Intelligent agricultural planning decision-making system based on Internet of Things

Abstract

The invention belongs to the technical field of agricultural supervision, and particularly relates to an intelligent agricultural planning decision-making system based on the Internet of Things, which comprises a planting plan decision-making unit, a resource allocation decision-making unit, an irrigation and fertilization monitoring unit, an agricultural planting management and analysis unit and an agricultural management and control terminal, planting plan decision-making information is generated through the planting plan decision-making unit to improve planting benefits, and monitoring analysis of the resource distribution decision-making unit and the pest and disease damage monitoring decision-making unit is beneficial for achieving precise irrigation and fertilization and timely preventing and treating pest and disease damage. The irrigation and fertilization monitoring unit analyzes the nutrient water content suitability abnormal performance of the corresponding area in the detection period, enhances subsequent irrigation and fertilization supervision when an irrigation and fertilization alarm signal is generated, and comprehensively evaluates the planting management performance of the corresponding area when an irrigation and fertilization qualification signal is generated; and subsequent planting supervision is enhanced when the planting management alarm signal is generated, so that the growth of crops in corresponding areas is ensured, and the intelligent level is high.

Description

Technical Field

[0001] The present invention relates to the technical field of agricultural supervision, and in particular to an intelligent agricultural planning and decision-making system based on the Internet of Things. Background Art

[0002] Traditional agricultural production mainly relies on manual experience for management, and there are many drawbacks. On the one hand, there are problems of large errors and poor timeliness in manually monitoring environmental parameters and crop growth status, making it difficult to grasp the changes in the farmland environment in real time and accurately. On the other hand, the decision-making process lacks scientific basis, and operations such as irrigation, fertilization, and pest control are often carried out based on experience, which is likely to cause waste of resources, environmental pollution, and crop yield reduction. With the development of Internet of Things technology, agricultural Internet of Things systems are currently commonly used for agricultural planting management. However, most of them have single functions, making it difficult to achieve precise irrigation and fertilization and timely prevent and control pests and diseases. Moreover, they are unable to analyze the abnormal manifestations of nutrient and water suitability in corresponding areas and comprehensively evaluate the planting management performance of corresponding areas, which is not conducive to timely adjusting the agricultural planting supervision plan and ensuring the effective growth of crops in corresponding areas. In view of the above technical defects, a solution is now proposed. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent agricultural planning and decision-making system based on the Internet of Things, which solves the problems in the prior art that it is difficult to achieve precise irrigation and fertilization and timely prevent and control pests and diseases, and is unable to analyze the abnormal manifestations of nutrient and water suitability in corresponding areas and comprehensively evaluate the planting management performance of corresponding areas, which is not conducive to timely adjusting the agricultural planting supervision plan and ensuring the effective growth of crops in corresponding areas, with low intelligent level and great difficulty in agricultural planting management.

[0004] To achieve the above purpose, the present invention provides the following technical solutions: An intelligent agricultural planning and decision-making system based on the Internet of Things, including a planting plan decision-making unit, a resource allocation decision-making unit, a pest and disease monitoring decision-making unit, an irrigation and fertilization monitoring unit, an agricultural planting management analysis unit, and an agricultural control terminal; the planting plan decision-making unit generates planting plan decision-making information before agricultural planting, and sends the planting plan decision-making information to the agricultural control terminal, and conducts agricultural planting in each area according to the planting plan decision-making information. The resource allocation decision-making unit generates irrigation and fertilization decision-making information during agricultural planting, sends the irrigation and fertilization decision-making information to the agricultural control terminal, and conducts irrigation and fertilization in each area according to the irrigation and fertilization decision-making information; the pest and disease monitoring decision-making unit conducts pest and disease monitoring during agricultural planting and generates pest and disease control decision-making information, sends the pest and disease control decision-making information to the agricultural control terminal, and sprays pesticides in the corresponding area according to the pest and disease control decision-making information. The irrigation and fertilization monitoring unit analyzes the abnormal manifestations of nutrient and water suitability for the corresponding area during the detection period, generates an irrigation and fertilization alarm signal or an irrigation and fertilization qualified signal through the analysis, sends the irrigation and fertilization alarm signal to the agricultural control terminal, and sends the irrigation and fertilization qualified signal to the agricultural planting management analysis unit; The agricultural planting management analysis unit comprehensively evaluates the planting management performance for the corresponding area during the detection period, generates a planting management qualified signal or a planting management alarm signal accordingly, and sends the planting management qualified signal or the planting management alarm signal to the agricultural control terminal.

