CN113642990B - Cloud-edge cooperation-based intelligent management and scheduling system and method for agricultural machinery - Google Patents
Cloud-edge cooperation-based intelligent management and scheduling system and method for agricultural machinery Download PDFInfo
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- 239000002689 soil Substances 0.000 claims description 30
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Abstract
The invention discloses an intelligent management and scheduling system and method for an agricultural machine based on cloud-edge coordination. And the data which is insensitive to delay, has small capacity and needs to be stored in a history record are uploaded to a cloud platform for processing and storage. For scheduling of multiple job orders, the present invention aims to minimize the agricultural machine scheduling cost for each job order and determines a cost-optimal scheduling scheme taking into account the order priority. The invention can improve the dispatching efficiency of the agricultural machinery, enhance the real-time performance of management and reduce the dispatching cost of the agricultural machinery.
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 great development of agricultural mechanization, the application of agricultural machinery has become more and more popular, and agricultural mechanization can play an important role in agricultural production, particularly grain production.
At present, agricultural mechanical equipment is various in variety, can basically meet the demands of agricultural production, saves labor force and greatly improves the efficiency of farmers.
However, agricultural machinery equipment is expensive and needs scientific management, but traditional manpower is difficult to manage accurately in real time; the rural areas are wide and thin, and the traditional manual work is time-consuming and labor-consuming for supervising the agricultural mechanical equipment; when the farm is busy, the traditional manpower scheduling efficiency is low, and the function of each agricultural mechanical device cannot be fully exerted.
The following problems generally exist in the existing intelligent management scheduling technology:
(1) The centralized processing, namely the scheduling strategy, the job scoring, the agricultural machinery management and the like are all processed in a centralized way by the cloud platform, so that the calculation and storage requirements on the cloud platform are too high, and single-point crashes are easy to form.
(2) The management timeliness is low, a certain time is required for transmitting data from the agricultural machine terminal to the remote cloud platform, and more time is required for transmitting large-capacity data such as video, so that the real-time performance of management cannot be ensured.
(3) The scheduling cost is high, and a simple scheduling strategy cannot meet a large number of job orders with complex priorities.
Disclosure of Invention
The invention aims to: the invention aims to solve the defects in the prior art and provides an intelligent management and scheduling system and method for agricultural machinery based on cloud edge cooperation.
The technical scheme is as follows: the invention discloses an intelligent management and scheduling system of an agricultural machine based on cloud edge coordination, which comprises a cloud platform, a farmland information collection assembly, a vehicle-mounted terminal and the agricultural machine management and scheduling system; the cloud platform is a central node, the vehicle-mounted terminal of the agricultural machine is an edge node, the vehicle-mounted terminal is connected with a vehicle-mounted information collecting assembly, and the vehicle-mounted information collecting assembly is connected with the farmland information collecting assembly through a vehicle-mounted WiFi module; the vehicle-mounted information collection assembly comprises a GPS positioning module, a camera module, an oil quantity detection module and a speed detection module, and position, operation video, oil quantity and speed information of the agricultural machinery are respectively collected in real time through the modules; the farmland information collection assembly comprises a soil temperature and humidity collection module, a soil nitrogen, phosphorus and potassium collection module and a soil PH value collection module, and the temperature and humidity, the nitrogen, phosphorus and potassium content and the PH value of farmland soil are respectively collected in real time through the modules; the vehicle-mounted terminal processes tasks of delay sensitive and large-capacity data; the vehicle-mounted terminal receives the operation order sent by the cloud platform and displays the operation order on a display screen of the vehicle-mounted terminal so as to prompt an agricultural machine operator; 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 omnibearing management of the agricultural machine according to the data of the vehicle-mounted information collection assembly, and the agricultural machine scheduling module carries out scheduling of the agricultural machine based on a scheduling scheme according to the agricultural machine data and the job order accepted by the cloud platform; in the process of real-time omnibearing management and agricultural machinery scheduling of the agricultural machinery, for the tasks of delay sensitivity and large capacity data, edge nodes close to a data source, namely the terminals of the agricultural machinery, are operated, and are not uploaded to a remote central node cloud platform any more, so that the transmission time and cost are reduced, and the instantaneity 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 a cloud platform.
