CN109197277B - Method and device for determining pesticide spraying information and plant protection system - Google Patents
Method and device for determining pesticide spraying information and plant protection system Download PDFInfo
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- CN109197277B CN109197277B CN201811217961.2A CN201811217961A CN109197277B CN 109197277 B CN109197277 B CN 109197277B CN 201811217961 A CN201811217961 A CN 201811217961A CN 109197277 B CN109197277 B CN 109197277B
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- 239000000575 pesticide Substances 0.000 title claims abstract description 273
- 238000005507 spraying Methods 0.000 title claims abstract description 135
- 238000000034 method Methods 0.000 title claims abstract description 47
- 230000006378 damage Effects 0.000 claims abstract description 205
- 241000607479 Yersinia pestis Species 0.000 claims abstract description 93
- 241000196324 Embryophyta Species 0.000 claims abstract description 42
- 241000238631 Hexapoda Species 0.000 claims abstract description 23
- 208000027418 Wounds and injury Diseases 0.000 claims abstract description 21
- 208000014674 injury Diseases 0.000 claims abstract description 21
- 238000004458 analytical method Methods 0.000 claims abstract description 18
- 238000012549 training Methods 0.000 claims abstract description 15
- 239000003814 drug Substances 0.000 claims description 33
- 239000007921 spray Substances 0.000 claims description 14
- 229940079593 drug Drugs 0.000 claims description 11
- 238000012545 processing Methods 0.000 claims description 4
- 238000012544 monitoring process Methods 0.000 claims description 3
- 244000285774 Cyperus esculentus Species 0.000 description 7
- 235000005853 Cyperus esculentus Nutrition 0.000 description 7
- 244000025254 Cannabis sativa Species 0.000 description 6
- 230000002265 prevention Effects 0.000 description 6
- 238000010586 diagram Methods 0.000 description 4
- 240000008042 Zea mays Species 0.000 description 3
- 235000005824 Zea mays ssp. parviglumis Nutrition 0.000 description 3
- 235000002017 Zea mays subsp mays Nutrition 0.000 description 3
- 235000005822 corn Nutrition 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- HKPHPIREJKHECO-UHFFFAOYSA-N butachlor Chemical compound CCCCOCN(C(=O)CCl)C1=C(CC)C=CC=C1CC HKPHPIREJKHECO-UHFFFAOYSA-N 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 239000003550 marker Substances 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012806 monitoring device Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- 244000099162 Cyperus alternifolius Species 0.000 description 1
- 206010061217 Infestation Diseases 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000006870 function Effects 0.000 description 1
- 230000002363 herbicidal effect Effects 0.000 description 1
- 239000004009 herbicide Substances 0.000 description 1
- 239000002917 insecticide Substances 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 239000010914 pesticide waste Substances 0.000 description 1
- 238000010408 sweeping Methods 0.000 description 1
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01G—HORTICULTURE; CULTIVATION OF VEGETABLES, FLOWERS, RICE, FRUIT, VINES, HOPS OR SEAWEED; FORESTRY; WATERING
- A01G13/00—Protecting plants
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- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01M—CATCHING, TRAPPING OR SCARING OF ANIMALS; APPARATUS FOR THE DESTRUCTION OF NOXIOUS ANIMALS OR NOXIOUS PLANTS
- A01M21/00—Apparatus for the destruction of unwanted vegetation, e.g. weeds
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- Insects & Arthropods (AREA)
- Pest Control & Pesticides (AREA)
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Abstract
The application discloses a method and a device for determining pesticide spraying information and a plant protection system. Wherein, the method comprises the following steps: acquiring current date information; inputting current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; and determining target pesticide spraying information at least according to the first target pesticide damage information. The application solves the technical problems that the manual work is used for preventing the insect pests and the weeds in the farmland, and the accuracy is low.
Description
Technical Field
The application relates to the field of agriculture, in particular to a method and a device for determining pesticide spraying information and a plant protection system.