[0005] Furthermore, the operation process of the planting plan decision-making unit is as follows: Collect local climate data, soil data, and market demand information for various agricultural products, evaluate the suitable planting areas and planting potentials of different crops, and comprehensively analyze factors such as crop yield, quality, economic benefits, and ecological benefits using a multi-objective optimization decision-making model to provide decision-making suggestions for planting variety selection and planting area allocation.

[0006] Furthermore, the generation processes of irrigation and fertilization decision-making information and pest control decision-making information are as follows: Comprehensively analyze factors such as soil type, crop growth stage, and meteorological conditions through an irrigation decision-making model, and accordingly output the irrigation water volume and irrigation time. Also, use a nutrient balance model to determine the fertilization type, fertilization amount, and fertilization time based on the content of various nutrients in the soil and the nutrient absorption amount of the crop to generate irrigation and fertilization decision-making information; Through a pest monitor and image recognition technology, real-time monitor the occurrence of crop pests and diseases. According to the types of pests and diseases, the degree of occurrence, and the crop growth stage, use a pesticide application decision-making model to select the matching pesticide type, application dose, and application time to generate pest control decision-making information.

[0007] Furthermore, the specific analysis process of the irrigation and fertilization monitoring unit is as follows: Set several detection points in the corresponding area, collect the soil moisture content data of the corresponding detection points, obtain the types of various nutrient elements to be monitored in the corresponding area, and collect the concentrations of various nutrient elements in the soil of the corresponding detection points. Numerically compare the soil moisture content data and the concentrations of various nutrient elements with the preset suitable soil moisture content data range and the preset suitable concentration range of various nutrient elements respectively. If both the soil moisture content data and the concentrations of various nutrient elements are within the corresponding preset ranges, it is determined that the corresponding detection point is in a state of suitable nutrient and water content; otherwise, it is determined that the corresponding detection point is in a state of unsuitable nutrient and water content. Obtain the total duration during the detection period when the corresponding detection point is in a non-optimal state of nutrient water content and mark it as the non-optimal value of nutrient water content. Calculate the average value of the non-optimal values of nutrient water content for all detection points to obtain the irrigation and fertilization evaluation value. Compare the irrigation and fertilization evaluation value with the preset irrigation and fertilization evaluation threshold. If the irrigation and fertilization evaluation value exceeds the preset irrigation and fertilization evaluation threshold, generate an irrigation and fertilization alarm signal.

[0008] Furthermore, if the irrigation and fertilization evaluation value does not exceed the preset irrigation and fertilization evaluation threshold, compare the non-optimal value of nutrient water content of the corresponding detection point with the preset non-optimal threshold of nutrient water content. If the non-optimal value of nutrient water content exceeds the preset non-optimal threshold of nutrient water content, mark the corresponding detection point as a non-optimal point for irrigation and fertilization; If the non-optimal value of nutrient water content does not exceed the preset non-optimal threshold of nutrient water content, mark the number of occurrences when the single continuous duration during the detection period when the corresponding detection point is in a non-optimal state of nutrient water content exceeds the preset single continuous duration threshold as the irrigation and fertilization abnormal duration frequency. Compare the irrigation and fertilization abnormal duration frequency with the preset irrigation and fertilization abnormal duration frequency threshold. If the irrigation and fertilization abnormal duration frequency exceeds the preset irrigation and fertilization abnormal duration frequency threshold, mark the corresponding detection point as a non-optimal point for irrigation and fertilization; Obtain the number of non-optimal points for irrigation and fertilization in the corresponding area and calculate the ratio with the number of detection points to obtain the irrigation and fertilization abnormal occupancy value. Mark the largest non-optimal value of nutrient water content in the corresponding area as the abnormal amplitude value of nutrient water content. Calculate the comprehensive evaluation value of irrigation and fertilization by weighted summation of the irrigation and fertilization abnormal occupancy value, the irrigation and fertilization evaluation value, and the abnormal amplitude value of nutrient water content; Compare the comprehensive evaluation value of irrigation and fertilization with the preset comprehensive evaluation threshold of irrigation and fertilization. If the comprehensive evaluation value of irrigation and fertilization exceeds the preset comprehensive evaluation threshold of irrigation and fertilization, generate an irrigation and fertilization alarm signal; if the comprehensive evaluation value of irrigation and fertilization exceeds the preset comprehensive evaluation threshold of irrigation and fertilization, generate an irrigation and fertilization qualified signal.

