set up according to conventional algorithm
Machine learning model, preset machine learning model and the corresponding algorithm of the model are routine techniques, herein no longer one by one
It repeats.
S102 is based on preset Machine Vision Recognition model, according to environmental data and image data, to setting crops area
The crops and various weeds of each kind in domain are identified, corresponding recognition result is obtained；
It should be noted that preset Machine Vision Recognition model in this step is set up according to conventional algorithm
The Machine Vision Recognition model come, preset Machine Vision Recognition model and the corresponding algorithm of the model are routine techniques,
This is no longer going to repeat them.
S103 first is sprayed by least one according to recognition result and the influence factor factor associated with recognition result
Day with fog carries out the corresponding fertilizer of intelligent sprinkling and the first drug to the crops of each kind of setting crop area,
In, the influence factor factor includes the corresponding first influence factor factor of environmental forecasting result and production forecast result corresponding second
The influence factor factor；In this way, through the embodiment of the present invention 1 provide scheme, can accomplish: to setting crop area in it is each
The crops of a kind carry out intelligent management, it may be assumed that corresponding fertilizer and drug are sprayed in intelligence, and targetedly sprinkling is corresponding
Fertilizer and drug not only increase the plantation efficiency of plantation crops, also improve the yield of crops, saved manpower and object
Power.
It should be noted that the first drug in step 103 refers to, according to recognition result, by least one first
Sprayer carries out the drug of intelligent sprinkling to the crops of each kind of setting crop area.In practical applications, needle
To the growing state of the crops of different cultivars and the crops, the first drug of sprinkling is often different and first
The amount of herbal sprinkling is also different, concrete condition, needs to be adjusted correspondingly according to different application scenarios, herein no longer
It repeats one by one.
In an optional example, the method also includes: according to the collected environmental data of at least one sensor
The image data arrived with image acquisition device is based on preset synoptic model, to the agricultural planting of setting crop area
Environment is predicted, corresponding environmental forecasting result is obtained；In this way, through the embodiment of the present invention 1 provide management method, can
The planting environment for the setting crop area for being implanted with crops to current kind is accurately predicted, corresponding environmental forecasting is obtained
As a result, and based on the environmental forecasting as a result, being adjusted to the type for the crops currently planted, so that the crops of plantation are more
Add and is suitable for current planting environment.
It should be noted that the above-mentioned preset synoptic model being mentioned to is set up according to conventional algorithm, in advance
If synoptic model and the corresponding algorithm of the model be routine techniques, this is no longer going to repeat them.
In an optional example, the method also includes: it is based on preset crop yield prediction model, according to ring
Border data and image data predict the crop yield of setting crop area, obtain corresponding production forecast result；
In this way, according to production forecast as a result, and combine practical crops yield be compared, obtain corresponding comparison result, and
Based on this comparison as a result, seeing whether the yield of current each crops has reached expected yield, if do not reached, to spray
Spill the type in the fertilizer on crops, dosage is adjusted, it is equally possible that the first medicine for being sprayed on crops of adjustment
The type of object, dosage.
Other than above-mentioned processing method, the kind of the crops of plantation can also be adjusted, until adjusting to most
Arable variety of crops.
It should be noted that the above-mentioned preset crop yield prediction model being mentioned to is established according to conventional algorithm
Get up, preset crop yield prediction model and the corresponding algorithm of the model are routine techniques, herein no longer one by one
It repeats.
In an optional example, the method also includes: based on preset first sprinkling model, tied according to identification
Fruit carries out corresponding second medicine of intelligent sprinkling by various weeds of at least one second sprayer to setting crop area
Object, wherein at least one image collecting device for being used to acquire corresponding image data is fixed on corresponding second sprayer.
In practical applications, the image collector for acquiring corresponding image data is set to camera, because camera is installed
It is easier.
It should be noted that the first sprinkling model is the model set up based on conventional algorithm, first sprays model,
And the corresponding algorithm of the model is routine techniques, this is no longer going to repeat them.
