The content of the invention
An embodiment of the present invention provides a kind of water and fertilizer irrigation autocontrol method and system, is used for realization the filling of growing area liquid manureIrrigate and automatically control, save human resources, improve water and fertilizer utilization rate.
First aspect of the embodiment of the present invention provides a kind of water and fertilizer irrigation autocontrol method, it is characterised in that including：
Gather the environmental parameter of growing area；
The environmental parameter is converted into environment vector according to preset rule；
Environment vector is inputted into preset sorter model and draws corresponding water and fertilizer irrigation parameter；
The growing area is irrigated according to the water and fertilizer irrigation parameter.
Optionally, as a kind of possible embodiment, the environmental parameter of the collection growing area, including：
Temperature, humidity, rainfall, sunshine, radiation, wind speed, time, the nutrient solution index of growing area are gathered by sensorIn environmental parameter of the one or more as growing area.
Optionally, it is described to obtain the preset sorter model of environment vector input as a kind of possible embodimentGo out corresponding water and fertilizer irrigation parameter, including：
It will classify in environment vector input decision tree classifier model, export corresponding water and fertilizer irrigation parameter.
Optionally, further included as a kind of possible embodiment, this method：
Adjust the species of the environmental parameter；
And/or the preset irrigation parameter is adjusted, parameter is irrigated with Optimized water-nitrogen.
Optionally, further included as a kind of possible embodiment, this method：
Region difference according to residing for the growing area sets different sorter models.
Second aspect of the embodiment of the present invention provides a kind of water and fertilizer irrigation automatic control system, it is characterised in that including：
Data acquisition module, for gathering the environmental parameter of growing area；
Data conversion module, for the environmental parameter to be converted to environment vector according to preset rule；
Data analysis module, show that corresponding water and fertilizer irrigation is joined for environment vector to be inputted preset sorter modelNumber；
Module is irrigated, for irrigating the growing area according to the water and fertilizer irrigation parameter.
Optionally, as a kind of possible embodiment, the data acquisition module, including：
Sensor, for gathering the temperature of growing area, humidity, rainfall, sunshine, radiation, wind speed, time, nutrient solution refer toEnvironmental parameter of the one or more as growing area in mark.
Optionally, as a kind of possible embodiment, the data analysis module, including：
Data analysis unit, for will classify in environment vector input decision tree classifier model, output is correspondingWater and fertilizer irrigation parameter.
Optionally, further included as a kind of possible embodiment, the system：
First adjustment module, for adjusting the species of the environmental parameter；
Second adjustment module, for adjusting the preset irrigation parameter, parameter is irrigated with Optimized water-nitrogen.
Optionally, further included as a kind of possible embodiment, the system：
Sort module, the sorter model different for the different settings in region according to residing for the growing area.
As can be seen from the above technical solutions, the embodiment of the present invention has the following advantages：
In the embodiment of the present invention, machine recognizable environment can be converted to after the environmental parameter of growing area is collectedVector, by the preset sorter model that is drawn based on big data machine learning of environment vector input, it can be deduced that environment toCorresponding water and fertilizer irrigation parameter is measured, and corresponding growing area is irrigated according to the water and fertilizer irrigation parameter, you can be filled according to the liquid manureIrrigate parameter call automation equipment and realize that plantation zone water and fertilizer irrigation automatically controls, human resources have been saved, based on big data analysisThe preset sorter model established can analyze rational water and fertilizer irrigation strategy, improve water and fertilizer utilization rate.
Term " comprising " and " having " in description and claims of this specification and above-mentioned attached drawing and theyAny deformation, it is intended that cover it is non-exclusive include, for example, containing the process of series of steps or unit, method, beingSystem, product or equipment are not necessarily limited to those steps or the unit clearly listed, but may include not list clearly orFor the intrinsic other steps of these processes, method, product or equipment or unit.
In order to make it easy to understand, the idiographic flow in the embodiment of the present invention is described below, referring to Fig. 1, of the inventionA kind of one embodiment of water and fertilizer irrigation autocontrol method may include in embodiment：
101st, the environmental parameter of growing area is gathered；
In agriculture field, water and fertilizer irrigation is that the environmental parameter based on growing area is adjusted, under different environmental parametersCorresponding different water and fertilizer irrigation parameter, can be only achieved the efficient utilization of resource.