Background
In the prior art, farmers generally judge according to subjective experience when applying pesticides to crops, and when the pesticides and the weeds in the farmland are prevented, actual data support is lacked, the subjectivity is strong, the accuracy is low, pesticide waste is caused, and the efficiency of preventing the pesticides and the weeds is low.
Disclosure of Invention
The embodiment of the application provides a method and a device for determining pesticide spraying information and a plant protection system, and aims to solve the technical problems that at least the manual work is used for preventing insect pests and weeds in farmlands, and the accuracy is low.
According to an aspect of an embodiment of the present application, there is provided a method for determining medicine spraying information, the method including: acquiring current date information; inputting current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; and determining target pesticide spraying information at least according to the first target pesticide damage information.
Optionally, the first target pest information corresponding to the current date information after the date includes: the current date information corresponds to first target pesticide damage information within a preset time period after the date.
Optionally, the target spray information comprises at least one of: pesticide type, spraying amount and spraying time.
Optionally, before determining the target pesticide spraying information at least according to the first target pesticide damage information, the method further includes: and determining the weather condition in the preset time period after the current date information based on the weather condition information after the historical weather data and/or the date corresponding to the current date information are taken as the starting point.
Optionally, determining the target pesticide spraying information at least according to the first target pesticide damage information comprises: inputting the first target pesticide damage information into a second preset model for analysis, and obtaining target pesticide spraying information corresponding to the first target pesticide damage information, wherein the second preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the second sample pesticide damage information and a mark used for identifying the sample pesticide spraying information corresponding to the second sample pesticide damage information.
Optionally, after determining the target pesticide spraying information at least according to the first target pesticide damage information, the method further includes: target spraying information is sent to the unmanned aerial vehicle; and controlling the unmanned aerial vehicle to spray the pesticide according to the target pesticide spraying information.
Optionally, determining target pesticide spraying information at least according to the first target pesticide damage information, including: looking up second target pesticide damage information corresponding to the current date information after the first historical date; and comparing the first target pesticide damage information with the second target pesticide damage information, and determining target pesticide spraying information according to the first target pesticide damage information if the first target pesticide damage information is consistent with the second target pesticide damage information.
Optionally, if the first target pest information is inconsistent with the second target pest information, the method further includes: looking up third target pesticide damage information corresponding to the current date information after the second historical date; and comparing the first target pesticide damage information with the third target pesticide damage information, if the first target pesticide damage information is consistent with the third target pesticide damage information, determining target pesticide spraying information according to the first target pesticide damage information, and if the first target pesticide damage information is not consistent with the third target pesticide damage information, determining target pesticide spraying information according to the third target pesticide damage information, wherein the number of the first historical dates is less than that of the second historical dates.
Optionally, after determining target pesticide spraying information at least according to the first target pesticide damage information, the method further includes: determining an area corresponding to the target spraying information; determining a drug sales strategy of the area according to the target spraying information, wherein the drug sales strategy comprises at least one of the following: determining the target supply amount of the medicine according to the spraying amount in the target spraying information; and determining the type of the pesticide to be supplied according to the pesticide type in the target spraying information.
Optionally, after determining target pesticide spraying information at least according to the first target pesticide damage information, the method further includes: determining the spraying time in the target spraying information; judging whether the spraying time is within a preset time period in a user travel log; and when the judgment result indicates that the pesticide spraying time is within the preset time period, determining the pesticide spraying time as the finally adopted pesticide spraying time.
According to another aspect of the embodiments of the present application, there is also provided a device for determining medicine spraying information, the device including: the acquisition module is used for acquiring current date information; the processing module is used for inputting current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; and the determining module is used for determining target pesticide spraying information at least according to the first target pesticide damage information.
According to another aspect of the embodiments of the present application, there is also provided a storage medium characterized in that the storage medium includes a stored program, wherein the program controls a device on which the storage medium is located to execute the above-described method for determining the medicine spraying information when the program is executed.
According to another aspect of the embodiments of the present application, there is also provided a processor, wherein the processor is configured to execute a program, and wherein the program executes the method for determining the medicine spraying information.