Further, the delay sensitive tasks include real-time omnibearing management and field management of agricultural machinery. The high volume data task includes a job quality score.
Further, the real-time omnibearing 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 are carried out, namely, the running track, the residual oil quantity and the current running speed of the agricultural machinery are displayed on the terminal in real time; and the early warning of the agricultural machinery, namely, the early warning is triggered once the position of the agricultural machinery is not in a 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, is displayed on an agricultural machinery terminal, and reminds an agricultural machinery hand.
Further, soil health detection is performed in field management, namely soil health is detected in real time through the nitrogen, phosphorus and potassium sensor acquisition module and the PH sensor acquisition module, and once a problem occurs, the soil health is immediately displayed on an agricultural machine terminal, so that an agricultural machine operator is reminded.
The agricultural machinery management module comprises a data processing module, an alarm module, a comprehensive scoring module and a database module; the data processing module processes GPS data, operation video, oil quantity data, speed data, temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data (including filtering and interference removing data on GPS position data, oil quantity data, speed data, temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data) and provides the data for the alarm module, the comprehensive scoring module and the database module to analyze, process and store in a short time;
the alarm module compares the data processed by the data module with a preset alarm value in the alarm module, and if any of the following conditions occurs, the alarm module gives an alarm to an agricultural machine hand: the agricultural machinery position is not in a specified operation area, the agricultural machinery oil quantity is lower than the warning value, the agricultural machinery running speed 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 the data acquired by the vehicle-mounted information collecting assembly and the farmland information collecting assembly, determines the comprehensive score of the agricultural machinery corresponding to the current operation of the agricultural machinery hand, and the scoring expression is as follows:
wherein S is m Is the job score of agricultural machinery m, Q t Represents the score of a temperature and humidity sensor, Q n Represents the score of the NPK sensor, Q p The PH sensor score is represented by A, the area of the agricultural machine is represented by A, T, the total time of the operation is represented by T, the total oil consumption of the operation is represented by O, and Q C Representing the video score of the operation, wherein alpha, beta, gamma, delta, lambda and theta are weight coefficients;
the database module stores historical data and periodically deletes the data.
Further, after the job order is completed, the task of scoring the job quality is executed by the agricultural machine terminal of the edge node, and after the job score is obtained, the terminal sends the score to the cloud platform as a reference of the operation cost of the subsequent agricultural machine. The job orders comprise order priority, job type and job area; the operation types comprise farmland, sowing, transplanting, irrigation, harvesting and the like.
Further, the agricultural machinery scheduling module comprises an order importing module, an agricultural machinery selecting module and a dispatching module; the order importing module imports a current operation order; the agricultural machinery selection module determines a target agricultural machinery which corresponds to the operation type, is nearest to the operation area and is in an idle state according to the current operation order; the dispatch 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 into a non-idle state after the dispatch module completes dispatch; and after the operation completion information sent by the vehicle-mounted terminal of the target agricultural machine is received, switching the agricultural machine into an idle state.
The invention also discloses a dispatching method for realizing the intelligent management and dispatching system of the agricultural machinery based on cloud edge coordination, wherein a cloud platform manager imports all the job orders through an order importing module, an agricultural machinery selecting module determines a target agricultural machinery according to an agricultural machinery dispatching scheme, and the job orders are dispatched to a target agricultural machinery terminal through a dispatching module, so that the agricultural machinery dispatching with the minimum dispatching cost is realized; the above process determines a preselected agricultural machine scheduling scheme based on the target order information and the received agricultural machine upload data, comprising: and determining a target agricultural machine based on the order priority, the job type and the job area corresponding to the target order and the job score uploaded by the agricultural machine.