The environmental parameter of different growing areas is different, such as the environmental parameter in outdoor growing area can include, such asThe meteorological datas such as temperature, humidity, rainfall, sunshine, radiation, wind speed, the environmental parameter in greenhouse gardening area can include greenhouseThe parameters such as air themperature, greenhouse air humidity, the soil moisture, nutrient solution index, it is to be understood that specific to need what is gatheredEnvironmental parameter can reasonably be adjusted according to the region of growing area and the species of long-term cropping, not limited herein.
Optionally, as a kind of possible embodiment, the temperature that sensor gathers growing area can be passed through in the present embodimentOne or more in degree, humidity, rainfall, sunshine, radiation, wind speed, time, nutrient solution index are joined as the environment of growing areaNumber.
Specifically, corresponding environmental parameter can be gathered by the sensor of thing network sensing layer, then pass through Internet of ThingsThe transmission network of transport layer carries out data (wire/wireless sensing network) transmission, can be uploaded to Cloud Server.
102nd, environmental parameter is converted into environment vector according to preset rule；
, can be by for the ease of machine recognition, it is necessary to be changed to data after required environmental parameter is collectedEnvironmental parameter is converted into environment vector according to preset rule.
Optionally, different types of environmental parameter can be corresponded to different dimensions, with the ring of dimension in environment vectorThe different values of border parameter correspond to different numerical value, while crop species, growing area institute possession can be added in environment vectorThe information of the dimensions such as domain, irrigation time.
Below will be by taking parameter information be converted to environment vector in table 1 as an example, to environmental parameter in practice according to presetRule be converted to the process of environment vector and carry out exemplary explanation.
Table 1
Ownership place：The canopy setting value of riverhead 1 is 0, and the canopy setting value of riverhead 2 is 1, and the canopy setting value of riverhead 3 is 3, Yunnan 1Number canopy setting value is 4, and the canopy setting value of Yunnan 2 is 5.
Product category：Cherry and tomato setting value is 0, and Fruit Cucumber setting value is 1, and milk Chinese cabbage setting value is 2, water east leaf mustardSetting value is 3, and Lettuce setting value is 4.
Irrigation time：8:00 setting value is 0,12:00 setting value is 1,16:00 setting value is 2,20：00 setting value is 3,24 setting values are 4.
Weather：It is 0 to become a fine day setting value, and cloudy setting value is 1, and cloudy setting value is 2, and moistening setting value is 3, setting of being exposed to the sunIt is worth for 4.
Whether irrigate：It is setting value 0, no, setting value 1.
Irrigation equipment：Spraying device setting value 0, shower apparatus setting value 1, solution device setting value are 2.
Irrigation volume：Micro setting value 0, a small amount of setting value 1, middle amount setting value 2, a large amount of setting values 3.
After dimension and value has been divided to above-mentioned parameter information, parameter information in above-mentioned table 1 can be exchanged into pair5 vectors answered, (0：0：0：0：0：0：1)、(1：1：1：1：0：1：2、(2：2：2：2：0：2：0)、(3：3：3：3：1：2：3)、(4：4：4：4：1：2：3).
It is understood that the process that parameter information is converted to environment vector according to preset rule in above-mentioned table 1 is onlyIt is exemplary, the environmental parameter of different dimensions can be rationally set according to the actual requirements in practice and corresponding specifically takenValue, does not limit specifically herein.
103rd, environment vector is inputted into preset sorter model and draws corresponding water and fertilizer irrigation parameter；
Based on big data, can gather in advance different geographical or identical region different growing areas with water and fertilizer irrigation parameterRelevant a large amount of ambient parameter informations and the corresponding production information of every kind of ambient parameter information, and using shown in step 102The a large amount of ambient parameter informations got are converted to corresponding environment vector by data transfer device, based on these environment vector andThe corresponding production information of every kind of ambient parameter information can train preset sorter model, for example, decision tree, naive Bayesian,The models such as neutral net, it is the prior art that specific sorter model, which establishes principle, and details are not described herein again.
