CN113826598A - Unmanned aerial vehicle pesticide spreading method and device based on neural network - Google Patents
Unmanned aerial vehicle pesticide spreading method and device based on neural network Download PDFInfo
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- CN113826598A CN113826598A CN202111058427.3A CN202111058427A CN113826598A CN 113826598 A CN113826598 A CN 113826598A CN 202111058427 A CN202111058427 A CN 202111058427A CN 113826598 A CN113826598 A CN 113826598A
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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
- A01M7/00—Special adaptations or arrangements of liquid-spraying apparatus for purposes covered by this subclass
- A01M7/0025—Mechanical sprayers
- A01M7/0032—Pressure sprayers
- A01M7/0042—Field sprayers, e.g. self-propelled, drawn or tractor-mounted
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B64—AIRCRAFT; AVIATION; COSMONAUTICS
- B64D—EQUIPMENT FOR FITTING IN OR TO AIRCRAFT; FLIGHT SUITS; PARACHUTES; ARRANGEMENTS OR MOUNTING OF POWER PLANTS OR PROPULSION TRANSMISSIONS IN AIRCRAFT
- B64D1/00—Dropping, ejecting, releasing, or receiving articles, liquids, or the like, in flight
- B64D1/16—Dropping or releasing powdered, liquid, or gaseous matter, e.g. for fire-fighting
- B64D1/18—Dropping or releasing powdered, liquid, or gaseous matter, e.g. for fire-fighting by spraying, e.g. insecticides
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
- G06F30/27—Design optimisation, verification or simulation using machine learning, e.g. artificial intelligence, neural networks, support vector machines [SVM] or training a model
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Neural networks
- G06N3/04—Architecture, e.g. interconnection topology
Abstract
The invention discloses an unmanned aerial vehicle pesticide spraying method and device based on a neural network. Wherein, the method comprises the following steps: acquiring liquid medicine information of the unmanned aerial vehicle; generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information; inputting the liquid medicine information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data; and carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data. The invention solves the technical problems that the pesticide spreading parameters are obtained only according to the fixed pesticide spreading data calculation rules when the unmanned aerial vehicle pesticide spreading task is executed in the prior art, flexible and variable pesticide spreading calculation cannot be carried out according to the historical pesticide spreading conditions of the unmanned aerial vehicle and other pesticide spreading factors, and the flexibility and the efficiency in the pesticide spreading calculation process are reduced.
Description
Technical Field
The invention relates to the field of unmanned aerial vehicles, in particular to an unmanned aerial vehicle pesticide spraying method and device based on a neural network.
Background
Along with the continuous development of intelligent science and technology, people use intelligent equipment more and more among life, work, the study, use intelligent science and technology means, improved the quality of people's life, increased the efficiency of people's study and work.
At present, when an unmanned aerial vehicle carries out pesticide spreading operation, the unmanned aerial vehicle pesticide spreading task execution parameters are usually calculated according to pesticide spreading information of the unmanned aerial vehicle through fixed pesticide spreading data calculation rules, pesticide spreading operation is carried out according to the calculated pesticide spreading parameters, but the traditional unmanned aerial vehicle pesticide spreading task execution only obtains the pesticide spreading parameters according to the fixed pesticide spreading data calculation rules, flexible and variable pesticide spreading calculation cannot be carried out according to the historical pesticide spreading conditions of the unmanned aerial vehicle and other pesticide spreading factors, and flexibility and efficiency in the pesticide spreading calculation process are reduced.
In view of the above problems, no effective solution has been proposed.
Disclosure of Invention
The embodiment of the invention provides an unmanned aerial vehicle pesticide spreading method and device based on a neural network, and the method and device provided by the invention are used for at least solving the technical problems that in the prior art, pesticide spreading parameters are obtained only according to fixed pesticide spreading data calculation rules when an unmanned aerial vehicle pesticide spreading task is executed, flexible and variable pesticide spreading calculation cannot be carried out according to the historical pesticide spreading conditions of the unmanned aerial vehicle and other pesticide spreading factors, and the flexibility and efficiency in the pesticide spreading calculation process are reduced.
According to an aspect of the embodiment of the invention, an unmanned aerial vehicle pesticide spraying method based on a neural network is provided, and comprises the following steps: acquiring liquid medicine information of the unmanned aerial vehicle; generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information; inputting the liquid medicine information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data; and carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
Optionally, obtaining unmanned aerial vehicle liquid medicine information includes: acquiring liquid medicine level information and liquid medicine type information of an unmanned aerial vehicle; and summarizing the liquid medicine liquid level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
Optionally, before the unmanned aerial vehicle liquid medicine information and the unmanned aerial vehicle pesticide spreading area are input into a pesticide spreading model to obtain pesticide spreading data, the method further includes: and training the medicine spreading model.
