Distributed digital agricultural park environment sensing system

Abstract

The invention discloses a distributed digital agricultural park environment perception system, and relates to the technical field of digital agricultural park environment perception, a data acquisition module deployed in an agricultural park is utilized to acquire environment parameters of temperature W, humidity S, illumination intensity G, soil humidity TS and carbon dioxide concentration CO2 in real time, and the environment parameters are stored in a storage unit of the data acquisition module. Historical data of related environment parameters are collected, a data processing and calculating module is utilized to calculate and output an environment comprehensive index HZ, an irrigation demand GG and an intelligent regulation and control evaluation value TK, data display and feedback are utilized, a trend chart is drawn in combination with the result of the intelligent regulation and control evaluation value TK, temperature W / humidity S / illumination intensity G / soil humidity TS is adjusted in a targeted mode, and the intelligent regulation and control evaluation value TK is obtained. According to the method, the perception regulation and control performance and the user experience of the system are further improved by improving the data accuracy, optimizing the intelligent regulation and control strategy, enhancing the self-adaptive capability of the system and enriching the solution optimization and innovation measures of the visual targeted regulation and control mode.

Description

Technical Field

[0001] The present invention relates to the technical field of digital agricultural park environment perception, and in particular to a distributed digital agricultural park environment perception system. Background Art

[0002] With the advancement of science and technology and the development of agriculture, a distributed digital agricultural park environmental perception system has emerged. The system integrates a variety of sensors and intelligent devices to realize real-time monitoring of key environmental parameters such as temperature, humidity, light intensity, soil moisture and carbon dioxide concentration in the agricultural park. It has greatly improved the planting efficiency and many aspects of planting control in traditional planting. However, the current agricultural park management system still has major shortcomings in terms of intelligence, human-computer interaction management, data acquisition and analysis, and monitoring and detection of crops, and cannot meet actual needs well. Among them, the Internet of Things technology connects sensor equipment to the Internet based on wireless and wired carriers to realize intelligent monitoring, identification, and control functions of the monitored objects.

[0003] At present, due to the limitations of sensor accuracy and data transmission factors of existing perception systems, errors exist in the data collection and transmission process of existing technologies, resulting in inaccurate calculated environmental integration, irrigation demand and intelligent regulation. In addition, the intelligent regulation strategies in existing technologies are often based on simple rules and threshold judgments, lacking in-depth consideration of different crop growth characteristics and environmental conditions, resulting in poor regulation effects. Systems in existing technologies also often lack adaptive capabilities and are unable to automatically adjust regulation strategies according to changes in crop growth stages and environmental conditions. Their visualization methods are often relatively simple, lacking intuitive and easy-to-understand graphic display methods, making it difficult for farmers to understand and operate the system. Summary of the invention

[0004] The purpose of the present invention is to provide a distributed digital agricultural park environment perception system to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution, and the specific implementation steps are as follows:

[0006] Step 1: Use the data acquisition module deployed in the agricultural park to collect environmental parameters such as temperature W, humidity S, light intensity G, soil moisture TS and carbon dioxide concentration CO2 in real time;

[0007] Step 2: collecting historical data of relevant environmental parameters from the storage unit of the data collection module;

[0008] Step 3: Use the data processing and calculation module to calculate and output the comprehensive environmental index HZ, irrigation demand GG and intelligent control evaluation value TK;

[0009] Step 4: Use data display and feedback, and draw a trend chart in combination with the results of the intelligent control evaluation value TK. According to the change trends of the intelligent control evaluation value TK and temperature W, humidity S, light intensity G, and soil moisture TS, adjust the temperature W / humidity S / light intensity G / soil moisture TS in a targeted manner;

[0010] The data processing and calculation module includes a unit that comprehensively reflects the overall environmental conditions of the agricultural park, a unit that reflects the irrigation demand under the current environment, and a unit that intelligently reflects and regulates strategies.

[0011] Optionally, the devices used in the data acquisition module include a temperature sensor, a humidity sensor, a light intensity sensor, a soil moisture sensor and a carbon dioxide concentration sensor;

[0012] The equipment used in the data processing and computing module includes a central processing unit;

[0013] The equipment used for data display and feedback includes data visualization equipment and intelligent control equipment.