Further, the agricultural machinery scheduling scheme aims at minimizing the scheduling cost, and the function is as follows:
Z m ＝ωS m (2)
c in equation (1) is the minimum scheduling cost; f (F) m Representing the transportation cost of the agricultural machinery m units; d (D) m,i,j Representing the distance from the current position i to the farmland j of the agricultural machinery m; z is Z m Representing the cost of an agricultural machine m operation; m is the set of all agricultural machinery; i is a set of current positions of all agricultural machinery; j is the set of all farmland locations;
s in formula (2) m Scoring the operation of the agricultural machinery m, wherein omega is a weight coefficient;
x in formula (3) m,i,j When the value of (1) is 1, the agricultural machinery m is idle, and the task from the current position i to the farmland j can be executed; x is X m,i,j When the value of (2) is 0, it indicates that the agricultural machine m cannot perform the task from the current position i to the farm field j.
Further, the agricultural machine dispatching method based on minimum dispatching cost comprises agricultural machine farmland initialization and specific dispatching, wherein the agricultural machine farmland initialization process is as follows:
(1) acquiring current positions i of all agricultural machinery, acquiring positions j of all farmlands, acquiring scores of all agricultural machinery, and acquiring states of all agricultural machinery;
(2) establishing an order queue, and arranging according to the priority of the job orders from high to low; orders with high priority are executed prior to low priority orders;
(3) establishing an agricultural machine queue, and ensuring that idle agricultural machines are in the queue and working agricultural machines are not in the queue;
(4) a waiting queue is established for placing orders that have not yet met the scheduled condition, and when multiple orders are being executed, there is a job order with a high priority and a job order with a low priority that has met the scheduled condition, then we should choose the job order that has met the scheduled condition rather than strictly following the priority of the task.
Further, the specific scheduling process of the agricultural machinery scheduling method based on minimum scheduling cost is as follows:
(1) Selecting a queue head order from an order priority sequence obtained by order priority ordering operation, traversing an agricultural machine sequence, searching whether an idle agricultural machine corresponding to the job type exists, if the idle agricultural machine corresponding to the job type exists, indicating that the order meets the scheduled condition, and if the idle agricultural machine corresponding to the job type does not exist, indicating that the order does not have the scheduled condition, and entering a waiting queue;
(2) The job order is executed with the goal of achieving a minimum scheduling cost. If a target agricultural machine is determined, deleting the order and the agricultural machine in a corresponding sequence, and dispatching the agricultural machine to complete order operation after the job order is distributed to the target agricultural machine;
(3) A round of job orders, current location of the agricultural machinery, agricultural machinery score, agricultural machinery status are updated and then returned to the first step until all orders are executed.
The beneficial effects are that: compared with the prior art, the invention has the following advantages:
(1) According to the invention, the agricultural machine terminal is used as an edge node, the cloud platform is used as a central node, and the edge-cloud collaborative distributed system architecture replaces the original single centralized architecture relying on the cloud platform, so that the problem that the centralized platform is easy to crash at a single point is solved, and meanwhile, the efficiency of the system is improved.
(2) According to the invention, the delay sensitive tasks are all calculated by the edge nodes, so that the real-time performance of the delay sensitive tasks is improved, and the timeliness of management is ensured.
(3) The invention aims at the optimal scheduling scheme of the cost, considers the priority order of orders and reduces the scheduling cost of 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 an embodiment of the present invention;
FIG. 3 is a schematic diagram of an agricultural machine management and scheduling system in accordance with an embodiment of the present invention;
FIG. 4 is a workflow diagram of an agricultural machine management module in an embodiment of the present invention;
FIG. 5 is a flowchart of the operation of the farm machine scheduling module according to an embodiment of the present invention.
