An intelligent management platform for agricultural planting based on the Internet of Things

Abstract

The invention discloses an intelligent management platform for agricultural planting based on the Internet of Things, and relates to the field of intelligent management technology. The system collects required data through sensors and cameras as a first data group and a second data group, and combines the first data group and the second data group to calculate and obtain: an agricultural demand index Nyxq, an environmental coefficient Hjxs and a growth state coefficient Szzt. The agricultural demand index Nyxq is compared with a preset threshold to identify abnormal state conditions, obtain a graded strategy plan, and use an automatic control system to control an irrigation system, greenhouse environmental equipment, fertilizer delivery equipment and pest and disease treatment equipment through the graded plan. According to the generated strategy plan, agricultural operations are remotely controlled, and real-time notifications and execution results are sent to relevant personnel. Resource allocation is adjusted as needed through resource optimization management, and market demand, price trend and supply chain information are collected and analyzed to help relevant personnel make decisions on crop variety selection, planting time and sales strategy.

Description

Technical Field

[0001] The present invention relates to the field of intelligent management technology, and in particular to an agricultural planting intelligent management platform based on the Internet of Things. Background Art

[0002] In today's digital age, IoT technology has become a key driving force for many industries, bringing unlimited possibilities for innovation in various fields. Agriculture, as one of the most important industries in the world, is also actively exploring how to integrate IoT technology into its planting and management processes. Agriculture no longer relies solely on traditional intuitive observation and experience, but begins to rely on highly intelligent solutions to improve production efficiency, resource utilization efficiency and agricultural product quality.

[0003] However, although IoT technology has shown great potential in the agricultural field, traditional agricultural management methods still have some significant shortcomings. First, many farms and farmers still rely on traditional observations and experience and lack the support of scientific data, which limits the accuracy and sustainability of their agricultural decision-making. Secondly, agricultural resource management in some areas is still not efficient enough, resulting in waste of water, fertilizer and energy, and adverse effects on the environment. Thirdly, the acquisition and analysis of market information is still not fast and accurate enough, making it difficult for farmers to adjust sales strategies and pricing in a timely manner. Summary of the invention

[0004] 1. Technical issues to be resolved

[0005] In view of the deficiencies in the prior art, the present invention provides an intelligent agricultural planting management platform based on the Internet of Things, which solves the problems mentioned in the background technology.

[0006] (II) Technical solution

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: an intelligent management platform for agricultural planting based on the Internet of Things, including a data acquisition module, a data analysis and processing module, an abnormality monitoring module, an automation control module, a remote control and notification module, a resource management module and a market information module;

[0008] The data acquisition module is used to collect various environmental data, including temperature, humidity and light data, as the first data group through the sensor group. The camera captures the plant growth and any pests or diseases that may occur, and the soil moisture, soil nutrition and pest monitoring data of the monitoring equipment are used as the second data group;

[0009] The data analysis and processing module is used to transmit the collected data to the cloud server through the Internet of Things connection for reception and processing, store it in the database for subsequent analysis, perform real-time cleaning processing on the collected data, extract key information features, combine the first data group and the second data group for calculation, and obtain: agricultural demand index Nyxq;

[0010] The agricultural demand index Nyxq is calculated by the following formula:

[0011] Nyxq=[(Hjxs*a)*45%+(Szzt*b)*35%]*15%+C

[0012] In the formula, Hjxs represents the environmental coefficient, Szzt represents the growth state coefficient, a represents the weight value of the environmental coefficient Hjxs, and b represents the weight value of the growth coefficient Szxs;

[0013] Where, 0.45≤a≤0.65, 0.55≤b≤0.65, where a+b≤1.5, C represents the correction constant;

[0014] The abnormal monitoring module is used to detect the comparison between the agricultural demand index Nyxq calculated by the data analysis and processing module and the threshold value to identify whether there is an abnormal situation;

[0015] The automation control module is used to control the automation operation of the irrigation system, greenhouse environment equipment, fertilizer delivery equipment and pest and disease treatment equipment, and perform corresponding agricultural operations according to preset parameters and real-time data;

[0016] The remote control and notification module is used to remotely start the irrigation system, fertilization equipment or pest control device according to the generated strategy plan, and send real-time notifications to relevant personnel, including current environmental conditions, adopted strategies and execution results;

[0017] The resource management module is used to manage and optimize the use of resources, including water resources, fertilizers and energy, to ensure the effective use of resources, reduce waste, and adjust resource allocation as needed;

[0018] The market information module is used to collect and analyze market demand, price trend and supply chain information to help relevant personnel make decisions on crop variety selection, planting time and sales strategy.