[0014] Optionally, the calculation formula for the unit that fully reflects the overall environmental status of the agricultural park is as follows:

[0015]

[0016] CO 2,avg =(CO 2,1 +CO 2,2 +CO 2,3 +......+CO 2,n ) / n;

[0017] in:

[0018] HZ is the comprehensive environmental index;

[0019] W is temperature;

[0020] S is humidity;

[0021] G is the light intensity;

[0022] TS is soil moisture;

[0023] CO2 is the concentration of carbon dioxide;

[0024] CO 2,avg is the reference concentration of carbon dioxide;

[0025] n is the total number of random inspections, which reflects the total number of times the reference concentration of carbon dioxide CO2 in the atmosphere is inspected;

[0026] CO 2,1The first sampling of carbon dioxide reference concentration, CO 2,2 The second sampling carbon dioxide reference concentration, CO 2,3 The third sampling carbon dioxide reference concentration, CO 2,n It is the reference concentration of carbon dioxide for the nth random inspection.

[0027] Optionally, the calculation formula reflecting the irrigation demand unit under the current environment is as follows:

[0028]

[0029] in:

[0030] GG is the irrigation demand;

[0031] HZ opt is the optimal comprehensive environmental index, HZ opt The comprehensive environmental index HZ reflects the highest value of crop growth trend in agricultural parks;

[0032] G min is the minimum intensity of light;

[0033] G max is the maximum intensity of light;

[0034] W base is the base temperature, W base Indicates the temperature reached for irrigation.

[0035] Optionally, the calculation formula of the intelligent reflection and regulation strategy unit is as follows:

[0036]

[0037] HZ tanget =(HZ1+HZ2+HZ3+......+HZ m ) / m;

[0038] TS tanget =(TS1+TS2+TS3+......+TS m ) / m;

[0039] in:

[0040] TK is the intelligent control evaluation value;

[0041] HZ prev is the last comprehensive environmental index;

[0042] HZ tanget It is a comprehensive environmental benchmark index;

[0043] m is the total number of historical test results, HZ tangetIn the calculation formula, m reflects the total number of historical result values ​​used to calculate the benchmark value of the comprehensive environmental index H;

[0044] HZ1 is the first historical testing environment comprehensive benchmark index, HZ2 is the second historical testing environment comprehensive benchmark index, HZ3 is the third historical testing environment comprehensive benchmark index, HZ m is the mth historical testing environment comprehensive benchmark index;

[0045] GG prev The last irrigation demand;

[0046] TS tanget is the soil base moisture;

[0047] TS tanget The calculation formula m reflects the total number of historical result values ​​used to calculate the soil moisture TS benchmark value;

[0048] TS1 is the first historical soil moisture detection, TS2 is the second historical soil moisture detection, TS3 is the third historical soil moisture detection, TS m Detect soil moisture for the mth history;

[0049] TS max is the maximum soil moisture value, TS min is the minimum soil moisture value.

[0050] Optionally, the trend analysis of drawing a line graph based on the intelligent control evaluation value TK is as follows:

[0051] If the intelligent control evaluation value TK in the line graph shows an upward trend, it means that the current intelligent control strategy is gradually being optimized, the crop growth environment is being improved, and the current control strategy should be maintained;

[0052] If the intelligent control evaluation value TK in the line chart shows a downward trend, it means that there are problems with the current control strategy and the crop growth environment is deteriorating. The control strategy should be adjusted immediately.

[0053] If the intelligent control evaluation value TK in the line chart fluctuates within a certain range and the overall trend is relatively stable, it means that the current control strategy is relatively stable.

[0054] Optionally, the control strategy is adjusted in combination with the trend of the intelligent control evaluation value TK on the linear graph, and the changes of temperature W, humidity S, light intensity G, and soil moisture TS on the linear graph. The specific adjustments are as follows:

[0055] If the intelligent control evaluation value TK shows a downward trend and is accompanied by large fluctuations in the temperature W on the line graph, the temperature W control device is adjusted;

[0056] If the intelligent control evaluation value TK shows a downward trend, accompanied by a linear downward and upward trend in humidity S on the line graph, the humidity S control device is adjusted;

[0057] If the change of the intelligent control evaluation value TK is closely related to the light intensity G, the light intensity G control device is adjusted;

[0058] If the intelligent control evaluation value TK reflects that the soil moisture TS is insufficient or excessive, the soil moisture TS control device is adjusted.

