Monitoring method and system based on agricultural Internet of Things

Abstract

The invention discloses a monitoring method and system based on agricultural Internet of Things, and relates to the technical field of intelligent agricultural monitoring. A data acquisition module is utilized to acquire real-time data and historical data related to soil humidity, temperature and irrigation volume, and a data processing module is utilized to process the real-time data and historical data. A soil humidity condition index TS, an irrigation demand GG and an irrigation equipment operation state adjustment value TZ are calculated and output respectively, the irrigation equipment operation state adjustment value TZ is automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment based on the irrigation equipment operation state adjustment value TZ, and a monitoring and feedback module is used for monitoring the irrigation equipment based on the agricultural Internet of Things. According to the crop growth environment real-time monitoring and precise irrigation system, real-time monitoring and precise irrigation of the crop growth environment are achieved through the integrated sensor technology, the communication technology, the data processing technology and the intelligent control technology.

Description

Technical Field

[0001] The present invention relates to the field of smart agricultural monitoring technology, and in particular to a monitoring method and system based on agricultural Internet of Things. Background Art

[0002] The Internet of Things is an important part of the new generation of information technology. It connects any object to the Internet through radio frequency identification, various sensors, global positioning system, laser scanner information sensing equipment, according to the agreed protocol, to exchange and communicate information, so as to realize the intelligent identification, positioning, tracking, monitoring and management of objects. The Internet of Things technology has broad application prospects, especially in the field of agriculture. It can realize the intelligent and refined management of the entire process of agricultural production. With the development of embedded technology and wireless sensor technology, the Internet of Things technology has been widely used in the field of agriculture.

[0003] With the development of modern agriculture, accurate monitoring and management of the crop growth environment has become increasingly important. However, existing technologies often rely on fixed irrigation time and amount, and cannot be flexibly adjusted according to the actual needs of crops and environmental changes, which leads to waste of water resources and poor crop growth. In addition, existing technologies lack the ability to monitor the crop growth environment in real time, and cannot promptly discover and respond to the impact of environmental changes on crop growth. In addition, when processing large amounts of sensor data, existing technologies often have insufficient data processing capabilities, resulting in the inability to effectively utilize the data. In addition, the irrigation equipment control of existing technologies often relies on manual operation and simple timing control, and cannot achieve intelligent control and adaptive adjustment. Summary of the invention

[0004] The purpose of the present invention is to provide a monitoring method and system based on agricultural Internet of Things, which solves the problems raised in the above background technology.

[0005] To achieve the above purpose, the present invention provides a monitoring method based on agricultural Internet of Things, and the specific implementation steps are as follows: Step 1: Use the data acquisition module to collect real-time and historical data related to soil moisture, temperature, and irrigation volume; Step 2: Using the data processing module, respectively calculate and output the soil moisture index TS, the irrigation demand GG, and the irrigation equipment operation status adjustment value TZ; Step 3: Based on the operation status of the irrigation equipment, the adjustment value TZ of the operation status of the irrigation equipment will be automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment; Step 4: Use the monitoring and feedback module to monitor the adjusted soil moisture, temperature and operating status of the irrigation equipment in real time; The data processing module includes a unit for determining the current soil moisture status, a unit for reflecting the actual irrigation demand of crops in the current stage and environment, and a unit for adjusting the operating status of irrigation equipment.

[0006] Optionally, the equipment used in the data acquisition module includes a soil moisture sensor, a temperature sensor, and irrigation equipment; The equipment used in the data processing module includes a data processing center; The equipment used in the monitoring and feedback module includes monitoring and control equipment.

[0007] Optionally, the calculation formula for determining the current soil moisture status unit is as follows: ; P=W best -W; in: TS is the soil moisture status index; S is the current humidity; S avg is the historical humidity average; G is the number of dry days, which means the number of consecutive dry days monitored recently; P is the temperature deviation; W best is the suitable growth temperature, W is the current temperature, W best Reflects the temperature at the time when the crop yield reached its maximum value during historical monitoring, and is updated and iterated based on continuous monitoring; Half of the current humidity S is added to reflect the positive impact of the current humidity S on irrigation demand.