[0009] Furthermore, the specific analysis process of the agricultural planting management analysis unit is as follows: Obtain the total amount of crop withering in the corresponding area during the detection period. Compare the total amount of crop withering with the preset total amount threshold of crop withering. If the total amount of crop withering exceeds the preset total amount threshold of crop withering, generate a planting management alarm signal; If the total amount of crop withering does not exceed the preset total amount threshold of crop withering, mark the number of occurrences when the single detection withering amount of the crop during the detection period exceeds the preset single detection withering amount threshold of the crop as the withering risk frequency value. Compare the withering risk frequency value with the preset withering risk frequency threshold. If the withering risk frequency value exceeds the preset withering risk frequency threshold, generate a planting management alarm signal; If the frequency value of the withering risk does not exceed the preset withering risk frequency threshold, the planting input cost during the detection period is obtained and the ratio of the planting input cost to the corresponding standard input cost is marked as the planting input value, and the equipment monitoring and evaluation value during the detection period is obtained. The planting management analysis value is calculated by performing a weighted sum of the total crop withering amount, the withering risk frequency value, the planting input value, and the equipment monitoring and evaluation value. The planting management analysis value is numerically compared with the preset planting management analysis threshold. If the planting management analysis value exceeds the preset planting management analysis threshold, a planting management alarm signal is generated; if the planting management analysis value does not exceed the preset planting management analysis threshold, a planting management qualified signal is generated.

[0010] Further, the agricultural planting management analysis unit is communicatively connected to the agricultural associated equipment monitoring unit. The agricultural associated equipment monitoring unit obtains all the agricultural equipment deployed in the corresponding area, monitors the operation of all the agricultural equipment in the corresponding area, analyzes to obtain the equipment monitoring and evaluation value during the detection period, and sends the equipment monitoring and evaluation value to the agricultural planting management analysis unit.

[0011] Further, the specific analysis process of the agricultural associated equipment monitoring unit is as follows: The moment when the corresponding agricultural equipment fails during the detection period is obtained and marked as the first moment, and the moment when the corresponding equipment is repaired to restore normal operation is collected and marked as the second moment. The interval duration between the first moment and the second moment is marked as the operation restoration duration; the operation restoration duration is numerically compared with the corresponding operation restoration duration threshold. If the operation restoration duration exceeds the preset operation restoration duration threshold, the corresponding operation restoration duration is marked as the warning restoration duration; The number of warning restoration durations corresponding to all agricultural equipment during the detection period is obtained and marked as the warning restoration detection value. The ratio of the operation restoration duration to the corresponding preset operation restoration duration threshold is calculated to obtain the operation restoration time occupancy value, and the average value of all operation restoration time occupancy values during the detection period is calculated to obtain the operation restoration situation value. The equipment monitoring and evaluation value is calculated by performing a weighted sum of the warning restoration detection value and the operation restoration situation value.

[0012] Compared with the prior art, the beneficial effects of the present invention are: 1. In the present invention, the planting plan decision unit provides decision suggestions for planting variety selection and planting area allocation before agricultural planting to improve planting efficiency. The monitoring and analysis of the resource allocation decision unit and the pest and disease monitoring decision unit are used to achieve precise irrigation and fertilization and timely control of pests and diseases. And through the irrigation and fertilization monitoring unit, the abnormal performance of the nutrient water suitability in the corresponding area during the detection period is analyzed. When generating an irrigation and fertilization alarm signal, the subsequent irrigation and fertilization supervision is strengthened, so that the soil environment of the crops in the corresponding area is maintained in a suitable state, ensuring the growth of the crops in the corresponding area. 2. In the present invention, the operation of all agricultural devices in the corresponding area is monitored by the agricultural-related device monitoring unit. Through analysis, the supervision performance of the agricultural devices in the corresponding area during the detection period is accurately fed back and data support is provided for the analysis process of the agricultural planting management analysis unit. When generating the qualified signal for irrigation and fertilization, the agricultural planting management analysis unit comprehensively evaluates the planting management performance in the corresponding area during the detection period. When generating the planting management alarm signal, subsequent planting supervision is strengthened to further ensure the growth of crops in the corresponding area, with a high level of intelligence. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] For the convenience of those skilled in the art to understand, the present invention will be further described below in conjunction with the accompanying drawings; Figure 1 It is the system block diagram of the first embodiment in the present invention; Figure 2 It is the system block diagram of the second embodiment in the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0014] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention.