[0019] Preferably, the data acquisition module includes a sensor interface unit, a camera interface unit and an information acquisition unit;

[0020] The sensor interface unit is used to connect various sensors, including soil moisture sensors, temperature sensors, humidity sensors, light sensors, wind speed sensors and rainfall sensors, and is responsible for communicating with the sensors and collecting environmental data;

[0021] The camera interface unit is used to connect a camera or a surveillance camera to capture plant growth conditions and detect conditions in the farmland, and obtain image and video data;

[0022] The information collection unit is used to read the sensor group and the camera to collect information related to the environment and crop growth. The sensor group is responsible for collecting parameter data related to the environment, including temperature value Wdz, humidity value Sdz, light intensity value Gzqd, rainwater irrigation rate Ggl and carbon dioxide concentration value Ndz, as the first data group, and the camera is responsible for obtaining the fertilization frequency Sfpl, the difference in growth conditions of different crops Sztj and the pest and disease rate Bchl, as the second data group.

[0023] Preferably, the data analysis and processing module includes a data receiving and storage unit, a real-time data processing unit and a historical data storage unit;

[0024] The data receiving and storage unit is used to receive sensor data, camera images and other relevant information from the data acquisition module, and store these data in a database;

[0025] The real-time data processing unit is used to perform analysis, processing and calculation based on the information of the first data group and the second data group to obtain: the environmental coefficient Hjxs and the growth state coefficient Szzt;

[0026] The historical data storage unit is used to store historical data for a long time, and supports review and tracing by relevant personnel.

[0027] Preferably, the environmental coefficient Hjxs is calculated by the following formula:

[0028]

[0029] Wherein, Wdz represents the temperature value, Sdz represents the humidity value, Gzqd represents the light intensity value, Ggl represents the rain irrigation rate, Ndz represents the carbon dioxide concentration value, d, e, f, and g represent the weight values ​​of the temperature value Wdz, the humidity value Sdz, the light intensity value Gzqd, the rain irrigation rate Ggl, and the carbon dioxide concentration value Ndz, respectively;

[0030] Among them, 0.35≤d≤0.55, 0.45≤e≤0.65, 0.35≤f≤0.55, 0.35≤g≤0.55, among which d+e+f+g≤2.5, and H represents the correction constant.

[0031] Preferably, the growth state coefficient Szzt is calculated by the following formula:

[0032] Szzt=[|(Sfpl*Bchl)*i-(Sztj*j)*65%|]+K

[0033] In the formula, Sfpl represents the frequency of fertilization, Bchl represents the rate of pests and diseases, Sztj represents the difference in growth conditions of different crops, i represents the weight value of the product of the fertilization frequency Sfpl and the rate of pests and diseases Bchl, and j represents the weight value of the difference in growth conditions of different crops Sztj;

[0034] Among them, 0.35≤i≤0.55, 0.25≤j≤0.45, wherein i+j≤1, and K represents a correction constant.

[0035] Preferably, the abnormality monitoring module includes an abnormality monitoring and evaluation unit;

[0036] The abnormal monitoring and evaluation unit is used to compare the agricultural demand index Nyxq with the preset threshold value to obtain the level warning strategy plan:

[0037] Nyxq≤2, obtain the first-level demand evaluation and wait for processing, no additional operation is required;

[0038] 2.1≤Nyxq≤4, obtain the secondary demand evaluation, perform low priority treatment, and carry out slight irrigation and fertilization;

[0039] 4.1≤Nyxq≤6, obtain the third-level demand assessment, perform medium priority treatment, and irrigate and fertilize as needed;

[0040] 6.1≤Nyxq≤8, obtain the fourth level demand assessment, perform high priority treatment, use regular irrigation and fertilization;

[0041] 8.1≤Nyxq≤10, obtain a level 5 demand assessment, perform emergency treatment, and immediately start the irrigation system or spray pesticides.

[0042] Preferably, the automation control unit includes an execution unit, a strategy adjustment unit and an emergency stop unit;

[0043] The execution unit is responsible for executing the decision-making strategy generated by the data analysis and processing module, and its specific functions include automatically controlling the opening, closing and adjustment of the irrigation system, fertilization equipment and pest control equipment;

[0044] The strategy adjustment unit is responsible for dynamically adjusting the operation strategy of the execution unit according to the sensor data feedback and the actual situation. When the environmental conditions change or the strategy is not suitable, the strategy adjustment unit will regenerate the strategy and pass it to the execution unit;

[0045] The emergency stop unit is responsible for safety monitoring and emergency stop system. In case of emergency, when equipment fails or operates abnormally, the emergency stop unit will immediately stop the automated operation to prevent potential danger.