There is also provided, in accordance with another aspect of an embodiment of the present application, a plant protection system, including: the monitoring equipment is used for acquiring current date information; inputting the current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of first sample pesticide damage information occurring after a date corresponding to the first sample date information; wherein the first target pest information and the first sample pest information each include at least one of: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; determining target pesticide spraying information at least according to the first target pesticide damage information; and the spraying operation equipment is used for carrying out medicine spraying operation on the target area according to the target spraying information.
The method comprises the steps of obtaining current date information; inputting current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; and determining target pesticide spraying information at least according to the first target pesticide damage information. And then solved artifical insect pest and the grass damage to the farmland and prevented, the lower technical problem of the degree of accuracy has been realized through introducing historical data, provides actual data support for the prevention of the insect pest and the grass damage in farmland, has improved the degree of accuracy of prevention to the prevention efficiency to insect pest and grass damage.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
fig. 1 is a schematic flow chart of a method for determining medicine spraying information according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of another device for determining pesticide spraying information according to an embodiment of the application;
fig. 3 is a schematic structural diagram of a plant protection system according to an embodiment of the present application.
Detailed Description
In order to make the technical solutions better understood by those skilled in the art, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only partial embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein. Furthermore, the terms "comprises," "comprising," and "having," and any variations thereof, are intended to cover a non-exclusive inclusion, such that a process, method, system, article, or apparatus that comprises a list of steps or elements is not necessarily limited to those steps or elements expressly listed, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
Fig. 1 is a flowchart illustrating a method for determining drug spraying information according to an embodiment of the present application. As shown in fig. 1, the method comprises:
step S102, obtaining current date information;
in an optional embodiment, the current date information may be obtained by the intelligent terminal through an input instruction of a user, or obtained by the intelligent terminal according to real-time beijing time.
And step S104, inputting the current date information into a first preset model for analysis to obtain first target pesticide damage information after the date corresponding to the current date information.
Wherein, first predetermined model obtains for training through multiunit data, and every group data in the multiunit data all includes: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: weed information, pest information, and target occurrence time of the pest.
The first target pest information corresponds to the first sample pest information, for example, when the first sample pest information is the weed information, the current date information is input into the first preset model, and the obtained weed information is the weed information after the date corresponding to the current date information.
Wherein, the weed information can be the type information of the weed; the pest information may be pest type information.
The first target pest information corresponding to the current date information after the date comprises: the current date information corresponds to first target pesticide damage information within a preset time period after the date.
In an alternative embodiment, the predetermined time period may be 1 month. For example: one set of data of the first preset model comprises: 8/month 22 for marking information on insect infestation occurring within 1 month after 8/month 22. Wherein the number 8/month 22 is the number 8/month 22 in the historical years.
In another alternative embodiment, the predetermined time period may be 2 months. For example: one set of data of the first preset model comprises: and 5, 10, and marking the information of the insect pests and the occurrence time of the insect pests within 2 months after the 5, 10. Wherein, above-mentioned 5 months 10 is 5 months 10 in the historical year, and pest emergence time can be 6 months 10, also can be a time quantum, for example: the occurrence time of the insect pests is No. 5-30-6-30.
And step S106, determining target pesticide spraying information at least according to the first target pesticide damage information.
The targeted pesticide spray information may be at least one of: pesticide type, spraying amount and spraying time.
The pesticide spraying time can be the time for spraying pesticides preventively or the time for actually removing pesticides.
Before the target pesticide spraying information is determined at least according to the first target pesticide damage information, the method further comprises the following steps: and determining the weather condition in the preset time period after the current date information based on the weather condition information after the historical weather data and/or the date corresponding to the current date information are taken as the starting point.
In an alternative embodiment, if the current date information is 2018, 9 and 10, the weather condition after 2018, 9 and 10, and within a half month can be determined based on the weather condition information indicated by the weather forecast within a half month after 9 and 10.
In another optional embodiment, if the current date information is number 9 and 10 in 2018, the weather condition in the half month after number 9 and 10 in 2018 can be determined based on the weather condition information corresponding to the weather data in the half month after number 10 in the historical year.
