CN113642990A - Agricultural machinery intelligent management and scheduling system and method based on cloud edge cooperation - Google Patents
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Abstract
The invention discloses an agricultural machinery intelligent management and scheduling system and method based on cloud edge cooperation. And the data which is insensitive to time delay, has small capacity and needs to be stored in the history record is uploaded to a cloud platform for processing and storage. For the scheduling of a plurality of job orders, the invention aims to minimize the agricultural scheduling cost of each job order and determines a scheduling scheme with optimal cost by considering the priority order of the orders. The invention can improve the agricultural machinery scheduling efficiency, enhance the real-time performance of management and reduce the agricultural machinery scheduling cost.
Description
Technical Field
The invention belongs to the field of intelligent agriculture, and particularly relates to an agricultural machinery intelligent management and scheduling system and method based on cloud edge cooperation
Background
With the rapid development of agricultural mechanization, the application of agricultural machinery is becoming more and more popular, and agricultural mechanization can play an important role in agricultural production, especially grain production.
At present, agricultural machinery equipment is various in types, the requirement of agricultural production can be basically met, labor force is saved, and meanwhile efficiency of farmers is greatly improved.
However, agricultural machinery is expensive and needs scientific management, but traditional manpower is difficult to manage accurately in real time; the rural areas are vast and rare, and the traditional manpower for monitoring the agricultural mechanical equipment is time-consuming and labor-consuming; in busy farming season, traditional manpower scheduling is inefficient, can't give full play to the effect of every agricultural machinery equipment.
The existing intelligent management scheduling technology generally has the following problems:
(1) centralized processing, namely a scheduling strategy, operation scoring, agricultural machinery management and the like, is adopted and is carried out by the cloud platform, the computing and storage requirements of the cloud platform are too high, and single-point breakdown is easy to form.
(2) Management timeliness is low, a certain time is needed for transmitting data to a remote cloud platform from an agricultural machine terminal, and time is needed for transmitting high-capacity data such as videos and the like, so that management instantaneity cannot be guaranteed.
(3) The scheduling cost is high, and a simple scheduling strategy cannot meet the job orders with large number and complex priorities.
Disclosure of Invention
The purpose of the invention is as follows: the invention aims to solve the defects in the prior art and provides an agricultural machinery intelligent management and scheduling system and method based on cloud edge cooperation.
The technical scheme is as follows: the invention discloses an agricultural machinery intelligent management and scheduling system based on cloud edge cooperation, which comprises a cloud platform, a farmland information collection assembly, a vehicle-mounted terminal and an agricultural machinery management and scheduling system; the cloud platform is a central node, the vehicle-mounted terminal of the agricultural machinery is an edge node, and the vehicle-mounted terminal is connected with a vehicle-mounted information collection assembly and is also connected with a farmland information collection assembly through a vehicle-mounted WiFi module; the vehicle-mounted information collection assembly comprises a GPS positioning module, a camera module, an oil mass detection module and a speed detection module, and the modules are used for respectively collecting the position, operation video, oil mass and speed information of the agricultural machinery in real time; the farmland information collection assembly comprises a soil temperature and humidity acquisition module, a soil nitrogen phosphorus potassium acquisition module and a soil pH value acquisition module, and the temperature and humidity, nitrogen phosphorus potassium content and pH value of farmland soil are acquired in real time respectively through the modules; the vehicle-mounted terminal processes the tasks of delay sensitive and large-capacity data; the vehicle-mounted terminal receives an operation order sent by the cloud platform and displays the operation order on a display screen of the vehicle-mounted terminal to prompt an agricultural aircraft driver; the agricultural machine management and scheduling system comprises an agricultural machine management module and an agricultural machine scheduling module, wherein the agricultural machine management module is deployed at an agricultural machine terminal, the agricultural machine scheduling module is deployed at a cloud platform, the agricultural machine management module carries out real-time all-around management on agricultural machines according to data of a vehicle-mounted information collection assembly, and the agricultural machine scheduling module carries out scheduling on the agricultural machines based on a scheduling scheme according to agricultural machine data and operation orders received by the cloud platform; in the process of real-time all-around management and agricultural machinery scheduling of the agricultural machinery, for the tasks of delay sensitive and large-capacity data, the tasks are calculated by edge nodes close to a data source, namely terminals of the agricultural machinery, and are not uploaded to a remote central node cloud platform, so that the transmission time and cost are reduced, and the real-time performance is improved; and uploading the tasks which are insensitive to delay and the tasks which need to store data for a long time to a central node for processing, namely processing by the cloud platform.
