CN116414129A - Agricultural machinery monitoring control method and system for intelligent agriculture based on digital twin platform - Google Patents
Agricultural machinery monitoring control method and system for intelligent agriculture based on digital twin platform Download PDFInfo
- Publication number
- CN116414129A CN116414129A CN202310278616.4A CN202310278616A CN116414129A CN 116414129 A CN116414129 A CN 116414129A CN 202310278616 A CN202310278616 A CN 202310278616A CN 116414129 A CN116414129 A CN 116414129A
- Authority
- CN
- China
- Prior art keywords
- target
- agricultural machinery
- agricultural machine
- path
- monitoring control
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000012544 monitoring process Methods 0.000 title claims abstract description 104
- 238000000034 method Methods 0.000 title claims abstract description 60
- 238000003860 storage Methods 0.000 claims description 15
- 238000002360 preparation method Methods 0.000 description 12
- 239000002689 soil Substances 0.000 description 11
- 238000004891 communication Methods 0.000 description 6
- 238000005516 engineering process Methods 0.000 description 3
- 238000004364 calculation method Methods 0.000 description 2
- 238000010586 diagram Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- GNFTZDOKVXKIBK-UHFFFAOYSA-N 3-(2-methoxyethoxy)benzohydrazide Chemical compound COCCOC1=CC=CC(C(=O)NN)=C1 GNFTZDOKVXKIBK-UHFFFAOYSA-N 0.000 description 1
- 238000012271 agricultural production Methods 0.000 description 1
- 238000013473 artificial intelligence Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000003306 harvesting Methods 0.000 description 1
- 238000010899 nucleation Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y10/00—Economic sectors
- G16Y10/05—Agriculture
-
- A—HUMAN NECESSITIES
- A01—AGRICULTURE; FORESTRY; ANIMAL HUSBANDRY; HUNTING; TRAPPING; FISHING
- A01B—SOIL WORKING IN AGRICULTURE OR FORESTRY; PARTS, DETAILS, OR ACCESSORIES OF AGRICULTURAL MACHINES OR IMPLEMENTS, IN GENERAL
- A01B76/00—Parts, details or accessories of agricultural machines or implements, not provided for in groups A01B51/00 - A01B75/00
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course or altitude of land, water, air, or space vehicles, e.g. automatic pilot
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0212—Control of position or course in two dimensions specially adapted to land vehicles with means for defining a desired trajectory
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16Y—INFORMATION AND COMMUNICATION TECHNOLOGY SPECIALLY ADAPTED FOR THE INTERNET OF THINGS [IoT]
- G16Y40/00—IoT characterised by the purpose of the information processing
- G16Y40/10—Detection; Monitoring
Abstract
The invention discloses an agricultural machinery monitoring control method and system based on digital twin platform for intelligent agriculture, wherein the method comprises the following steps: when a job instruction is received, determining a target agricultural machine according to the job instruction; acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters; controlling the target agricultural machine to operate based on the operation information and the operation path; according to the invention, the operation path of the target agricultural machine is determined based on the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machine, and the target agricultural machine is controlled to operate based on the operation information and the operation path, so that the target agricultural machine is ensured to operate based on the operation path, repeated operation on a certain position is avoided, and the operation efficiency of the agricultural machine is improved.
Description
Technical Field
The invention relates to the technical field of artificial intelligence, in particular to an agricultural machinery monitoring control method and system for intelligent agriculture based on a digital twin platform.
Background
Along with the development of science and technology, more agricultural machinery for executing different agricultural production operations is developed and widely applied, however, at present, the agricultural machinery is manually operated by farmers, and the possibility of repeated operation on a certain position exists in the process of operating the agricultural machinery, so that the operation efficiency of the agricultural machinery is low; therefore, how to improve the working efficiency of the agricultural machinery is an urgent problem to be solved.
Disclosure of Invention
The invention mainly aims to provide an agricultural machinery monitoring control method and system for intelligent agriculture based on a digital twin platform, and aims to solve the problem of how to improve the operation efficiency of the agricultural machinery.
In order to achieve the above purpose, the invention provides an agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform, which comprises the following steps:
when a job instruction is received, determining a target agricultural machine according to the job instruction;
acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters;
and controlling the target agricultural machine to operate based on the operation information and the operation path.
Optionally, the step of determining the job path according to the job information and the job parameters includes:
determining a target working area according to the working information, and determining the working coverage width of the target agricultural machine according to the working parameters;
a total area of the target job area is calculated, and a job path is determined based on the total area and the job coverage width.
Optionally, based on the job information and the job path, the step of controlling the target agricultural machine to perform a job includes:
determining target job content and target job duration according to the job information, and acquiring historical job data of the target job content;
and determining the current working parameters of the target agricultural machinery according to the historical working data and the target working time length, and controlling the target agricultural machinery to carry out the operation according to the current working parameters and the working path.
Optionally, before the step of controlling the target agricultural machine to perform the operation according to the current working parameter and the operation path, the method includes:
determining an operation starting point according to the operation path, and acquiring the current parking position of the target agricultural machine;
and determining a running path of the target agricultural machine according to the operation starting point and the current parking position, and controlling the target agricultural machine to reach the operation starting point according to the running path.
Optionally, after the step of controlling the target agricultural machine to perform the job based on the job information and the job path, the method includes:
determining standard operation data according to the operation information, and acquiring actual operation data of the target agricultural machinery according to a preset time interval;
comparing the standard operation data with the actual operation data;
if the difference value between the standard operation data and the actual operation data is smaller than a preset difference value threshold, not adjusting the current working parameters of the target agricultural machinery, and controlling the target agricultural machinery to operate based on the current working parameters;
and if the difference value between the standard operation data and the actual operation data is not smaller than the preset difference value threshold, adjusting the current working parameter according to the difference value, and controlling the target agricultural machine to operate based on the adjusted current working parameter.