After determining the weather condition in the preset time period after the current date information, the target pesticide spraying information can be determined by combining the weather condition in the preset time period after the current date information and the first target pesticide damage information.
For example: if the weather condition indicates that rain is present in the half month after the date corresponding to the current date information, the spraying amount can be properly increased when the target spraying information is determined, or if the weather condition indicates wind, the pesticide spraying time can be automatically adjusted by farmers.
In an optional embodiment, the obtained current time information is No. 4/month 20, after the No. 4/month 20 is input into the first preset model for analysis, the first target pest information within one month corresponding to the No. 4/month 20 is obtained and is the pest, and the pest occurrence time is No. 5/month 20. And determining the target pesticide spraying information corresponding to the first target pesticide damage information as that the corresponding crops are sprayed in No. 5/month and No. 15 to prevent the pests, wherein the pesticide type can be determined according to the specific pests corresponding to the pests, and can also be the pesticide type capable of sweeping most of the pests.
The determination of the target pesticide spraying information at least according to the first target pesticide damage information can be realized by the following steps: inputting the first target pesticide damage information into a second preset model for analysis, and obtaining target pesticide spraying information corresponding to the first target pesticide damage information, wherein the second preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the second sample pesticide damage information and a mark used for identifying the sample pesticide spraying information corresponding to the second sample pesticide damage information.
The second sample pest information includes at least one of: weed information, pest information, and target occurrence time of the pest.
And after the current date information is input into a first preset model for analysis and first target pesticide damage information after the date corresponding to the current date information is obtained, the first target pesticide damage information is input into a second preset model for analysis.
In an alternative embodiment, the set of data for the second predetermined model may be: the chufa and the corresponding spraying information for marking the chufa are as follows: the marker of herbicide butachlor corresponding to the cyperus esculentus, and the marker of prophylactical spraying time of the butachlor from 3 month No. 1 to 4 month No. 20.
In another alternative embodiment, the set of data for the second predetermined model may be: the corn northern leaf blight and the corresponding spraying information for identifying the corn northern leaf blight are as follows: marking of insecticide-pyrethrin insecticide corresponding to corn northern leaf blight.
After the target pesticide spraying information is determined at least according to the first target pesticide damage information, the method can also comprise the following steps: target spraying information is sent to the unmanned aerial vehicle; and controlling the unmanned aerial vehicle to spray the pesticide according to the target pesticide spraying information.
In an optional embodiment, after the intelligent terminal determines that the target sprays the medicine information, the intelligent terminal can send the target spraying medicine information to the unmanned aerial vehicle through the network and send a control instruction to the unmanned aerial vehicle so as to control the unmanned aerial vehicle to spray the medicine according to the target spraying medicine information.
The target pesticide spraying information is determined at least according to the first target pesticide damage information, and the method can be realized by the following steps: looking up second target pesticide damage information corresponding to the current date information after the first historical date; and comparing the first target pesticide damage information with the second target pesticide damage information, and determining target pesticide spraying information according to the first target pesticide damage information if the first target pesticide damage information is consistent with the second target pesticide damage information.
And a first history date indicating a date of the same month and date corresponding to the current date information for a first preset number of history years.
Wherein the first historical date comprises a date of at least one historical year, and when the first historical date comprises historical dates of N years, the number of the first historical dates is N.
The first historical date comprises a first type date and a second type date. The first type of pesticide information corresponding to the first type of date is consistent with the first target pesticide information, and the second type of pesticide information corresponding to the second type of date is inconsistent with the first target pesticide information; and when the number of the first type of dates is larger than that of the second type of dates, determining that the second target pest information is the first type of pest information, and at the moment, enabling the second target pest information to be consistent with the first target pest information. And when the number of the first type of dates is smaller than that of the second type of dates, determining that the second target pesticide damage information is the second type of pesticide damage information, wherein the second target pesticide damage information is inconsistent with the first target pesticide damage information.
The first type date may be followed by a preset time period after the first type date, and the second type date may be followed by a preset time period after the second type date.