Further, the delay sensitive tasks include real-time all-around management and field management of agricultural machinery. The high-volume data task includes a job quality score.
Furthermore, the real-time all-around management of the agricultural machinery comprises track management, oil mass management, speed management and agricultural machinery early warning; track management, oil quantity management and speed management, namely displaying the running track, the residual oil quantity and the current running speed of the agricultural machine on a terminal in real time; the agricultural machinery early warning means that once the position of the agricultural machinery is not in the designated operation area, or the oil quantity of the agricultural machinery is lower than a warning value, or the speed of the agricultural machinery is higher than the warning value, an alarm is triggered and displayed at an agricultural machinery terminal to remind an agricultural machinery driver.
Further, field management is soil property health detection promptly, and it is healthy to detect soil property through NPK sensor acquisition module and PH sensor acquisition module real-time detection, in case the problem appears and show at agricultural machinery terminal at once, reminds the agricultural machinery hand.
The agricultural machinery management module comprises a data processing module, an alarm module, a comprehensive grading module and a database module; the data processing module processes GPS data, operation videos, oil mass data and speed data, and provides temperature and humidity data, nitrogen and phosphorus potassium data and PH value data (including data for filtering and removing interference on GPS position data, oil mass data, speed data, temperature and humidity data, nitrogen and phosphorus potassium data and PH value data) to the alarm module, the comprehensive grading module and the database module for analysis, processing and short-time storage;
the alarm module compares the data processed by the data module with a preset warning value in the alarm module, and if any of the following conditions occurs, the alarm module gives an alarm to an agricultural machinery driver: the position of the agricultural machine is not in a specified operation area, the oil quantity of the agricultural machine is lower than a warning value, the running speed of the agricultural machine is higher than the warning value, the temperature and humidity data are higher than the warning value, the nitrogen, phosphorus and potassium data are higher than the warning value, and the PH value data are higher than the warning value;
the comprehensive scoring module comprehensively analyzes data collected by the vehicle-mounted information collecting assembly and the farmland information collecting assembly, determines comprehensive scoring of the agricultural machinery corresponding to the operation of the agricultural machinery at this time, and has the following scoring expression:
wherein S ismIs the operation score, Q, of agricultural machine mtIndicating temperature and humidity sensor score, QnIndicates the NPK sensor score, QpIndicates the pH sensor score, A indicates the area of the agricultural machine, T indicates the total time spent working, O indicates the total fuel consumption spent working, QCRepresenting the score of the job video, wherein alpha, beta, gamma, delta, lambda and theta are all weight coefficients;
the database module stores historical data and deletes the data periodically.
Further, after the operation order is completed, the task of scoring the operation quality is executed by the agricultural machinery terminal of the edge node, and after the operation score is obtained, the terminal sends the score to the cloud platform to serve as a reference of the subsequent agricultural machinery operation cost. The job orders comprise order priority, job types and job areas; the operation types comprise ploughing, sowing, transplanting, irrigating, harvesting and the like.
Furthermore, the agricultural machinery scheduling module comprises an order importing module, an agricultural machinery selecting module and an order dispatching module; the order importing module imports a current operation order; the agricultural machine selection module determines a target agricultural machine which corresponds to the operation type, is closest to the operation area at present and is in an idle state according to the current operation order; the order sending module sends the current operation order to a vehicle-mounted terminal corresponding to the selected target agricultural machine; the state switching module switches the target agricultural machine to a non-idle state after the order dispatching module finishes dispatching orders; and after receiving operation completion information sent by the vehicle-mounted terminal of the target agricultural machine, switching the agricultural machine to an idle state.
The invention also discloses a scheduling method for realizing the agricultural machinery intelligent management and scheduling system based on cloud edge cooperation, a cloud platform manager imports all operation orders through an order import module, an agricultural machinery selection module determines a target agricultural machinery according to an agricultural machinery scheduling scheme, and an operation order is dispatched to a target agricultural machinery terminal through a dispatching module, so that agricultural machinery scheduling with the minimum scheduling cost is realized; the process determines a preselected agricultural machinery scheduling scheme based on the target order information and the received agricultural machinery uploading data, and comprises the following steps: and determining a target agricultural machine based on the order priority, the operation type and the operation area corresponding to the target order and the operation score uploaded by the agricultural machine.