[0046] Preferably, the remote control and notification module includes a user interface unit, a remote control unit and an alarm notification unit;

[0047] The user interface unit is used to provide a user-friendly interface, allowing the user to manually intervene and adjust the automated control, providing a graphical interface, allowing the user to view current environmental data, decision strategies, execution status and historical data, and view real-time data and notifications, so that relevant personnel can remotely monitor and control agricultural operations, perform manual operations and adjust strategies through the interface;

[0048] The remote control unit receives the instruction from the user interface unit, transmits the instruction to the execution unit, manually starts or stops the irrigation system, the fertilization equipment and the pest treatment device, or adjusts their operating parameters;

[0049] The alarm notification unit is used to monitor the system status, execution results and the agricultural demand index Nyxq in the environment. When there are potential problems or emergencies, the information is conveyed through a variety of notification methods, including SMS, email, mobile application notification and sound alarm, and alarm notifications are sent to relevant personnel to ensure that the information is conveyed to the responsible personnel in a timely manner so that they can take appropriate measures to deal with the problems.

[0050] Preferably, the resource management module includes a resource allocation and planning unit;

[0051] The resource allocation and planning unit is responsible for comprehensively considering the use of water resources, fertilizers and energy, monitoring soil moisture in real time, controlling the operation of fertilizer delivery equipment to accurately apply fertilizers according to soil needs, formulating resource allocation and conservation strategies based on data and needs, planning schedules for irrigation, fertilization and energy use, and considering resource availability and cost to promote economic and sustainable use of resources.

[0052] Preferably, the market information module includes a market demand analysis unit, a supply chain management unit and a marketing strategy unit;

[0053] The market demand analysis unit is responsible for collecting and analyzing market demand data, including food prices, demand trends and consumer preferences, to help relevant personnel understand the opportunities and challenges of the current market and select crop varieties and quantities suitable for the market;

[0054] The supply chain management unit is used to monitor and manage the supply chain of crops, including production, picking, packaging, transportation and sales, and to reduce logistics costs, reduce product losses and provide better quality by optimizing the supply chain;

[0055] The marketing strategy unit is used to support users in formulating marketing strategies, including pricing strategies, advertising and sales channel selection, and to improve the market visibility and competitiveness of products through precise market positioning and marketing strategies.

[0056] (III) Beneficial effects

[0057] The present invention provides an intelligent agricultural planting management platform based on the Internet of Things, which has the following beneficial effects:

[0058] (1) When the system is running, the required data is collected through sensors and cameras as the first data group and the second data group. The first data group and the second data group are combined to calculate and obtain: agricultural demand index Nyxq, environmental coefficient Hjxs and growth state coefficient Szzt. The agricultural demand index Nyxq is compared with the preset threshold to identify abnormal conditions and obtain a hierarchical strategy plan. The irrigation system, greenhouse environmental equipment, fertilizer delivery equipment and pest control equipment are controlled by an automated control system through the hierarchical plan. According to the generated strategy plan, agricultural operations are remotely controlled, and real-time notifications and execution results are sent to relevant personnel. Resource allocation is adjusted as needed through resource optimization management. Market demand, price trends and supply chain information are collected and analyzed to help relevant personnel make decisions on crop variety selection, planting time and sales strategy.

[0059] (2) By monitoring the agricultural demand index Nyxq in real time and comparing it with the preset threshold, the farm can make real-time adjustments based on the current demand level instead of relying on a fixed schedule, which helps to ensure that agricultural operations are always consistent with the current environment and demand, improving the pertinence and effectiveness of operations. The system can provide farmers with intelligent decision-making suggestions, helping farmers to adopt appropriate agricultural operation strategies, including irrigation, fertilization and pest control, based on actual demand conditions. This intelligent decision support can improve crop growth and yield while reducing unnecessary waste of resources. It optimizes the use of resources based on demand evaluation, avoids excessive use or waste of resources, helps reduce resource costs and waste, especially the effective management of resources such as water, fertilizers and pesticides, which helps to achieve sustainable use of resources.

[0060] (3) The present invention enables farmers to better understand market conditions and adjust their agricultural strategies according to market demands and trends, which helps to improve the market competitiveness of crops, increase sales revenue, and better meet consumer needs, and facilitates agricultural production planning and resource allocation to better adapt to market changes. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] Figure 1This is a schematic diagram of a flowchart of an agricultural planting intelligent management platform based on the Internet of Things in the present invention; DETAILED DESCRIPTION

[0062] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0063] Example 1

[0064] The present invention provides an intelligent agricultural planting management platform based on the Internet of Things. Figure 1 , including data acquisition module, data analysis and processing module, abnormality monitoring module, automation control module, remote control and notification module, resource management module and market information module;

[0065] The data acquisition module is used to collect various environmental data, including temperature, humidity and light data, as the first data group through the sensor group. The camera captures the plant growth and any pests or diseases that may occur, and the soil moisture, soil nutrition and pest monitoring data of the monitoring equipment are used as the second data group;