In practical applications, it by the camera of installation, can be accurately obtained with production estimation in setting agriculture
The condition of production of the various weeds of crop area, the condition of production of type and weeds based on weeds carry out intelligent sprinkling phase
The second drug answered, wherein the second drug is for distinguishing the first drug, and the second drug refers to according to recognition result, passes through
At least one second sprayer carries out the drug of intelligent sprinkling to the various weeds of setting crop area.
In practical applications, for the growing state of the weeds of different cultivars and the weeds, the second drug of sprinkling is past
Toward being different and the amount of the second herbal sprinkling is also different, concrete condition, need to be carried out according to different application scenarios
Corresponding adjustment, this is no longer going to repeat them.
In this way, in practical applications, according to recognition result, by least one second sprayer to setting crop area
Various weeds intelligent spray corresponding second drug and improve and apply in this way, having accomplished targetedly to spray drug
The efficiency of medicine avoids the waste of drug.
In an optional example, the method also includes: according to recognition result, according to preset second sprinkling mould
It is corresponding to carry out intelligent sprinkling by crops of at least one first sprayer to each kind of setting crop area for type
Fertilizer and the first drug, wherein at least one, which is used to acquire image collecting device of corresponding image data, is fixed on accordingly
The first sprayer on.
In practical applications, the image collector for acquiring corresponding image data is set to camera, because camera is installed
It is easier.
It should be noted that the second sprinkling model is the model set up based on conventional algorithm, second sprays model,
And the corresponding algorithm of the model is routine techniques, this is no longer going to repeat them.
In practical applications, by the camera of installation, plantation can be accurately obtained in setting crop area
The condition of production of each crops can accurately see the problem existing for the preceding crop based on the condition of production, provide rationally
Fertilizer and drug also improve the efficiency of application in this way, improving the efficiency of fertilising, avoid waste fertilizer, also avoid
Waste drug.
In an optional example, sensor includes first sensor, second sensor, 3rd sensor and the 4th biography
Sensor, first sensor are used to measure every soil data associated with soil in setting crop area；Second sensing
Device is used to measure the air themperature data associated with surrounding air that setting kind is implanted in crop area；3rd sensor is used
In the air humidity data associated with surrounding air that measurement setting kind is implanted in crop area；4th sensor is for surveying
The light data that amount setting kind is implanted in crop area；In this way, by the way that each different types of sensor is set to setting
The different zones of crop area, so that collected all data is accurately.
It should be noted that the above-mentioned type that common sensor has only been set out, can also have other types, and have
There is the sensor of other functions, this is no longer going to repeat them.
In practical applications, the different demands of different application scene can be directed to, between the time of sensor acquisition data
Every being configured, in order to enable all data got is more accurate, time interval can be arranged it is more shorter, alternatively,
It is set as real-time data collection.
In other application scenarios, in order to improve the arithmetic speed of Cloud Server, the memory space of Cloud Server is saved,
The time interval that sensor can also be acquired to the time interval setting of all data is long, can be according to practical different application field
The demand of scape, is adjusted correspondingly, and details are not described herein.
In an optional example, image collecting device is included at least with the next item down: being equipped with defending for the first camera
Star image collecting device, the unmanned plane image collecting device for being equipped with second camera and the shooting for being equipped with third camera dress
It sets, wherein the image data that image acquisition device arrives is used to show the farming of each kind in setting crop area
The maturity of object.
In conclusion the crops intelligent management method that the embodiment of the present invention 1 provides, has the advantages that pair
The crops for setting each kind in crop area carry out intelligent management, it may be assumed that corresponding fertilizer and medicine are sprayed in intelligence
Object targetedly sprays corresponding fertilizer and drug, not only increases the plantation efficiency of plantation crops, also improves crops
Yield, saved man power and material.
In addition, the crops intelligent management method that the embodiment of the present invention 1 provides, due to using advanced science and technology,
It can be realized accurate sowing, reasonable water and fertilizer irrigation, realize agricultural production low-consumption high-efficiency, agricultural product good quality and high output.