[0008] Optionally, the historical humidity average S avg The calculation formula is as follows: S avg =(S1+S2+S3+......+S n ) / n; n is the total number of historical monitoring times; S1 is the first humidity monitoring, S2 is the second humidity monitoring, S3 is the third humidity monitoring, S n Monitor humidity for the nth time.

[0009] Optionally, the calculation formula reflecting the actual irrigation demand unit of crops in the current stage and environment is as follows: ; in: GG is the irrigation demand; TS bestTS is the soil moisture index suitable for growth. best The temperature and humidity at the time reflecting the maximum value of crop yield during the historical monitoring process are substituted into the current soil moisture condition determination unit, and the output soil moisture condition index TS is calculated and output, and the index is changed and iterated according to continuous monitoring; X is the irrigation rate, X represents the amount of irrigation that the irrigation equipment can provide per hour; GG avg is the historical average irrigation demand, GG avg Reflecting the average value of the historical data result value calculated by using the unit reflecting the actual irrigation demand of the crop in the current stage and environment; S×0.5 also adds half of the current humidity S, reflecting the positive impact of the current humidity S on irrigation demand.

[0010] Optionally, the historical average irrigation demand GG avg The calculation formula is as follows: GG avg =(GG1+GG2+GG3+......+GG n ) / n; GG1 is the first monitoring of irrigation demand, GG2 is the first monitoring of irrigation demand, GG3 is the first monitoring of irrigation demand, GG n The first monitoring humidity S1 corresponds to the first monitoring irrigation demand GG1, the second monitoring humidity S2 corresponds to the second monitoring irrigation demand GG2, the third monitoring humidity S3 corresponds to the third monitoring irrigation demand GG3, and the nth monitoring humidity S n and the nth monitored irrigation demand GG n Monitoring correspondence.

[0011] Optionally, the calculation formula of the irrigation equipment operation status adjustment unit is as follows: ; in: TZ is the adjustment value of the irrigation equipment operation status; GG old Monitor irrigation requirements for the previous time; TZ old Adjust the value of the irrigation equipment operation status monitored last time; TZ old ×0.2The previous monitoring irrigation equipment operation status adjustment value TZ old 20% is added to reflect the continuous state of operating status adjustment.

[0012] Optionally, based on the irrigation equipment operation state adjustment value TZ, the irrigation equipment operation state adjustment value TZ is automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment. After the adjustment, the irrigation equipment intelligently adjusts the irrigation amount and time automatically, and the values ​​monitored by the current humidity S, the current temperature W and the irrigation rate X will change in real time. If the result value of the irrigation equipment operation status adjustment value TZ is small, it reflects that the degree of monitoring that needs adjustment is small, and the real-time changes in the monitoring of the current humidity S, the current temperature W, and the irrigation rate X are small; If the result value of the irrigation equipment operation status adjustment value TZ is large, it reflects that the degree of monitoring that needs adjustment is large, and the real-time monitoring changes of the current humidity S, the current temperature W and the irrigation rate X are large.

[0013] We also provide monitoring systems based on agricultural IoT, including: Data acquisition module, used to collect real-time and historical data related to soil moisture, temperature, and irrigation volume; A data processing module is used to calculate and output the soil moisture index TS, the irrigation demand GG and the irrigation equipment operation status adjustment value TZ; Wherein, the data processing module includes a unit for determining the current soil moisture status, a unit for reflecting the actual irrigation demand of crops in the current stage and environment, and a unit for adjusting the operating status of irrigation equipment; The monitoring and feedback module is used to monitor the soil moisture, temperature and operating status of the irrigation equipment in real time after feedback adjustment.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention can automatically adjust the irrigation strategy according to the actual needs of crops and environmental changes by determining the current soil moisture status unit, reflecting the actual irrigation demand unit of crops in the current stage and environment, and calculating and analyzing the irrigation equipment operation status adjustment unit, so as to achieve precise irrigation, thereby improving the utilization efficiency of water resources and promoting the healthy growth of crops.