[0066] The data analysis and processing module is used to transmit the collected data to the cloud server through the Internet of Things connection for reception and processing, store it in the database for subsequent analysis, perform real-time cleaning processing on the collected data, extract key information features, combine the first data group and the second data group for calculation, and obtain: agricultural demand index Nyxq;

[0067] The agricultural demand index Nyxq is calculated by the following formula:

[0068] Nyxq=[(Hjxs*a)*45%+(Szzt*b)*35%]*15%+C

[0069] In the formula, Hjxs represents the environmental coefficient, Szzt represents the growth state coefficient, a represents the weight value of the environmental coefficient Hjxs, and b represents the weight value of the growth coefficient Szxs;

[0070] Where, 0.45≤a≤0.65, 0.55≤b≤0.65, where a+b≤1.5, C represents the correction constant;

[0071] The abnormal monitoring module is used to detect the comparison between the agricultural demand index Nyxq calculated by the data analysis and processing module and the threshold value to identify whether there is an abnormal situation;

[0072] The automation control module is used to control the automation operation of the irrigation system, greenhouse environment equipment, fertilizer delivery equipment and pest and disease treatment equipment, and perform corresponding agricultural operations according to preset parameters and real-time data;

[0073] The remote control and notification module is used to remotely start the irrigation system, fertilization equipment or pest control device according to the generated strategy plan, and send real-time notifications to relevant personnel, including current environmental conditions, adopted strategies and execution results;

[0074] The resource management module is used to manage and optimize the use of resources, including water resources, fertilizers and energy, to ensure the effective use of resources, reduce waste, and adjust resource allocation as needed;

[0075] The market information module is used to collect and analyze market demand, price trend and supply chain information to help relevant personnel make decisions on crop variety selection, planting time and sales strategy.

[0076] In this embodiment, the required data is collected by sensors and cameras as the first data group and the second data group. The first data group and the second data group are combined to calculate and obtain: the agricultural demand index Nyxq, the environmental coefficient Hjxs and the growth state coefficient Szzt. The agricultural demand index Nyxq is compared with a preset threshold to identify abnormal conditions and obtain a graded strategy plan. The irrigation system, greenhouse environmental equipment, fertilizer delivery equipment and pest control equipment are controlled by an automated control system through the graded plan. According to the generated strategy plan, agricultural operations are remotely controlled and real-time notifications are sent to relevant personnel, including current environmental conditions, strategies adopted and execution results, so as to help farmers and managers understand the farm status and operation progress, adjust resource allocation as needed through resource optimization management, collect and analyze market demand, price trends and supply chain information, and help relevant personnel make decisions on crop variety selection, planting time and sales strategy.

[0077] Example 2

[0078] This embodiment is explained in Example 1, please refer to Figure 1 ,Specifically: the data acquisition module includes a sensor interface unit, a camera interface unit and an information acquisition unit;

[0079] The sensor interface unit is used to connect various sensors, including soil moisture sensors, temperature sensors, humidity sensors, light sensors, wind speed sensors and rainfall sensors, and is responsible for communicating with the sensors and collecting environmental data;

[0080] The camera interface unit is used to connect a camera or a surveillance camera to capture plant growth conditions and detect conditions in the farmland, and obtain image and video data;

[0081] The information collection unit is used to read the sensor group and the camera to collect information related to the environment and crop growth. The sensor group is responsible for collecting parameter data related to the environment, including temperature value Wdz, humidity value Sdz, light intensity value Gzqd, rainwater irrigation rate Ggl and carbon dioxide concentration value Ndz, as the first data group, and the camera is responsible for obtaining the fertilization frequency Sfpl, the difference in growth conditions of different crops Sztj and the pest and disease rate Bchl, as the second data group.

[0082] The data analysis and processing module includes a data receiving and storage unit, a real-time data processing unit and a historical data storage unit;

[0083] The data receiving and storage unit is used to receive sensor data, camera images and other relevant information from the data acquisition module, and store these data in a database;

[0084] The real-time data processing unit is used to perform analysis, processing and calculation based on the information of the first data group and the second data group to obtain: the environmental coefficient Hjxs and the growth state coefficient Szzt;

[0085] The historical data storage unit is used to store historical data for a long time, and supports review and tracing by relevant personnel.

[0086] In this embodiment, the sensor interface unit can connect to a variety of sensors to monitor environmental parameters in real time, which enables farmers to accurately understand the environmental conditions in the farmland and helps to better manage crops. The camera interface unit is connected to the camera and can provide visual data for capturing plant growth conditions and detecting conditions in the farmland, which helps to promptly detect plant health problems, insect pests or other abnormal conditions. By calculating the environmental coefficient Hjxs and the growth status coefficient Szzt, the system can provide farmers with accurate environmental assessments and crop growth status information. Through accurate data collection and intelligent decision-making, farmers can use water resources, fertilizers and energy more effectively, reduce resource waste, and reduce economic costs.