Optionally, after the step of controlling the target agricultural machine to perform the job based on the job information and the job path, the method further includes:
acquiring a current operation position of the target agricultural machine, and determining a current advancing direction of the target agricultural machine according to the current operation position;
Calculating an included angle between the current advancing direction and the working path, and calculating a distance between the current working position and the working path;
and determining whether to adjust the current advancing direction based on the included angle and the distance.
Optionally, based on the angle and the distance, the step of determining whether to adjust the current heading comprises:
comparing the included angle with a preset included angle threshold value;
if the included angle is larger than the preset included angle threshold, the current advancing direction is adjusted so that the target agricultural machine keeps advancing in the working path;
if the included angle is not larger than the preset included angle threshold, comparing the distance with a preset distance threshold;
if the distance is smaller than the preset distance threshold, not adjusting the current advancing direction so that the target agricultural machine advances based on the current advancing direction;
and if the distance is not smaller than the preset distance threshold, adjusting the current advancing direction so as to enable the target agricultural machine to keep advancing in the working path.
In addition, in order to achieve the above object, the present invention also provides an agricultural machinery monitoring and controlling device of intelligent agriculture based on a digital twin platform, the agricultural machinery monitoring and controlling device of intelligent agriculture based on a digital twin platform includes:
The determining module is used for determining a target agricultural machine according to the operation instruction when the operation instruction is received;
the acquisition module is used for acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machine and determining an operation path according to the operation information and the operation parameters;
and the control module is used for controlling the target agricultural machine to operate based on the operation information and the operation path.
Further, the obtaining module further includes a calculating module, where the calculating module is configured to:
a target job area is determined based on the job information, determining the operation coverage width of the target agricultural machine according to the operation parameters;
a total area of the target job area is calculated, and a job path is determined based on the total area and the job coverage width.
Further, the control module is further configured to:
determining target job content and target job duration according to the job information, and acquiring historical job data of the target job content;
and determining the current working parameters of the target agricultural machinery according to the historical working data and the target working time length, and controlling the target agricultural machinery to carry out the operation according to the current working parameters and the working path.
Further, the control module is further configured to:
determining an operation starting point according to the operation path, and acquiring the current parking position of the target agricultural machine;
and determining a running path of the target agricultural machine according to the operation starting point and the current parking position, and controlling the target agricultural machine to reach the operation starting point according to the running path.
Further, the control module is further configured to:
determining standard operation data according to the operation information, and acquiring actual operation data of the target agricultural machinery according to a preset time interval;
comparing the standard operation data with the actual operation data;
if the difference value between the standard operation data and the actual operation data is smaller than a preset difference value threshold, not adjusting the current working parameters of the target agricultural machinery, and controlling the target agricultural machinery to operate based on the current working parameters;
and if the difference value between the standard operation data and the actual operation data is not smaller than the preset difference value threshold, adjusting the current working parameter according to the difference value, and controlling the target agricultural machine to operate based on the adjusted current working parameter.
Further, the control module is further configured to:
acquiring a current operation position of the target agricultural machine, and determining a current advancing direction of the target agricultural machine according to the current operation position;
calculating an included angle between the current advancing direction and the working path, and calculating a distance between the current working position and the working path;
and determining whether to adjust the current advancing direction based on the included angle and the distance.
Further, the control module further includes an adjustment module further configured to:
comparing the included angle with a preset included angle threshold value;
if the included angle is larger than the preset included angle threshold, the current advancing direction is adjusted so that the target agricultural machine keeps advancing in the working path;
if the included angle is not larger than the preset included angle threshold, comparing the distance with a preset distance threshold;
if the distance is smaller than the preset distance threshold, not adjusting the current advancing direction so that the target agricultural machine advances based on the current advancing direction;
and if the distance is not smaller than the preset distance threshold, adjusting the current advancing direction so as to enable the target agricultural machine to keep advancing in the working path.
In addition, in order to achieve the above object, the present invention also provides an agricultural machinery monitoring control system of a smart agriculture based on a digital twin platform, the agricultural machinery monitoring control system of a smart agriculture based on a digital twin platform comprising: the intelligent agricultural machine monitoring control method based on the digital twin platform comprises the steps of a memory, a processor and an agricultural machine monitoring control program which is stored in the memory and can run on the processor, wherein the agricultural machine monitoring control program is executed by the processor.
In addition, in order to achieve the above object, the present invention also provides a computer readable storage medium, the readable storage medium is a computer readable storage medium, the readable storage medium stores an agricultural machinery monitoring control program, and the agricultural machinery monitoring control program when executed by a processor implements the steps of the intelligent agricultural machinery monitoring control method based on the digital twin platform as described above.
According to the intelligent agriculture agricultural machinery monitoring control method based on the digital twin platform, when an operation instruction is received, a target agricultural machinery is determined according to the operation instruction; acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters; controlling the target agricultural machine to operate based on the operation information and the operation path; according to the invention, the operation path of the target agricultural machine is determined based on the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machine, and the target agricultural machine is controlled to operate based on the operation information and the operation path, so that the target agricultural machine is ensured to operate based on the operation path, repeated operation on a certain position is avoided, and the operation efficiency of the agricultural machine is improved.
Drawings
FIG. 1 is a schematic diagram of a device architecture of a hardware operating environment according to an embodiment of the present invention;
FIG. 2 is a schematic flow chart of a first embodiment of an agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform of the present invention;
FIG. 3 is a flow chart of a second embodiment of the intelligent agricultural machine monitoring control method based on the digital twin platform of the present invention;
FIG. 4 is a schematic flow chart of a third embodiment of an agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform of the present invention;
FIG. 5 is a schematic diagram of the agricultural machinery monitoring control device based on the digital twin platform.