Optionally, the dispensing data includes: medicine information, medicine spreading range and medicine spreading time.
According to another aspect of the embodiments of the present invention, there is also provided an unmanned aerial vehicle insecticide spraying device based on a neural network, including: the acquisition module is used for acquiring the liquid medicine information of the unmanned aerial vehicle; the generation module is used for generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle pesticide information; the pesticide spreading module is used for inputting the pesticide information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data; and the operation module is used for carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
Optionally, the obtaining module includes: the acquisition unit is used for acquiring liquid medicine level information and liquid medicine type information of the unmanned aerial vehicle; the collecting unit is used for collecting the liquid medicine level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
Optionally, the apparatus further comprises: and the training module is used for training the medicine spreading model.
Optionally, the dispensing data includes: medicine information, medicine spreading range and medicine spreading time.
According to another aspect of the embodiment of the invention, a non-volatile storage medium is further provided, and the non-volatile storage medium comprises a stored program, wherein the program is operated to control a device where the non-volatile storage medium is located to execute a neural network-based unmanned aerial vehicle pesticide spreading method.
According to another aspect of the embodiment of the invention, a non-volatile storage medium is further provided, and the non-volatile storage medium comprises a stored program, wherein the program is operated to control a device where the non-volatile storage medium is located to execute a neural network-based unmanned aerial vehicle pesticide spreading method.
In the embodiment of the invention, the unmanned aerial vehicle liquid medicine information is obtained; generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information; inputting the liquid medicine information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data; according to the mode of carrying out unmanned aerial vehicle operation of spilling the powder of spreading the powder of the unmanned aerial vehicle in the prior art, can't carry out the calculation of the powder of the unmanned aerial vehicle.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the invention and together with the description serve to explain the invention without limiting the invention. In the drawings:
fig. 1 is a flow chart of a neural network-based unmanned aerial vehicle pesticide application method according to an embodiment of the present invention;
fig. 2 is a block diagram of a neural network-based unmanned aerial vehicle pesticide spraying device according to an embodiment of the invention.
Detailed Description
In order to make the technical solutions of the present invention better understood, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the 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 invention.
It should be noted that the terms "first," "second," and the like in the description and claims of the present invention 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 invention 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.
According to an embodiment of the present invention, there is provided a method embodiment of a neural network-based unmanned aerial vehicle insecticide dispensing method, it is noted that the steps illustrated in the flowchart of the drawings may be performed in a computer system such as a set of computer executable instructions, and that while a logical order is illustrated in the flowchart, in some cases the steps illustrated or described may be performed in an order different than here.
Example one
Fig. 1 is a flowchart of a neural network-based unmanned aerial vehicle pesticide spraying method according to an embodiment of the present invention, as shown in fig. 1, the method includes the following steps:
and S102, acquiring the liquid medicine information of the unmanned aerial vehicle.
Specifically, in the embodiment of the present invention, the unmanned aerial vehicle needs to perform the corresponding unmanned aerial vehicle pesticide spreading work by determining the pesticide information and the pesticide in the unmanned aerial vehicle, so that the unmanned aerial vehicle needs to acquire and collect the pesticide information through devices in the unmanned aerial vehicle, such as liquid level inspection, pesticide label identification, and the like, and transmit and store the collected pesticide information data for subsequent generation of the pesticide spreading information of the unmanned aerial vehicle through the pesticide information data.
Optionally, obtaining unmanned aerial vehicle liquid medicine information includes: acquiring liquid medicine level information and liquid medicine type information of an unmanned aerial vehicle; and summarizing the liquid medicine liquid level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
Specifically, in order to realize the process of using the unmanned aerial vehicle for spreading the medicine, the liquid medicine information of the unmanned aerial vehicle is firstly acquired, wherein the liquid medicine information comprises liquid medicine level information and liquid medicine type information of the unmanned aerial vehicle, for example, the liquid medicine level information and the liquid medicine type information of the unmanned aerial vehicle are acquired; and summarizing the liquid medicine liquid level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
And step S104, generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information.
Specifically, because different liquid medicine information corresponds different regional and the scope of spreading pesticides, consequently need confirm unmanned aerial vehicle's the regional of spreading pesticides according to above-mentioned liquid medicine information after having obtained unmanned aerial vehicle's liquid medicine information, and then for follow-up unmanned aerial vehicle operation of spreading pesticides makes preparation.
For example, in unmanned aerial vehicle obtained liquid medicine information, learn that the medicine that unmanned aerial vehicle carried is A type anthelmintic, carry out information matching to A type anthelmintic then in unmanned aerial vehicle treater, and send out database call instruction, call liquid medicine and the regional database data that correspond that sprinkles, the regional pesticide that spills that obtains A type anthelmintic after the call is rural area B to C, therefore rural area B to C are the regional pesticide that spills that A type anthelmintic corresponds, unmanned aerial vehicle will fly to the sky of rural area B and C and carry out the operation of spilling the pesticide promptly.