[0015] Embodiment 1: As Figure 1 shown, an intelligent agricultural planning and decision-making system based on the Internet of Things proposed by the present invention includes a planting plan decision-making unit, a resource allocation decision-making unit, a pest and disease monitoring decision-making unit, an irrigation and fertilization monitoring unit, an agricultural planting management analysis unit, and an agricultural control terminal; Before agricultural planting, the planting plan decision-making unit collects local climate data (such as annual average temperature, precipitation, sunshine duration, etc.), soil data (such as soil type, fertility status, pH value, etc.), and market demand information of various agricultural products (such as price trends of agricultural products, consumer preferences, etc.), and evaluates the suitable planting areas and planting potentials of different crops; and uses a multi-objective optimization decision-making model to comprehensively analyze factors such as crop yield, quality, economic benefits, and ecological benefits, and provides decision-making suggestions for the selection of planting varieties and the allocation of planting areas to generate planting plan decision-making information. For example, in areas with high soil fertility and sufficient water sources, high-yield and high-quality crop varieties are preferentially recommended, and in areas with strong market demand, the planting area of the corresponding crops is appropriately increased; and the planting plan decision-making information is sent to the agricultural control terminal through the Internet of Things, and agricultural planting in each area is carried out according to the planting plan decision-making information, which is beneficial to improving planting efficiency.

[0016] The resource allocation decision-making unit comprehensively analyzes factors such as soil type, crop growth stage, and meteorological conditions through an irrigation decision-making model during the agricultural planting process, and outputs the irrigation water volume and irrigation time accordingly. For example, in the dry season, increase the irrigation frequency and water volume; during the critical growth period of the crop, ensure sufficient water supply; and use the nutrient balance model to determine the type, amount, and time of fertilization based on the content of various nutrients in the soil and the nutrient absorption of the crop to generate irrigation and fertilization decision-making information, and send the irrigation and fertilization decision-making information to the agricultural control terminal through the Internet of Things, and perform irrigation and fertilization in each area according to the irrigation and fertilization decision-making information.

[0017] The pest and disease monitoring decision-making unit monitors pests and diseases during the agricultural planting process. Through pest and disease monitors and image recognition technology, it monitors the occurrence of crop pests and diseases in real time. According to the types of pests and diseases, the degree of occurrence, and the crop growth stage, it uses a pesticide use decision-making model to select the matching pesticide type, dosage, and application time to generate pest and disease control decision-making information, and sends the pest and disease control decision-making information to the agricultural control terminal through the Internet of Things, and sprays pesticides in the corresponding area according to the pest and disease control decision-making information to achieve precise control and reduce the pollution of pesticides to the environment and agricultural products.