Further, the agricultural machinery scheduling scheme aims at minimizing the scheduling cost, and the function is as follows:
Zm＝ωSm (2)
c in formula (1) is the minimum scheduling cost; fmRepresenting the transportation cost of the agricultural machinery m units; dm,i,jRepresenting the distance of the agricultural machine m from the current position i to the farmland j; zmRepresents the cost of the operation of the agricultural machine m; m is the set of all agricultural machines; i is the set of all farm machinery current positions; j is the set of all farmland positions;
s in formula (2)mThe operation score of the agricultural machinery m is shown, and omega is a weight coefficient;
x in formula (3)m,i,jWhen the value of (1) is 1, the agricultural machine m is idle, and a task from the current position i to a farmland j can be executed; xm,i,jWhen the value of (b) is 0, it indicates that the farm machine m cannot perform a task from the current position i to the farm field j.
Further, the agricultural machinery scheduling method based on the minimum scheduling cost comprises agricultural machinery farmland initialization and specific scheduling, wherein the agricultural machinery farmland initialization process is as follows:
firstly, acquiring current positions i of all agricultural machines, acquiring positions j of all farmlands, acquiring scores of all agricultural machines and acquiring states of all agricultural machines;
establishing an order queue, and arranging from high to low according to the priority of the job order; orders with high priority are executed before orders with low priority;
establishing an agricultural machinery queue to ensure that the idle agricultural machinery is in the queue and the operating agricultural machinery is not in the queue;
establishing a waiting queue for storing orders which do not meet the scheduled condition, when a plurality of orders are executed, a job order with high priority and a job order with low priority which meets the scheduled condition, and selecting the job order which meets the scheduled condition instead of strictly according to the priority of the task.
Further, the specific scheduling process of the agricultural machinery scheduling method based on the minimum scheduling cost is as follows:
(1) selecting a head-of-line order from an order priority sequence obtained by order priority sorting operation, traversing an agricultural machinery sequence, searching whether an idle agricultural machinery corresponding to the operation type exists or not, if the idle agricultural machinery corresponding to the operation type exists, indicating that the order meets a scheduled condition, and if the idle agricultural machinery corresponding to the operation type does not exist, indicating that the order does not have the scheduled condition, entering a waiting queue;
(2) the job order is executed with the goal of obtaining a minimum scheduling cost. If a target agricultural machine is determined, deleting the order and the agricultural machine in the corresponding sequence, and after the operation order is distributed to the target agricultural machine, scheduling the agricultural machine to complete the operation of the order;
(3) and updating the order of the first round of operation, the current position of the agricultural machine, the grade of the agricultural machine and the state of the agricultural machine, and then returning to the first step until all orders are executed.
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) according to the invention, the edge cloud cooperative distributed system architecture with the agricultural machine terminal as the edge node and the cloud platform as the center node replaces the original single centralized architecture depending on the cloud platform, so that the problem that the centralized platform is easy to crash in a single point is solved, and the efficiency of the system is improved.
(2) The invention calculates all the delay sensitive tasks by the edge nodes, improves the real-time performance of the delay sensitive tasks and ensures the management timeliness.
(3) The invention takes the scheduling scheme with the optimal cost as the target, takes the priority order of the orders into consideration, and reduces the scheduling cost of the agricultural machinery.
Drawings
FIG. 1 is a system block diagram of one embodiment of the present invention;
FIG. 2 is a system block diagram of one embodiment of the present invention;
FIG. 3 is a schematic diagram of an agricultural machinery management and scheduling system in an embodiment of the present invention;
FIG. 4 is a flow chart of the operation of the agricultural machinery management module in the embodiment of the present invention;
FIG. 5 is a flowchart of the operation of the agricultural machinery scheduling module in the embodiment of the present invention.
Detailed Description
The technical solution of the present invention is described in detail below, but the scope of the present invention is not limited to the embodiments.