The achievement of the objects, functional features and advantages of the present invention will be further described with reference to the accompanying drawings, in conjunction with the embodiments.
Detailed Description
It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Referring to fig. 1, fig. 1 is a schematic device structure of a hardware running environment according to an embodiment of the present invention.
The device of the embodiment of the invention can be a PC or a server device.
As shown in fig. 1, the apparatus may include: a processor 1001, such as a CPU, a network interface 1004, a user interface 1003, a memory 1005, a communication bus 1002. Wherein the communication bus 1002 is used to enable connected communication between these components. The user interface 1003 may include a Display, an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may further include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a wireless interface (e.g., WI-FI interface). The memory 1005 may be a high-speed RAM memory or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also optionally be a storage device separate from the processor 1001 described above.
It will be appreciated by those skilled in the art that the device structure shown in fig. 1 is not limiting of the device and may include more or fewer components than shown, or may combine certain components, or a different arrangement of components.
As shown in fig. 1, an operating system, a network communication module, a user interface module, and an agricultural machinery monitoring control program may be included in the memory 1005 as one type of computer storage medium.
The operating system is a program for managing and controlling the portable storage equipment and the software resources, and supports the operation of a network communication module, a user interface module, an agricultural machinery monitoring control program and other programs or software; the network communication module is used to manage and control the network interface 1002; the user interface module is used to manage and control the user interface 1003.
In the storage device shown in fig. 1, the storage device invokes an agricultural machinery monitoring control program stored in a memory 1005 through a processor 1001, and performs operations in various embodiments of the agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform described below.
Based on the hardware structure, the embodiment of the intelligent agricultural machine monitoring control method based on the digital twin platform is provided.
Referring to fig. 2, fig. 2 is a schematic flow chart of a first embodiment of an agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform according to the present invention, the method includes:
step S10, when a job instruction is received, determining a target agricultural machine according to the job instruction;
step S20, acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters;
and step S30, controlling the target agricultural machine to perform work based on the work information and the work path.
The agricultural machinery monitoring control method of the intelligent agriculture based on the digital twin platform is applied to an agricultural machinery monitoring control system of the intelligent agriculture based on the digital twin platform, and it can be understood that the agricultural machinery monitoring control system of the intelligent agriculture based on the digital twin platform comprises an artificial intelligent Internet of things PaaS platform and an artificial intelligent digital twin DaaS platform, the artificial intelligent Internet of things PaaS platform is connected with an agricultural machinery and is responsible for collecting operation parameters and operation data of the agricultural machinery, and the artificial intelligent digital twin DaaS platform is responsible for processing the data collected by the artificial intelligent Internet of things PaaS platform; for convenience of description, an agricultural machinery monitoring control system based on intelligent agriculture of a digital twin platform is taken as an example for illustration; when an operation instruction is received, an agricultural machine monitoring control system of intelligent agriculture based on the digital twin platform determines a target agricultural machine according to the operation instruction; the intelligent agricultural machine monitoring control system based on the digital twin platform acquires operation information corresponding to the operation instruction and operation parameters of the target agricultural machine through the artificial intelligent Internet of things PaaS platform, determines a target operation area according to the operation information through the artificial intelligent digital twin DaaS platform, and determines the operation coverage width of the target agricultural machine according to the operation parameters; the intelligent agricultural machine monitoring control system based on the digital twin platform calculates the total area of a target operation area through the artificial intelligent digital twin DaaS platform, and determines an operation path based on the total area and the operation coverage width; an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform determines target operation content and target operation duration according to operation information through an artificial intelligent Internet of things PaaS platform, and acquires historical operation data of the target operation content; the intelligent agricultural machine monitoring control system based on the digital twin platform determines the current working parameters of the target agricultural machine according to the historical working data and the target working time length through the artificial intelligent digital twin DaaS platform, and controls the target agricultural machine to work according to the current working parameters and the working path.
It should be noted that the artificial intelligent digital twin DaaS platform comprises a service middle station and a data middle station which are connected with each other; the data center is used for collecting, calculating, storing and processing the data collected in the DaaS mode, and the formed standard data is stored on one hand and transmitted to the service center on the other hand; the business center is used for forming a model and a product aiming at the industry application by combining standard data transmitted by the data center with the industry application, so that a user can quickly package the business product based on the business center. The artificial intelligent Internet of things PaaS platform comprises AI edge calculation, a digital chip, edge storage calculation and a module technology, and the invention mainly utilizes the artificial intelligent Internet of things PaaS platform to acquire data and transmit the acquired data.
According to the intelligent agriculture agricultural machinery monitoring control method based on the digital twin platform, when an operation instruction is received, a target agricultural machinery is determined according to the operation instruction; acquiring operation information corresponding to the operation instruction and operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters; controlling a target agricultural machine to perform operation based on the operation information and the operation path; according to the invention, the operation path of the target agricultural machine is determined based on the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machine, and the target agricultural machine is controlled to operate based on the operation information and the operation path, so that the target agricultural machine is ensured to operate based on the operation path, repeated operation on a certain position is avoided, and the operation efficiency of the agricultural machine is improved.
The following will explain each step in detail:
step S10, when a job instruction is received, determining a target agricultural machine according to the job instruction;
in this embodiment, the agricultural machine monitoring control system of the intelligent agriculture based on the digital twin platform includes a man-machine interaction terminal, and related operators can input corresponding operation instructions to the agricultural machine monitoring control system of the intelligent agriculture based on the digital twin platform through the man-machine interaction terminal, and when the agricultural machine monitoring control system of the intelligent agriculture based on the digital twin platform receives the operation instructions, the operation instructions are analyzed to determine the corresponding operation type, and an agricultural machine capable of executing the operation type is selected as a target agricultural machine according to the operation type. Note that the job types include: subsoiling soil preparation operation, sprinkling and fertilizing operation, seeding operation, harvesting operation and the like, and different operation types correspond to different agricultural machinery.