Detailed Description
The technical scheme 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 intelligent management and scheduling system and method for the agricultural machinery based on cloud-edge coordination, the cloud platform is used as a central node, the vehicle-mounted terminal of the agricultural machinery is used as an edge node, the farmland information collection assembly and the vehicle-mounted information collection assembly are responsible for collecting data of the agricultural machinery and the farmland, and for tasks of delay sensitivity and large-capacity data, the edge node close to a data source, namely the terminal of the agricultural machinery, is used for carrying out operation, and is not uploaded to a remote cloud, so that the transmission time and cost are reduced, and the instantaneity 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, the cloud platform for processing. The vehicle-mounted information collection assembly comprises a GPS positioning module, a camera module, an oil quantity detection module and a speed detection module, and the position, the operation video, the oil quantity and the speed of the agricultural machinery are respectively collected in real time through the modules; the vehicle-mounted terminal is connected with the vehicle-mounted information collecting assembly and is used for processing tasks of delay sensitive and large-capacity data; receiving a job order sent by a cloud platform, and displaying the job order on a display screen of a vehicle-mounted terminal to prompt an agricultural machine operator; 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 collection module, a soil nitrogen, phosphorus and potassium collection module and a soil PH value collection module, and the temperature and humidity, the nitrogen, phosphorus and potassium content and the PH value of the land are respectively collected in real time through the modules; 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 the agricultural machine terminal, the agricultural machine scheduling module is deployed at the cloud platform, the agricultural machine management module carries out real-time omnibearing management of the agricultural machine according to the data of the vehicle-mounted information collection assembly, and the agricultural machine scheduling module carries out scheduling of the agricultural machine based on a scheduling scheme according to the agricultural machine data and the job order accepted by the cloud platform.
Example 1:
as shown in fig. 1, the intelligent management and scheduling system for agricultural machinery based on cloud edge coordination in this 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 is used as a central node, the vehicle-mounted terminal 12 is used as an edge node, the vehicle-mounted information collecting component 13 and the farmland information collecting component 14 are used for collecting data of a data source, tasks of delay sensitive and large-capacity data are calculated by the edge node, tasks of delay insensitive data and tasks of long-time data storage are calculated by the central node.
Example 2:
as shown in fig. 2, the present embodiment is based on embodiment 1. The intelligent management and scheduling system and method for the agricultural machinery based on cloud edge cooperation comprise a cloud platform 21, a vehicle-mounted wireless communication module 22, a vehicle-mounted terminal 23, a vehicle-mounted WiFi module 24, a farmland information collection assembly 25 and a vehicle-mounted information collection assembly 26.
The farmland information collection assembly 25 comprises a soil temperature and humidity collection module 251, a soil nitrogen, phosphorus and potassium collection module 252 and a soil PH value collection module 253. The soil temperature and humidity acquisition module 251 uploads temperature and humidity information of soil to the vehicle-mounted terminal 23 through the vehicle-mounted WiFi module 24, and the vehicle-mounted terminal 23 carries out filtering treatment on the temperature and humidity information to obtain accurate soil temperature and humidity; the soil nitrogen, phosphorus and potassium acquisition module 252 uploads the nitrogen, phosphorus and 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 treatment on the information to obtain accurate nitrogen, phosphorus and 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 carries out filtering processing on the PH value of the soil to obtain an accurate soil PH value.
The vehicle information collecting component 26 includes a GPS positioning module 261, a camera module 262, an oil amount detecting module 263, and a speed detecting module 264. The GPS positioning module 261 is connected with the vehicle-mounted terminal 23 through a USB interface, and uploads the position information of the agricultural machinery to the vehicle-mounted terminal 23, and the vehicle-mounted terminal 23 carries out filtering processing on GPS data to obtain accurate longitude and latitude position data; the camera module 262 is connected with the vehicle-mounted terminal 23 through a USB interface, uploads the agricultural machinery operation video to the vehicle-mounted terminal 23, and the vehicle-mounted terminal 23 compresses the video; the oil quantity detection module 263 is connected with the vehicle-mounted terminal 23 through an RS485 interface, and uploads the agricultural machinery oil quantity information to the vehicle-mounted terminal 23, and converts the height value of the residual oil quantity in the agricultural machinery oil tank, which is measured by the ultrasonic oil quantity sensor, into a specific oil quantity value; the speed detection module 264 is connected with the vehicle-mounted terminal 23 through a USB interface, and uploads the agricultural machinery speed information to the vehicle-mounted terminal 23, and the vehicle-mounted terminal 23 performs filtering processing on the speed data to obtain an accurate speed value.