Embodiment 2
Embodiment according to the present invention 2 additionally provides crops intellectualized management system, as shown in Fig. 2, real for the present invention
The structural schematic diagram of the crops intellectualized management system of the offer of example 2 is provided.
The crops intellectualized management system that the embodiment of the present invention 2 provides includes data record unit 201, recognition unit
202 and spray unit 203.
Specifically, data record unit 201, is based on preset machine learning model, is acquired according to data acquisition device
To the image data that arrives of environmental data and image acquisition device, the environmental data and image of record setting crop area
Data, wherein data acquisition device includes at least the solar panel for being set to setting crop area and is set to setting
At least one sensor of crop area；
Recognition unit 202 is based on preset Machine Vision Recognition model, the environment recorded according to data record unit 201
Data and image data identify the crops and various weeds of each kind in setting crop area, obtain phase
The recognition result answered；
Spray unit 203, the recognition result identified according to recognition unit 202 and influence associated with recognition result because
Prime factor carries out intelligent sprinkling by crops of at least one first sprayer to each kind of setting crop area
Corresponding fertilizer and the first drug, wherein the influence factor factor includes the corresponding first influence factor factor of environmental forecasting result
The second influence factor factor corresponding with production forecast result；In this way, the 2 crops intelligence provided through the embodiment of the present invention
Management system can accomplish: carry out intelligent management to the crops of each kind in setting crop area, it may be assumed that intelligence
Change and spray corresponding fertilizer and drug, targetedly spray corresponding fertilizer and drug, not only increases the kind of plantation crops
Efficiency is planted, the yield of crops is also improved, has saved man power and material.
Part in the partial content in scheme that the embodiment of the present invention 2 provides and the scheme of the offer of the embodiment of the present invention 1
The same or similar part of content, please be referring to the description of the corresponding portion for the embodiment of the present invention 1, and details are not described herein.
In conclusion the crops intellectualized management system that the embodiment of the present invention 2 provides, has the advantages that pair
The crops for setting each kind in crop area carry out intelligent management, it may be assumed that corresponding fertilizer and medicine are sprayed in intelligence
Object targetedly sprays corresponding fertilizer and drug, not only increases the plantation efficiency of plantation crops, also improves crops
Yield, saved man power and material.
In addition, the crops intellectualized management system that the embodiment of the present invention 2 provides, due to using advanced science and technology,
It can be realized accurate sowing, reasonable water and fertilizer irrigation, realize agricultural production low-consumption high-efficiency, agricultural product good quality and high output.
Embodiment 3
Embodiment according to the present invention 3, additionally provides electronic equipment, and the electronic equipment includes: memory and processor,
The processor and the memory complete mutual communication by bus；The memory is stored with can be by the processor
The program instruction of execution, the processor call described program instruction to be able to carry out following method: based on preset machine learning
Model, according to the image data that the collected environmental data of data acquisition device and image acquisition device arrive, record setting
The environmental data and image data of crop area, wherein data acquisition device, which includes at least, is set to setting crop area
Solar panel and be set to setting crop area at least one sensor；Based on preset Machine Vision Recognition mould
Type carries out the crops and various weeds of each kind in setting crop area according to environmental data and image data
Identification, obtains corresponding recognition result；According to recognition result and the influence factor factor associated with recognition result, by least
One the first sprayer carries out the crops of each kind of setting crop area intelligent to spray corresponding fertilizer and the
One drug, wherein the influence factor factor includes the corresponding first influence factor factor of environmental forecasting result and production forecast result
The corresponding second influence factor factor.
Part in the partial content in scheme that the embodiment of the present invention 3 provides and the scheme of the offer of the embodiment of the present invention 1
The same or similar part of content, please be referring to the description of the corresponding portion for the embodiment of the present invention 1, and details are not described herein.
In conclusion a kind of electronic equipment that the embodiment of the present invention 3 provides, has the advantages that setting farming
The crops of each kind in object area carry out intelligent management, it may be assumed that corresponding fertilizer and drug are sprayed in intelligence, are directed to
Property the corresponding fertilizer of sprinkling and drug, not only increase the plantation efficiency of plantation crops, also improve the yield of crops, save
About man power and material.