Preferably, decision tree classifier model can be used in this implementation, can be from other environmental parameters based on big dataThe of a relatively high target growing area of yield ranking is selected in the different growing area of the identical water and fertilizer irrigation parameter of information, and determines meshThe ambient parameter information and the corresponding environment vector of water and fertilizer irrigation parameter for marking growing area are effective environment vector, and are based on effective ringBorder vector trains decision tree classifier model, hereafter, will can be divided in environment vector input decision tree classifier modelClass, exports corresponding water and fertilizer irrigation parameter.
Specific training process is as follows：
The environment vector X after water and fertilizer irrigation parameter is removed using similar method construct in above-mentioned steps 102, it is correspondingWater and fertilizer irrigation parameter is denoted as vectorial Y；
Vectorial X and vector Y are input in sorter model and are trained, such as vectorial X and vector Y are input to decision-makingIn Tree Classifier model, decision-tree model can calculate according to preset arithmetic of linearity regression vectorial X being mapped to vectorial Y'sParameter needed for process, decision-tree model is finally obtained based on these parameters.The model can by unknown vector set X toThe mapping of duration set Y：X—>Y, the algorithm principle of specific decision tree classifier model is the prior art, is not repeated herein.
Optionally, the water and fertilizer irrigation parameter in the present embodiment can include irrigation equipment, irrigation volume, irrigate nutrient solution intoPoint, the one or more in the information such as irrigation time, do not limit herein specifically.
It is understood that both can be according to different points of the different settings in the region residing for growing area in the embodiment of the present inventionClass device model, or the growing area of different geographical sets identical sorter model, does not limit herein specifically.
104th, growing area is irrigated according to water and fertilizer irrigation parameter.
After definite water and fertilizer irrigation parameter, corresponding water and fertilizer irrigation automatic control system can control corresponding machinery to setIt is standby to implement water and fertilizer irrigation action according to water and fertilizer irrigation parameter automatically, human resources have been saved, have improved water and fertilizer utilization rate.
In the embodiment of the present invention, machine recognizable environment can be converted to after the environmental parameter of growing area is collectedVector, by the preset sorter model that is drawn based on big data machine learning of environment vector input, it can be deduced that environment toCorresponding water and fertilizer irrigation parameter is measured, and corresponding growing area is irrigated according to the water and fertilizer irrigation parameter, you can be filled according to the liquid manureIrrigate parameter call automation equipment and realize that plantation zone water and fertilizer irrigation automatically controls, human resources have been saved, based on big data analysisThe preset sorter model established can analyze rational water and fertilizer irrigation strategy, improve water and fertilizer utilization rate.
On the basis of above-described embodiment, in practice, in order to adapt to season conversion or soil property, soil moisture content, the growth of cereal crop seedlings,The conversion of the scenes such as insect pest situation, for every suit sorter model after initially training generation, plant personnel can be according to the actual requirementsParameter adjustment is carried out, to train a set of more practical sorter model.
Specifically, can be with the species of adjusting ambient parameter；And/or preset irrigation parameter is adjusted, irrigated and joined with Optimized water-nitrogenNumber.
Based on big data, using the crop yield under identical environmental parameter as foundation, plant personnel can be according to the actual requirementsThe species of environmental parameter is increased or decreased, for example, a dimension of the increase crop growth stage as environment vector, can basisIt is actually needed, the nutrient composition in the different stages of growth change liquid manure of crop, or the different grades of irrigation volume of modificationStandard, for example, by the irrigation volume of " a small amount of " grade corresponding 100 milliliters be revised as 50 milliliters.It is multiple based on big data, processThe adjustment in crop cycle so that sorter model is more in line with actual plantation demand, adds the practicality of sorter model.
It is understood that in various embodiments of the present invention, the size of the sequence number of above steps is not meant toThe priority of execution sequence, the execution sequence of each step should be determined with its function and internal logic, without tackling the embodiment of the present inventionImplementation process form any restriction.