In practical application, the mobile operator's SIM card for internet of things is inserted into the vehicle-mounted wireless communication module 22, and the farmland information collection component 25 sends the 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 performs agricultural machinery scheduling, the work order is issued to the vehicle-mounted terminal 23 through the vehicle-mounted wireless communication module 22 and displayed on the display screen.
Example 3:
as shown in fig. 3, the agricultural machinery management and dispatch system (based on a cloud platform) of the present embodiment includes an agricultural machinery management system 31 and an agricultural machinery dispatch system 32.
Wherein the agricultural machinery management system 31 includes a data processing module 312, an alarm module 313, a composite scoring module 314, a database module 315. The data processing module 312 is configured to process GPS data, operation video, oil volume data, speed data, temperature and humidity data, nitrogen, phosphorus, potassium data, and PH value data (including filtering the GPS position data, oil volume data, speed data, temperature and humidity data, nitrogen, phosphorus, potassium data, and PH value data to remove interference data), and provide the processed and processed 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 processing module 312 with a preset alarm value, and if any of the following conditions occurs, an alarm is sent to the agricultural machinery hand: the agricultural machinery position is not in a specified operation area, the agricultural machinery oil quantity is lower than the warning value, the agricultural machinery running speed 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 314 comprehensively analyzes the data collected by the vehicle-mounted information collecting component and the farmland information collecting component to determine the comprehensive score of the agricultural machinery corresponding to the current operation of the agricultural machinery hand; the database module 315 maintains historical data and periodically deletes data.
Wherein the agricultural machinery scheduling system 32 includes an order importation module 322, an agricultural machinery selection module 323, and a dispatch module 324. The cloud platform manager imports all orders through the order importing module 322, the agricultural machinery selecting module 323 determines a target agricultural machinery according to a scheduling scheme, and sends the orders to the target agricultural machinery terminal through the dispatching module 324 to achieve agricultural machinery scheduling.
As shown in fig. 4, the concrete flow of agricultural machinery management in this embodiment is as follows:
step 41: processing all uploaded data including GPS data, oil quantity data, operation video, speed, temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data of the agricultural machinery;
step 42: all the processed data are stored in a cloud database;
step 43: comparing the GPS position information of the agricultural machinery with the position of the operation area, and executing step 44 if the agricultural machinery is not in the operation area; otherwise, go to step 45; comparing the oil quantity of the agricultural machinery with the minimum oil quantity warning value, and if the oil quantity is lower than the minimum warning value, executing the step 44; otherwise, go to step 45; comparing the current speed of the agricultural machine with the maximum guard speed, and if the current speed is higher than the maximum guard speed, executing step 44; otherwise, go to step 45; comparing the current temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data of the field with reasonable value intervals of the temperature and humidity, nitrogen, phosphorus and potassium and PH values, and executing step 45 if the current temperature and humidity data, nitrogen, phosphorus and potassium data and PH value data of the field are in the reasonable value intervals; otherwise, go to step 44;
step 44: alarming to the agricultural machinery hand on the display screen of the terminal;
step 45: obtaining comprehensive scores of the operation after the operation is finished according to the processed GPS data, oil quantity data, operation video, speed, temperature and humidity data, nitrogen, phosphorus, potassium data and PH value data;
step 46: the data is stored to a local database.