[0018] The irrigation and fertilization monitoring unit analyzes the abnormal manifestations of nutrient and water suitability in the corresponding area during the detection period (preferably, the detection period is 20 days), generates an irrigation and fertilization alarm signal or an irrigation and fertilization qualified signal through the analysis, and sends the irrigation and fertilization alarm signal to the agricultural control terminal; When the agricultural control terminal receives the irrigation and fertilization alarm signal, it issues a corresponding warning to remind agricultural managers to strengthen the subsequent supervision of irrigation and fertilization, which is conducive to maintaining the soil environment of the crops in the corresponding area in a suitable state, thereby ensuring the growth of the crops in the corresponding area; it should be noted that the specific analysis process of the irrigation and fertilization monitoring unit is as follows: Set several detection points in the corresponding area, collect the soil moisture content data of the corresponding detection points, and obtain the types of various nutrient elements to be monitored in the corresponding area (such as nitrogen, phosphorus, potassium fertilizers, etc.), and collect the concentrations of various nutrient elements in the soil of the corresponding detection points, and compare the soil moisture content data and the concentrations of various nutrient elements with the preset suitable soil moisture content data range and the preset suitable concentration range of various nutrient elements respectively; If the soil moisture content data and the concentrations of various nutrient elements are all within the corresponding preset ranges, indicating that the soil environmental conditions of the corresponding detection points are good and conducive to the growth of the corresponding crops, then it is judged that the corresponding detection points are in a state of suitable nutrient and water content, otherwise it is judged that the corresponding detection points are in a state of unsuitable nutrient and water content; Obtain the total duration during the detection period when the corresponding detection point is in a non-optimal state of nutrient water content and mark it as the non-optimal value of nutrient water content. Calculate the average value of the non-optimal values of nutrient water content for all detection points to obtain the irrigation and fertilization evaluation value. Compare the irrigation and fertilization evaluation value with the preset irrigation and fertilization evaluation threshold. If the irrigation and fertilization evaluation value exceeds the preset irrigation and fertilization evaluation threshold, it indicates that the implementation status of irrigation and fertilization for the corresponding area during the detection period is poor, and then generate an irrigation and fertilization alarm signal.

[0019] Furthermore, if the irrigation and fertilization evaluation value does not exceed the preset irrigation and fertilization evaluation threshold, then compare the non-optimal value of nutrient water content of the corresponding detection point with the preset non-optimal threshold of nutrient water content. If the non-optimal value of nutrient water content exceeds the preset non-optimal threshold of nutrient water content, it indicates that the management status of irrigation and fertilization for the corresponding detection point during the detection period is poor, and then mark the corresponding detection point as a non-good point for irrigation and fertilization; If the non-optimal value of nutrient water content does not exceed the preset non-optimal threshold of nutrient water content, then mark the number of occurrences when the single continuous duration during the detection period when the corresponding detection point is in a non-optimal state of nutrient water content exceeds the preset single continuous duration threshold as the irrigation and fertilization different duration frequency. Compare the irrigation and fertilization different duration frequency with the preset irrigation and fertilization different duration frequency threshold. If the irrigation and fertilization different duration frequency exceeds the preset irrigation and fertilization different duration frequency threshold, it indicates that the overall management status of irrigation and fertilization for the corresponding detection point during the detection period is poor, and then mark the corresponding detection point as a non-good point for irrigation and fertilization; Obtain the number of non-good points for irrigation and fertilization in the corresponding area and calculate the ratio with the number of detection points to obtain the irrigation and fertilization different occupancy value. And mark the largest non-optimal value of nutrient water content in the corresponding area as the non-optimal amplitude value of nutrient water content. Calculate the comprehensive evaluation value of irrigation and fertilization by weighted summing the irrigation and fertilization different occupancy value, the irrigation and fertilization evaluation value, and the non-optimal amplitude value of nutrient water content; That is, assign corresponding preset weight coefficients to the irrigation and fertilization different occupancy value, the irrigation and fertilization evaluation value, and the non-optimal amplitude value of nutrient water content respectively. Multiply the irrigation and fertilization different occupancy value, the irrigation and fertilization evaluation value, and the non-optimal amplitude value of nutrient water content by the corresponding preset weight coefficients respectively. And mark the sum value of the three groups of product results as the comprehensive evaluation value of irrigation and fertilization; Moreover, the larger the value of the comprehensive evaluation value of irrigation and fertilization, the worse the overall implementation status of irrigation and fertilization for the corresponding area during the detection period; Compare the comprehensive evaluation value of irrigation and fertilization with the preset comprehensive evaluation threshold of irrigation and fertilization. If the comprehensive evaluation value of irrigation and fertilization exceeds the preset comprehensive evaluation threshold of irrigation and fertilization, it indicates that the overall implementation status of irrigation and fertilization for the corresponding area during the detection period is poor, and then generate an irrigation and fertilization alarm signal; If the comprehensive evaluation value of irrigation and fertilization exceeds the preset comprehensive evaluation threshold of irrigation and fertilization, it indicates that the overall implementation status of irrigation and fertilization for the corresponding area during the detection period is good, and then generate an irrigation and fertilization qualified signal.