In an alternative embodiment, the number of the first historical dates is 10, and the determination of the target pesticide spraying information at least according to the first target pesticide damage information can be realized by the following steps: setting the first target pest information as follows: the weed information includes the type of the weed. If the current date information is No. 3/10 in 2018, the corresponding pesticide damage information in a month after No. 3/10 every year in the last 10 years is consulted, for example: within 10 years, 6 years of agricultural injury information is weed injury information, and the type of the weed injury is cyperus esculentus; if the 4-year agricultural injury information is other agricultural injury information, the 3 month 10 corresponding to the 6 years is the first type date, and the 3 month 10 corresponding to the 4 years is the second type date. And 6>4, so that the second target information is determined to be the first type of pest information, namely the second target pest information is the weed information, and the weed type is the cyperus esculentus.
If the first target agricultural damage information is inconsistent with the second target agricultural damage information, looking up third target agricultural damage information corresponding to a second historical date corresponding to the current date information; and comparing the first target pesticide damage information with the third target pesticide damage information, if the first target pesticide damage information is consistent with the third target pesticide damage information, determining target pesticide spraying information according to the first target pesticide damage information, and if the first target pesticide damage information is not consistent with the third target pesticide damage information, determining target pesticide spraying information according to the third target pesticide damage information, wherein the number of the first historical dates is less than that of the second historical dates.
And a second history date indicating a date of which the month and date corresponding to the current date information are the same for a second preset number of history years, and the second preset number is greater than the first preset number.
When the second history date includes history dates of M years, the number of the second history dates is M.
The second historical dates include dates of the third type and dates of the fourth type. The corresponding third type of pesticide information after the third type of date is consistent with the first target pesticide information, and the corresponding fourth type of pesticide information after the fourth type of date is inconsistent with the first target pesticide information; and when the number of the third type of date is larger than that of the fourth type of date, determining that the third target pesticide damage information is the third type of pesticide damage information, wherein the third target pesticide damage information is consistent with the first target pesticide damage information.
And when the number of the third type of dates is smaller than that of the fourth type of dates, determining that the third target pesticide damage information is the fourth type of pesticide damage information, wherein the third target pesticide damage information is inconsistent with the first target pesticide damage information.
In an alternative embodiment, the number of the second history dates is 50, and the first target pest information is: and (3) the weed information is cyperus alternifolius, if the first target pest information is inconsistent with the second target pest information and the current date information is No. 3/10 in 2018, the corresponding pest information in the month after No. 3/10 in each year in nearly 50 years is consulted, for example: within 50 years, 30 years of agricultural injury information is weed injury information, and the type of the weed injury is cyperus esculentus; if the 20-year agricultural injury information is other agricultural injury information, the 3 month 10 corresponding to the 30 years is the third kind of date, and the 3 month 10 corresponding to the 20 years is the fourth kind of date. 30>20, so that the third target information is determined to be the third type of pest information, namely the third target pest information is the weed information, and the type of the weed is the cyperus esculentus.
In some embodiments of the present application, after step S106, a marketing strategy or a production strategy of the drug may be formulated using the determined targeted drug spraying information, for example, for the former: determining an area corresponding to target spraying information; determining a drug marketing strategy of the area according to the target spraying information, wherein the drug marketing strategy comprises at least one of the following: determining the target supply amount of the medicine according to the spraying amount in the target spraying information; the type of the drug to be supplied is determined according to the type of the pesticide in the target spraying information. By using the scheme, the sales strategy of the current region can be determined, for example, when the spraying amount in the target spraying information is larger than a preset threshold value, it is determined that more sales are required to be released to the current region.
When the target spraying information includes the spraying time, various factors can be considered comprehensively to decide whether to adopt the spraying time, for example, the journey information of the user can be considered, specifically: determining the spraying time in the target spraying information; judging whether the spraying time is within a preset time period in a user travel log; and when the judgment result indicates that the pesticide spraying time is within the preset time period, determining the pesticide spraying time as the finally adopted pesticide spraying time.