According to the agricultural machinery intelligent management and scheduling system and method based on cloud-edge cooperation, a cloud platform is used as a center node, a vehicle-mounted terminal of an agricultural machinery is used as an edge node, a farmland information collection component and a vehicle-mounted information collection component are responsible for collecting data of the agricultural machinery and the farmland, and for a task of delay sensitive and large-capacity data, operation is performed on the edge node close to a data source, namely the terminal of the agricultural machinery, and the operation is not uploaded to a remote cloud, so that the transmission time and cost are reduced, and the real-time performance is improved. And uploading the tasks which are insensitive to delay and need to store data for a long time to a central node, namely a cloud platform for processing. The vehicle-mounted information collection assembly comprises a GPS positioning module, a camera module, an oil mass detection module and a speed detection module, and the position, operation video, oil mass and speed of the agricultural machine are respectively collected in real time through the modules; the vehicle-mounted terminal is connected with the vehicle-mounted information collection assembly and is used for processing the tasks of delay sensitive and large-capacity data; receiving an operation order sent by the cloud platform, and displaying the operation order on a display screen of the vehicle-mounted terminal to prompt an agricultural driver; the farmland information collection assembly is connected with the vehicle-mounted terminal through the vehicle-mounted communication module and comprises a soil temperature and humidity acquisition module, a soil nitrogen phosphorus potassium acquisition module and a soil pH value acquisition module, and the temperature and humidity, the nitrogen phosphorus potassium content and the pH value of the soil are acquired in real time through the modules respectively; the agricultural machine management and scheduling system comprises an agricultural machine management module and an agricultural machine scheduling module, the agricultural machine management module is deployed at an agricultural machine terminal, the agricultural machine scheduling module is deployed at a cloud platform, the agricultural machine management module carries out real-time all-around management on agricultural machines according to data of the vehicle-mounted information collection assembly, and the agricultural machine scheduling module carries out scheduling on the agricultural machines based on a scheduling scheme according to agricultural machine data and operation orders received by the cloud platform.
Example 1:
as shown in fig. 1, an agricultural machinery intelligent management and scheduling system based on cloud-edge collaboration according to the embodiment includes a cloud platform 11, a vehicle-mounted terminal 12, a vehicle-mounted information collection component 13, and a farmland information collection component 14. The cloud platform 11 serves as a central node, the vehicle-mounted terminal 12 serves as an edge node, the vehicle-mounted information collection component 13 and the farmland information collection component 14 are used for collecting data of a data source, tasks sensitive to delay and large-volume data are calculated by the edge node, and tasks insensitive to delay and tasks needing to store data for a long time are calculated by the central node.
Example 2:
as shown in fig. 2, the present embodiment is based on embodiment 1. The agricultural machinery intelligent management and scheduling system and method based on cloud edge cooperation comprises a cloud platform part 21, a vehicle-mounted wireless communication module 22, a vehicle-mounted terminal 23, a vehicle-mounted WiFi module 24, a farmland information collection component 25 and a vehicle-mounted information collection component 26.
The farmland information collecting component 25 comprises a soil temperature and humidity collecting module 251, a soil nitrogen phosphorus potassium collecting module 252 and a soil pH value collecting module 253. The soil temperature and humidity acquisition module 251 uploads the temperature and humidity information of the soil to the vehicle-mounted terminal 23 through the vehicle-mounted WiFi module 24, and the vehicle-mounted terminal 23 performs filtering processing on the temperature and humidity information to obtain the accurate temperature and humidity of the soil; the soil nitrogen phosphorus potassium acquisition module 252 uploads the nitrogen phosphorus potassium information of the soil to the vehicle-mounted terminal 23 through the vehicle-mounted WiFi module 24, and the vehicle-mounted terminal 23 performs filtering processing on the nitrogen phosphorus potassium information to obtain accurate nitrogen phosphorus potassium content of the soil; the soil pH value acquisition module 253 uploads the pH value of the soil to the vehicle-mounted terminal 23 through the vehicle-mounted WiFi module 24, and the vehicle-mounted terminal 23 performs filtering processing on the soil to obtain the accurate soil pH value.
The vehicle-mounted information collection assembly 26 includes a GPS positioning module 261, a camera module 262, an oil amount detection module 263, and a speed detection module 264. The GPS positioning module 261 is connected with the vehicle-mounted terminal 23 through a USB interface, the position information of the agricultural machinery is uploaded to the vehicle-mounted terminal 23, and the vehicle-mounted terminal 23 performs filtering processing on GPS data to obtain accurate position data such as longitude and latitude; the camera module 262 is connected with the vehicle-mounted terminal 23 through a USB interface, agricultural machinery operation videos are uploaded to the vehicle-mounted terminal 23, and the vehicle-mounted terminal 23 compresses the videos; the oil quantity detection module 263 is connected with the vehicle-mounted terminal 23 through an RS485 interface, and uploads the oil quantity information of the agricultural machine to the vehicle-mounted terminal 23, and the height value of the residual oil quantity in the oil tank of the agricultural machine, which is measured by the ultrasonic oil quantity sensor, is converted into a specific oil quantity value; the speed detection module 264 is connected with the vehicle-mounted terminal 23 through a USB interface, agricultural machinery speed information is uploaded to the vehicle-mounted terminal 23, and the vehicle-mounted terminal 23 performs filtering processing on speed data to obtain an accurate speed value.