A kind of water and fertilizer irrigation autocontrol method in the embodiment of the present invention is described in above-described embodiment, below willA kind of water and fertilizer irrigation automatic control system in the embodiment of the present invention is described, referring to Fig. 2, in the embodiment of the present inventionA kind of one embodiment of water and fertilizer irrigation automatic control system may include：
Data acquisition module 201, for gathering the environmental parameter of growing area；
Data conversion module 202, for environmental parameter to be converted to environment vector according to preset rule；
Data analysis module 203, show that corresponding water and fertilizer irrigation is joined for environment vector to be inputted preset sorter modelNumber；
Module 204 is irrigated, for irrigating growing area according to water and fertilizer irrigation parameter.
Optionally, as a kind of possible embodiment, the data acquisition module 201 in the present embodiment, can include：
Sensor, for gathering the temperature of growing area, humidity, rainfall, sunshine, radiation, wind speed, time, nutrient solution refer toEnvironmental parameter of the one or more as growing area in mark.
Optionally, as a kind of possible embodiment, the data analysis module 203 in the present embodiment can be furtherIncluding：
Data analysis unit 2031, for will classify in environment vector input decision tree classifier model, output pairThe water and fertilizer irrigation parameter answered.
Optionally, referring to Fig. 3, as a kind of possible embodiment, the water and fertilizer irrigation in the present embodiment automatically controlsSystem can also include：
First adjustment module 205, the species for adjusting ambient parameter；
Second adjustment module 206, for adjusting preset irrigation parameter, parameter is irrigated with Optimized water-nitrogen.
Optionally, as a kind of possible embodiment, water and fertilizer irrigation automatic control system in the present embodiment can be withIncluding：
Sort module 207, the sorter model different for the different settings in region according to residing for growing area.
In the embodiment of the present invention, machine recognizable environment can be converted to after the environmental parameter of growing area is collectedVector, by the preset sorter model that is drawn based on big data machine learning of environment vector input, it can be deduced that environment toCorresponding water and fertilizer irrigation parameter is measured, and corresponding growing area is irrigated according to the water and fertilizer irrigation parameter, you can be filled according to the liquid manureIrrigate parameter call automation equipment and realize that plantation zone water and fertilizer irrigation automatically controls, human resources have been saved, based on big data analysisThe preset sorter model established can analyze rational water and fertilizer irrigation strategy, improve water and fertilizer utilization rate.
It is apparent to those skilled in the art that for convenience and simplicity of description, the system of foregoing description,The specific work process of device and unit, may be referred to the corresponding process in preceding method embodiment, details are not described herein.
In several embodiments provided herein, it should be understood that disclosed system, apparatus and method can be withRealize by another way.For example, system embodiment described above is only schematical, for example, the unitDivision, is only a kind of division of logic function, can there is other dividing mode, such as multiple units or component when actually realizingAnother system can be combined or be desirably integrated into, or some features can be ignored, or do not perform.It is another, it is shown orThe mutual coupling, direct-coupling or communication connection discussed can be the indirect coupling by some interfaces, device or unitClose or communicate to connect, can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unitThe component shown may or may not be physical location, you can with positioned at a place, or can also be distributed to multipleIn network unit.Some or all of unit therein can be selected to realize the mesh of this embodiment scheme according to the actual needs's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can alsoThat unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated listMember can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or useWhen, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantiallyThe part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software productsEmbody, which is stored in a storage medium, including some instructions are used so that a computerEquipment (can be personal computer, server, or network equipment etc.) performs the complete of each embodiment the method for the present inventionPortion or part steps.And foregoing storage medium includes：USB flash disk, mobile hard disk, read-only storage (ROM, Read-OnlyMemory), random access memory (RAM, Random Access Memory), magnetic disc or CD etc. are various can store journeyThe medium of sequence code.
The above, the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations；Although with reference to beforeEmbodiment is stated the present invention is described in detail, it will be understood by those of ordinary skill in the art that：It still can be to precedingState the technical solution described in each embodiment to modify, or equivalent substitution is carried out to which part technical characteristic；And theseModification is replaced, and the essence of appropriate technical solution is departed from the spirit and scope of various embodiments of the present invention technical solution.