The method comprises the steps of obtaining current date information; inputting current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; and determining target pesticide spraying information at least according to the first target pesticide damage information. And then solved artifical insect pest and the grass damage to the farmland and prevented, the lower technical problem of the degree of accuracy has been realized through introducing historical data, provides actual data support for the prevention of the insect pest and the grass damage in farmland, has improved the degree of accuracy of prevention to the prevention efficiency to insect pest and grass damage.
The embodiment of the application further provides a device for determining medicine spraying information, and fig. 2 is a schematic structural diagram of the device for determining medicine spraying information according to the embodiment of the application. As shown in fig. 2, the apparatus includes:
an obtaining module 22, configured to obtain current date information;
processing module 24 is used for inputting current date information into a first preset model for analysis, and first target agricultural injury information after the date corresponding to the current date information is obtained, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data includes: the first sample date information is used for identifying a mark of the first sample pesticide damage information occurring after the date corresponding to the first sample date information; wherein, the first target pest information and the first sample pest information both comprise at least one of the following: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests;
and the determining module 26 is used for determining target pesticide spraying information at least according to the first target pesticide damage information.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 1 for a preferred implementation of the embodiment shown in fig. 2, and details are not described here again.
The embodiment of the application also provides a storage medium which comprises a stored program, wherein when the program runs, the device where the storage medium is located is controlled to execute the above determining method for the medicine spraying information.
The embodiment of the application further provides a processor, which is characterized in that the processor is used for running the program, wherein the program executes the above method for determining the medicine spraying information when running.
Fig. 3 is a schematic structural diagram of a plant protection system according to an embodiment of the present application. As shown in fig. 3, the plant protection system includes:
a monitoring device 30 for acquiring current date information; inputting the current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of first sample pesticide damage information occurring after a date corresponding to the first sample date information; wherein the first target pest information and the first sample pest information each include at least one of: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; determining target pesticide spraying information at least according to the first target pesticide damage information;
and the spraying operation equipment 32 is used for carrying out medicine spraying operation on the target area according to the target spraying information.
Optionally, the monitoring device includes but is not limited to: ground monitoring facilities, high in the clouds server etc. above-mentioned spraying operation equipment includes but not limited to: unmanned aerial vehicles, unmanned work vehicles, and the like.
It should be noted that, reference may be made to the description related to the embodiment shown in fig. 1 for a preferred implementation of the embodiment shown in fig. 3, and details are not described here again.
The above-mentioned serial numbers of the embodiments of the present application are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present application, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In the embodiments provided in the present application, it should be understood that the disclosed technology can be implemented in other ways. The above-described embodiments of the apparatus are merely illustrative, and for example, a division of a unit may be a division of a logic function, and an actual implementation may have another division, for example, a plurality of units or components may be combined or may be integrated into another system, or some features may be omitted, or may not be executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, units or modules, and may be in an electrical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a removable hard disk, a magnetic or optical disk, and other various media capable of storing program codes.
The foregoing is only a preferred embodiment of the present application and it should be noted that those skilled in the art can make several improvements and modifications without departing from the principle of the present application, and these improvements and modifications should also be considered as the protection scope of the present application.
Claims (13)
1. A method for determining medicine spraying information, the method comprising:
acquiring current date information;
inputting the current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of first sample pesticide damage information occurring after a date corresponding to the first sample date information; wherein the first target pest information and the first sample pest information each include at least one of: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests;
determining target pesticide spraying information at least according to the first target pesticide damage information, wherein the method comprises the following steps:
looking up second target pesticide damage information corresponding to the current date information after a first historical date, wherein the first historical date comprises a first class date and a second class date, the first class pesticide damage information corresponding to the first class date is consistent with the first target pesticide damage information, and the second class pesticide damage information corresponding to the second class date is inconsistent with the first target pesticide damage information; when the number of the first type dates is larger than that of the second type dates, determining that the second target pesticide damage information is the first type pesticide damage information, and when the number of the first type dates is smaller than that of the second type dates, determining that the second target pesticide damage information is the second type pesticide damage information, wherein the second target pesticide damage information is inconsistent with the first target pesticide damage information;
and when the first target pesticide damage information is inconsistent with the second target pesticide damage information, looking up third target pesticide damage information corresponding to a second historical date corresponding to the current date information, comparing the first target pesticide damage information with the third target pesticide damage information, when the first target pesticide damage information is consistent with the third target pesticide damage information, determining target pesticide spraying information according to the first target pesticide damage information, and when the first target pesticide damage information is inconsistent with the third target pesticide damage information, determining the target pesticide spraying information according to the third target pesticide damage information, wherein the number of the first historical date is smaller than that of the second historical date.