As shown in fig. 5, the specific flow of agricultural machinery scheduling in this embodiment:
step 501: executing an initialization step;
step 502: judging whether the order alignment is empty or not; if it is empty, go to step 503; otherwise, execute step 504;
step 503 is performed: judging whether the waiting queue is empty or not; if the signal is empty, go to step 512; otherwise, executing step 504;
step 504: the last step is 502, selecting the head of the queue order of the order queue; the last step is 503, selecting the head of the queue order;
step 505: judging whether the order meets the scheduled condition, namely whether the agricultural machinery corresponding to the job type is in an idle state or not; if yes, go to step 507; otherwise, go to step 506;
step 506: placing the job order into a waiting queue, and executing 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 queue head order of the waiting queue is higher than the priority of the current job order and whether the scheduled condition is met; if yes, go to step 510; otherwise, go to step 509;
step 509: according to the agricultural machinery position, farmland position and operation score uploaded by the terminal, the method is represented by the formulaZ m ＝ωS m Determining a target agricultural machine with the lowest scheduling cost;
step 510: preferentially executing the queue head orders in the waiting queue;
step 511: distributing the order to a terminal of a target agricultural machine, deleting the order in the operation order, deleting the agricultural machine in an agricultural machine queue, updating a round of operation order, the current position of the agricultural machine, the agricultural machine score and the agricultural machine state, and then executing step 502;
step 512: the order queue and the waiting queue are empty, which indicates that all orders are scheduled and ended.
Examples:
the embodiment includes that if there are four job orders currently, agricultural machinery is required to be operated on the four job ordersIs scheduled for a given time period. Four job orders are (1, m) 1 ,j 1 )(2,m 2 ,j 2 )(3,m 3 ,j 3 )(2,m 3 ,j 4 ) The three parameters respectively represent order priority, job type and job area.
Firstly, initializing a system, and acquiring all agricultural machinery positions, farmland positions, agricultural machinery operation scores and agricultural machinery states. Order queues { (3, m) are established according to order priority 3 ,j 3 )(2,m 2 ,j 2 )(2,m 3 ,j 4 )(1,m 1 ,j 1 ) }. Establishing an agricultural machine queue including all idle agricultural machines, if the agricultural machine queue is { m } 1 ,1，m 2 ,1，m 2 ,2，m 2,3 }. A waiting queue is established, and the waiting queue is empty.
Selecting a head of line order (3, m) from an order queue 3 ,j 3 ) Searching whether the farm machinery queue has the corresponding operation type m 3 Is not found m 3 Agricultural machinery of the type in which the order enters a waiting queue { (3, m 3 ,j 3 ) Because the job order queue is not empty at this point, the head of queue order (2, m) 2 ,j 2 )。
Three corresponding operation types m are found in a queue of the agricultural machine 2 Agricultural machinery m of (2) 2,1 ,m 2,2 ,m 2,3 ，(m 2,1 Represents m 2 Type 1 farm machinery) order (2, m 2 ,j 2 ) The conditions to be scheduled are satisfied when the waiting queue is not empty but the head of the waiting queue order (3, m 3 ,j 3 ) The scheduled condition is not satisfied so the current order is still being executed.
From m according to the cost formula 2,1 ,m 2,2 ,m 2,3 Determining an agricultural machine with the minimum cost for executing the current order, if m is 2,3 Send order to m 2,3 Is a terminal of (a).
Delete (2, m) from order queue 2 ,j 2 ) Order, delete m from farm machine queue 2,3 And updating a round of operation order, the current position of the agricultural machinery, the agricultural machinery score and the agricultural machinery state.
And continuing to select the first order from the order queue for agricultural machine scheduling until the order sequence is empty.