In addition, a kind of electronic equipment that the embodiment of the present invention 4 provides can be realized due to using advanced science and technology
Accurate sowing, realizes agricultural production low-consumption high-efficiency, agricultural product good quality and high output at reasonable water and fertilizer irrigation.
Embodiment 4
Embodiment according to the present invention 4 additionally provides a kind of computer readable storage medium, is stored thereon with computer journey
Sequence, the computer program realize following method when being executed by processor: being based on preset machine learning model, adopted according to data
The image data that the collected environmental data of acquisition means and image acquisition device arrive, the environment of record setting crop area
Data and image data, wherein data acquisition device include at least be set to setting crop area solar panel and
It is set at least one sensor of setting crop area；Based on preset Machine Vision Recognition model, according to environmental data
And image data, the crops and various weeds of each kind in setting crop area are identified, are obtained corresponding
Recognition result；According to recognition result and the influence factor factor associated with recognition result, pass through at least one the first sprayer
The corresponding fertilizer of intelligent sprinkling and the first drug are carried out to the crops of each kind of setting crop area, wherein shadow
Ringing Factors includes that the corresponding first influence factor factor of environmental forecasting result and production forecast result corresponding second influence
Factors.
Part in the partial content in scheme that the embodiment of the present invention 4 provides and the scheme of the offer of the embodiment of the present invention 1
The same or similar part of content, please be referring to the description of the corresponding portion for the embodiment of the present invention 1, and details are not described herein.
In conclusion a kind of computer readable storage medium that the embodiment of the present invention 4 provides, has the advantages that
Intelligent management is carried out to the crops of each kind in setting crop area, it may be assumed that intelligence spray corresponding fertilizer and
Drug targetedly sprays corresponding fertilizer and drug, not only increases the plantation efficiency of plantation crops, also improves farming
The yield of object, has saved man power and material.
In addition, a kind of computer readable storage medium that the embodiment of the present invention 4 provides, due to using advanced scientific skill
Art can be realized accurate sowing, reasonable water and fertilizer irrigation, realize agricultural production low-consumption high-efficiency, agricultural product good quality and high output.
Although above having used general explanation and specific embodiment, the present invention is described in detail, at this
On the basis of invention, it can be made some modifications or improvements, this will be apparent to those skilled in the art.Therefore,
These modifications or improvements without departing from theon the basis of the spirit of the present invention are fallen within the scope of the claimed invention.
Claims (10)
1. crops intelligent management method characterized by comprising
Based on preset machine learning model, according to the collected environmental data of data acquisition device and image acquisition device
The image data arrived, the environmental data and described image data of record setting crop area, wherein the data acquisition
Device includes at least the solar panel for being set to the setting crop area and is set to the setting crop area
At least one sensor；
Based on preset Machine Vision Recognition model, according to the environmental data and described image data, to the setting farming
The crops and various weeds of each kind in object area are identified, corresponding recognition result is obtained；
It is first spraying by least one according to the recognition result and the influence factor factor associated with the recognition result
Device carries out the corresponding fertilizer of intelligent sprinkling and the first drug to the crops of each kind of the setting crop area,
In, the influence factor factor includes that the corresponding first influence factor factor of environmental forecasting result and production forecast result are corresponding
The second influence factor factor.
2. the method according to claim 1, wherein the method also includes: adopted according at least one sensor
The image data that the environmental data and image acquisition device collected arrives is based on preset synoptic model, sets to described
The agricultural planting environment for determining crop area is predicted, corresponding environmental forecasting result is obtained.
3. the method according to claim 1, wherein the method also includes: be based on preset crop yield
Prediction model carries out the crop yield of the setting crop area according to the environmental data and described image data
Prediction, obtains corresponding production forecast result.