Further, an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform needs to determine whether an idle agricultural machinery capable of executing the operation type exists currently before determining a target agricultural machinery, and if so, the target agricultural machinery is directly determined; if not, the job instruction is added into the waiting queue, and when the idle agricultural machinery is waiting, the allocation is performed.
Further, the intelligent agricultural machine monitoring control system based on the digital twin platform can determine the corresponding operation area according to the operation instruction before determining the target agricultural machine, and determine the corresponding target agricultural machine according to the operation area, namely when the operation area is large, the agricultural machine with large coverage width of single operation is selected as the target agricultural machine, so that the operation efficiency of the agricultural machine is improved. The corresponding operation standard can be determined according to the operation instruction, and the corresponding target agricultural machine can be determined according to the operation standard, for example: when the deep scarification soil preparation operation is needed, the operation standard is 13 cm in depth, and at the moment, the agricultural machinery with the depth exceeding 13 cm is needed to be selected as a target agricultural machinery, so that the standard rate of the agricultural machinery operation is improved.
Step S20, acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters;
in this embodiment, after determining a target agricultural machine, the agricultural machine monitoring control system for intelligent agriculture based on the digital twin platform obtains operation information corresponding to an operation instruction and operation parameters of the target agricultural machine through the artificial intelligent internet of things PaaS platform, sends the operation information operation parameters to the artificial intelligent digital twin DaaS platform through the artificial intelligent internet of things PaaS platform, and determines an operation path according to the operation information and the operation parameters through the artificial intelligent digital twin DaaS platform.
Specifically, the step of determining the job path according to the job information and the job parameters includes:
step a, determining a target working area according to the working information, and determining the working coverage width of the target agricultural machine according to the working parameters;
in the step, an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform determines a target operation area according to operation information through an artificial intelligent internet of things PaaS platform, and determines the operation coverage width of a target agricultural machinery according to operation parameters; it will be appreciated that the job coverage width is the width of the land that can be treated simultaneously with each job of the target agricultural machine.
And b, calculating the total area of the target working area, and determining a working path based on the total area and the working coverage width.
In the step, the intelligent agricultural machine monitoring control system based on the digital twin platform further comprises a GPS high-precision positioning platform, after the target operation area is determined, the intelligent agricultural machine monitoring control system based on the digital twin platform acquires the longitude and latitude of the target operation area through the GPS high-precision positioning platform, further calculates the total area of the target operation area according to the longitude and latitude, and determines an operation path according to the total area of the target operation area and the operation coverage width of the target agricultural machine through the artificial intelligent digital twin DaaS platform; such as: the total area of the target working area is 100 square kilometers, the working coverage width of the target agricultural machine is 3 meters, the intelligent agricultural machine monitoring control system based on the digital twin platform can determine that the width of the working path is 3 meters, and a working path of the target agricultural machine with the width of 3 meters is generated on the target working area with the total area of 100 square kilometers, and the target agricultural machine advances along the target path to execute corresponding work.
Further, since the target operation area is usually a rectangular area, the target agricultural machine starts to operate from one side of the target operation area, needs to turn around to enter the target operation area again after the other side of the target operation area, and the operation time of the target agricultural machine can be wasted in the process of turning around, so that when the operation path is determined, the agricultural machine monitoring control system of intelligent agriculture based on the digital twin platform takes the longest side of the target operation area as the length of the operation path, the turning around times of the target agricultural machine are reduced, and the operation efficiency of the agricultural machine is improved. Such as: the target operation area is a rectangular area with the length of 500 meters and the width of 30 meters, the operation coverage width of the target agricultural machine is 3 meters, when the operation path is determined, the length of the longest side of the target operation area, namely 500 meters, is used as the length of the operation path, the operation coverage width of the target agricultural machine is 3 meters, and at the moment, the number of times of turning around the target agricultural machine in the operation process is only 9, so that the number of times of turning around the agricultural machine is obviously reduced, and the operation efficiency of the agricultural machine is improved.
And step S30, controlling the target agricultural machine to perform work based on the work information and the work path.
In this embodiment, the agricultural machinery monitoring control system of the smart agriculture based on the digital twin platform controls the target agricultural machinery to perform the operation based on the operation information and the operation path after determining the operation information and the operation path.
Specifically, step S30 includes:
step c, determining target job content and target job duration according to the job information, and acquiring historical job data of the target job content;
in the step, an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform determines target operation content and target operation duration according to operation information, and acquires historical operation data of the target operation content through an artificial intelligent Internet of things PaaS platform; the historical operation data includes various operation parameters of the agricultural machinery and the standard reaching rate of the operation.
And d, determining the current working parameters of the target agricultural machinery according to the historical working data and the target working time length, and controlling the target agricultural machinery to work according to the current working parameters and the working path.
In the step, an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform screens target historical operation data with the operation time similar to the target operation time according to the target operation time through an artificial intelligent digital twin DaaS platform, selects target historical operation data with the maximum operation standard reaching rate from the target historical operation data, acquires all operation parameters of the agricultural machinery, correspondingly adjusts all operation parameters of the target agricultural machinery according to all operation parameters of the agricultural machinery, further determines the current operation parameters of the target agricultural machinery, and controls the target agricultural machinery to operate according to the current operation parameters and the operation path.
Further, before the step of controlling the target agricultural machine to perform the operation according to the current working parameter and the operation path, the method includes:
step e, determining an operation starting point according to the operation path, and acquiring the current parking position of the target agricultural machine;
and f, determining a driving path of the target agricultural machine according to the operation starting point and the current parking position, and controlling the target agricultural machine to reach the operation starting point according to the driving path.