And S106, inputting the liquid medicine information of the unmanned aerial vehicle and the unmanned aerial vehicle pesticide spreading area into a pesticide spreading model to obtain pesticide spreading data.
Optionally, before the unmanned aerial vehicle liquid medicine information and the unmanned aerial vehicle pesticide spreading area are input into a pesticide spreading model to obtain pesticide spreading data, the method further includes: and training the medicine spreading model.
Specifically, since the unmanned aerial vehicle needs to generate the pesticide application data according to the pesticide application model formed by the neural network, after the complete pesticide application model is trained, the unmanned aerial vehicle is required to input the pesticide liquid information of the unmanned aerial vehicle and the pesticide application area of the unmanned aerial vehicle into the pesticide application model, and the pesticide application data is generated according to calculation of the pesticide application model.
Optionally, the dispensing data includes: medicine information, medicine spreading range and medicine spreading time.
And S108, carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
Specifically, after the unmanned aerial vehicle pesticide spreading data is acquired, the content in the pesticide spreading data can be executed by the processor of the unmanned aerial vehicle, and the execution result of the pesticide spreading operation is fed back to the mobile terminal of the user.
Through the embodiment, the technical problems that the unmanned aerial vehicle pesticide spreading task in the prior art is executed only according to the fixed pesticide spreading data calculation rule to obtain pesticide spreading parameters, flexible and variable pesticide spreading calculation cannot be carried out according to the historical pesticide spreading condition of the unmanned aerial vehicle and other pesticide spreading factors, and flexibility and efficiency in the pesticide spreading calculation process are reduced are solved.
Example two
Fig. 2 is a block diagram of a neural network-based unmanned aerial vehicle pesticide spraying device according to an embodiment of the present invention, and as shown in fig. 2, the device includes:
and the acquisition module 20 is used for acquiring the liquid medicine information of the unmanned aerial vehicle.
Specifically, in the embodiment of the present invention, the unmanned aerial vehicle needs to perform the corresponding unmanned aerial vehicle pesticide spreading work by determining the pesticide information and the pesticide in the unmanned aerial vehicle, so that the unmanned aerial vehicle needs to acquire and collect the pesticide information through devices in the unmanned aerial vehicle, such as liquid level inspection, pesticide label identification, and the like, and transmit and store the collected pesticide information data for subsequent generation of the pesticide spreading information of the unmanned aerial vehicle through the pesticide information data.
Optionally, the obtaining module includes: the acquisition unit is used for acquiring liquid medicine level information and liquid medicine type information of the unmanned aerial vehicle; the collecting unit is used for collecting the liquid medicine level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
Specifically, in order to realize the process of using the unmanned aerial vehicle for spreading the medicine, the liquid medicine information of the unmanned aerial vehicle is firstly acquired, wherein the liquid medicine information comprises liquid medicine level information and liquid medicine type information of the unmanned aerial vehicle, for example, the liquid medicine level information and the liquid medicine type information of the unmanned aerial vehicle are acquired; and summarizing the liquid medicine liquid level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
And the generating module 22 is used for generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information.
Specifically, because different liquid medicine information corresponds different regional and the scope of spreading pesticides, consequently need confirm unmanned aerial vehicle's the regional of spreading pesticides according to above-mentioned liquid medicine information after having obtained unmanned aerial vehicle's liquid medicine information, and then for follow-up unmanned aerial vehicle operation of spreading pesticides makes preparation.
For example, in unmanned aerial vehicle obtained liquid medicine information, learn that the medicine that unmanned aerial vehicle carried is A type anthelmintic, carry out information matching to A type anthelmintic then in unmanned aerial vehicle treater, and send out database call instruction, call liquid medicine and the regional database data that correspond that sprinkles, the regional pesticide that spills that obtains A type anthelmintic after the call is rural area B to C, therefore rural area B to C are the regional pesticide that spills that A type anthelmintic corresponds, unmanned aerial vehicle will fly to the sky of rural area B and C and carry out the operation of spilling the pesticide promptly.
And the pesticide spreading module 24 is used for inputting the unmanned aerial vehicle liquid medicine information and the unmanned aerial vehicle pesticide spreading area into a pesticide spreading model to obtain pesticide spreading data.
Optionally, the apparatus further comprises: and the training module is used for training the medicine spreading model.