[0087] Example 3

[0088] This embodiment is explained in Example 1, please refer to Figure 1 Specifically: the environmental coefficient Hjxs is calculated by the following formula:

[0089]

[0090] Wherein, Wdz represents the temperature value, Sdz represents the humidity value, Gzqd represents the light intensity value, Ggl represents the rain irrigation rate, Ndz represents the carbon dioxide concentration value, d, e, f, and g represent the weight values ​​of the temperature value Wdz, the humidity value Sdz, the light intensity value Gzqd, the rain irrigation rate Ggl, and the carbon dioxide concentration value Ndz, respectively;

[0091] Among them, 0.35≤d≤0.55, 0.45≤e≤0.65, 0.35≤f≤0.55, 0.35≤g≤0.55, among which d+e+f+g≤2.5, and H represents the correction constant.

[0092] The growth state coefficient Szzt is calculated by the following formula:

[0093] Szzt=[|(Sfpl*Bchl)*i-(Sztj*j)*65%|]+K

[0094] In the formula, Sfpl represents the frequency of fertilization, Bchl represents the rate of pests and diseases, Sztj represents the difference in growth conditions of different crops, i represents the weight value of the product of the fertilization frequency Sfpl and the rate of pests and diseases Bchl, and j represents the weight value of the difference in growth conditions of different crops Sztj;

[0095] Where, 0.35≤i≤0.55, 0.25≤j≤0.45, where i+j≤1, K represents the correction constant;

[0096] The pest rate Bchl is based on installing cameras in the farmland. These cameras will regularly capture images or video data of the farmland. The positions of the cameras cover different areas in the farmland to obtain comprehensive information. After image processing, relevant features are extracted, including color, shape, size and texture, so as to analyze the presence of pests and diseases. By analyzing the number and distribution of pests and diseases detected in the farmland, the pest rate Bchl is obtained. The pest rate Bchl can be expressed as the number of pests and diseases per unit area or per unit plant;

[0097] The abnormality monitoring module includes an abnormality monitoring and evaluation unit;

[0098] The abnormal monitoring and evaluation unit is used to compare the agricultural demand index Nyxq with the preset threshold value to obtain the level warning strategy plan:

[0099] Nyxq≤2, get the first-level demand assessment, wait for treatment, do not carry out additional irrigation, rely only on natural rainfall to reduce the waste of water resources, suspend fertilization to reduce the risk of nutrient excess, and do not carry out pest treatment because the pest threat is low;

[0100] 2.1≤Nyxq≤4, obtain the secondary demand assessment, perform low priority treatment, reduce the frequency of irrigation to save water resources, but ensure that plants are not affected by drought, reduce the amount of fertilizer to reduce the risk of pesticide residues and environmental pollution, regularly check the pest situation, and take control measures only when there is an outbreak of pests;

[0101] 4.1≤Nyxq≤6, get the third-level demand assessment, implement medium priority treatment, reduce the irrigation frequency according to soil moisture monitoring to avoid over-wetting, adjust the frequency and amount of fertilization according to plant growth and nutrient analysis, monitor pest conditions regularly, and spray pesticides only when necessary to reduce the use of chemicals;

[0102] 6.1≤Nyxq≤8, obtain the fourth-level demand assessment, implement high-priority treatment, irrigate regularly to maintain soil moisture at a suitable level, fertilize regularly to ensure that plants get enough nutrients, monitor pest conditions, and spray pesticides regularly as needed to prevent the spread of pests;

[0103] 8.1≤Nyxq≤10, obtain the fifth-level demand assessment, implement emergency treatment, immediately start the irrigation system to ensure that the soil moisture is within an acceptable range, when the soil nutrients are seriously insufficient, immediately spray an appropriate amount of fertilizer, when there is an obvious threat of insect pests or diseases, immediately spray pesticides to control pests.

[0104] In this embodiment, the agricultural demand index Nyxq can be monitored in real time and compared with a preset threshold, which means that farm operations can be adjusted in real time according to the current demand level instead of relying on a fixed schedule. By comparing the agricultural demand index Nyxq with the preset threshold, the system can provide farmers with intelligent decision-making suggestions, which helps farmers to adopt appropriate irrigation, fertilization and pest control strategies under different demand conditions, optimize the use of resources according to demand evaluation, avoid excessive use or waste of resources, help reduce resource costs, and reduce unnecessary use of water, fertilizers and pesticides. The system's intelligent monitoring and automated decision-making reduce farmers' manual intervention and save time and labor costs.