In the steps e to f, an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform acquires a current parking position of a target agricultural machinery through a GPS high-precision positioning platform, and determines a point of the operation path closest to the current parking position of the target agricultural machinery according to the current parking position of the target agricultural machinery, a target operation area and the operation path, and the point is used as an operation starting point of the operation path; the intelligent agricultural machine monitoring control system based on the digital twin platform calculates the shortest connecting line between the operation starting point and the current parking position through the GPS high-precision positioning platform, determines the connecting line as the running path of the target agricultural machine, controls the target agricultural machine to reach the operation starting point according to the running path so as to finish preparation before operation, and uses the shortest connecting line between the operation starting point and the current parking position as the running path of the target agricultural machine, so that the time for the target agricultural machine to move from the current parking position to the operation starting point is shortest, and the efficiency is improved.
Further, if an obstacle incapable of being traversed exists before the shortest connecting line between the operation starting point and the current parking position, determining the shortest path between the operation starting point and the current parking position as the running path of the target agricultural machine by combining the GPS high-precision positioning platform with the electronic map.
The intelligent agricultural machine monitoring control system based on the digital twin platform determines a target agricultural machine according to the operation instruction when the operation instruction is received; the intelligent agricultural machine monitoring control system based on the digital twin platform acquires operation information corresponding to the operation instruction and operation parameters of the target agricultural machine through the artificial intelligent Internet of things PaaS platform, determines a target operation area according to the operation information through the artificial intelligent digital twin DaaS platform, and determines the operation coverage width of the target agricultural machine according to the operation parameters; the intelligent agricultural machine monitoring control system based on the digital twin platform calculates the total area of a target operation area through the artificial intelligent digital twin DaaS platform, and determines an operation path based on the total area and the operation coverage width; an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform determines target operation content and target operation duration according to operation information through an artificial intelligent Internet of things PaaS platform, and acquires historical operation data of the target operation content; the intelligent agricultural machine monitoring control system based on the digital twin platform determines the current working parameters of the target agricultural machine according to the historical working data and the target working time length through the artificial intelligent digital twin DaaS platform, and controls the target agricultural machine to work according to the current working parameters and the working path. According to the invention, the operation path of the target agricultural machine is determined based on the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machine, and the target agricultural machine is controlled to operate based on the operation information and the operation path, so that the target agricultural machine is ensured to operate based on the operation path, repeated operation on a certain position is avoided, and the operation efficiency of the agricultural machine is improved.
Further, as shown in fig. 3, a first embodiment of the method for controlling agricultural machinery monitoring of the intelligent agriculture based on the digital twin platform of the present invention is provided, and a second embodiment of the method for controlling agricultural machinery monitoring of the intelligent agriculture based on the digital twin platform of the present invention is provided.
The second embodiment of the agricultural machinery monitoring control method of the intelligent agriculture based on the digital twin platform of the present invention is different from the first embodiment of the agricultural machinery monitoring control method of the intelligent agriculture based on the digital twin platform in that after step S30, it includes:
step S40, determining standard operation data according to the operation information, and acquiring actual operation data of the target agricultural machinery according to a preset time interval;
s50, comparing the standard operation data with the actual operation data;
step S60, if the difference value between the standard operation data and the actual operation data is smaller than a preset difference value threshold value, not adjusting the current working parameters of the target agricultural machinery, and controlling the target agricultural machinery to operate based on the current working parameters;
and step S70, if the difference value between the standard operation data and the actual operation data is not smaller than the preset difference value threshold value, adjusting the current working parameter according to the difference value, and controlling the target agricultural machine to operate based on the adjusted current working parameter.
In the embodiment, in the process of operating the target agricultural machinery, the agricultural machinery monitoring control system of intelligent agriculture based on the digital twin platform determines standard operation data according to operation information, and acquires actual operation data of the target agricultural machinery through an artificial intelligent Internet of things PaaS platform according to a preset time interval; calculating a difference value between standard operation data and actual operation data through an artificial intelligent digital twin DaaS platform, comparing the difference value with a preset difference value threshold, if the difference value between the standard operation data and the actual operation data is smaller than the preset difference value threshold, not adjusting the current working parameters of the target agricultural machinery, and controlling the target agricultural machinery to operate based on the current working parameters; and if the difference value between the standard operation data and the actual operation data is not smaller than the preset difference value threshold value, adjusting the current working parameter according to the difference value, and controlling the target agricultural machine to operate based on the adjusted current working parameter.
In a feasible embodiment, the target agricultural machine is a deep scarification soil preparation agricultural machine, the preset difference threshold value is 0.5 cm, the standard operation data is that the deep scarification soil preparation standard depth is 13 cm, the intelligent agricultural machine monitoring control system based on the digital twin platform obtains the deep scarification soil preparation actual depth of the deep scarification soil preparation agricultural machine through the artificial intelligent Internet of things PaaS platform according to the preset time interval, calculates the difference value of the deep scarification soil preparation standard depth and the deep scarification soil preparation actual depth through the artificial intelligent digital twin DaaS platform, compares the difference value with the preset difference value threshold value, and does not adjust the current working parameter of the target agricultural machine if the difference value is smaller than the preset difference value threshold value, namely the deep scarification soil preparation actual depth is between 12.5 cm and 13.5 cm, and controls the target agricultural machine to operate based on the current working parameter; if the difference value is not smaller than a preset difference value threshold value, namely the actual depth of the subsoiling and soil preparation is not between 12.5 cm and 13.5 cm, the current working parameters are adjusted according to the difference value, so that the actual depth of the subsoiling and soil preparation agricultural machinery is between 12.5 cm and 13.5 cm, and then the target agricultural machinery is controlled to operate based on the adjusted current working parameters.
According to the intelligent agriculture agricultural machinery monitoring control system based on the digital twin platform, standard operation data and actual operation data are compared, and if the difference between the actual operation data and the standard operation data is determined to be larger than the preset difference threshold, current operation parameters of the agricultural machinery are adjusted, so that the actual operation data is close to the standard operation data, and the operation standard rate of the agricultural machinery is improved.