[0020] The irrigation and fertilization monitoring unit sends the qualified signal of irrigation and fertilization to the agricultural planting management analysis unit. The agricultural planting management analysis unit comprehensively evaluates the planting management performance of the corresponding area during the detection period, and generates a qualified signal or an alarm signal for planting management accordingly; And send the qualified signal or the alarm signal for planting management to the agricultural control terminal. When the agricultural control terminal receives the alarm signal for planting management, it issues a corresponding warning to remind agricultural managers to adjust the subsequent agricultural planting supervision plan in time, strengthen the subsequent planting supervision, and further ensure the growth of crops in the corresponding area, with a high level of intelligence. The specific analysis process of the agricultural planting management analysis unit is as follows: Obtain the total crop withering amount in the corresponding area during the detection period (that is, the sum of the crop withering amounts found in several detection processes during the detection period), and compare the total crop withering amount with the preset total crop withering amount threshold. If the total crop withering amount exceeds the preset total crop withering amount threshold, it indicates that the planting management performance of the corresponding area during the detection period is poor, and an alarm signal for planting management is generated; If the total crop withering amount does not exceed the preset total crop withering amount threshold, then mark the number of occurrences of the single - detection crop withering amount (that is, the crop withering amount found in the corresponding detection process) exceeding the preset single - detection crop withering amount threshold during the detection period as the withering risk frequency value, and compare the withering risk frequency value with the preset withering risk frequency threshold. If the withering risk frequency value exceeds the preset withering risk frequency threshold, it indicates that the planting management performance of the corresponding area during the detection period is poor, and an alarm signal for planting management is generated; If the withering risk frequency value does not exceed the preset withering risk frequency threshold, then obtain the planting input cost during the detection period and mark the ratio of it to the corresponding standard input cost as the planting input value, and obtain the equipment monitoring evaluation value during the detection period; Calculate the planting management analysis value by weighted summation of the total crop withering amount, the withering risk frequency value, the planting input value, and the equipment monitoring evaluation value; that is, assign corresponding preset weight coefficients to the total crop withering amount, the withering risk frequency value, the planting input value, and the equipment monitoring evaluation value respectively, multiply the total crop withering amount, the withering risk frequency value, the planting input value, and the equipment monitoring evaluation value by the corresponding preset weight coefficients respectively, and mark the sum value of the four groups of product results as the planting management analysis value; moreover, the larger the value of the planting management analysis value, the worse the comprehensive planting management performance of the corresponding area during the detection period; Numerically compare the planting management analysis value with the preset planting management analysis threshold. If the planting management analysis value exceeds the preset planting management analysis threshold, it indicates that the overall planting management performance for the corresponding area during the detection period is relatively poor, and a planting management alarm signal is generated; if the planting management analysis value does not exceed the preset planting management analysis threshold, it indicates that the overall planting management performance for the corresponding area during the detection period is relatively good, and a planting management qualified signal is generated.

[0021] Embodiment 2: As Figure 2 shown, the difference between this embodiment and Embodiment 1 is that the agricultural planting management analysis unit is communicatively connected to the agricultural associated equipment monitoring unit. The agricultural associated equipment monitoring unit acquires all agricultural equipment (including irrigation equipment, fertilization equipment, ventilation equipment, etc.) arranged in the corresponding area and monitors the operation of all agricultural equipment in the corresponding area; By analyzing to obtain the equipment monitoring evaluation value during the detection period and sending the equipment monitoring evaluation value to the agricultural planting management analysis unit, it can not only accurately reflect the supervision performance of agricultural equipment in the corresponding area during the detection period, but also provide data support for the analysis process of the agricultural planting management analysis unit, thus facilitating the guarantee of its analysis comprehensiveness and analysis result accuracy; among them, the specific analysis process of the agricultural associated equipment monitoring unit is as follows: Obtain the moment when the corresponding agricultural equipment fails during the detection period and mark it as the first moment, and collect the moment when the corresponding equipment is repaired to restore normal operation and mark it as the second moment. Mark the interval duration between the first moment and the second moment as the operation restoration duration; numerically compare the operation restoration duration with the corresponding operation restoration duration threshold. If the operation restoration duration exceeds the preset operation restoration duration threshold, it indicates that the processing efficiency of the corresponding equipment failure is slow, and mark the corresponding operation restoration duration as the alarm restoration duration; Obtain the quantity of the alarm restoration durations corresponding to all agricultural equipment during the detection period and mark it as the alarm restoration detection value, calculate the ratio of the operation restoration duration to the corresponding preset operation restoration duration threshold to obtain the operation restoration time occupancy value, and calculate the average value of all operation restoration time occupancy values during the detection period to obtain the operation restoration situation value; Calculate the equipment monitoring evaluation value by performing weighted summation on the alarm restoration detection value and the operation restoration situation value, that is, assign corresponding preset weight coefficients to the alarm restoration detection value and the operation restoration situation value, multiply the alarm restoration detection value and the operation restoration situation value by the corresponding preset weight coefficients respectively, and calculate the sum of the two product results to obtain the equipment monitoring evaluation value; moreover, the larger the value of the equipment monitoring evaluation value, the worse the supervision performance of agricultural equipment in the corresponding area during the detection period.