[0015] 2. The monitoring method based on the agricultural Internet of Things of the present invention can monitor the information of the crop growth environment in real time, including the current humidity S and the current temperature W, and timely discover potential problems and make timely adjustments through data analysis, which helps to timely discover and respond to the impact of environmental changes on crop growth.

[0016] 3. The method of the present invention integrates advanced data processing technology, can efficiently process and analyze a large amount of sensor data, extract useful information for the formulation and adjustment of irrigation strategies, and intelligently control the operating state of the irrigation equipment through the calculation of the irrigation equipment operating state adjustment unit, realize adaptive adjustment and intelligent control, thereby further improving the utilization efficiency of the irrigation equipment and reducing the cost and complexity of manual operation.

[0017] 4. The current soil moisture status unit of the present invention forms a circular dependency relationship between the actual irrigation demand unit of crops in the current stage and environment and the irrigation equipment operation status adjustment unit, which means that the adjustment of the irrigation strategy will indirectly affect the environmental factors of soil moisture and surface temperature, thereby forming a dynamic and continuously optimized system, which helps to continuously improve the accuracy and adaptability of the irrigation strategy. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 The method flow chart of the monitoring method based on agricultural Internet of Things; Figure 2 It is a structural schematic diagram of the data processing module of the present invention; Figure 3 Schematic diagram of the adjustment feedback of the monitoring method based on agricultural Internet of Things. DETAILED DESCRIPTION

[0019] 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.

[0020] This monitoring method based on agricultural Internet of Things is different from traditional irrigation methods. Traditional irrigation methods often rely on manual experience and timed irrigation, and cannot be flexibly adjusted according to the actual needs of crops, resulting in waste of water resources and poor crop growth. There is a lack of real-time monitoring, insufficient data processing capabilities, and unintelligent control of irrigation equipment. This algorithm unit integrates sensor technology, communication technology, data processing technology, and intelligent control technology to achieve real-time monitoring of the crop growth environment and precise irrigation.

[0021] For examples, see Figures 1 to 3 ,This implementation provides a monitoring method based on agricultural Internet of Things, and the specific implementation steps are as follows: Step 1: Use the data acquisition module to collect real-time and historical data related to soil moisture, temperature, and irrigation volume; Step 2: Using the data processing module, respectively calculate and output the soil moisture index TS, the irrigation demand GG, and the irrigation equipment operation status adjustment value TZ; Step 3: Based on the operation status of the irrigation equipment, the adjustment value TZ of the operation status of the irrigation equipment will be automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment; Step 4: Use the monitoring and feedback module to monitor the adjusted soil moisture, temperature and operating status of the irrigation equipment in real time; The data processing module includes a unit for determining the current soil moisture status, a unit for reflecting the actual irrigation demand of crops in the current stage and environment, and a unit for adjusting the operating status of irrigation equipment; The equipment used in the data acquisition module includes soil moisture sensors, temperature sensors, and irrigation equipment; The equipment used in the data processing module includes a data processing center; The equipment used in the monitoring and feedback module includes monitoring and control equipment; The monitoring system based on the monitoring method of agricultural Internet of Things includes: Data acquisition module, used to collect real-time and historical data related to soil moisture, temperature, and irrigation volume; A data processing module is used to calculate and output the soil moisture index TS, the irrigation demand GG and the irrigation equipment operation status adjustment value TZ; Wherein, the data processing module includes a unit for determining the current soil moisture status, a unit for reflecting the actual irrigation demand of crops in the current stage and environment, and a unit for adjusting the operating status of irrigation equipment; The monitoring and feedback module is used to monitor the soil moisture, temperature and operating status of the irrigation equipment in real time after feedback adjustment.

[0022] In summary, this embodiment is based on the monitoring method of the agricultural Internet of Things, and realizes intelligent control of irrigation equipment by collecting and analyzing the environmental information and growth information of crops. The method includes data collection, data preprocessing, soil moisture calculation, irrigation demand calculation, irrigation equipment operation status adjustment and irrigation equipment control steps, and involves a data acquisition module, a data processing module and a monitoring and feedback module and unit. At the same time, the method also relies on the support of soil moisture sensors, temperature sensors, irrigation equipment, data processing centers and control equipment.

[0023] In this embodiment, the system, through the mutual cooperation of three algorithm units, jointly constitutes the core part of the monitoring method based on the agricultural Internet of Things. Combined with the three operation results of TS, GG and TZ, through the calculation and analysis of these formulas, we can realize the precise monitoring of the growth environment of crops and the intelligent control of irrigation equipment. TS is the soil moisture condition index. This value can reflect the actual moisture condition of the soil under the current environmental conditions. This is the basis for formulating a reasonable irrigation strategy for the subsequent irrigation demand calculation and irrigation equipment operation state adjustment. GG is the irrigation demand. This demand can reflect the actual irrigation demand of crops under the current growth stage and environmental conditions. This is for the intelligent control of irrigation equipment and the formulation of optimized irrigation strategies to ensure the healthy growth of crops and avoid the waste of water resources. TZ is the irrigation equipment operation state adjustment value. This value can guide the irrigation equipment to make intelligent adjustments according to the current irrigation demand and environmental conditions. The intelligent adjustment ensures that the irrigation equipment operates in the most suitable growth state. At the same time, flexible irrigation operations are performed according to actual needs. The calculation result of TZ will directly affect the calculation of TS and GG, so that the three algorithm units together constitute a closed-loop feedback control system, realizing precise monitoring of the growth environment of crops and intelligent irrigation.

[0024] See also Figures 1 to 3 , the calculation formula for determining the current soil moisture status unit is as follows: ; P=W best -W; in: TS is the soil moisture status index; S is the current humidity; S avg is the historical humidity average; G is the number of dry days, which means the number of consecutive dry days monitored recently; P is the temperature deviation; W best is the suitable growth temperature, W is the current temperature, W best Reflects the temperature at the time when the crop yield reached its maximum value during historical monitoring, and is updated and iterated based on continuous monitoring; Half of the current humidity S is added to reflect the positive impact of the current humidity S on irrigation demand; Historical humidity average S avg The calculation formula is as follows: S avg =(S1+S2+S3+......+S n ) / n; n is the total number of historical monitoring times; S1 is the first humidity monitoring, S2 is the second humidity monitoring, S3 is the third humidity monitoring, S n Monitor humidity for the nth time.

[0025] In this embodiment: First, in this algorithm unit, "S×S avg The calculation part of " calculates the product of the current soil moisture sensor reading and the historical average soil moisture. This product reflects the current humidity S and the historical humidity average S avg If the current humidity S is high and the historical humidity average S avg It is also relatively high, indicating that the current humidity S is close to the historical average and does not require excessive irrigation. The calculation part of " calculates the product of the sum of the number of dry days G, the square root of the temperature deviation P and half of the soil moisture sensor reading. This product introduces the impact of the number of dry days G and the temperature deviation P on the current humidity S. The more dry days G, the drier the soil is and more irrigation is needed. The square root of the temperature deviation P is used to smooth the impact of temperature on the current humidity S, while half of the current humidity S reflects the direct contribution of the current soil moisture. This algorithm introduces the historical humidity average S avg The parameters of the current soil moisture status unit and the number of dry days G enable the unit to fully reflect the soil moisture status, avoiding the error caused by a single sensor reading. The introduction of the square root of the temperature deviation P smoothes the effect of temperature on soil moisture, improving the accuracy of humidity monitoring. The accurate soil moisture status index TS provides basic data for the calculation of irrigation demand, which helps agricultural managers make scientific and reasonable irrigation decisions based on real-time soil moisture conditions. By comparing the current humidity S with the historical humidity average S avg The difference in soil moisture can determine whether irrigation is needed and the urgency of irrigation. Accurate soil moisture monitoring helps avoid over-irrigation and insufficient water problems, thereby achieving water-saving irrigation and reducing water waste.

[0026] See also Figures 1 to 3 , the calculation formula reflecting the actual irrigation demand unit of crops in the current stage and environment is as follows: ; in: GG is the irrigation demand; TS best TS is the soil moisture index suitable for growth. best The temperature and humidity at the time reflecting the maximum value of crop yield during the historical monitoring process are substituted into the current soil moisture condition determination unit, and the output soil moisture condition index TS is calculated and output, and the index is changed and iterated according to continuous monitoring; X is the irrigation rate, X represents the amount of irrigation that the irrigation equipment can provide per hour; GG avg is the historical average irrigation demand, GG avg Reflecting the average value of the historical data result value calculated by using the unit reflecting the actual irrigation demand of the crop in the current stage and environment; S×0.5 also adds half of the current humidity S, reflecting the positive impact of the current humidity S on irrigation demand; Historical average irrigation demand GG avg The calculation formula is as follows: GG avg =(GG1+GG2+GG3+......+GG n ) / n; GG1 is the first monitoring of irrigation demand, GG2 is the first monitoring of irrigation demand, GG3 is the first monitoring of irrigation demand, GG n The first monitoring humidity S1 corresponds to the first monitoring irrigation demand GG1, the second monitoring humidity S2 corresponds to the second monitoring irrigation demand GG2, the third monitoring humidity S3 corresponds to the third monitoring irrigation demand GG3, and the nth monitoring humidity S n and the nth monitored irrigation demand GG n Monitoring correspondence.

[0027] In this embodiment, "TS-TS best The calculation part of "Calculate the soil moisture index TS and the soil moisture index suitable for growth TS best This difference reflects the gap between the current soil moisture and the appropriate target moisture and is the basis for calculating irrigation needs. The calculation section calculates the irrigation rate X and the square root of the soil moisture sensor reading and the historical average irrigation demand GG avg The sum of the irrigation rate X and the historical average irrigation demand GG. avg The adjustment of the water sensor readings on the irrigation rate can be smoothed by taking into account the square root of soil moisture, while the basic irrigation demand ensures that crops still receive the necessary irrigation when there is no other information. The historical average irrigation demand GG is constantly monitored and replaced. avg , which further reflects the real-time iterative characteristics of the monitoring method; It is worth noting that in the agricultural Internet of Things monitoring system, the current humidity S represents the reading of the soil moisture sensor, which reflects the actual moisture content in the soil. However, directly using the current humidity S as the only basis for irrigation demand may cause the irrigation strategy to be too sensitive and inaccurate. Multiplying by 0.5 is actually a "compromise" treatment of the soil moisture reading. The purpose of this practice is to balance the calculation accuracy of irrigation demand and the feasibility of actual operation. By multiplying by 0.5, it ensures that the soil moisture reading occupies a certain proportion in the irrigation demand calculation, but it will not cause frequent adjustments to the irrigation strategy due to small reading fluctuations. From the perspective of agricultural Internet of Things monitoring, the current humidity S is multiplied by 0.5 for system stability and reliability considerations. The agricultural Internet of Things system needs to process a large amount of real-time data and make decisions based on this data. If the irrigation strategy is too sensitive to the soil moisture reading, the system will frequently adjust the irrigation equipment due to data noise or sensor errors, which will not only increase the system's computing burden, but also have an adverse effect on crops. By multiplying by 0.5, this sensitivity can be reduced, the stability and reliability of the system can be improved, and the formulation of the irrigation strategy can be ensured to be more scientific and reasonable. This algorithm reflects the actual irrigation demand unit of crops in the current stage and environment by comprehensively introducing the soil moisture condition index TS and the suitable growth soil moisture condition index TS. best , irrigation rate X, historical average irrigation demand GG avg The factors of the irrigation demand can be used to calculate the current amount of irrigation required by crops, thus achieving precision irrigation. Precision irrigation helps to meet the water needs of crops at different growth stages and improve the quality and yield of crops. By combining the irrigation demand calculation results with the adjustment of the operating status of the irrigation equipment, intelligent control of the irrigation equipment can be achieved.

[0028] See also Figures 1 to 3 , the calculation formula of the irrigation equipment operation status adjustment unit is as follows: ; in: TZ is the adjustment value of the irrigation equipment operation status; GG old Monitor irrigation requirements for the previous time; TZ old Adjust the value of the irrigation equipment operation status monitored last time; TZ old ×0.2The previous monitoring irrigation equipment operation status adjustment value TZ old 20% is added to reflect the continuous state of operating status adjustment.

[0029] In this embodiment, the algorithm unit first "GG-GG oldThe calculation part calculates the current irrigation demand GG and the previous monitored irrigation demand GG old This difference reflects the change in irrigation demand and is the basis for adjusting the operating status of irrigation equipment. The calculation part of ” reflects the combined adjustments relative to soil moisture and temperature; The last monitored irrigation equipment operating status adjustment value TZ old Represents the adjustment value of the last irrigation equipment operation status, which reflects the execution effect of the last irrigation strategy. In the irrigation equipment operation status adjustment unit, the last monitoring irrigation equipment operation status adjustment value TZ old Multiplying by 0.2 and adding it to the calculation of the current adjustment value is actually using historical data to optimize the current irrigation strategy. The purpose of this practice is to ensure that the adjustment of the irrigation strategy has a certain degree of continuity and stability, and to avoid drastic fluctuations in the irrigation strategy due to abnormal single data. By multiplying by 0.2, it can ensure that historical data occupies a certain proportion in the adjustment of the irrigation strategy, but will not completely rely on historical data and ignore current environmental changes. From the perspective of agricultural IoT monitoring, the previous monitoring of the irrigation equipment operation status adjustment value TZ old Multiplying by 0.2 is also for the sake of system intelligence and adaptability. The agricultural IoT system needs to be able to automatically adjust the irrigation strategy according to real-time data and environmental changes. However, if the system relies entirely on real-time data and ignores historical data, it will make wrong decisions due to the abnormality of a single data. By introducing the adjustment value TZ of the previous monitoring of the operating status of the irrigation equipment old The multiplication by 0.2 mechanism allows the system to more intelligently use historical data to optimize the current irrigation strategy, thereby improving the system's adaptability and robustness; The irrigation equipment operation status adjustment unit of this algorithm optimizes the irrigation strategy by adjusting the operation status of the irrigation equipment, so that irrigation is more in line with the actual needs of crops. The intelligent control of the irrigation equipment operation status adjustment helps to achieve water-saving irrigation and precision irrigation, and promote the sustainability of agricultural production.

[0030] See also Figures 1 to 3 , based on the irrigation equipment operation status adjustment value TZ, and the irrigation equipment operation status adjustment value TZ is automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment. After the adjustment, the irrigation equipment automatically adjusts the irrigation amount and time intelligently, and the current humidity S, current temperature W and irrigation rate X monitored values ​​will change in real time If the result value of the irrigation equipment operation status adjustment value TZ is small, it reflects that the degree of monitoring that needs adjustment is small, and the real-time changes in the monitoring of the current humidity S, the current temperature W, and the irrigation rate X are small; If the result value of the irrigation equipment operation status adjustment value TZ is large, it reflects that the degree of monitoring that needs adjustment is large, and the real-time monitoring changes of the current humidity S, the current temperature W and the irrigation rate X are large.

[0031] In this embodiment, accurate calculation of the irrigation equipment operation state adjustment value TZ helps to realize intelligent control of the irrigation equipment. By optimizing the operation state of the irrigation equipment, energy consumption and operating costs can be reduced, and the economic benefits of agricultural production can be improved. The calculation process of the irrigation equipment operation state adjustment value TZ takes into account the influence of the previous irrigation equipment operation state adjustment value, making the adjustment process of the irrigation system smoother and continuous, and enhancing the reliability and stability of the system. The loop feedback mechanism allows the irrigation strategy to be dynamically adjusted according to real-time data. The temperature deviation P in the current soil moisture condition unit is determined as the input variable, which reflects the difference between the current environmental conditions and the crop growth requirements. These difference information is input into the control strategy. The irrigation demand is calculated by reflecting the actual irrigation demand unit of the crops in the current stage and environment, and then the irrigation equipment operation state adjustment value TZ is obtained through the irrigation equipment operation state adjustment unit. This process is real-time and can be adjusted quickly according to environmental changes and crop growth needs, thereby improving the flexibility of the irrigation strategy. The loop feedback mechanism optimizes irrigation efficiency by precisely controlling the operating status of irrigation equipment. The irrigation demand GG in the unit that reflects the actual irrigation demand of crops at the current stage and environment is calculated based on the crop growth model, soil moisture and temperature monitoring data, and weather forecast information. This comprehensive consideration ensures that the irrigation amount is neither too much nor too little, thereby meeting the growth needs of crops. At the same time, the irrigation equipment operating status adjustment value TZ in the irrigation equipment operating status adjustment unit is used as one of the inputs of the irrigation equipment control strategy. By adjusting the operating status of the irrigation equipment, precise irrigation control is achieved, further improving irrigation efficiency. The loop feedback mechanism provides a more suitable environment for crop growth by adjusting soil moisture, temperature and environmental factors. The temperature deviation P in the current soil moisture condition unit reflects the quality of the crop growth environment. The loop feedback mechanism optimizes these environmental factors by adjusting the irrigation strategy. When the current humidity S is too low, the irrigation equipment will increase the irrigation amount. When the current temperature is too high W, the irrigation equipment will spray water mist to reduce the temperature. This adjustment process ensures that the crops are always in a suitable growth environment, thereby promoting the growth and development of crops. In summary, the loop feedback mechanism has significant beneficial effects in the agricultural Internet of Things monitoring system. It combines the factors in the unit for determining the current soil moisture status, the unit for reflecting the actual irrigation demand of crops in the current stage and environment, and the unit for adjusting the operating status of irrigation equipment, realizing the intelligent and refined control of irrigation strategies, improving irrigation efficiency, promoting crop growth, and increasing crop yield and quality. This mechanism provides strong support for the development of modern precision agriculture.

[0032] 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. A monitoring method based on agricultural Internet of Things, characterized in that: The specific implementation steps are as follows: Step 1: Use the data acquisition module to collect real-time and historical data related to soil moisture, temperature, and irrigation volume; Step 2: Using the data processing module, respectively calculate and output the soil moisture index TS, the irrigation demand GG, and the irrigation equipment operation status adjustment value TZ; Step 3: Based on the operation status of the irrigation equipment, the adjustment value TZ of the operation status of the irrigation equipment will be automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment; Step 4: Use the monitoring and feedback module to monitor the adjusted soil moisture, temperature and operating status of the irrigation equipment in real time; The data processing module includes a unit for determining the current soil moisture status, a unit for reflecting the actual irrigation demand of crops in the current stage and environment, and a unit for adjusting the operating status of irrigation equipment.

2. A monitoring method based on agricultural Internet of Things according to claim 1, characterized in that: The equipment used in the data acquisition module includes soil moisture sensors, temperature sensors, and irrigation equipment; The equipment used by the data processing module includes a data processing center; The equipment used in the monitoring and feedback module includes monitoring and control equipment.

3. A monitoring method based on agricultural Internet of Things according to claim 2, characterized in that: The calculation formula for determining the current soil moisture status unit is as follows: ； P=W best -W; in: TS is the soil moisture status index; S is the current humidity; S avg is the historical humidity average; G is the number of dry days, which means the number of consecutive dry days monitored recently; P is the temperature deviation; W best is the suitable growth temperature, W is the current temperature, W best Reflects the temperature at the time when the crop yield reached its maximum value during historical monitoring, and is updated and iterated based on continuous monitoring; Half of the current humidity S is added to reflect the positive impact of the current humidity S on irrigation demand.

4. A monitoring method based on agricultural Internet of Things according to claim 3, characterized in that: The historical humidity average value S avg The calculation formula is as follows: <h2 style=";text-align:left;direction:ltr">S<h2 style=";text-align:left;direction:ltr"> avg <h2 style=";text-align:left;direction:ltr"> =(S1+S2+S3+......+S<h2 style=";text-align:left;direction:ltr"> n <h2 style=";text-align:left;direction:ltr"> ) / n; n is the total number of historical monitoring times; S1 is the first humidity monitoring, S2 is the second humidity monitoring, S3 is the third humidity monitoring, S n Monitor humidity for the nth time.

5. A monitoring method based on agricultural Internet of Things according to claim 4, characterized in that: The calculation formula reflecting the actual irrigation demand unit of crops in the current stage and environment is as follows: ； in: GG is the irrigation demand; TS best TS is the index of soil moisture conditions suitable for growth. best The temperature and humidity at the time reflecting the maximum value of crop yield during the historical monitoring process are substituted into the current soil moisture condition determination unit, and the output soil moisture condition index TS is calculated and output, and the index is changed and iterated according to continuous monitoring; X is the irrigation rate, X represents the amount of irrigation that the irrigation equipment can provide per hour; GG avg is the historical average irrigation demand, GG avg Reflecting the average value of the historical data result value calculated by using the unit reflecting the actual irrigation demand of the crop in the current stage and environment; S×0.5 also adds half of the current humidity S, reflecting the positive impact of the current humidity S on irrigation demand.

6. A monitoring method based on agricultural Internet of Things according to claim 5, characterized in that: The historical average irrigation demand GG avg The calculation formula is as follows: GG avg =(GG1+GG2+GG3+......+GG n ) / n; GG1 is the first monitoring of irrigation demand, GG2 is the first monitoring of irrigation demand, GG3 is the first monitoring of irrigation demand, GG n The first monitoring humidity S1 corresponds to the first monitoring irrigation demand GG1, the second monitoring humidity S2 corresponds to the second monitoring irrigation demand GG2, the third monitoring humidity S3 corresponds to the third monitoring irrigation demand GG3, and the nth monitoring humidity S n and the nth monitored irrigation demand GG n Monitoring correspondence.

7. A monitoring method based on agricultural Internet of Things according to claim 6, characterized in that: The calculation formula of the irrigation equipment operation state adjustment unit is as follows: ； in: TZ is the adjustment value of the irrigation equipment operation status; GG old Monitor irrigation requirements for the previous time; TZ old Adjust the value of the irrigation equipment operation status monitored last time; TZ old ×0.2The previous monitoring irrigation equipment operation status adjustment value TZ old 20% is added to reflect the continuous state of operating status adjustment.

8. A monitoring method based on agricultural Internet of Things according to claim 7, characterized in that: Based on the irrigation equipment operation state adjustment value TZ, the irrigation equipment operation state adjustment value TZ is automatically input into the irrigation equipment based on the agricultural Internet of Things for adjustment. After the adjustment, the irrigation equipment intelligently adjusts the irrigation amount and time automatically, and the values ​​monitored by the current humidity S, the current temperature W and the irrigation rate X will change in real time; If the result value of the irrigation equipment operation status adjustment value TZ is small, it reflects that the degree of monitoring that needs adjustment is small, and the real-time changes in the monitoring of the current humidity S, the current temperature W, and the irrigation rate X are small; If the result value of the irrigation equipment operation status adjustment value TZ is large, it reflects that the degree of monitoring that needs adjustment is large, and the real-time monitoring changes of the current humidity S, the current temperature W and the irrigation rate X are large.

9. A monitoring system according to the monitoring method based on agricultural Internet of Things according to claim 1, characterized in that: include: Data acquisition module, used to collect real-time and historical data related to soil moisture, temperature, and irrigation volume; A data processing module is used to calculate and output the soil moisture index TS, the irrigation demand GG and the irrigation equipment operation status adjustment value TZ; Wherein, the data processing module includes a unit for determining the current soil moisture status, a unit for reflecting the actual irrigation demand of crops in the current stage and environment, and a unit for adjusting the operating status of irrigation equipment; The monitoring and feedback module is used to monitor the soil moisture, temperature and operating status of the irrigation equipment in real time after feedback adjustment.

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