Further, as shown in fig. 4, the first embodiment and the second implementation of the agricultural machinery monitoring control method based on the intelligent agriculture based on the digital twin platform of the present invention propose a third embodiment of the agricultural machinery monitoring control method based on the intelligent agriculture based on the digital twin platform of the present invention.
The third embodiment of the agricultural machinery monitoring control method of the intelligent agriculture based on the digital twin platform of the present invention is different from the first embodiment and the second embodiment of the agricultural machinery monitoring control method of the intelligent agriculture based on the digital twin platform in that after step S30, further includes:
step S80, acquiring a current operation position of the target agricultural machine, and determining a current advancing direction of the target agricultural machine according to the current operation position;
in the embodiment, in the process of operating the target agricultural machine, the intelligent agricultural machine monitoring control system based on the digital twin platform acquires the current operation position of the target agricultural machine in the target operation area through the GPS high-precision positioning platform, and determines the current advancing direction of the target agricultural machine based on the current operation position. It will be appreciated that during operation, the current direction of travel of the target agricultural machine may or may not coincide with the work path and may include an angle.
Step S90, calculating an included angle between the current advancing direction and the operation path, and calculating a distance between the current operation position and the operation path;
in the embodiment, an agricultural machinery monitoring control system of intelligent agriculture based on a digital twin platform calculates an included angle between a current advancing direction and a working path through a GPS high-precision positioning platform, and calculates a distance between a current working position and the working path.
Step S100, determining whether to adjust the current advancing direction based on the included angle and the distance.
In this embodiment, the agricultural machinery monitoring control system of intelligent agriculture based on the digital twin platform compares the included angle with a preset included angle threshold value through the artificial intelligent digital twin DaaS platform, compares the distance with a preset distance threshold value, and determines whether to adjust the current advancing direction of the target agricultural machinery according to the comparison result.
Specifically, step S100 includes:
step g, comparing the included angle with a preset included angle threshold;
step h, if the included angle is larger than the preset included angle threshold, adjusting the current advancing direction so as to enable the target agricultural machine to keep advancing in the working path;
Step i, if the included angle is not larger than the preset included angle threshold, comparing the distance with a preset distance threshold;
j, if the distance is smaller than the preset distance threshold, not adjusting the current advancing direction so as to advance the target agricultural machine based on the current advancing direction;
and step k, if the distance is not smaller than the preset distance threshold, adjusting the current advancing direction so as to enable the target agricultural machine to keep advancing in the working path.
In the steps g to k, comparing the included angle with a preset included angle threshold value through an artificial intelligent digital twin DaaS platform by an intelligent agricultural machine monitoring control system based on the digital twin platform, if the included angle is larger than the preset included angle threshold value, indicating that the target agricultural machine deviates from the working path, and adjusting the current advancing direction of the target agricultural machine so as to enable the target agricultural machine to advance in the working path; if the included angle is not larger than a preset included angle threshold, comparing the distance with a preset distance threshold through an artificial intelligent digital twin DaaS platform by an intelligent agricultural machine monitoring control system of the digital twin platform, and if the distance is smaller than the preset distance threshold, indicating that the target agricultural machine does not deviate from the operation path and not adjusting the current advancing direction of the target agricultural machine so as to advance the target agricultural machine based on the current advancing direction; and if the distance is not smaller than the preset distance threshold value, indicating that the target agricultural machine deviates from the working path, and adjusting the current advancing direction of the target agricultural machine so as to keep the target agricultural machine advancing in the working path.
According to the intelligent agricultural machine monitoring control system based on the digital twin platform, whether the target agricultural machine deviates from the operation path or not is determined through the included angle between the current advancing direction of the target agricultural machine and the operation path and the distance between the current operation position of the target agricultural machine and the operation path, if so, adjustment is carried out, the target agricultural machine is ensured to advance on the operation path, repeated operation of the target agricultural machine on a certain position is avoided, the operation efficiency of the agricultural machine is improved, operation confusion caused by deviation of the agricultural machine from the operation path is avoided, and the standard reaching rate of operation of the agricultural machine is improved.
As shown in fig. 5, the invention further provides an agricultural machinery monitoring control device of intelligent agriculture based on the digital twin platform. The invention relates to an agricultural machinery monitoring control device based on digital twin platform for intelligent agriculture, which comprises:
a determining module 101, configured to determine, when a job instruction is received, a target agricultural machine according to the job instruction;
the acquiring module 102 is configured to acquire job information corresponding to the job instruction and a job parameter of the target agricultural machine, and determine a job path according to the job information and the job parameter;
and the control module 103 is used for controlling the target agricultural machine to perform work based on the work information and the work path.
Further, the obtaining module further includes a calculating module, where the calculating module is configured to:
determining a target working area according to the working information, and determining the working coverage width of the target agricultural machine according to the working parameters;
a total area of the target job area is calculated, and a job path is determined based on the total area and the job coverage width.
Further, the control module is further configured to:
determining target job content and target job duration according to the job information, and acquiring historical job data of the target job content;
and determining the current working parameters of the target agricultural machinery according to the historical working data and the target working time length, and controlling the target agricultural machinery to carry out the operation according to the current working parameters and the working path.
Further, the control module is further configured to:
determining an operation starting point according to the operation path, and acquiring the current parking position of the target agricultural machine;
and determining a running path of the target agricultural machine according to the operation starting point and the current parking position, and controlling the target agricultural machine to reach the operation starting point according to the running path.