In practical application, an internet of things SIM card of a mobile operator is inserted into the vehicle-mounted wireless communication module 22, and the farmland information collection component 25 sends collected data to the vehicle-mounted terminal 23 through the vehicle-mounted WiFi module 24. The in-vehicle terminal 23 transmits a part of the data to the cloud platform 21 through the in-vehicle wireless communication module 22. When the cloud platform 21 carries out agricultural machinery scheduling, the work order is issued to the vehicle-mounted terminal 23 through the vehicle-mounted wireless communication module 22 and is displayed on the display screen.
Example 3:
as shown in fig. 3, the agricultural machinery management and scheduling system (based on the cloud platform) of the present embodiment includes an agricultural machinery management system 31 and an agricultural machinery scheduling system 32.
The agricultural machinery management system 31 comprises a data processing module 312, an alarm module 313, a comprehensive grading module 314 and a database module 315. The data processing module 312 is configured to process GPS data, job video, oil volume data, speed data, temperature and humidity data, nitrogen and phosphorus and potassium data, and PH value data (including data obtained by filtering and removing interference on GPS position data, oil volume data, speed data, temperature and humidity data, nitrogen and phosphorus and potassium data, and PH value data), and provide the data to the alarm module 313, the comprehensive scoring module 314, and the database module 315 for analysis, processing, and short-time storage; the alarm module 313 compares the data processed by the data module 312 with a preset warning value, and gives an alarm to the agricultural machinery staff if any of the following conditions occur: the position of the agricultural machine is not in a specified operation area, the oil quantity of the agricultural machine is lower than a warning value, the running speed of the agricultural machine is higher than the warning value, the temperature and humidity data are higher than the warning value, the nitrogen, phosphorus and potassium data are higher than the warning value, and the PH value data are higher than the warning value; the comprehensive grading module 314 comprehensively analyzes data collected by the vehicle-mounted information collecting component and the farmland information collecting component and determines the comprehensive grading of the agricultural machinery corresponding to the operation of the agricultural machinery at this time; the database module 313 stores historical data and deletes data periodically.
The agricultural machinery scheduling system 32 includes an order import module 322, an agricultural machinery determination module 323, and an order dispatch module 324. The cloud platform manager imports all orders through the order import module 322, the agricultural machinery selection module 323 determines a target agricultural machinery according to the scheduling scheme, and the order dispatching module 324 dispatches the orders to the target agricultural machinery terminal to achieve agricultural machinery scheduling.
As shown in fig. 4, the specific flow of agricultural machinery management in this embodiment is as follows:
step 41: processing all uploaded data including GPS data, oil mass data, operation video, speed, temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data of the agricultural machinery;
step 42: storing all processed data to a cloud database;
step 43: comparing the GPS position information of the agricultural machinery with the position of the operation area, and if the GPS position information is not in the operation area, executing the step 44; otherwise, go to step 45; comparing the oil quantity of the agricultural machine with the minimum oil quantity alarm value, and if the oil quantity is lower than the minimum alarm value, executing a step 44; otherwise, go to step 45; comparing the current speed of the agricultural machine with the maximum alert speed, and if the current speed is higher than the maximum alert speed, executing step 44; otherwise, go to step 45; comparing the current temperature and humidity data, nitrogen phosphorus potassium data and pH value data of the field with reasonable value intervals of the temperature, the humidity, the nitrogen phosphorus potassium and the pH value, and if the current temperature and humidity data, the nitrogen phosphorus potassium data and the pH value are in the reasonable value intervals, executing the step 45; otherwise, go to step 44;
step 44: sending an alarm to the agricultural machinery staff on a display screen of the terminal;
step 45: according to the processed GPS data, the oil mass data, the operation video, the speed, the temperature and humidity data, the nitrogen, phosphorus and potassium data and the PH value data, obtaining a comprehensive score of the operation after the operation is finished;
step 46: the data is stored to a local database.