[0105] Example 4

[0106] This embodiment is explained in Example 1, please refer to Figure 1 , specifically: the automation control unit includes an execution unit, a strategy adjustment unit and an emergency stop unit;

[0107] The execution unit is responsible for executing the decision-making strategy generated by the data analysis and processing module, and its specific functions include automatically controlling the opening, closing and adjustment of the irrigation system, fertilization equipment and pest control equipment;

[0108] The strategy adjustment unit is responsible for dynamically adjusting the operation strategy of the execution unit according to the sensor data feedback and the actual situation. When the environmental conditions change or the strategy is not suitable, the strategy adjustment unit will regenerate the strategy and pass it to the execution unit;

[0109] The emergency stop unit is responsible for safety monitoring and emergency stop system. In case of emergency, when equipment fails or operates abnormally, the emergency stop unit will immediately stop the automated operation to prevent potential danger.

[0110] The remote control and notification module includes a user interface unit, a remote control unit and an alarm notification unit;

[0111] The user interface unit is used to provide a user-friendly interface, allowing the user to manually intervene and adjust the automated control, providing a graphical interface, allowing the user to view current environmental data, decision strategies, execution status and historical data, and view real-time data and notifications, so that relevant personnel can remotely monitor and control agricultural operations, perform manual operations and adjust strategies through the interface;

[0112] The remote control unit receives the instruction from the user interface unit, transmits the instruction to the execution unit, manually starts or stops the irrigation system, the fertilization equipment and the pest treatment device, or adjusts their operating parameters;

[0113] The alarm notification unit is used to monitor the system status, execution results and the agricultural demand index Nyxq in the environment. When there are potential problems or emergencies, the information is conveyed through a variety of notification methods, including SMS, email, mobile application notification and sound alarm, and alarm notifications are sent to relevant personnel to ensure that the information is conveyed to the responsible personnel in a timely manner so that they can take appropriate measures to deal with the problems.

[0114] The resource management module includes a resource allocation and planning unit;

[0115] The resource allocation and planning unit is responsible for comprehensively considering the use of water resources, fertilizers and energy, monitoring soil moisture in real time, controlling the operation of fertilizer delivery equipment to accurately apply fertilizers according to soil needs, formulating resource allocation and conservation strategies based on data and needs, planning schedules for irrigation, fertilization and energy use, and considering resource availability and cost to promote economic and sustainable use of resources.

[0116] The market information module includes a market demand analysis unit, a supply chain management unit and a marketing strategy unit;

[0117] The market demand analysis unit is responsible for collecting and analyzing market demand data, including food prices, demand trends and consumer preferences, to help relevant personnel understand the opportunities and challenges of the current market and select crop varieties and quantities suitable for the market;

[0118] The supply chain management unit is used to monitor and manage the supply chain of crops, including production, picking, packaging, transportation and sales, and to reduce logistics costs, reduce product losses and provide better quality by optimizing the supply chain;

[0119] The marketing strategy unit is used to support users in formulating marketing strategies, including pricing strategies, advertising and sales channel selection, and to improve the market visibility and competitiveness of products through precise market positioning and marketing strategies.

[0120] In this embodiment, the use and cost of resources are comprehensively considered to help farmers optimize the use of water resources, fertilizers and energy, reduce waste, and lower economic costs, thereby achieving economic and sustainable use of resources. By real-time monitoring of soil moisture and precise fertilization, the system helps to improve the growth efficiency of crops, reduce over-fertilization and irrigation, and reduce environmental impact. Resource allocation strategies and schedules for irrigation, fertilization, and energy use are formulated based on data and needs, which helps to improve the planning and efficiency of agricultural operations and ensure the timely supply of resources.

[0121] Specific example:

[0122] Assume that a certain agricultural planting area has installed corresponding sensors and cameras to monitor environmental parameters. The following are example parameter values:

[0123] Temperature value Wdz: 28°, humidity value Sdz: 60%, light intensity value Gzqd: 60lux, rainwater irrigation rate Ggl: 0 / h, carbon dioxide concentration value Ndz: 400ppm, corresponding weight values: d=0.45, e=0.65, f=0.4, g=0.5, correction constant H=3;

[0124] Environmental Factor

[0125] Fertilization frequency Sfpl: 3 / per cycle, pest rate Bchl: 35%, difference in growth conditions of different crops Sztj: 5, corresponding weight values: i=0.38, j=0.32, correction constant K=3;

[0126] Growth state coefficient Szzt = [|(35%*3)*0.38-(5*0.32)*65%|]+3 = 3.64

[0127] Corresponding weight values: a = 0.5, b = 0.62, correction constant C = 4;

[0128] Agricultural demand index Nyxq = [(7.86*0.5)*45%+(3.64*0.62)*35%]*15%+4=4.38

[0129] Therefore, according to the above parameter values, the example value of the agricultural demand index Nyxq is 4.38. According to this value, the third-level demand evaluation is obtained, and the medium priority treatment is performed. According to soil moisture monitoring, the irrigation frequency will be reduced to avoid over-wetting. According to plant growth and nutrient analysis, the frequency and amount of fertilization are adjusted. Pests are monitored regularly and pesticides are sprayed only when necessary to reduce the use of chemicals. The operation level of irrigation, fertilization and pest control of farmland is determined according to the corresponding strategy plan.