Further, the control module is further configured to:
determining standard operation data according to the operation information, and acquiring actual operation data of the target agricultural machinery according to a preset time interval;
comparing the standard operation data with the actual operation data;
if the difference value between the standard operation data and the actual operation data is smaller than a preset difference value threshold, not adjusting the current working parameters of the target agricultural machinery, and controlling the target agricultural machinery to operate based on the current working parameters;
and if the difference value between the standard operation data and the actual operation data is not smaller than the preset difference value threshold, adjusting the current working parameter according to the difference value, and controlling the target agricultural machine to operate based on the adjusted current working parameter.
Further, the control module is further configured to:
acquiring a current operation position of the target agricultural machine, and determining a current advancing direction of the target agricultural machine according to the current operation position;
calculating an included angle between the current advancing direction and the working path, and calculating a distance between the current working position and the working path;
And determining whether to adjust the current advancing direction based on the included angle and the distance.
Further, the control module further includes an adjustment module further configured to:
comparing the included angle with a preset included angle threshold value;
if the included angle is larger than the preset included angle threshold, the current advancing direction is adjusted so that the target agricultural machine keeps advancing in the working path;
if the included angle is not larger than the preset included angle threshold, comparing the distance with a preset distance threshold;
if the distance is smaller than the preset distance threshold, not adjusting the current advancing direction so that the target agricultural machine advances based on the current advancing direction;
and if the distance is not smaller than the preset distance threshold, adjusting the current advancing direction so as to enable the target agricultural machine to keep advancing in the working path.
The invention further provides an agricultural machinery monitoring control system based on the digital twin platform.
An agricultural machinery monitoring control system of intelligent agriculture based on digital twin platform includes: the intelligent agricultural machine monitoring control method based on the digital twin platform comprises the steps of a memory, a processor and an agricultural machine monitoring control program which is stored in the memory and can run on the processor, wherein the agricultural machine monitoring control program is executed by the processor.
The method implemented when the agricultural machinery monitoring control program running on the processor is executed may refer to various embodiments of the agricultural machinery monitoring control method for intelligent agriculture based on a digital twin platform according to the present invention, which are not described herein.
The invention also provides a computer readable storage medium.
The computer readable storage medium stores an agricultural machinery monitoring control program which, when executed by a processor, implements the steps of the agricultural machinery monitoring control method of intelligent agriculture based on the digital twin platform.
The method implemented when the agricultural machinery monitoring control program running on the processor is executed may refer to various embodiments of the agricultural machinery monitoring control method for intelligent agriculture based on a digital twin platform according to the present invention, which are not described herein.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article, or system that comprises the element.
The foregoing embodiment numbers of the present invention are merely for the purpose of description, and do not represent the advantages or disadvantages of the embodiments.
From the above description of the embodiments, it will be clear to those skilled in the art that the above-described embodiment method may be implemented by means of software plus a necessary general hardware platform, but of course may also be implemented by means of hardware, but in many cases the former is a preferred embodiment. Based on such understanding, the technical solution of the present invention may be embodied essentially or in a part contributing to the prior art in the form of a software product stored in a storage medium (e.g. ROM/RAM, magnetic disk, optical disk) as described above, comprising instructions for causing a terminal device (which may be a mobile phone, a computer, a server, or a network device, etc.) to perform the method according to the embodiments of the present invention.
The foregoing description is only of the preferred embodiments of the present invention, and is not intended to limit the scope of the invention, but rather is intended to cover any equivalents of the structures or equivalent processes disclosed herein, or any application, directly or indirectly, in the field of other related technology.
Claims (10)
1. The agricultural machinery monitoring control method of the intelligent agriculture based on the digital twin platform is characterized by comprising the following steps of:
when a job instruction is received, determining a target agricultural machine according to the job instruction;
acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machinery, and determining an operation path according to the operation information and the operation parameters;
and controlling the target agricultural machine to operate based on the operation information and the operation path.
2. The agricultural machinery monitoring control method of a digital twin platform based intelligent agriculture of claim 1, wherein the step of determining a working path based on the working information and the working parameters comprises:
determining a target working area according to the working information, and determining the working coverage width of the target agricultural machine according to the working parameters;
a total area of the target job area is calculated, and a job path is determined based on the total area and the job coverage width.
3. The agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform as defined in claim 1, wherein the step of controlling the target agricultural machinery to perform an operation based on the operation information and the operation path comprises:
Determining target job content and target job duration according to the job information, and acquiring historical job data of the target job content;
and determining the current working parameters of the target agricultural machinery according to the historical working data and the target working time length, and controlling the target agricultural machinery to carry out the operation according to the current working parameters and the working path.
4. A method of agricultural machinery monitoring and controlling for intelligent agriculture based on a digital twin platform as defined in claim 3, wherein prior to the step of controlling the target agricultural machinery to operate based on the current operating parameters and the operating path, comprising:
determining an operation starting point according to the operation path, and acquiring the current parking position of the target agricultural machine;
and determining a running path of the target agricultural machine according to the operation starting point and the current parking position, and controlling the target agricultural machine to reach the operation starting point according to the running path.
5. The agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform as defined in claim 1, wherein after the step of controlling the target agricultural machinery to perform an operation based on the operation information and the operation path, it comprises:
Determining standard operation data according to the operation information, and acquiring actual operation data of the target agricultural machinery according to a preset time interval;
comparing the standard operation data with the actual operation data;
if the difference value between the standard operation data and the actual operation data is smaller than a preset difference value threshold, not adjusting the current working parameters of the target agricultural machinery, and controlling the target agricultural machinery to operate based on the current working parameters;
and if the difference value between the standard operation data and the actual operation data is not smaller than the preset difference value threshold, adjusting the current working parameter according to the difference value, and controlling the target agricultural machine to operate based on the adjusted current working parameter.