As shown in fig. 5, the specific flow of agricultural machinery scheduling of this embodiment is as follows:
step 501: performing an initialization step;
step 502: judging whether the order alignment is empty or not; if it is empty, go to step 503; otherwise, go to step 504;
step 503 is executed: judging whether the waiting queue is empty or not; if it is empty, go to step 512; otherwise, go to step 504;
step 504: the previous step is 502, selecting the head order of the order queue; the previous step is 503, selecting the head order of the waiting queue;
step 505: judging whether the order meets the scheduled conditions, namely whether the agricultural machinery corresponding to the operation type is in an idle state or not; if yes, go to step 507; otherwise, go to step 506;
step 506: putting the job order into a waiting queue, and executing the step 502;
step 507: judging whether the waiting queue is empty or not; if it is empty, go to step 509; otherwise, go to step 508;
step 508: judging whether the priority of the head order of the waiting queue is higher than the priority of the current job order and whether the head order meets the scheduled condition; if yes, go to step 510; otherwise, go to step 509;
step 509: according to the positions of agricultural machines and farmland and the uploading of terminalsBusiness score, from formula
Zm＝ωSmDetermining a target agricultural machine with the lowest scheduling cost;
step 510: preferentially executing the head order in the waiting queue;
step 511: dispatching the order to a terminal of a target agricultural machine, deleting the order from the operation order, deleting the agricultural machine from an agricultural machine queue, updating a round of operation order, the current position of the agricultural machine, the grade of the agricultural machine and the state of the agricultural machine, and then executing step 502;
step 512: and (4) the order queue and the waiting queue are empty, which indicates that all orders are scheduled and ends.
Example (b):
the embodiment includes that if there are four job orders currently, the agricultural machinery needs to be scheduled. The four job orders are respectively (1, m)1,j1)(2,m2,j2)(3,m3,j3)(2,m3,j4) The three parameters respectively represent order priority, job type, and job area.
Firstly, system initialization is carried out, and all agricultural machine positions, farmland positions, agricultural machine operation scores and agricultural machine states are obtained. Establishing order queue according to order priority (3, m)3,j3)(2,m2,j2)(2,m3,j4)(1,m1,j1)}. Establishing an agricultural machinery queue which comprises all idle agricultural machinery, if the agricultural machinery queue is m1,1，m2,1，m2,2，m2,3}. A wait queue is established, with the wait queue empty.
Selecting a head order (3, m) from the order queue3,j3) Finding whether the agricultural machinery queue has the corresponding operation type m3Agricultural machinery of, m is not found3Agricultural machines of the type, this order entering the waiting queue { (3, m)3,j3) At this time, since the job order queue is not empty, the head of queue order (2, m) is selected2,j2)。
Three corresponding operation types m are found in the queue of agricultural machinery2Agricultural machinery m2,1,m2,2,m2,3，(m2,1Represents m2Type 1 agricultural machine) so as to order (2, m)2,j2) Meets the scheduled condition when the waiting queue is not empty but waits for the head order of the queue (3, m)3,j3) The scheduled condition is not satisfied, so the current order is still executed.
From m according to the cost formula2,1,m2,2,m2,3Determining an agricultural machine with the minimum cost for executing the current order, if m is m2,3Sending the order to m2,3The terminal of (1).
Delete (2, m) from order queue2,j2) Order, deleting m from queue of agricultural machinery2,3And updating a round of operation order, the current position of the agricultural machine, the grade of the agricultural machine and the state of the agricultural machine.
And continuously selecting a head order from the order queue to carry out agricultural machinery scheduling until the order sequence is empty.
Claims (10)
1. The utility model provides an agricultural machinery wisdom management and dispatch system based on cloud limit is cooperative which characterized in that: the agricultural machinery management and scheduling system comprises a cloud platform, a farmland information collection assembly, a vehicle-mounted terminal and an agricultural machinery management and scheduling system; the cloud platform is a central node, the vehicle-mounted terminal of the agricultural machinery is an edge node, and the vehicle-mounted terminal is connected with a vehicle-mounted information collection assembly and is also connected with a farmland information collection assembly through a vehicle-mounted WiFi module;
the vehicle-mounted information collection assembly comprises a GPS positioning module, a camera module, an oil mass detection module and a speed detection module, and the modules are used for respectively collecting the position, operation video, oil mass and speed information of the agricultural machinery in real time;
the farmland information collection assembly comprises a soil temperature and humidity acquisition module, a soil nitrogen phosphorus potassium acquisition module and a soil pH value acquisition module, and the temperature and humidity, nitrogen phosphorus potassium content and pH value of farmland soil are acquired in real time respectively through the modules;
the vehicle-mounted terminal processes the tasks of delay sensitive and large-capacity data; the vehicle-mounted terminal receives an operation order sent by the cloud platform and displays the operation order on a display screen of the vehicle-mounted terminal to prompt an agricultural aircraft driver;
the agricultural machine management and scheduling system comprises an agricultural machine management module and an agricultural machine scheduling module, wherein the agricultural machine management module is deployed at an agricultural machine terminal, the agricultural machine scheduling module is deployed at a cloud platform, the agricultural machine management module carries out real-time all-around management on agricultural machines according to data of a vehicle-mounted information collection assembly, and the agricultural machine scheduling module carries out scheduling on the agricultural machines based on a scheduling scheme according to agricultural machine data and operation orders received by the cloud platform;
in the process of real-time all-around management and agricultural machinery scheduling of the agricultural machinery, for the tasks of delay sensitive and large-capacity data, the tasks are calculated by edge nodes close to a data source and are not uploaded to a remote central node cloud platform; and uploading the tasks which are not sensitive to delay and the tasks which need to store data for a long time to a central node for processing.