4. the method according to claim 1, wherein the method also includes: based on it is preset first sprinkling mould
Type is carried out according to the recognition result by various weeds of at least one second sprayer to the setting crop area
Corresponding second drug is sprayed in intelligence, wherein the image collecting device that at least one is used to acquire corresponding image data is solid
Due on corresponding second sprayer.
5. the method according to claim 1, wherein the method also includes: according to the recognition result, according to
Preset second sprinkling model, the farming by least one first sprayer to each kind of the setting crop area
Object carries out the corresponding fertilizer of intelligent sprinkling and the first drug, wherein at least one is used to acquire the figure of corresponding image data
As acquisition device is fixed on corresponding first sprayer.
6. the method according to claim 1, wherein
The sensor includes first sensor, second sensor, 3rd sensor and the 4th sensor,
The first sensor is used to measure every soil data associated with soil in the setting crop area；
The second sensor is used to measure the air associated with surrounding air that the setting kind is implanted in crop area
Temperature data；
The 3rd sensor is used to measure the air-conditioning associated with surrounding air that the setting kind is implanted in crop area
Humidity data；
4th sensor is used to measure the light data that the setting kind is implanted in crop area.
7. the method according to claim 1, wherein described image acquisition device is included at least with the next item down:
Be equipped with the satellite image acquisition device of the first camera, be equipped with second camera unmanned plane image collecting device and
The filming apparatus of third camera is installed, wherein the collected described image data of described image acquisition device are for showing
The maturity of the crops of each kind in the setting crop area.
8. crops intellectualized management system characterized by comprising
Data record unit is based on preset machine learning model, according to the collected environmental data of data acquisition device and figure
As acquisition device acquired image data, record sets the environmental data and described image data of crop area,
In, the data acquisition device includes at least the solar panel for being set to the setting crop area and is set to described
In at least one sensor for setting crop area；
Recognition unit is based on preset Machine Vision Recognition model, the environment number recorded according to the data record unit
According to described image data, to it is described setting crop area in each kind crops and various weeds identify,
Obtain corresponding recognition result；
Spray unit, the recognition result identified according to the recognition unit and influence associated with the recognition result
Factors carry out intelligence by crops of at least one first sprayer to each kind of the setting crop area
Change and spray corresponding fertilizer and the first drug, wherein the influence factor factor includes corresponding first shadow of environmental forecasting result
Ring Factors and the corresponding second influence factor factor of production forecast result.
9. a kind of electronic equipment characterized by comprising
Memory and processor, the processor and the memory complete mutual communication by bus；The memory
It is stored with the program instruction that can be executed by the processor, the processor calls described program instruction to be able to carry out right such as and wants
Seek 1 to 7 any method.
10. a kind of computer readable storage medium, which is characterized in that be stored thereon with computer program, the computer program
The step of the method as any such as claim 1 to 7 is realized when being executed by processor.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811475067.5A CN109711272A (en) | 2018-12-04 | 2018-12-04 | Crops intelligent management method, system, electronic equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201811475067.5A CN109711272A (en) | 2018-12-04 | 2018-12-04 | Crops intelligent management method, system, electronic equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN109711272A true CN109711272A (en) | 2019-05-03 |