Claims (7)
1. Agricultural machinery intelligent management and dispatch system based on cloud limit is cooperated, its characterized in that: the 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 machine is an edge node, the vehicle-mounted terminal is connected with a vehicle-mounted information collecting assembly, and the vehicle-mounted information collecting assembly is connected with the farmland information collecting assembly through a vehicle-mounted WiFi module;
the vehicle-mounted information collection assembly comprises a GPS positioning module, a camera module, an oil quantity detection module and a speed detection module, and position, operation video, oil quantity and speed information of the agricultural machinery are respectively collected in real time through the modules;
the farmland information collection assembly comprises a soil temperature and humidity collection module, a soil nitrogen, phosphorus and potassium collection module and a soil PH value collection module, and the temperature and humidity, the nitrogen, phosphorus and potassium content and the PH value of farmland soil are respectively collected in real time through the modules;
the vehicle-mounted terminal processes tasks of delay sensitive and large-capacity data; the vehicle-mounted terminal receives the operation order sent by the cloud platform and displays the operation order on a display screen of the vehicle-mounted terminal so as to prompt an agricultural machine operator;
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 omnibearing management of the agricultural machine according to the data of the vehicle-mounted information collection assembly, and the agricultural machine scheduling module carries out scheduling of the agricultural machine based on a scheduling scheme according to the agricultural machine data and the job order accepted by the cloud platform;
the agricultural machinery management module comprises a data processing module, an alarm module, a comprehensive scoring module and a database module;
the data processing module processes GPS data, operation video, oil quantity data and speed data, and provides the obtained temperature and humidity data, nitrogen, phosphorus, potassium data and PH value data for the alarm module, the comprehensive scoring 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 alarm value in the alarm module, and if any of the following conditions occurs, the alarm module gives an alarm to an agricultural machine hand: the agricultural machinery position is not in the specified operation area, the agricultural machinery oil quantity is lower than the warning value, the agricultural machinery running speed 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 the data acquired by the vehicle-mounted information collecting assembly and the farmland information collecting assembly, determines the comprehensive score of the current operation of the agricultural machinery corresponding to the agricultural machinery hand, and the scoring expression is as follows:
wherein S is m Is the job score of agricultural machinery m, Q t Represents the score of a temperature and humidity sensor, Q n Represents the score of the NPK sensor, Q p The PH sensor score is represented by A, the area of the agricultural machine is represented by A, T, the total time of the operation is represented by T, the total oil consumption of the operation is represented by O, and Q C Representing the video score of the operation, wherein alpha, beta, gamma, delta, lambda and theta are weight coefficients; the database module stores historical data;
in the process of real-time omnibearing management and agricultural machinery scheduling of the agricultural machinery, for the tasks of delay sensitivity and large-capacity data, edge nodes close to a data source are operated, and the tasks are not uploaded to a remote central node cloud platform any more; and uploading the data to a central node for processing for delay-insensitive tasks and tasks needing to store the data for a long time.
2. The cloud-edge collaboration-based intelligent management and scheduling system for agricultural machinery of claim 1, wherein the intelligent management and scheduling system is characterized by: the system comprises a vehicle-mounted wireless communication module, wherein the vehicle-mounted wireless communication module transmits related data of the agricultural machinery to a cloud platform by adopting a 5G mobile network, and the farmland information collection assembly is connected with a vehicle-mounted terminal through a hot spot generated by a vehicle-mounted WiFi module to transmit collected farmland information to the vehicle-mounted terminal.
3. The cloud-edge collaboration-based intelligent management and scheduling system for agricultural machinery of claim 1, wherein the intelligent management and scheduling system is characterized by: the time delay sensitive tasks comprise real-time omnibearing management and field management of the agricultural machinery; the high-capacity data task comprises a job quality score;
the real-time omnibearing 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 are carried out, namely, the running track, the residual oil quantity and the current running speed of the agricultural machinery are displayed on the terminal in real time; the early warning of the agricultural machinery comprises triggering an alarm once the position of the agricultural machinery is not in a 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, displaying the alarm on an agricultural machinery terminal, and reminding an agricultural machinery hand;
the field management comprises soil health detection, soil health is detected in real time through the nitrogen-phosphorus-potassium sensor acquisition module and the PH sensor acquisition module, and once a problem occurs, the soil health is immediately displayed on an agricultural machine terminal, and an agricultural machine hand is reminded.
4. The cloud-edge collaboration-based intelligent management and scheduling system for agricultural machinery of claim 1, wherein the intelligent management and scheduling system is characterized by: the job orders comprise order priority, job type and job area; and after the job order is completed, the agricultural machine vehicle-mounted terminal of the edge node scores the job quality of the job order, and after the job score is obtained, the vehicle-mounted terminal sends the score to the cloud platform to serve as a reference of the operation cost of the subsequent agricultural machine.