[0022] Working principle of the present invention: When in use, the planting plan decision-making unit provides decision-making suggestions for variety selection and planting area allocation before agricultural planting to generate planting plan decision-making information, which is beneficial to improving planting efficiency. The resource allocation decision-making unit generates irrigation and fertilization decision-making information during agricultural planting and sends it to the agricultural control terminal. The pest and disease monitoring decision-making unit monitors pests and diseases during agricultural planting and generates pest and disease control decision-making information, realizing precise irrigation and fertilization and being beneficial to pest and disease control. Moreover, the irrigation and fertilization monitoring unit analyzes the abnormal manifestations of nutrient water suitability for the corresponding area during the detection period, strengthens the subsequent irrigation and fertilization supervision when generating an irrigation and fertilization alarm signal, which is beneficial to maintaining the soil environment of the crops in the corresponding area in a suitable state, thereby ensuring the growth of the crops in the corresponding area. And when generating an irrigation and fertilization qualified signal, the agricultural planting management analysis unit comprehensively evaluates the planting management performance for the corresponding area during the detection period, strengthens the subsequent planting supervision when generating a planting management alarm signal, and further ensures the growth of the crops in the corresponding area, with a high level of intelligence.

[0023] The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific implementation manners. Obviously, many modifications and variations can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principle and practical application of the present invention, so that those skilled in the art in the relevant technical field can well understand and utilize the present invention. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent agricultural planning and decision-making system based on the Internet of Things, characterized in that, It includes a planting plan decision-making unit, a resource allocation decision-making unit, a pest and disease monitoring decision-making unit, an irrigation and fertilization monitoring unit, an agricultural planting management analysis unit, and an agricultural control terminal; the planting plan decision-making unit generates planting plan decision-making information before agricultural planting, and conducts agricultural planting in each region according to the planting plan decision-making information. The resource allocation decision-making unit generates irrigation and fertilization decision-making information during agricultural planting, and conducts irrigation and fertilization in each region according to the irrigation and fertilization decision-making information; the pest and disease monitoring decision-making unit conducts pest and disease monitoring during agricultural planting and generates pest and disease control decision-making information, and sprays pesticides in the corresponding region according to the pest and disease control decision-making information. The irrigation and fertilization monitoring unit analyzes the abnormal performance of nutrient water suitability for the corresponding region during the detection period, generates an irrigation and fertilization alarm signal or an irrigation and fertilization qualified signal through the analysis, sends the irrigation and fertilization alarm signal to the agricultural control terminal, and sends the irrigation and fertilization qualified signal to the agricultural planting management analysis unit; the agricultural planting management analysis unit comprehensively evaluates the planting management performance for the corresponding region during the detection period, generates a planting management qualified signal or a planting management alarm signal accordingly, and sends the planting management qualified signal or the planting management alarm signal to the agricultural control terminal.

2. The intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 1, characterized in that, The operation process of the planting plan decision-making unit is as follows: Collect local climate data, soil data, and market demand information for various agricultural products, evaluate the suitable planting areas and planting potentials of different crops, and comprehensively analyze factors such as crop yield, quality, economic benefits, and ecological benefits using a multi-objective optimization decision-making model to provide decision-making suggestions for planting variety selection and planting area allocation.