Family
ID=66254061
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201811475067.5A Pending CN109711272A (en) | 2018-12-04 | 2018-12-04 | Crops intelligent management method, system, electronic equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN109711272A (en) |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110197308A (en) * | 2019-06-05 | 2019-09-03 | 黑龙江省七星农场 | A kind of crop monitoring system and method for agriculture Internet of Things |
| CN110632930A (en) * | 2019-09-30 | 2019-12-31 | 上海寰钛教育科技有限公司 | Intelligent driving control method and device suitable for garden intellectualization, and storage medium |
| CN112790180A (en) * | 2021-01-04 | 2021-05-14 | 罗峰 | Standardized metering guidance system for crop fertilization and pesticide application |
| CN113366956A (en) * | 2021-06-16 | 2021-09-10 | 中国农业大学 | Control method for simultaneous application of pesticide and fertilizer and device for simultaneous application of pesticide and fertilizer |
| US11783207B2 (en) | 2020-02-18 | 2023-10-10 | International Business Machines Corporation | Robotic Toxicodendron weeding |
Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120109614A1 (en) * | 2010-10-25 | 2012-05-03 | Lindores Robert J | Crop characteristic estimation |
| CN104881017A (en) * | 2015-06-11 | 2015-09-02 | 张迪 | Beidou-based crop growth monitoring system |
| CN106383522A (en) * | 2016-09-22 | 2017-02-08 | 华南农业大学 | Virtual reality-based farmland agricultural condition information real-time monitoring system |
| CN106585992A (en) * | 2016-12-15 | 2017-04-26 | 上海土是宝农业科技有限公司 | Method and system for intelligent identification and accurate pesticide spraying using unmanned aerial vehicles |
| CN107426958A (en) * | 2015-01-11 | 2017-12-01 | Aaa塔拉尼斯视觉有限公司 | Agricultural monitoring system and method |
| US20180012168A1 (en) * | 2016-07-06 | 2018-01-11 | Agrian, Inc. | Multi-year crop yield analysis using remotely-sensed imagery for missing or incomplete yield events for site-specific variable rate applications |
| CN107807598A (en) * | 2017-11-24 | 2018-03-16 | 吉林省农业机械研究院 | Internet of Things+water saving, the fertile Precision Irrigation system and method for section |
| CN107944596A (en) * | 2017-10-20 | 2018-04-20 | 上海交通大学 | A kind of muskmelon growth management expert system based on Internet of Things |
| US20180197287A1 (en) * | 2017-01-08 | 2018-07-12 | Adrian Ronaldo Macias | Process of using machine learning for cannabis plant health diagnostics |
| CN108684282A (en) * | 2018-04-11 | 2018-10-23 | 北京麦飞科技有限公司 | A kind of agricultural, which is examined, beats integrated machine system and sprinkling control method |
| CN108776803A (en) * | 2018-04-20 | 2018-11-09 | 中国农业大学 | The method and system of weeds in a kind of removal farmland |
-
2018
- 2018-12-04 CN CN201811475067.5A patent/CN109711272A/en active Pending
Patent Citations (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120109614A1 (en) * | 2010-10-25 | 2012-05-03 | Lindores Robert J | Crop characteristic estimation |
| CN107426958A (en) * | 2015-01-11 | 2017-12-01 | Aaa塔拉尼斯视觉有限公司 | Agricultural monitoring system and method |
| CN104881017A (en) * | 2015-06-11 | 2015-09-02 | 张迪 | Beidou-based crop growth monitoring system |
| US20180012168A1 (en) * | 2016-07-06 | 2018-01-11 | Agrian, Inc. | Multi-year crop yield analysis using remotely-sensed imagery for missing or incomplete yield events for site-specific variable rate applications |
| CN106383522A (en) * | 2016-09-22 | 2017-02-08 | 华南农业大学 | Virtual reality-based farmland agricultural condition information real-time monitoring system |
| CN106585992A (en) * | 2016-12-15 | 2017-04-26 | 上海土是宝农业科技有限公司 | Method and system for intelligent identification and accurate pesticide spraying using unmanned aerial vehicles |
| US20180197287A1 (en) * | 2017-01-08 | 2018-07-12 | Adrian Ronaldo Macias | Process of using machine learning for cannabis plant health diagnostics |
| CN107944596A (en) * | 2017-10-20 | 2018-04-20 | 上海交通大学 | A kind of muskmelon growth management expert system based on Internet of Things |
| CN107807598A (en) * | 2017-11-24 | 2018-03-16 | 吉林省农业机械研究院 | Internet of Things+water saving, the fertile Precision Irrigation system and method for section |