Specifically, since the unmanned aerial vehicle needs to generate the pesticide application data according to the pesticide application model formed by the neural network, after the complete pesticide application model is trained, the unmanned aerial vehicle is required to input the pesticide liquid information of the unmanned aerial vehicle and the pesticide application area of the unmanned aerial vehicle into the pesticide application model, and the pesticide application data is generated according to calculation of the pesticide application model.
Optionally, the dispensing data includes: medicine information, medicine spreading range and medicine spreading time.
And the operation module 26 is used for carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
Specifically, after the unmanned aerial vehicle pesticide spreading data is acquired, the content in the pesticide spreading data can be executed by the processor of the unmanned aerial vehicle, and the execution result of the pesticide spreading operation is fed back to the mobile terminal of the user.
According to another aspect of the embodiment of the invention, a non-volatile storage medium is further provided, and the non-volatile storage medium comprises a stored program, wherein the program is operated to control a device where the non-volatile storage medium is located to execute a neural network-based unmanned aerial vehicle pesticide spreading method.
Specifically, the method comprises the following steps: acquiring liquid medicine information of the unmanned aerial vehicle; generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information; inputting the liquid medicine information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data; and carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
According to another aspect of the embodiment of the invention, a non-volatile storage medium is further provided, and the non-volatile storage medium comprises a stored program, wherein the program is operated to control a device where the non-volatile storage medium is located to execute a neural network-based unmanned aerial vehicle pesticide spreading method.
Specifically, the method comprises the following steps: acquiring liquid medicine information of the unmanned aerial vehicle; generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information; inputting the liquid medicine information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data; and carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
Through the embodiment, the technical problems that the unmanned aerial vehicle pesticide spreading task in the prior art is executed only according to the fixed pesticide spreading data calculation rule to obtain pesticide spreading parameters, flexible and variable pesticide spreading calculation cannot be carried out according to the historical pesticide spreading condition of the unmanned aerial vehicle and other pesticide spreading factors, and flexibility and efficiency in the pesticide spreading calculation process are reduced are solved.
The above-mentioned serial numbers of the embodiments of the present invention are merely for description and do not represent the merits of the embodiments.
In the above embodiments of the present invention, 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, the division of the units may be a logical division, and in actual implementation, there may be another division, for example, multiple units or components may be combined or integrated into another system, or some features may be omitted, or not 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 invention 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 invention may be embodied in the form of 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 invention. 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 invention, and it should be noted that, for those skilled in the art, various modifications and decorations can be made without departing from the principle of the present invention, and these modifications and decorations should also be regarded as the protection scope of the present invention.
Claims (10)
1. An unmanned aerial vehicle pesticide spraying method based on a neural network is characterized by comprising the following steps:
acquiring liquid medicine information of the unmanned aerial vehicle;
generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle liquid medicine information;
inputting the liquid medicine information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data;
and carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
2. The method of claim 1, wherein the obtaining drone liquid information comprises:
acquiring liquid medicine level information and liquid medicine type information of an unmanned aerial vehicle;
and summarizing the liquid medicine liquid level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
3. The method of claim 1, wherein prior to said inputting said drone solution information and said drone application area into an application model resulting in application data, said method further comprises:
and training the medicine spreading model.
4. The method of claim 1, wherein the application data comprises: medicine information, medicine spreading range and medicine spreading time.
5. The utility model provides an unmanned aerial vehicle device that spreads pesticides based on neural network which characterized in that includes:
the acquisition module is used for acquiring the liquid medicine information of the unmanned aerial vehicle;
the generation module is used for generating an unmanned aerial vehicle pesticide spreading area according to the unmanned aerial vehicle pesticide information;
the pesticide spreading module is used for inputting the pesticide information of the unmanned aerial vehicle and the pesticide spreading area of the unmanned aerial vehicle into a pesticide spreading model to obtain pesticide spreading data;
and the operation module is used for carrying out unmanned aerial vehicle pesticide spreading operation according to the pesticide spreading data.
6. The apparatus of claim 5, wherein the obtaining module comprises:
the acquisition unit is used for acquiring liquid medicine level information and liquid medicine type information of the unmanned aerial vehicle;
the collecting unit is used for collecting the liquid medicine level information and the liquid medicine type information to generate the liquid medicine information of the unmanned aerial vehicle.
7. The apparatus of claim 5, further comprising:
and the training module is used for training the medicine spreading model.
8. The apparatus of claim 5, wherein the application data comprises: medicine information, medicine spreading range and medicine spreading time.
9. A non-volatile storage medium, comprising a stored program, wherein the program, when executed, controls an apparatus in which the non-volatile storage medium is located to perform the method of any one of claims 1 to 4.
10. An electronic device comprising a processor and a memory; the memory has stored therein computer readable instructions for execution by the processor, wherein the computer readable instructions when executed perform the method of any one of claims 1 to 4.
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