3. An intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 1, characterized in that, The generation processes of the irrigation and fertilization decision-making information and the pest and disease control decision-making information are as follows: Comprehensively analyze factors such as soil type, crop growth stage, and meteorological conditions through an irrigation decision-making model, and accordingly output the irrigation water volume and irrigation time, and use a nutrient balance model to determine the fertilization type, fertilization amount, and fertilization time based on the content of various nutrients in the soil and the nutrient absorption amount of the crop to generate the irrigation and fertilization decision-making information; Through a pest and disease monitor and image recognition technology, monitor the occurrence of crop pests and diseases in real time, and select the matching pesticide type, dosage, and application time using a pesticide application decision-making model according to the pest and disease type, occurrence degree, and crop growth stage to generate the pest and disease control decision-making information.

4. An intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 1, characterized in that, The specific analysis process of the irrigation and fertilization monitoring unit is as follows: Set several detection points in the corresponding region, obtain the total duration of the nutrient water non-suitable state of the corresponding detection points during the detection period and mark it as the nutrient water non-suitable value, calculate the average value of the nutrient water non-suitable values of all detection points to obtain the irrigation and fertilization evaluation value. If the irrigation and fertilization evaluation value exceeds the preset irrigation and fertilization evaluation threshold, an irrigation and fertilization alarm signal is generated.

5. The intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 4, characterized in that, If the irrigation and fertilization evaluation value does not exceed the preset irrigation and fertilization evaluation threshold, the comprehensive irrigation and fertilization evaluation value is calculated by weighted summation of the irrigation application difference value, the irrigation and fertilization evaluation value, and the nutrient water content difference value; if the comprehensive irrigation and fertilization evaluation value exceeds the preset comprehensive irrigation and fertilization evaluation threshold, an irrigation and fertilization alarm signal is generated; if the comprehensive irrigation and fertilization evaluation value exceeds the preset comprehensive irrigation and fertilization evaluation threshold, an irrigation and fertilization qualified signal is generated.

6. The intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 1, characterized in that, The specific analysis process of the agricultural planting management analysis unit is as follows: The total amount of crop wilt in the corresponding area during the detection period is obtained. If the total amount of crop wilt exceeds the preset total crop wilt threshold, a planting management alarm signal is generated; if the total amount of crop wilt does not exceed the preset total crop wilt threshold, the number of occurrences of the single detection of crop wilt exceeding the preset single detection of crop wilt threshold during the detection period is marked as the wilt risk frequency value. If the wilt risk frequency value exceeds the preset wilt risk frequency threshold, a planting management alarm signal is generated; If the wilt risk frequency value does not exceed the preset wilt risk frequency threshold, the planting management analysis value is calculated by weighted summation of the total amount of crop wilt, the wilt risk frequency value, the planting input value, and the equipment monitoring evaluation value; If the planting management analysis value exceeds the preset planting management analysis threshold, a planting management alarm signal is generated; if the planting management analysis value does not exceed the preset planting management analysis threshold, a planting management qualified signal is generated.

7. An intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 6, characterized in that, The agricultural planting management analysis unit is communicatively connected to the agricultural associated equipment monitoring unit. The agricultural associated equipment monitoring unit obtains all the agricultural equipment deployed in the corresponding area, monitors the operation of all the agricultural equipment in the corresponding area, analyzes to obtain the equipment monitoring evaluation value during the detection period, and sends the equipment monitoring evaluation value to the agricultural planting management analysis unit.

8. An intelligent agricultural planning and decision-making system based on the Internet of Things according to claim 7, characterized in that, The specific analysis process of the agricultural associated equipment monitoring unit is as follows: The number of alarm recovery durations corresponding to all agricultural equipment during the detection period is obtained and marked as the alarm recovery detection value, and the ratio of the operation recovery duration to the corresponding preset operation recovery duration threshold is calculated to obtain the operation recovery time occupancy value. The average value of all the operation recovery time occupancy values during the detection period is calculated to obtain the operation recovery situation value. The equipment monitoring evaluation value is calculated by weighted summation of the alarm recovery detection value and the operation recovery situation value.

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