2. The method of claim 1, wherein the first target pest information corresponding to the current date information after the date comprises:
the current date information corresponds to first target pesticide damage information in a preset time period after the date.
3. The method of claim 1, wherein the targeted drug spray information comprises at least one of: pesticide type, spraying amount and spraying time.
4. The method of claim 1, wherein determining targeted pesticide spray information based at least on the first targeted pesticide damage information further comprises:
and determining the weather condition in a preset time period after the current date information based on historical weather data and/or weather condition information after the date corresponding to the current date information is taken as a starting point.
5. The method of claim 1, wherein determining targeted pesticide spray information based at least on the first targeted pesticide damage information comprises:
inputting the first target pesticide damage information into a second preset model for analysis, and obtaining target pesticide spraying information corresponding to the first target pesticide damage information, wherein the second preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the second sample pesticide damage information and a mark used for identifying the sample pesticide spraying information corresponding to the second sample pesticide damage information.
6. The method of claim 1, wherein after determining target pesticide spray information based at least on the first target pesticide damage information, the method further comprises:
sending the target spraying information to an unmanned aerial vehicle;
and controlling the unmanned aerial vehicle to spray the pesticide according to the target pesticide spraying information.
7. The method of claim 1, wherein determining targeted pesticide spray information based at least on the first targeted pesticide damage information comprises:
looking up second target pesticide damage information corresponding to the current date information after the first historical date;
and comparing the first target pesticide damage information with the second target pesticide damage information, and determining the target pesticide spraying information according to the first target pesticide damage information when the first target pesticide damage information is consistent with the second target pesticide damage information.
8. The method of claim 1, wherein after determining target pesticide spray information based at least on the first target pesticide damage information, the method further comprises: determining an area corresponding to the target spraying information; determining a drug sales strategy of the area according to the target spraying information, wherein the drug sales strategy comprises at least one of the following: determining the target supply amount of the medicine according to the spraying amount in the target spraying information; and determining the type of the pesticide to be supplied according to the pesticide type in the target spraying information.
9. The method according to any one of claims 1 to 8, wherein after determining target pesticide spray information based on at least the first target pesticide damage information, the method further comprises:
determining the spraying time in the target spraying information; judging whether the spraying time is within a preset time period in a user travel log; and when the judgment result indicates that the pesticide spraying time is within the preset time period, determining the pesticide spraying time as the finally adopted pesticide spraying time.
10. A pesticide spraying device, characterized in that the device comprises:
the acquisition module is used for acquiring current date information;
the processing module is used for inputting the current date information into a first preset model for analysis to obtain first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of first sample pesticide damage information occurring after a date corresponding to the first sample date information; wherein the first target pest information and the first sample pest information each include at least one of: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests;
the determining module is used for determining target pesticide spraying information at least according to the first target pesticide damage information, and comprises the following steps:
looking up second target pesticide damage information corresponding to the current date information after a first historical date, wherein the first historical date comprises a first class date and a second class date, the first class pesticide damage information corresponding to the first class date is consistent with the first target pesticide damage information, and the second class pesticide damage information corresponding to the second class date is inconsistent with the first target pesticide damage information; when the number of the first type dates is larger than that of the second type dates, determining that the second target pesticide damage information is the first type pesticide damage information, and when the number of the first type dates is smaller than that of the second type dates, determining that the second target pesticide damage information is the second type pesticide damage information, wherein the second target pesticide damage information is inconsistent with the first target pesticide damage information;
and when the first target pesticide damage information is inconsistent with the second target pesticide damage information, looking up third target pesticide damage information corresponding to a second historical date corresponding to the current date information, comparing the first target pesticide damage information with the third target pesticide damage information, when the first target pesticide damage information is consistent with the third target pesticide damage information, determining target pesticide spraying information according to the first target pesticide damage information, and when the first target pesticide damage information is inconsistent with the third target pesticide damage information, determining the target pesticide spraying information according to the third target pesticide damage information, wherein the number of the first historical date is smaller than that of the second historical date.