[0130] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An intelligent agricultural planting management platform based on the Internet of Things, characterized by: It includes data collection module, data analysis and processing module, abnormality monitoring module, automation control module, remote control and notification module, resource management module and market information module; The data acquisition module is used to collect various environmental data, including temperature, humidity and light data, as the first data group through the sensor group. The camera captures the plant growth and any pests or diseases that may occur, and the soil moisture, soil nutrition and pest monitoring data of the monitoring equipment are used as the second data group; The data analysis and processing module is used to transmit the collected data to the cloud server through the Internet of Things connection for reception and processing, store it in the database for subsequent analysis, perform real-time cleaning processing on the collected data, extract key information features, combine the first data group and the second data group for calculation, and obtain: agricultural demand index Nyxq; The agricultural demand index Nyxq is calculated by the following formula: Nyxq=[(Hjxs*a)*45%+(Szzt*b)*35%]*15%+C In the formula, Hjxs represents the environmental coefficient, Szzt represents the growth state coefficient, a represents the weight value of the environmental coefficient Hjxs, and b represents the weight value of the growth coefficient Szxs; Where, 0.45≤a≤0.65, 0.55≤b≤0.65, where a+b≤1.5, C represents the correction constant; The abnormal monitoring module is used to detect the comparison between the agricultural demand index Nyxq calculated by the data analysis and processing module and the threshold value to identify whether there is an abnormal situation; The automation control module is used to control the automation operation of the irrigation system, greenhouse environment equipment, fertilizer delivery equipment and pest and disease treatment equipment, and perform corresponding agricultural operations according to preset parameters and real-time data; The remote control and notification module is used to remotely start the irrigation system, fertilization equipment or pest control device according to the generated strategy plan, and send real-time notifications to relevant personnel, including current environmental conditions, adopted strategies and execution results; The resource management module is used to manage and optimize the use of resources, including water resources, fertilizers and energy, to ensure the effective use of resources, reduce waste, and adjust resource allocation as needed; The market information module is used to collect and analyze market demand, price trend and supply chain information to help relevant personnel make decisions on crop variety selection, planting time and sales strategy.

2. According to claim 1, an intelligent agricultural planting management platform based on the Internet of Things is characterized by: The data acquisition module includes a sensor interface unit, a camera interface unit and an information acquisition unit; The sensor interface unit is used to connect various sensors, including soil moisture sensors, temperature sensors, humidity sensors, light sensors, wind speed sensors and rainfall sensors, and is responsible for communicating with the sensors and collecting environmental data; The camera interface unit is used to connect a camera or a surveillance camera to capture plant growth conditions and detect conditions in the farmland, and obtain image and video data; The information collection unit is used to read the sensor group and the camera to collect information related to the environment and crop growth. The sensor group is responsible for collecting parameter data related to the environment, including temperature value Wdz, humidity value Sdz, light intensity value Gzqd, rainwater irrigation rate Ggl and carbon dioxide concentration value Ndz, as the first data group, and the camera is responsible for obtaining the fertilization frequency Sfpl, the difference in growth conditions of different crops Sztj and the pest and disease rate Bchl, as the second data group.

3. According to claim 1, an intelligent agricultural planting management platform based on the Internet of Things is characterized by: The data analysis and processing module includes a data receiving and storage unit, a real-time data processing unit and a historical data storage unit; The data receiving and storage unit is used to receive sensor data, camera images and other relevant information from the data acquisition module, and store these data in a database; The real-time data processing unit is used to perform analysis, processing and calculation based on the information of the first data group and the second data group to obtain: the environmental coefficient Hjxs and the growth state coefficient Szzt; The historical data storage unit is used to store historical data for a long time, and supports review and tracing by relevant personnel.

4. According to claim 3, an intelligent agricultural planting management platform based on the Internet of Things is characterized by: The environmental coefficient Hjxs is calculated by the following formula: Wherein, Wdz represents the temperature value, Sdz represents the humidity value, Gzqd represents the light intensity value, Ggl represents the rain irrigation rate, Ndz represents the carbon dioxide concentration value, d, e, f, and g represent the weight values ​​of the temperature value Wdz, the humidity value Sdz, the light intensity value Gzqd, the rain irrigation rate Ggl, and the carbon dioxide concentration value Ndz, respectively; Among them, 0.35≤d≤0.55, 0.45≤e≤0.65, 0.35≤f≤0.55, 0.35≤g≤0.55, among which d+e+f+g≤2.5, and H represents the correction constant.