| CN108684282A (en) * | 2018-04-11 | 2018-10-23 | 北京麦飞科技有限公司 | A kind of agricultural, which is examined, beats integrated machine system and sprinkling control method |
| CN108776803A (en) * | 2018-04-20 | 2018-11-09 | 中国农业大学 | The method and system of weeds in a kind of removal farmland |
Non-Patent Citations (3)
| Title |
|---|
| MAREK KULBACKI等: "Survey of Drones for Agriculture Automation from Planting to Harvest", 《2018 IEEE 22ND INTERNATIONAL CONFERENCE ON INTELLIGENT ENGINEERING SYSTEMS (INES)》 * |
| 张自清: ""渤海粮仓"小麦生产信息管理系统研发", 《中国优秀硕士学位论文全文数据库农业科技辑》 * |
| 曹宏鑫: "《互联网+现代农业 给农业插上梦想的翅膀》", 31 October 2017, 南京：江苏科学技术出版社 * |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110197308A (en) * | 2019-06-05 | 2019-09-03 | 黑龙江省七星农场 | A kind of crop monitoring system and method for agriculture Internet of Things |
| CN110197308B (en) * | 2019-06-05 | 2020-06-26 | 黑龙江省七星农场 | Crop monitoring system and method for agricultural Internet of things |
| CN110632930A (en) * | 2019-09-30 | 2019-12-31 | 上海寰钛教育科技有限公司 | Intelligent driving control method and device suitable for garden intellectualization, and storage medium |
| US11783207B2 (en) | 2020-02-18 | 2023-10-10 | International Business Machines Corporation | Robotic Toxicodendron weeding |
| CN112790180A (en) * | 2021-01-04 | 2021-05-14 | 罗峰 | Standardized metering guidance system for crop fertilization and pesticide application |
| CN113366956A (en) * | 2021-06-16 | 2021-09-10 | 中国农业大学 | Control method for simultaneous application of pesticide and fertilizer and device for simultaneous application of pesticide and fertilizer |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN109711272A (en) | Crops intelligent management method, system, electronic equipment and storage medium | |
| CN203241793U (en) | Agriculture production monitoring and management system based on internet of things | |
| Kajol et al. | Automated agricultural field analysis and monitoring system using IOT | |
| CN106657401A (en) | Crop growth monitoring platform based on Internet of Things and monitoring method thereof | |
| CN107945042A (en) | A kind of plant growth irrigation decision control system | |
| CN107173184A (en) | A kind of Agricultural Intelligent System irrigation system and method | |
| Marcu et al. | IoT based system for smart agriculture | |
| CN205819567U (en) | A kind of unmanned plane plant protection system | |
| CN107238574A (en) | The detection of plant growing way and the diagnostic method of fertilising are targetted towards cotton | |
| CN103985056A (en) | Method and system for collecting agricultural product production records under WSN farmland free partitions | |
| CN102413160A (en) | Chinese gooseberry garden accurate management system | |
| CN207053612U (en) | A kind of three-dimensional agriculture planting shed long-distance management system based on cell phone application | |
| CN110198352A (en) | A kind of Internet of Things management system of farmland robot | |
| CN108650321A (en) | A kind of intelligence vegetable garden control system and its control method | |
| CN103609363A (en) | Managing and monitoring system for seedling culture in greenhouses | |
| CN106841568A (en) | Good farmland soil detection system and its implementation based on technology of Internet of things | |
| Ukhurebor et al. | Precision agriculture: Weather forecasting for future farming | |
| CN205375166U (en) | Agriculture monitored control system of intelligence based on thing networking | |
| Mohanty et al. | Cultivation of cash crops under automated greenhouse using internet of things (IoT) | |
| CN115629585A (en) | Planting management method and system for smart agriculture | |
| Singh et al. | Role of IoT technology in agriculture for reshaping the future of farming in India: a review | |
| CN203692049U (en) | Greenhouse seedling culture management monitoring system | |
| CN109102419A (en) | Greenhouse gardening management system based on Internet of Things | |
| CN107995306A (en) | A kind of cotton precision planting system | |
| Krishna et al. | Inclusion of cloud, blockchain and iot based technologies in agriculture sector |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| AD01 | Patent right deemed abandoned | ||
| AD01 | Patent right deemed abandoned |
Effective date of abandoning: 20220325 |