5. The cloud-edge collaboration-based intelligent management and scheduling system for agricultural machinery of claim 1, wherein the intelligent management and scheduling system is characterized by: the agricultural machinery scheduling module comprises an order importing module, an agricultural machinery selecting module, a dispatching module and a state switching module;
the order importing module imports a current operation order;
the agricultural machinery selection module determines a target agricultural machinery which corresponds to the operation type, is nearest to the operation area and is in an idle state according to the current operation order;
the dispatch 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 into a non-idle state after the dispatch module completes dispatch; and after the operation completion information sent by the vehicle-mounted terminal of the target agricultural machine is received, switching the agricultural machine into an idle state.
6. A scheduling method for implementing the cloud-edge collaboration-based intelligent management and scheduling system for agricultural machinery, which is characterized in that: the cloud platform manager imports all the job orders through the order importing module, the agricultural machinery selecting module determines a target agricultural machinery according to an agricultural machinery scheduling scheme, and the job orders are sent to the target agricultural machinery terminal through the dispatching module, so that agricultural machinery scheduling with minimum scheduling cost is realized;
based on the target order information and the received agricultural machinery upload data, determining a preselected agricultural machinery scheduling scheme includes: determining a target agricultural machine based on the order priority, the job type and the job area corresponding to the target order, and the job scores uploaded by the agricultural machine; the agricultural machinery scheduling scheme aims at minimizing scheduling cost, and the functions are as follows:
Z m ＝ωS m (2)
c in equation (1) is the minimum scheduling cost; f (F) m Representing the transportation cost of the agricultural machinery m units; d (D) m,i,j Representing the distance from the current position i to the farmland j of the agricultural machinery m; z is Z m Representing the cost of an agricultural machine m operation; m is the set of all agricultural machinery; i is a set of current positions of all agricultural machinery; j is the set of all farmland locations;
s in formula (2) m Scoring the operation of the agricultural machinery m, wherein omega is a weight coefficient;
x in formula (3) m,i,j When the value of (1) is 1, the agricultural machinery m is idle, and the task from the current position i to the farmland j can be executed; x is X m,i,j When the value of (2) is 0, the agricultural machinery m cannot execute the task from the current position i to the farmland j; the agricultural machine dispatching method based on minimum dispatching cost comprises the steps of agricultural machine farmland initialization and specific dispatching, wherein the agricultural machine farmland initialization process is as follows:
(1) acquiring current positions i of all agricultural machinery, acquiring positions j of all farmlands, acquiring scores of all agricultural machinery, and acquiring states of all agricultural machinery;
(2) establishing an order queue, and arranging according to the priority of the job orders from high to low; orders with high priority are executed prior to low priority orders;
(3) establishing an agricultural machine queue, and ensuring that idle agricultural machines are in the queue and working agricultural machines are not in the queue;
(4) a waiting queue is established for placing orders that have not yet met the scheduled condition, and when a plurality of orders are being executed, a job order with a high priority and a job order with a low priority that has met the scheduled condition are selected.
7. The scheduling method of the intelligent management and scheduling system for the agricultural machinery based on cloud computing as claimed in claim 6, wherein the scheduling method is characterized by comprising the following steps: the specific scheduling process of the agricultural machinery scheduling method based on minimum scheduling cost is as follows:
(1) Selecting a queue head order from an order priority sequence obtained by order priority ordering operation, traversing an agricultural machine sequence, searching whether an idle agricultural machine corresponding to the job type exists, if the idle agricultural machine corresponding to the job type exists, indicating that the order meets the scheduled condition, and if the idle agricultural machine corresponding to the job type does not exist, indicating that the order does not have the scheduled condition, and entering a waiting queue;
(2) Executing a job order, taking the minimum scheduling cost as a target, deleting the order and the agricultural machine in a corresponding sequence if a target agricultural machine is determined, and scheduling the agricultural machine after the job order is distributed to the target agricultural machine to complete order operation;
(3) A round of job orders, current location of the agricultural machinery, agricultural machinery score, agricultural machinery status are updated and then returned to the first step until all orders are executed.
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