5. According to claim 3, an intelligent agricultural planting management platform based on the Internet of Things is characterized by: The growth state coefficient Szzt is calculated by the following formula: Szzt=[|(Sfpl*Bchl)*i-(Sztj*j)*65%|]+K In the formula, Sfpl represents the frequency of fertilization, Bchl represents the rate of pests and diseases, Sztj represents the difference in growth conditions of different crops, i represents the weight value of the product of the fertilization frequency Sfpl and the rate of pests and diseases Bchl, and j represents the weight value of the difference in growth conditions of different crops Sztj; Among them, 0.35≤i≤0.55, 0.25≤j≤0.45, i+j≤1, and K represents a correction constant.

6. The agricultural planting intelligent management platform based on the Internet of Things according to claim 1 is characterized by: The abnormality monitoring module includes an abnormality monitoring and evaluation unit; The abnormal monitoring and evaluation unit is used to compare the agricultural demand index Nyxq with the preset threshold value to obtain the level warning strategy plan: Nyxq≤2, obtain the first-level demand evaluation and wait for processing, no additional operation is required; 2.1≤Nyxq≤4, obtain the secondary demand evaluation, perform low priority treatment, and carry out slight irrigation and fertilization; 4.1≤Nyxq≤6, obtain the third-level demand assessment, perform medium priority treatment, and irrigate and fertilize as needed; 6.1≤Nyxq≤8, obtain the fourth level demand assessment, perform high priority treatment, use regular irrigation and fertilization; 8.1≤Nyxq≤10, obtain a level 5 demand assessment, perform emergency treatment, and immediately start the irrigation system or spray pesticides.

7. The agricultural planting intelligent management platform based on the Internet of Things according to claim 1 is characterized by: The automation control module includes an execution unit, a strategy adjustment unit and an emergency stop unit; The execution unit is responsible for executing the decision-making strategy generated by the data analysis and processing module, and its specific functions include automatically controlling the opening, closing and adjustment of the irrigation system, fertilization equipment and pest control equipment; The strategy adjustment unit is responsible for dynamically adjusting the operation strategy of the execution unit according to the sensor data feedback and the actual situation. When the environmental conditions change or the strategy is not suitable, the strategy adjustment unit will regenerate the strategy and pass it to the execution unit; The emergency stop unit is responsible for safety monitoring and emergency stop system. In case of emergency, when equipment fails or operates abnormally, the emergency stop unit will immediately stop the automated operation to prevent potential danger.

8. The agricultural planting intelligent management platform based on the Internet of Things according to claim 1 is characterized by: The remote control and notification module includes a user interface unit, a remote control unit and an alarm notification unit; The user interface unit is used to provide a user-friendly interface, allowing the user to manually intervene and adjust the automated control, providing a graphical interface, allowing the user to view current environmental data, decision strategies, execution status and historical data, and view real-time data and notifications, so that relevant personnel can remotely monitor and control agricultural operations, perform manual operations and adjust strategies through the interface; The remote control unit receives the instruction from the user interface unit, transmits the instruction to the execution unit, manually starts or stops the irrigation system, the fertilization equipment and the pest treatment device, or adjusts their operating parameters; The alarm notification unit is used to monitor the system status, execution results and the agricultural demand index Nyxq in the environment. When there are potential problems or emergencies, the information is conveyed through a variety of notification methods, including SMS, email, mobile application notification and sound alarm, and alarm notifications are sent to relevant personnel to ensure that the information is conveyed to the responsible personnel in a timely manner so that they can take appropriate measures to deal with the problems.

9. The agricultural planting intelligent management platform based on the Internet of Things according to claim 1 is characterized by: The resource management module includes a resource allocation and planning unit; The resource allocation and planning unit is responsible for comprehensively considering the use of water resources, fertilizers and energy, monitoring soil moisture in real time, controlling the operation of fertilizer delivery equipment to accurately apply fertilizers according to soil needs, formulating resource allocation and conservation strategies based on data and needs, planning schedules for irrigation, fertilization and energy use, and considering resource availability and cost to promote economic and sustainable use of resources.

10. The agricultural planting intelligent management platform based on the Internet of Things according to claim 1, characterized in that: The market information module includes a market demand analysis unit, a supply chain management unit and a marketing strategy unit; The market demand analysis unit is responsible for collecting and analyzing market demand data, including food prices, demand trends and consumer preferences, to help relevant personnel understand the opportunities and challenges of the current market and select crop varieties and quantities suitable for the market; The supply chain management unit is used to monitor and manage the supply chain of crops, including production, picking, packaging, transportation and sales, and to reduce logistics costs, reduce product losses and provide better quality by optimizing the supply chain; The marketing strategy unit is used to support users in formulating marketing strategies, including pricing strategies, advertising and sales channel selection, and to improve the market visibility and competitiveness of products through precise market positioning and marketing strategies.

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