2. The agricultural machinery intelligent management and scheduling system based on cloud edge coordination of claim 1, wherein: still include on-vehicle wireless communication module, on-vehicle wireless communication module adopts 5G mobile network to transmit the relevant data of agricultural machinery to the cloud platform, the hot spot that the farmland information collection subassembly produced through on-vehicle wiFi module links to each other with vehicle mounted terminal, transmits the farmland information of gathering for vehicle mounted terminal.
3. The agricultural machinery intelligent management and scheduling system based on cloud edge coordination of claim 1, wherein: the delay sensitive tasks comprise real-time all-around management and field management of agricultural machinery; the high-capacity data task comprises a job quality score;
the real-time all-around management of the agricultural machinery comprises track management, oil quantity management, speed management and agricultural machinery early warning; track management, oil quantity management and speed management, namely displaying the running track, the residual oil quantity and the current running speed of the agricultural machine on a terminal in real time; the agricultural machinery early warning means that once the position of the agricultural machinery is not in the designated operation area, or the oil quantity of the agricultural machinery is lower than a warning value, or the speed of the agricultural machinery is higher than the warning value, an alarm is triggered and displayed at an agricultural machinery terminal to remind an agricultural machinery driver;
the field management is soil property health detection promptly, and it is healthy to detect soil property through nitrogen phosphorus potassium sensor acquisition module and PH sensor acquisition module real-time detection, in case the problem appears and shows at the agricultural machinery terminal at once, reminds the agricultural machinery hand.
4. The agricultural machinery intelligent management and scheduling system based on cloud edge coordination of claim 1, wherein: the agricultural machinery management module comprises a data processing module, an alarm module, a comprehensive grading module and a database module;
the data processing module processes GPS data, operation videos, oil mass data and speed data, and provides the acquired temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data to the alarm module, the comprehensive grading module and the database module for analysis, processing and short-time storage;
the alarm module compares the data processed by the data module with a preset warning value in the alarm module, and if any of the following conditions occurs, the alarm module gives an alarm to an agricultural machinery driver: the position of the agricultural machine is not in a specified operation area, the oil quantity of the agricultural machine is lower than a warning value, the running speed of the agricultural machine is higher than the warning value, and the temperature and humidity data, the nitrogen, phosphorus and potassium data and the PH value data are not in a reasonable value interval;
the comprehensive scoring module comprehensively analyzes data collected by the vehicle-mounted information collecting assembly and the farmland information collecting assembly, determines comprehensive scoring of the agricultural machinery corresponding to the operation of the agricultural machinery at this time, and has the following scoring expression:
wherein S ismIs the operation score, Q, of agricultural machine mtIndicating temperature and humidity sensor score, QnIndicates the NPK sensor score, QpIndicates the pH sensor score, A indicates the area of the agricultural machine, T indicates the total time spent working, O indicates the total fuel consumption spent working, QCRepresenting the job video score, alpha, beta, gamma, delta, lambda, theta are all weightsA weight coefficient;
the database module stores historical data.
5. The agricultural machinery intelligent management and scheduling system based on cloud edge coordination of claim 1, wherein: the job orders comprise order priority, job types and job areas; after the operation order is completed, the agricultural machinery vehicle-mounted terminal of the edge node scores the operation quality of the operation order, and after the operation score is obtained, the vehicle-mounted terminal sends the score to the cloud platform to serve as a reference of the subsequent agricultural machinery operation cost.