11. A plant protection system, comprising:
the monitoring equipment is used for acquiring current date information; inputting the current date information into a first preset model for analysis, and obtaining first target agricultural injury information after the date corresponding to the current date information, wherein the first preset model is obtained through training of multiple groups of data, and each group of data in the multiple groups of data comprises: the first sample date information is used for identifying a mark of first sample pesticide damage information occurring after a date corresponding to the first sample date information; wherein the first target pest information and the first sample pest information each include at least one of: the information of the weeds, the information of the insect pests and the target occurrence time of the agricultural pests; determining target pesticide spraying information at least according to the first target pesticide damage information, wherein the method comprises the following steps:
looking up second target pesticide damage information corresponding to the current date information after a first historical date, wherein the first historical date comprises a first class date and a second class date, the first class pesticide damage information corresponding to the first class date is consistent with the first target pesticide damage information, and the second class pesticide damage information corresponding to the second class date is inconsistent with the first target pesticide damage information; when the number of the first type dates is larger than that of the second type dates, determining that the second target pesticide damage information is the first type pesticide damage information, and when the number of the first type dates is smaller than that of the second type dates, determining that the second target pesticide damage information is the second type pesticide damage information, wherein the second target pesticide damage information is inconsistent with the first target pesticide damage information;
when the first target pesticide damage information is inconsistent with the second target pesticide damage information, looking up third target pesticide damage information corresponding to a second historical date corresponding to the current date information, comparing the first target pesticide damage information with the third target pesticide damage information, when the first target pesticide damage information is consistent with the third target pesticide damage information, determining target pesticide spraying information according to the first target pesticide damage information, and when the first target pesticide damage information is inconsistent with the third target pesticide damage information, determining the target pesticide spraying information according to the third target pesticide damage information, wherein the number of the first historical date is smaller than that of the second historical date;
and the spraying operation equipment is used for carrying out medicine spraying operation on the target area according to the target spraying information.
12. A storage medium characterized by comprising a stored program, wherein a device in which the storage medium is located is controlled to execute the determination method of medicine spraying information according to any one of claims 1 to 9 when the program is executed.
13. A processor, characterized in that the processor is configured to run a program, wherein the program is configured to execute the method for determining the medicine spraying information according to any one of claims 1 to 9 when running.
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| CN201811217961.2A CN109197277B (en) | 2018-10-18 | 2018-10-18 | Method and device for determining pesticide spraying information and plant protection system |
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| CN201811217961.2A CN109197277B (en) | 2018-10-18 | 2018-10-18 | Method and device for determining pesticide spraying information and plant protection system |
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| CN100568127C (en) * | 2007-12-12 | 2009-12-09 | 中国水利水电科学研究院 | Underground drip irrigation water, fertilizer, the integrated autocontrol method of medicine |
| CN102541030B (en) * | 2012-02-07 | 2014-02-19 | 蔡诗伟 | System for intelligently monitoring and controlling crop pests and diseases |
| CN103701850A (en) * | 2013-11-27 | 2014-04-02 | 中国农业科学院农业信息研究所 | Farming almanac cloud management system and method |
| CN105353689B (en) * | 2015-12-03 | 2018-03-13 | 中农网购（江苏）电子商务有限公司 | Pesticide spraying machinery management control system based on Internet of Things |
| CN206909516U (en) * | 2017-06-02 | 2018-01-23 | 潍坊派康塑料科技有限公司 | A kind of irrigation system of precisely automatic dispenser |
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