6. The agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform as defined in claim 1, wherein after the step of controlling the target agricultural machinery to perform the operation based on the operation information and the operation path, further comprising:
acquiring a current operation position of the target agricultural machine, and determining a current advancing direction of the target agricultural machine according to the current operation position;
Calculating an included angle between the current advancing direction and the working path, and calculating a distance between the current working position and the working path;
and determining whether to adjust the current advancing direction based on the included angle and the distance.
7. The agricultural machinery monitoring control method of intelligent agriculture based on a digital twin platform as defined in claim 6, wherein the step of determining whether to adjust the current heading based on the included angle and the distance comprises:
comparing the included angle with a preset included angle threshold value;
if the included angle is larger than the preset included angle threshold, the current advancing direction is adjusted so that the target agricultural machine keeps advancing in the working path;
if the included angle is not larger than the preset included angle threshold, comparing the distance with a preset distance threshold;
if the distance is smaller than the preset distance threshold, not adjusting the current advancing direction so that the target agricultural machine advances based on the current advancing direction;
and if the distance is not smaller than the preset distance threshold, adjusting the current advancing direction so as to enable the target agricultural machine to keep advancing in the working path.
8. An agricultural machinery monitoring control device of wisdom agriculture based on digital twin platform, its characterized in that, agricultural machinery monitoring control device of wisdom agriculture based on digital twin platform includes:
the determining module is used for determining a target agricultural machine according to the operation instruction when the operation instruction is received;
the acquisition module is used for acquiring the operation information corresponding to the operation instruction and the operation parameters of the target agricultural machine and determining an operation path according to the operation information and the operation parameters;
and the control module is used for controlling the target agricultural machine to operate based on the operation information and the operation path.
9. An agricultural machinery monitoring control system of intelligent agriculture based on digital twin platform, its characterized in that, agricultural machinery monitoring control system of intelligent agriculture based on digital twin platform includes: a memory, a processor and an agricultural machinery monitoring control program stored on the memory and executable on the processor, which when executed by the processor implements the steps of the digital twin platform based intelligent agriculture agricultural machinery monitoring control method of any one of claims 1 to 7.
10. A computer-readable storage medium, wherein an agricultural machinery monitoring control program is stored on the computer-readable storage medium, and the agricultural machinery monitoring control program, when executed by a processor, implements the steps of the agricultural machinery monitoring control method of the digital twin platform-based smart agriculture of any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310278616.4A CN116414129A (en) | 2023-03-21 | 2023-03-21 | Agricultural machinery monitoring control method and system for intelligent agriculture based on digital twin platform |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310278616.4A CN116414129A (en) | 2023-03-21 | 2023-03-21 | Agricultural machinery monitoring control method and system for intelligent agriculture based on digital twin platform |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN116414129A true CN116414129A (en) | 2023-07-11 |
Family
ID=87052549
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310278616.4A Pending CN116414129A (en) | 2023-03-21 | 2023-03-21 | Agricultural machinery monitoring control method and system for intelligent agriculture based on digital twin platform |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116414129A (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116738766A (en) * | 2023-08-11 | 2023-09-12 | 安徽金海迪尔信息技术有限责任公司 | Intelligent agriculture online industrialization service system based on digital twinning |
-
2023
- 2023-03-21 CN CN202310278616.4A patent/CN116414129A/en active Pending
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116738766A (en) * | 2023-08-11 | 2023-09-12 | 安徽金海迪尔信息技术有限责任公司 | Intelligent agriculture online industrialization service system based on digital twinning |
| CN116738766B (en) * | 2023-08-11 | 2023-10-13 | 安徽金海迪尔信息技术有限责任公司 | Intelligent agriculture online industrialization service system based on digital twinning |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10912247B2 (en) | Machine guidance for optimal working direction of travel | |
| CN107544548B (en) | Method and device for controlling operation of unmanned aerial vehicle and unmanned aerial vehicle | |
| US11954743B2 (en) | Harvest logistics | |
| CN109634285B (en) | Mowing robot and control method thereof | |
| US20180139896A1 (en) | Robotic vehicle with adjustable operating area | |
| CN109491397B (en) | Mowing robot and mowing area defining method thereof | |
| CN116414129A (en) | Agricultural machinery monitoring control method and system for intelligent agriculture based on digital twin platform | |
| CN106483975A (en) | Determine the method and device in unmanned plane course line | |
| CN109062171B (en) | Unmanned aerial vehicle plant protection operation control method, system, device and storage medium | |
| CN109189062A (en) | Form the method for lawn pattern and the mowing system using it | |
| CN111753388B (en) | Spraying control method, spraying control device, electronic equipment and computer-readable storage medium | |
| WO2022095040A1 (en) | Method and apparatus for planning spraying route for unmanned aerial vehicle | |
| CN111338381A (en) | Unmanned aerial vehicle operation control method and device, remote controller and storage medium | |
| CN111615647A (en) | Position estimation device, moving object, position estimation method, and program | |
| CN111504297B (en) | Road network-free navigation operation method and device and navigation equipment | |
| CN116429129A (en) | Method for generating operation map of self-mobile device, control terminal and storage medium | |
| CN106296866A (en) | A kind of system and method obtaining equipment availability cost information | |
| CN114547227A (en) | Ant colony and A-Star algorithm parallel grid map path planning method | |
| CN112381663B (en) | Variable job processing method, device, platform and storage medium | |
| CN113870310A (en) | Target tracking method, device and storage medium based on unmanned aerial vehicle | |
| CN108990500B (en) | Method, device and system for intelligently adding fertilizer to fertilizer dissolving tank in pipeline fertilizing system | |
| CN112528506A (en) | Method and device for determining working dosage, unmanned equipment and storage medium | |
| KR20220020532A (en) | Apparatus for managing earth of smart farms in open field by analysis of earth in real time | |
| CN211857291U (en) | Plant protection operating system based on unmanned aerial vehicle dotting | |
| CN111504319A (en) | Automatic driving control method and system based on agricultural unmanned aerial vehicle |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |