Agricultural machinery sowing operation monitoring system based on Beidou system

Abstract

The present invention belongs to the field of sowing monitoring technology, and specifically relates to an agricultural machinery sowing operation monitoring system based on the Beidou system, including a sowing plan acquisition module, an operation monitoring characteristic value acquisition module, a sowing monitoring characteristic value acquisition module, and an agricultural machinery sowing operation status monitoring module. The present invention realizes real-time monitoring and management of sowing operations through the Beidou system, effectively improving the automation level of the operation; it can intelligently formulate and adjust the sowing plan according to the soil state data set to ensure that seeds are sown under optimal conditions, thereby improving the germination rate and growth quality of crops; it not only reduces the dependence on manual monitoring, but also improves the efficiency of sowing operations and crop yields; through real-time monitoring and early warning mechanisms, agricultural producers can respond quickly, take measures to correct deviations, and avoid possible yield losses.

Description

Technical Field

[0001] The present invention belongs to the technical field of sowing monitoring, and in particular relates to an agricultural machinery sowing operation monitoring system based on the Beidou system. Background Art

[0002] With the continuous growth of food demand and the increasing shortage of agricultural land resources, how to improve agricultural output efficiency and resource utilization efficiency has become an urgent problem to be solved. As an emerging agricultural model, precision agriculture optimizes the crop planting, management and harvesting processes by integrating advanced information technology, satellite navigation systems and automated equipment to ensure that resource inputs can achieve maximum output. The Beidou system provides strong technical support for precision agriculture with its high-precision positioning and navigation functions.

[0003] However, despite the great potential of precision agriculture technology in improving agricultural production efficiency, the existing monitoring systems for agricultural machinery sowing operations still have some limitations. These systems often rely on manual operation, have a low degree of automation, and lack the durability and reliability of the equipment, making it difficult to adapt to long-term and large-scale operation needs. In addition, traditional monitoring systems are difficult to ensure the consistency of sowing depth and density, which directly affects the uniform growth and final yield of crops. Summary of the invention

[0004] In view of the shortcomings of the prior art, the purpose of the present invention is to provide an agricultural machinery sowing operation monitoring system based on the Beidou system, which can realize precise monitoring and management through the Beidou system, improve sowing efficiency and crop yield, reduce resource waste, and ensure the intelligence and sustainability of agricultural production.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0006] The agricultural machinery sowing operation monitoring system based on the Beidou system includes a sowing plan acquisition module, an operation monitoring characteristic value acquisition module, a sowing monitoring characteristic value acquisition module and an agricultural machinery sowing operation status monitoring module, wherein:

[0007] A sowing plan acquisition module is used to acquire a data set of soil state required for sowing operations, and compare and obtain a sowing plan for the soil required for sowing operations based on the acquired data set of soil state required for sowing operations;

[0008] The operation monitoring characteristic value acquisition module obtains the real-time operation status data set of agricultural machinery sowing operation based on the Beidou system under the sowing plan of the soil to be sown. Based on the obtained real-time operation status data set of agricultural machinery sowing operation, the real-time operation monitoring characteristic value of agricultural machinery sowing operation is obtained through comprehensive analysis;

[0009] A sowing monitoring characteristic value acquisition module obtains a real-time sowing status data set of agricultural machinery sowing operations, and based on the obtained real-time sowing status data set of agricultural machinery sowing operations, obtains a real-time sowing monitoring characteristic value of agricultural machinery sowing operations through comprehensive analysis;

[0010] The agricultural machinery sowing operation status monitoring module imports the real-time operation monitoring characteristic values ​​of the agricultural machinery sowing operation and the real-time sowing monitoring characteristic values ​​of the agricultural machinery sowing operation into the agricultural machinery sowing operation monitoring model to monitor the real-time status of the agricultural machinery sowing operation.

[0011] Preferably, the soil state data set requiring sowing operation specifically includes soil moisture requiring sowing operation, soil hardness requiring sowing operation, and soil area requiring sowing operation.

[0012] Preferably, the sowing scheme of the soil requiring sowing operation is obtained by comparing the acquired soil state data set requiring sowing operation, and the analysis process is as follows:

[0013] Based on the acquired soil state data set for sowing operations, a comprehensive analysis is performed to obtain an assessment value of the soil state for sowing operations, and the assessment value of the soil state for sowing operations is used as an analysis basis for comparing and obtaining a sowing plan for the soil for sowing operations;

[0014] The soil state assessment value for sowing operation is compared one by one with each soil state assessment value interval for sowing operation stored in the database. After the comparison is successful, the sowing plan corresponding to the successfully compared soil state assessment value interval for sowing operation is obtained, and the sowing plan corresponding to the successfully compared soil state assessment value interval for sowing operation is used as the sowing plan for the soil requiring sowing operation corresponding to the soil state assessment value for sowing operation.

[0015] Preferably, the soil state assessment value for sowing operation is analyzed in the following process:

[0016] ;

[0017] Wherein, ω is the soil state assessment value of the soil to be sown, SD is the soil moisture required for sowing, YD is the soil hardness required for sowing, S is the soil area required for sowing, SD0 is the reference soil moisture required for sowing stored in the database, YD0 is the reference soil hardness required for sowing stored in the database, S0 is the reference soil area required for sowing stored in the database, μ1 is the compensation factor for the set soil moisture required for sowing, μ2 is the compensation factor for the set soil hardness required for sowing, μ3 is the compensation factor for the set soil area required for sowing, and e is a natural constant.

[0018] Preferably, the real-time operation status data set of the agricultural machinery sowing operation is obtained by comprehensive analysis to obtain the real-time operation monitoring characteristic value of the agricultural machinery sowing operation, and the analysis process is:

[0019] Under the sowing plan of the soil that needs sowing, based on the Beidou system, obtain the real-time operation status data set of agricultural machinery sowing operation. The real-time operation status data set of agricultural machinery sowing operation specifically includes the operation speed of agricultural machinery sowing operation, the deviation angle between the operation direction of agricultural machinery sowing operation and the specified direction, and the number of times the operation of agricultural machinery sowing operation exceeds the defined area;

[0020] Based on the acquired real-time operation status dataset of agricultural machinery sowing operations, a comprehensive analysis is performed to obtain the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations. The real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations are used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operations.

[0021] Preferably, the real-time operation monitoring characteristic value of the agricultural machinery sowing operation is analyzed in the following process:

[0022] ;

[0023] Wherein, α is the real-time operation monitoring characteristic value of agricultural machinery seeding operation, V is the operation speed of agricultural machinery seeding operation, θ is the deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction, CC is the number of times the operation of agricultural machinery seeding operation exceeds the defined area, V0 is the reference operation speed of agricultural machinery seeding operation stored in the database, θ0 is the defined deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction stored in the database, CC0 is the number of times the operation of agricultural machinery seeding operation exceeds the defined area stored in the database, σ1 is the compensation factor of the set operation speed of agricultural machinery seeding operation, σ2 is the compensation factor of the set deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction, and σ3 is the compensation factor of the set number of times the operation of agricultural machinery seeding operation exceeds the defined area.

[0024] Preferably, the real-time sowing status data set of the agricultural machinery sowing operation is obtained, and the real-time sowing monitoring characteristic value of the agricultural machinery sowing operation is obtained by comprehensive analysis, and the analysis process is:

[0025] Acquire a real-time sowing status data set for agricultural machinery sowing operations, wherein the real-time sowing status data set for agricultural machinery sowing operations specifically includes a sowing seed flow rate, a sowing depth, and a sowing seed spacing for agricultural machinery sowing operations;

[0026] Based on the acquired real-time sowing status dataset of agricultural machinery sowing operations, a comprehensive analysis is performed to obtain the real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations. The real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations are used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operations.

[0027] Preferably, the real-time sowing monitoring characteristic value of the agricultural machinery sowing operation is analyzed in the following process:

[0028] ;

[0029] Where β is the real-time sowing monitoring characteristic value of agricultural machinery sowing operation, LL is the sowing seed flow rate of agricultural machinery sowing operation, ZS is the sowing depth of agricultural machinery sowing operation, JL is the sowing seed spacing of agricultural machinery sowing operation, LL0 is the sowing seed reference flow rate of agricultural machinery sowing operation stored in the database, ZS0 is the sowing reference depth of agricultural machinery sowing operation stored in the database, JL0 is the sowing seed reference spacing of agricultural machinery sowing operation stored in the database, τ1 is the compensation factor of the set sowing seed flow rate of agricultural machinery sowing operation, τ2 is the compensation factor of the set sowing depth of agricultural machinery sowing operation, and τ3 is the compensation factor of the set sowing seed spacing of agricultural machinery sowing operation.

[0030] Preferably, the real-time operation monitoring characteristic value of the agricultural machinery sowing operation and the real-time sowing monitoring characteristic value of the agricultural machinery sowing operation are imported into the agricultural machinery sowing operation monitoring model to monitor the real-time state of the agricultural machinery sowing operation, and the analysis process is:

[0031] Import the real-time operation monitoring characteristic value of agricultural machinery sowing operation and the real-time sowing monitoring characteristic value of agricultural machinery sowing operation into the agricultural machinery sowing operation monitoring model, and obtain the real-time monitoring evaluation value of agricultural machinery sowing operation through comprehensive analysis. The real-time monitoring evaluation value of agricultural machinery sowing operation is used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operation.

[0032] Compare the real-time monitoring evaluation value of the agricultural machinery sowing operation with the real-time monitoring reference evaluation value of the agricultural machinery sowing operation stored in the database;

[0033] If the real-time monitoring evaluation value of the agricultural machinery sowing operation is higher than or equal to the real-time monitoring reference evaluation value of the agricultural machinery sowing operation, the agricultural machinery sowing operation state corresponding to the real-time monitoring evaluation value of the agricultural machinery sowing operation is marked as good;

[0034] If the real-time monitoring evaluation value of the agricultural machinery sowing operation is lower than the real-time monitoring reference evaluation value of the agricultural machinery sowing operation, the agricultural machinery sowing operation status corresponding to the real-time monitoring evaluation value of the agricultural machinery sowing operation is marked as bad, and an alarm is issued for the agricultural machinery sowing operation status.

[0035] Preferably, the agricultural machinery sowing operation monitoring model has the following analysis process:

[0036] ;

[0037] Where γ is the real-time monitoring evaluation value of agricultural machinery sowing operation, α is the real-time operation monitoring characteristic value of agricultural machinery sowing operation, and β is the real-time sowing monitoring characteristic value of agricultural machinery sowing operation.

[0038] The present invention has the following advantages or beneficial effects:

[0039] The present invention uses the Beidou system to achieve real-time monitoring and management of seeding operations, effectively improving the automation level of operations. The system can intelligently formulate and adjust the seeding plan based on the soil state data set to ensure that seeds are sown under optimal conditions, thereby improving the germination rate and growth quality of crops. This data-driven decision support not only reduces dependence on manual monitoring, but also improves the efficiency of seeding operations and crop yields.

[0040] The present invention provides agricultural producers with accurate soil status assessment by real-time collection and analysis of key parameters such as soil moisture, hardness and area. These data help agricultural producers to understand soil conditions in a timely manner, optimize irrigation and fertilization strategies, and reduce resource waste. At the same time, by monitoring sowing depth and density, the uniformity of crop growth can be ensured, further improving the overall quality and market competitiveness of crops.

[0041] The invention has real-time feedback and alarm functions, which can promptly detect and prompt potential problems during the sowing operation, such as improper speed or uneven sowing. This instant monitoring and early warning mechanism enables agricultural producers to respond quickly and take measures to correct deviations and avoid possible yield losses. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 It is a schematic diagram of system module connection of the present invention. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present invention are clearly and completely described below in conjunction with the accompanying drawings.

[0044] like Figure 1 As shown, the agricultural machinery sowing operation monitoring system based on the Beidou system includes a sowing plan acquisition module, an operation monitoring characteristic value acquisition module, a sowing monitoring characteristic value acquisition module and an agricultural machinery sowing operation status monitoring module.

[0045] The sowing plan acquisition module acquires a soil state data set for sowing operations, and obtains a sowing plan for the soil to be sown based on the acquired soil state data set for sowing operations.

[0046] The soil status dataset for sowing operations includes soil moisture, soil hardness, and soil area for sowing operations. Soil moisture refers to the water content in the soil, usually expressed as the percentage of water in the soil. It reflects the degree of moisture in the soil and is a key factor affecting seed germination and root development. Soil hardness, also known as soil compressive strength, is an indicator of soil compactness and can be evaluated by measuring the force required to enter the soil.

[0047] The moisture level of the soil directly affects its hardness. Wetter soil is softer and easier to till and sow, while drier soil is generally harder and may require more physical labor or mechanical force to break the soil for sowing. Soil with high moisture content may become too compacted after heavy mechanical pressure, affecting air and water permeability, which in turn affects seed germination and root development. Soil moisture content may vary from region to region, which requires careful water management over a wide range of soil areas. Understanding soil moisture content in various regions can help to implement more targeted irrigation strategies, especially in large areas of farmland, to avoid wasting water resources and optimize water supply for crops.

[0048] In a wide sowing area, changes in soil hardness may require adjustments to the settings of the sowing machinery. Hard soil areas may require increased tillage depth or the use of more powerful machinery to ensure that the seeds are properly implanted in the soil. Understanding the distribution of soil hardness in different areas helps plan the machinery's path and work plan, thereby improving the efficiency and effectiveness of the entire sowing process.

[0049] Based on the acquired data set of soil state that needs sowing operations, the sowing plan of the soil that needs sowing operations is obtained by comparison. The specific analysis process is: based on the acquired data set of soil state that needs sowing operations, a comprehensive analysis is performed to obtain an assessment value of the soil state that needs sowing operations, and the assessment value of the soil state that needs sowing operations is used as the analysis basis for obtaining the sowing plan of the soil that needs sowing operations; the assessment value of the soil state that needs sowing operations is compared one by one with each interval of soil state assessment value that needs sowing operations stored in the database. After the comparison is successful, the sowing plan corresponding to the successfully compared interval of soil state assessment value that needs sowing operations is obtained, and the sowing plan corresponding to the successfully compared interval of soil state assessment value that needs sowing operations is used as the sowing plan of the soil that needs sowing operations corresponding to the soil state assessment value that needs sowing operations.

[0050] By comparing the soil status assessment value with the interval in the database, the sowing plan that best suits the current soil conditions can be selected to ensure that the seed type, planting depth and density are most suitable for the current soil conditions. A suitable sowing plan helps to create a more favorable growth environment and promote healthy growth of crops, thereby improving yield and quality; the correct sowing plan reduces crop growth problems caused by unsuitable soil conditions. By implementing a sowing plan based on precise soil assessment, the time management of agricultural operations is more efficient, sowing can be carried out at the best time, and time waste caused by operations under unsuitable conditions can be reduced; a suitable sowing plan helps to maintain soil structure and fertility, and avoid soil degradation caused by repeated single crop planting or improper management. The systematic approach provides a data-based decision-making platform, and all operations are based on actual soil data analysis, reducing the bias of subjective judgment.

[0051] The above-mentioned method obtains the soil status data set for the sowing operation and compares it to obtain the sowing plan of the soil for sowing operation. Based on the soil quality data, the seed sowing density and depth can be adjusted to optimize the seed distribution and reduce seed waste. The monitoring system can collect soil and sowing status data in real time and adjust the sowing strategy in time. The feedback mechanism makes the sowing process more adaptive and flexible. Continuous monitoring of soil status helps to identify soil health problems and trends, and helps to implement long-term sustainable land management and crop rotation strategies.

[0052] The soil status assessment value for sowing operation is required, and the specific analysis process is as follows:

[0053] ;

[0054] Wherein, ω is the soil state assessment value of the soil to be sown, SD is the soil moisture required for sowing, YD is the soil hardness required for sowing, S is the soil area required for sowing, SD0 is the reference soil moisture required for sowing stored in the database, YD0 is the reference soil hardness required for sowing stored in the database, S0 is the reference soil area required for sowing stored in the database, μ1 is the compensation factor for the set soil moisture required for sowing, μ2 is the compensation factor for the set soil hardness required for sowing, μ3 is the compensation factor for the set soil area required for sowing, and e is a natural constant.

[0055] Monitoring parameters such as soil moisture and hardness can determine the most suitable soil conditions for sowing, which helps determine the best sowing time and method, thereby improving sowing efficiency; by monitoring soil status assessment values, the sowing depth and density can be adjusted according to parameters such as soil moisture and hardness to ensure good growth of plant roots, thereby increasing crop yield and quality; by calculating factors such as soil area, the number of seeds and amount of fertilizer required for sowing can be accurately calculated to avoid excessive investment or waste of resources and achieve effective use of resources; by obtaining and analyzing soil status assessment values, sowing operations can be reasonably planned according to actual needs, unnecessary costs in agricultural production can be avoided, and economic benefits can be improved; monitoring parameters such as soil moisture and hardness can help to use soil rationally, avoid soil erosion and ecological environmental damage caused by excessive tillage, and protect soil quality and ecological environmental stability.

[0056] The soil moisture required for sowing operations is detected by a soil moisture sensor, the soil hardness required for sowing operations is detected by a soil hardness meter, and the soil area required for sowing operations is accurately measured and defined by the Beidou system. With reference to relevant industry standards, the reference soil moisture required for sowing operations, the reference soil hardness required for sowing operations, and the reference soil area required for sowing operations stored in the database are obtained.

[0057] In this embodiment, each compensation factor is obtained from a database. For example, for μ1, μ2 and μ3, a mapping set of historically measured SD, YD, S and corresponding compensation factors is established based on historical data to obtain the compensation factors corresponding to the current SD, YD, S.

[0058] The operation monitoring characteristic value acquisition module obtains the real-time operation status data set of agricultural machinery sowing operations based on the Beidou system under the sowing plan of the soil to be sown. Based on the obtained real-time operation status data set of agricultural machinery sowing operations, a comprehensive analysis is performed to obtain the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations.

[0059] The specific analysis process is as follows: Under the sowing plan of the soil to be sown, based on the Beidou system, the real-time operation status data set of agricultural machinery sowing operations is obtained. The real-time operation status data set of agricultural machinery sowing operations specifically includes the operation speed of agricultural machinery sowing operations, the deviation angle between the operation direction of agricultural machinery sowing operations and the specified direction, and the number of times the operation of agricultural machinery sowing operations exceeds the defined area;

[0060] The operating speed of agricultural machinery seeding operation refers to the speed of agricultural machinery during seeding operation, usually measured in kilometers per hour (km / h). The operating speed of agricultural machinery will directly affect the operating efficiency and quality. Too fast may lead to uneven seeding, while too slow may lead to low efficiency. The deviation angle between the operating direction of agricultural machinery seeding operation and the specified direction indicates the angle between the agricultural machinery and the specified direction (usually the north direction) during seeding operation, reflecting whether the operating direction of the agricultural machinery deviates from the predetermined direction. Too large a deviation angle may affect the accuracy of seeding operation. The number of times that agricultural machinery seeding operation exceeds the defined area indicates the number of times that the agricultural machinery exceeds the predetermined operating area during the process of agricultural machinery seeding operation, reflecting the number of errors in the process of agricultural machinery operation. Frequently exceeding the defined area may lead to irregular seeding or waste of resources.

[0061] Based on the acquired real-time operation status dataset of agricultural machinery sowing operations, a comprehensive analysis is performed to obtain the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations. The real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations are used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operations.

[0062] If the above-mentioned agricultural machinery sowing operation runs too fast, the risk of damage to the agricultural machinery and equipment will increase, and may also cause uneven sowing. If the agricultural machinery sowing operation runs too slowly, the operation efficiency will be reduced. Too large a deviation angle will usually affect the accuracy of sowing, resulting in a large sowing deviation. If the agricultural machinery sowing operation runs too fast, it may increase the difficulty of the agricultural machinery driver to control the defined area, resulting in an increase in the number of times the defined area is exceeded, while a slower operation speed can improve the agricultural machinery driver's control over the operation area and reduce the number of times the defined area is exceeded. When the agricultural machinery sowing operation is running, a large deviation angle will increase the difficulty of the agricultural machinery driver's control, resulting in an increased possibility. When the deviation angle is moderate, the agricultural machinery driver can more easily control the direction of the agricultural machinery and reduce the number of times the defined area is exceeded.

[0063] The above comprehensive analysis of the real-time operation status data set of seeding operations can realize real-time monitoring of the state of agricultural machinery seeding operations, timely understand the situation during the operation, and help agricultural machinery drivers or managers make timely adjustments and decisions; comprehensive analysis of multiple data indicators such as the operation speed, deflection angle, and the number of times the agricultural machinery seeding operations exceed the defined area can provide a basis for the comprehensive evaluation of the seeding operations and help grasp the details and operation status of the operation process; by monitoring characteristic values, it is possible to identify and detect abnormal conditions or problems that may exist in agricultural machinery seeding operations, such as abnormal operation speed, excessive deflection angle, frequent exceeding of the defined area, etc., and to give early warnings and handle them in advance to avoid a decline in operation quality or waste of resources;

[0064] The real-time operation monitoring characteristic values ​​of agricultural machinery seeding operations obtained based on comprehensive analysis can provide support for optimization decisions for agricultural machinery seeding operations, such as adjusting the operation speed, improving the operation direction control, optimizing the operation process, etc., to improve the efficiency and quality of seeding operations; the real-time operation monitoring characteristic values ​​of agricultural machinery seeding operations can serve as the analysis basis for monitoring the real-time status of agricultural machinery seeding operations, which can provide important reference for subsequent data analysis, operation records and experience accumulation, and promote the continuous improvement and optimization of agricultural machinery seeding operations.

[0065] The real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations, the specific analysis process is as follows:

[0066] ;

[0067] Wherein, α is the real-time operation monitoring characteristic value of agricultural machinery seeding operation, V is the operation speed of agricultural machinery seeding operation, θ is the deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction, CC is the number of times the operation of agricultural machinery seeding operation exceeds the defined area, V0 is the reference operation speed of agricultural machinery seeding operation stored in the database, θ0 is the defined deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction stored in the database, CC0 is the number of times the operation of agricultural machinery seeding operation exceeds the defined area stored in the database, σ1 is the compensation factor of the set operation speed of agricultural machinery seeding operation, σ2 is the compensation factor of the set deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction, and σ3 is the compensation factor of the set number of times the operation of agricultural machinery seeding operation exceeds the defined area.

[0068] Real-time monitoring of the operating speed and deflection angle of agricultural machinery can timely detect abnormal operation or overspeed of agricultural machinery, prevent accidents, and ensure the safety of operators and equipment; based on the analysis results of the characteristic values ​​of agricultural machinery operation monitoring, the speed and driving direction of agricultural machinery can be adjusted to ensure the accuracy and consistency of sowing operations and improve sowing quality; monitoring the number of times agricultural machinery sowing operations exceed the defined area can avoid repeated sowing or missed sowing, effectively save the use of resources such as seeds and pesticides, and reduce production costs; real-time monitoring of the operating status characteristic values ​​of agricultural machinery can detect abnormal operations and make timely adjustments to maintain the continuity and high efficiency of operations and improve the production efficiency of agricultural machinery sowing operations; by collecting and analyzing the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations, data support and decision-making references can be provided to farm managers, helping them optimize operation processes and improve management strategies, thereby improving overall agricultural production benefits;

[0069] Beidou receivers or GPS receivers can receive satellite signals and calculate the position changes of agricultural machinery, and then determine the speed through changes in time and distance. Beidou receivers equipped on agricultural machinery receive signals from multiple satellites in real time, calculate the movement speed of agricultural machinery through changes in positioning data, and transmit them to the monitoring system. Combined with the location tracking data provided by the Beidou or GPS system and the orientation data of the electronic compass, the monitoring system can calculate the actual direction of travel of the agricultural machinery, compare it with the preset sowing direction, and calculate the deviation angle; through the Beidou receivers installed on the agricultural machinery, the system can track the geographical location of the agricultural machinery in real time. After setting the boundary coordinates of the farmland, the monitoring system will detect the position of the agricultural machinery in real time. Once the agricultural machinery exceeds these preset boundaries, the system will record an out-of-bounds event, which can be used for subsequent analysis, optimize the operation path and improve the accuracy of the operation; refer to relevant industry standards to obtain the reference operating speed of the agricultural machinery sowing operation, the defined deviation angle between the agricultural machinery sowing operation direction and the specified direction, and the number of permitted times the agricultural machinery sowing operation exceeds the defined area stored in the database.

[0070] The sowing monitoring characteristic value acquisition module obtains the real-time sowing status data set of agricultural machinery sowing operations, and based on the obtained real-time sowing status data set of agricultural machinery sowing operations, comprehensively analyzes and obtains the real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations.

[0071] The specific analysis process is as follows: obtaining a real-time sowing status data set for agricultural machinery sowing operations, which specifically includes the sowing seed flow rate, sowing depth, and sowing seed spacing of agricultural machinery sowing operations; sowing seed flow rate refers to the number of seeds sown per unit time by agricultural machinery during sowing operations, usually expressed in terms of unit area (such as per mu); the size of the sowing seed flow rate directly affects the density and uniformity of crops, and too large or too small sowing seed flow rate will affect the growth and yield of crops. Reasonable regulation of the sowing seed flow rate is crucial to the growth and development of crops; sowing depth refers to the time at which seeds are sown The depth of seeds planted in the soil. Different crops have different requirements for seeding depth. Too shallow or too deep a seeding depth will affect seed germination and growth. According to the growth characteristics of crops and soil conditions, setting the seeding depth reasonably is one of the key factors to ensure crop growth. Seed spacing refers to the distance between adjacent seeds, usually expressed in unit length (such as centimeters). The size of the seed spacing directly affects the growth space and competition relationship of crops. Too dense seed spacing will lead to fierce competition among crops, while too sparse seed spacing will affect the full utilization of soil resources by crops. Reasonable adjustment of seed spacing helps optimize the crop growth environment and improve yield and quality.

[0072] Based on the acquired real-time sowing status dataset of agricultural machinery sowing operations, a comprehensive analysis is performed to obtain the real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations. The real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations are used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operations.

[0073] The above-mentioned larger sowing seed flow rate usually requires a larger sowing depth to ensure that a sufficient number of seeds are sown per unit area. The adjustment of the sowing depth can affect the landing position of the seeds and the soil covering of the seeds, thereby affecting the growth and development of the seeds. Deeper sowing will provide more protection and nutrition, but it will also increase the difficulty of the seeds to absorb nutrients and water; the sowing depth is closely related to the sowing seed spacing. When the depth is shallow, it is necessary to maintain appropriate seed spacing to avoid seed competition, while when the depth is deep, the seed spacing can be appropriately reduced to increase the sowing density; reasonable seed spacing helps to avoid excessive competition between crops and ensure that each crop can obtain sufficient nutrients and water, thereby improving yield and quality; the relationship between the sowing seed flow rate and the seed spacing depends on the required sowing density. A larger sowing seed flow rate usually means a smaller seed spacing because more seeds need to be sown per unit area; reasonable adjustment of the sowing seed flow rate and seed spacing can ensure a reasonable density of crops and a good growth environment, and promote the root development and nutrient absorption of crops.

[0074] The above analysis of real-time sowing status data can timely discover the changes in parameters such as sowing seed flow, sowing depth, and sowing seed spacing, so as to make timely adjustments and optimizations; based on the monitoring characteristic values, it can accurately determine whether the sowing parameters need to be adjusted to ensure the good growth and development of crops; real-time monitoring of sowing status can help agricultural machinery operators control the operation of agricultural machinery more accurately and avoid wasting seeds and time; monitoring characteristic values ​​can be used to evaluate the efficiency of sowing operations and help decision makers optimize and adjust the sowing process in real time; by monitoring characteristic values, it can be timely discovered whether the sowing status meets the requirements of crop growth, which helps to ensure the uniformity and suitability of crop seeds, is conducive to the growth of crop roots, and improves crop yield and quality; based on the monitoring characteristic values ​​of real-time sowing status data, a data-based decision-making basis can be formed, which helps agricultural machinery operators and agricultural managers make accurate decisions and adjustments. Data-driven decisions can improve production efficiency and quality, reduce waste and errors, and form a feedback loop by continuously collecting, analyzing and applying sowing monitoring characteristic values, continuously improving the technology and methods of sowing operations, and further improving agricultural production efficiency and sustainability.

[0075] Real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations. The specific analysis process is as follows:

[0076] ;

[0077] Where β is the real-time sowing monitoring characteristic value of agricultural machinery sowing operation, LL is the sowing seed flow rate of agricultural machinery sowing operation, ZS is the sowing depth of agricultural machinery sowing operation, JL is the sowing seed spacing of agricultural machinery sowing operation, LL0 is the sowing seed reference flow rate of agricultural machinery sowing operation stored in the database, ZS0 is the sowing reference depth of agricultural machinery sowing operation stored in the database, JL0 is the sowing seed reference spacing of agricultural machinery sowing operation stored in the database, τ1 is the compensation factor of the set sowing seed flow rate of agricultural machinery sowing operation, τ2 is the compensation factor of the set sowing depth of agricultural machinery sowing operation, and τ3 is the compensation factor of the set sowing seed spacing of agricultural machinery sowing operation.

[0078] Ensuring that each seed is planted at the optimal depth and spacing helps improve crop growth conditions, thereby increasing yield and quality; appropriate depth and spacing are conducive to root development and nutrient absorption. By precisely controlling seed flow, waste and over-seeding can be avoided, which not only saves costs, but also reduces competition between seeds, so that each seed can get enough water and nutrients; real-time monitoring and adjustment of seed spacing and sowing depth ensures uniformity and consistency of the sowing process, which is particularly important for large-scale agricultural operations. Precision sowing technology reduces the need for chemical fertilizers and pesticides because crops grow healthier and more balanced, and have strong natural disease resistance. Long-term collection of sowing monitoring data provides a scientific basis for future sowing strategies and helps agricultural producers optimize operating patterns and crop management;

[0079] Seed flow sensors usually work based on photoelectric principles or mechanical counting principles. When seeds pass through the sensor, the sensor records the number of seeds and converts it into seed flow. The data can then be displayed in real time on the control panel of the agricultural machinery or transmitted to the central monitoring system; the sowing depth is usually controlled by adjusting the mechanical settings on the sowing machinery, and the depth sensor provides real-time feedback to ensure that the sowing depth remains within the preset range, allowing the operator or automatic control system to make instant adjustments to the sowing depth; the seed spacing can be adjusted and monitored by calculating the ratio of the frequency of seed droppers to the forward speed of the agricultural machinery. The visual system or other sensors detect the passing seeds to ensure that they are evenly spaced to avoid seed aggregation or excessive spacing; refer to relevant industry standards to obtain the reference sowing depth and reference spacing of sowing seeds for agricultural machinery sowing operations stored in the database.

[0080] The agricultural machinery sowing operation status monitoring module imports the real-time operation monitoring characteristic values ​​of the agricultural machinery sowing operation and the real-time sowing monitoring characteristic values ​​of the agricultural machinery sowing operation into the agricultural machinery sowing operation monitoring model to monitor the real-time status of the agricultural machinery sowing operation.

[0081] The specific analysis process is as follows: the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations and the real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations are imported into the agricultural machinery sowing operation monitoring model, and the real-time monitoring evaluation values ​​of agricultural machinery sowing operations are obtained through comprehensive analysis. The real-time monitoring evaluation values ​​of agricultural machinery sowing operations are used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operations; the real-time monitoring evaluation values ​​of agricultural machinery sowing operations are compared with the real-time monitoring reference evaluation values ​​of agricultural machinery sowing operations stored in the database; if the real-time monitoring evaluation value of agricultural machinery sowing operations is higher than or equal to the real-time monitoring reference evaluation value of agricultural machinery sowing operations, the agricultural machinery sowing operation status corresponding to the real-time monitoring evaluation value of agricultural machinery sowing operations is marked as good; if the real-time monitoring evaluation value of agricultural machinery sowing operations is lower than the real-time monitoring reference evaluation value of agricultural machinery sowing operations, the agricultural machinery sowing operation status corresponding to the real-time monitoring evaluation value of agricultural machinery sowing operations is marked as bad, and an alarm is issued for the agricultural machinery sowing operation status.

[0082] By comparing the above-mentioned monitoring evaluation values ​​with the reference evaluation values, potential problems or abnormal situations can be identified in time and responded to quickly. Once it is found that the state of agricultural machinery sowing operation is lower than the expected level, an alarm can be issued immediately and necessary measures can be taken to reduce risks; ensure the crop growth environment and yield, real-time monitoring and automated alarm system, can quickly identify problems and make timely adjustments to avoid wasting time and resources; timely detection of problems and optimization of operation status can help improve production efficiency and operation quality, and timely alarms can prevent problems from further deterioration and reduce losses and damage; rapid response and processing can minimize losses caused by abnormal situations, and the alarm system based on real-time monitoring evaluation values ​​can provide decision makers with more accurate information to help them make wise decisions; through the feedback information of the monitoring model, agricultural machinery operators and managers can adjust operation strategies in time to improve the accuracy and timeliness of decision-making; through continuous monitoring and evaluation of the state of agricultural machinery sowing operation, the monitoring model and operation process can be continuously improved, the accuracy and reliability of monitoring can be improved, and the continuous improvement and modernization of agricultural production can be promoted.

[0083] The specific analysis process of the agricultural machinery sowing operation monitoring model is as follows:

[0084] ;

[0085] Where γ is the real-time monitoring evaluation value of agricultural machinery sowing operation, α is the real-time operation monitoring characteristic value of agricultural machinery sowing operation, and β is the real-time sowing monitoring characteristic value of agricultural machinery sowing operation.

[0086] The above-mentioned real-time status of agricultural machinery sowing operations is monitored by importing the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations and the real-time sowing monitoring characteristic values ​​of agricultural machinery sowing operations into the agricultural machinery sowing operation monitoring model. Real-time monitoring allows precise adjustment of agricultural machinery operations to ensure that sowing depth, speed and seed distribution meet predetermined parameters. This accuracy is critical to improving the uniformity of crop growth and overall yield. Real-time monitoring ensures that each operation is efficient and effective, avoiding repeated sowing or missed areas due to insufficient monitoring. The system's real-time feedback mechanism increases the reliability of operations and reduces the risks caused by human errors.

[0087] The above-mentioned system provides a Beidou-based agricultural machinery sowing operation monitoring system, analyzes soil status data sets to formulate sowing plans, and can adjust seed types, sowing density and sowing depth according to specific soil conditions to ensure that seeds grow in the most suitable environment; real-time acquisition of agricultural machinery operating status and sowing status data, the system can promptly monitor any deviation from the predetermined sowing plan, such as inappropriate speed, uneven sowing, etc. The high degree of automation of the system reduces the need for manual operation, reduces problems caused by human errors, and improves the repeatability and reliability of operations.

Claims

1. The agricultural machinery sowing operation monitoring system based on Beidou system is characterized by: It includes a sowing plan acquisition module, an operation monitoring characteristic value acquisition module, a sowing monitoring characteristic value acquisition module and an agricultural machinery sowing operation status monitoring module, wherein: A sowing plan acquisition module is used to acquire a data set of soil state required for sowing operations, and compare and obtain a sowing plan for the soil required for sowing operations based on the acquired data set of soil state required for sowing operations; The operation monitoring characteristic value acquisition module obtains the real-time operation status data set of agricultural machinery sowing operation based on the Beidou system under the sowing plan of the soil to be sown. Based on the obtained real-time operation status data set of agricultural machinery sowing operation, the real-time operation monitoring characteristic value of agricultural machinery sowing operation is obtained through comprehensive analysis; A sowing monitoring characteristic value acquisition module obtains a real-time sowing status data set of agricultural machinery sowing operations, and based on the obtained real-time sowing status data set of agricultural machinery sowing operations, obtains a real-time sowing monitoring characteristic value of agricultural machinery sowing operations through comprehensive analysis; The agricultural machinery sowing operation status monitoring module imports the real-time operation monitoring characteristic values ​​of the agricultural machinery sowing operation and the real-time sowing monitoring characteristic values ​​of the agricultural machinery sowing operation into the agricultural machinery sowing operation monitoring model to monitor the real-time status of the agricultural machinery sowing operation; The soil state data set for sowing operation specifically includes soil moisture for sowing operation, soil hardness for sowing operation, and soil area for sowing operation; Based on the obtained soil state data set for sowing operation, the sowing plan of the soil for sowing operation is obtained by comparison, and the analysis process is as follows: Based on the acquired soil state data set for sowing operations, a comprehensive analysis is performed to obtain an assessment value of the soil state for sowing operations, and the assessment value of the soil state for sowing operations is used as an analysis basis for comparing and obtaining a sowing plan for the soil for sowing operations; The soil state assessment value for the sowing operation is compared one by one with each soil state assessment value interval for the sowing operation stored in the database. After the comparison is successful, the sowing plan corresponding to the successfully compared soil state assessment value interval for the sowing operation is obtained, and the sowing plan corresponding to the successfully compared soil state assessment value interval for the sowing operation is used as the sowing plan for the soil for the sowing operation corresponding to the soil state assessment value for the sowing operation; Based on the obtained real-time sowing status data set of agricultural machinery sowing operation, the real-time sowing monitoring characteristic value of agricultural machinery sowing operation is obtained through comprehensive analysis. The analysis process is as follows: Acquire a real-time sowing status data set for agricultural machinery sowing operations, wherein the real-time sowing status data set for agricultural machinery sowing operations specifically includes a sowing seed flow rate, a sowing depth, and a sowing seed spacing for agricultural machinery sowing operations; Based on the acquired real-time sowing status data set of agricultural machinery sowing operation, the real-time sowing monitoring characteristic value of agricultural machinery sowing operation is obtained through comprehensive analysis. The real-time sowing monitoring characteristic value of agricultural machinery sowing operation is used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operation. Based on the acquired real-time operation status data set of agricultural machinery sowing operation, the real-time operation monitoring characteristic value of agricultural machinery sowing operation is obtained through comprehensive analysis. The analysis process is as follows: Under the sowing plan of the soil that needs sowing, based on the Beidou system, obtain the real-time operation status data set of agricultural machinery sowing operation. The real-time operation status data set of agricultural machinery sowing operation specifically includes the operation speed of agricultural machinery sowing operation, the deviation angle between the operation direction of agricultural machinery sowing operation and the specified direction, and the number of times the operation of agricultural machinery sowing operation exceeds the defined area; Based on the acquired real-time operation status dataset of agricultural machinery sowing operations, a comprehensive analysis is performed to obtain the real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations. The real-time operation monitoring characteristic values ​​of agricultural machinery sowing operations are used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operations.

2. The agricultural machinery sowing operation monitoring system based on the Beidou system according to claim 1 is characterized in that: The soil state assessment value for sowing operation is analyzed in the following process: ； Wherein, ω is the soil state assessment value of the soil to be sown, SD is the soil moisture required for sowing, YD is the soil hardness required for sowing, S is the soil area required for sowing, SD0 is the reference soil moisture required for sowing stored in the database, YD0 is the reference soil hardness required for sowing stored in the database, S0 is the reference soil area required for sowing stored in the database, μ1 is the compensation factor for the set soil moisture required for sowing, μ2 is the compensation factor for the set soil hardness required for sowing, μ3 is the compensation factor for the set soil area required for sowing, and e is a natural constant.

3. The agricultural machinery sowing operation monitoring system based on Beidou system according to claim 1 is characterized in that: The real-time operation monitoring characteristic value of the agricultural machinery sowing operation, the analysis process is: ； Wherein, α is the real-time operation monitoring characteristic value of agricultural machinery seeding operation, V is the operation speed of agricultural machinery seeding operation, θ is the deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction, CC is the number of times the operation of agricultural machinery seeding operation exceeds the defined area, V0 is the reference operation speed of agricultural machinery seeding operation stored in the database, θ0 is the defined deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction stored in the database, CC0 is the number of times the operation of agricultural machinery seeding operation exceeds the defined area stored in the database, σ1 is the compensation factor of the set operation speed of agricultural machinery seeding operation, σ2 is the compensation factor of the set deviation angle between the operation direction of agricultural machinery seeding operation and the specified direction, and σ3 is the compensation factor of the set number of times the operation of agricultural machinery seeding operation exceeds the defined area.

4. The agricultural machinery sowing operation monitoring system based on Beidou system according to claim 1 is characterized in that: The real-time sowing monitoring characteristic value of the agricultural machinery sowing operation, the analysis process is: ； Where β is the real-time sowing monitoring characteristic value of agricultural machinery sowing operation, LL is the sowing seed flow rate of agricultural machinery sowing operation, ZS is the sowing depth of agricultural machinery sowing operation, JL is the sowing seed spacing of agricultural machinery sowing operation, LL0 is the sowing seed reference flow rate of agricultural machinery sowing operation stored in the database, ZS0 is the sowing reference depth of agricultural machinery sowing operation stored in the database, JL0 is the sowing seed reference spacing of agricultural machinery sowing operation stored in the database, τ1 is the compensation factor of the set sowing seed flow rate of agricultural machinery sowing operation, τ2 is the compensation factor of the set sowing depth of agricultural machinery sowing operation, and τ3 is the compensation factor of the set sowing seed spacing of agricultural machinery sowing operation.

5. The agricultural machinery sowing operation monitoring system based on Beidou system according to claim 1 is characterized in that: The real-time operation monitoring characteristic value of the agricultural machinery sowing operation and the real-time sowing monitoring characteristic value of the agricultural machinery sowing operation are imported into the agricultural machinery sowing operation monitoring model to monitor the real-time status of the agricultural machinery sowing operation. The analysis process is as follows: Import the real-time operation monitoring characteristic value of agricultural machinery sowing operation and the real-time sowing monitoring characteristic value of agricultural machinery sowing operation into the agricultural machinery sowing operation monitoring model, and obtain the real-time monitoring evaluation value of agricultural machinery sowing operation through comprehensive analysis. The real-time monitoring evaluation value of agricultural machinery sowing operation is used as the analysis basis for monitoring the real-time status of agricultural machinery sowing operation. Compare the real-time monitoring evaluation value of the agricultural machinery sowing operation with the real-time monitoring reference evaluation value of the agricultural machinery sowing operation stored in the database; If the real-time monitoring evaluation value of the agricultural machinery sowing operation is higher than or equal to the real-time monitoring reference evaluation value of the agricultural machinery sowing operation, the agricultural machinery sowing operation state corresponding to the real-time monitoring evaluation value of the agricultural machinery sowing operation is marked as good; If the real-time monitoring evaluation value of the agricultural machinery sowing operation is lower than the real-time monitoring reference evaluation value of the agricultural machinery sowing operation, the agricultural machinery sowing operation status corresponding to the real-time monitoring evaluation value of the agricultural machinery sowing operation is marked as bad, and an alarm is issued for the agricultural machinery sowing operation status.

6. The agricultural machinery sowing operation monitoring system based on Beidou system according to claim 5 is characterized in that: The agricultural machinery sowing operation monitoring model, the analysis process is: ； Where γ is the real-time monitoring evaluation value of agricultural machinery sowing operation, α is the real-time operation monitoring characteristic value of agricultural machinery sowing operation, and β is the real-time sowing monitoring characteristic value of agricultural machinery sowing operation.

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