6. The agricultural machinery intelligent management and scheduling system based on cloud edge coordination of claim 1, wherein: the agricultural machinery scheduling module comprises an order importing module, an agricultural machinery selecting module, an order dispatching module and a state switching module;
the order importing module imports a current operation order;
the agricultural machine selection module determines a target agricultural machine which corresponds to the operation type, is closest to the operation area at present and is in an idle state according to the current operation order;
the order sending module sends the current operation order to a vehicle-mounted terminal corresponding to the selected target agricultural machine;
the state switching module switches the target agricultural machine to a non-idle state after the order dispatching module finishes dispatching orders; and after receiving operation completion information sent by the vehicle-mounted terminal of the target agricultural machine, switching the agricultural machine to an idle state.
7. A scheduling method for realizing the intelligent agricultural machinery management and scheduling system based on cloud edge coordination of any one of claims 1 to 6 is characterized in that: the cloud platform manager imports all operation orders through the order import module, the agricultural machine selection module determines a target agricultural machine according to an agricultural machine scheduling scheme, and the operation orders are dispatched to a target agricultural machine terminal through the order dispatch module, so that agricultural machine scheduling with the minimum scheduling cost is realized;
the process determines a preselected agricultural machinery scheduling scheme based on the target order information and the received agricultural machinery uploading data, and comprises the following steps: and determining a target agricultural machine based on the order priority, the operation type and the operation area corresponding to the target order and the operation score uploaded by the agricultural machine.
8. The scheduling method of the intelligent agricultural machinery management and scheduling system based on cloud edge coordination as claimed in claim 7, wherein: the agricultural machinery scheduling scheme aims at minimizing the scheduling cost, and the function is as follows:
Zm＝ωSm (2)
c in formula (1) is the minimum scheduling cost; fmRepresenting the transportation cost of the agricultural machinery m units; dm,i,jRepresenting the distance of the agricultural machine m from the current position i to the farmland j; zmRepresents the cost of the operation of the agricultural machine m; m is the set of all agricultural machines; i is the set of all farm machinery current positions; j is the set of all farmland positions;
s in formula (2)mThe operation score of the agricultural machinery m is shown, and omega is a weight coefficient;
x in formula (3)m,i,jWhen the value of (1) is 1, the agricultural machine m is idle, and a task from the current position i to a farmland j can be executed; xm,i,jWhen the value of (b) is 0, it indicates that the farm machine m cannot perform a task from the current position i to the farm field j.
9. The scheduling method of the intelligent agricultural machinery management and scheduling system based on cloud edge coordination as claimed in claim 7, wherein: the agricultural machinery scheduling method based on the minimum scheduling cost comprises agricultural machinery farmland initialization and specific scheduling, wherein the agricultural machinery farmland initialization process is as follows:
firstly, acquiring current positions i of all agricultural machines, acquiring positions j of all farmlands, acquiring scores of all agricultural machines and acquiring states of all agricultural machines;
establishing an order queue, and arranging from high to low according to the priority of the job order; orders with high priority are executed before orders with low priority;
establishing an agricultural machinery queue to ensure that the idle agricultural machinery is in the queue and the operating agricultural machinery is not in the queue;
establishing a waiting queue for storing orders which do not meet the scheduled condition, when a plurality of orders are executed, a job order with high priority and a job order with low priority which meets the scheduled condition, and selecting the job order which meets the scheduled condition instead of strictly according to the priority of the task.
10. The scheduling method of the intelligent agricultural machinery management and scheduling system based on cloud edge coordination according to claim 9, wherein: the specific scheduling process of the agricultural machinery scheduling method based on the minimum scheduling cost is as follows:
(1) selecting a head-of-line order from an order priority sequence obtained by order priority sorting operation, traversing an agricultural machinery sequence, searching whether an idle agricultural machinery corresponding to the operation type exists or not, if the idle agricultural machinery corresponding to the operation type exists, indicating that the order meets a scheduled condition, and if the idle agricultural machinery corresponding to the operation type does not exist, indicating that the order does not have the scheduled condition, entering a waiting queue;
(2) the job order is executed with the goal of obtaining a minimum scheduling cost. If a target agricultural machine is determined, deleting the order and the agricultural machine in the corresponding sequence, and after the operation order is distributed to the target agricultural machine, scheduling the agricultural machine to complete the operation of the order;
(3) and updating the order of the first round of operation, the current position of the agricultural machine, the grade of the agricultural machine and the state of the agricultural machine, and then returning to the first step until all orders are executed.
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