[0059] Optionally, if the intelligent control evaluation value TK continuously shows an upward trend and fluctuations within a certain range in the linear graph, the data acquisition module is used to continuously sense the agricultural park and stop the control strategy.

[0060] Compared with the prior art, the present invention has the following beneficial effects:

[0061] 1. The present invention improves the accuracy of data collection and transmission by adopting higher-precision sensors and more reliable data transmission methods, thereby ensuring the accuracy of the calculated environmental comprehensive index HZ, irrigation demand GG and intelligent control evaluation value TK.

[0062] 2. The present invention combines the growth characteristics and environmental conditions of different crops to formulate more accurate intelligent control strategies. At the same time, it uses machine learning technology to mine and analyze historical data to improve the accuracy and adaptability of the control strategies. By introducing adaptive algorithms and models, the system can automatically adjust the control strategies according to changes in crop growth stages and environmental conditions, thereby achieving more intelligent control.

[0063] 3. The present invention introduces an intuitive and easy-to-understand graphical display method of line graphs, which makes it easier to understand and operate the system. At the same time, it provides a variety of visualization options and customization functions to meet different needs and preferences. According to the line graph of the intelligent control evaluation value TK and the changing trends of temperature W, humidity S, light intensity G, and soil moisture TS, it can more accurately find and make targeted adjustments to one of the influencing factors of temperature W, humidity S, light intensity G, and soil moisture TS, thereby achieving the purpose of real-time and accurate perception of control. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] Figure 1 This is a method flow chart of the distributed digital agricultural park environment perception system;

[0065] Figure 2 It is a linear trend diagram of the intelligent control evaluation value TK and the temperature W in the present invention;

[0066] Figure 3It is a linear trend diagram of the intelligent control evaluation value TK and humidity S in the present invention;

[0067] Figure 4 It is a linear trend diagram of the intelligent control evaluation value TK and the light intensity G in the present invention;

[0068] Figure 5 It is a linear trend diagram of the intelligent control evaluation value TK and soil moisture TS in the present invention. DETAILED DESCRIPTION

[0069] 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.

[0070] Regarding this distributed digital agricultural park environment perception system, it is different from the existing agricultural park environment perception system. The existing agricultural park environment perception system still has problems and shortcomings in data accuracy, intelligent control strategy accuracy, system adaptability and visualization methods. This algorithm unit further improves the system's perception and control performance and user experience by solving optimization and innovative measures such as improving data accuracy, optimizing intelligent control strategies, enhancing system adaptability and enriching visualization targeted control methods.

[0071] For example, see Figures 1 to 4 ,This implementation provides a distributed digital agricultural park environment perception system. The specific implementation steps are as follows:

[0072] Step 1: Use the data acquisition module deployed in the agricultural park to collect environmental parameters such as temperature W, humidity S, light intensity G, soil moisture TS and carbon dioxide concentration CO2 in real time;

[0073] Step 2: Collect historical data of relevant environmental parameters from the storage unit of the data acquisition module;

[0074] Step 3: Use the data processing and calculation module to calculate and output the comprehensive environmental index HZ, irrigation demand GG and intelligent control evaluation value TK;

[0075] Step 4: Use data display and feedback, and draw a trend chart in combination with the results of the intelligent control evaluation value TK. According to the change trends of the intelligent control evaluation value TK and temperature W, humidity S, light intensity G, and soil moisture TS, adjust the temperature W / humidity S / light intensity G / soil moisture TS in a targeted manner;

[0076] Among them, the data processing and calculation module includes a unit that comprehensively reflects the overall environmental conditions of the agricultural park, a unit that reflects the irrigation demand under the current environment, and a unit that intelligently reflects and regulates strategies;

[0077] The equipment used in the data acquisition module includes temperature sensor, humidity sensor, light intensity sensor, soil moisture sensor and carbon dioxide concentration sensor;

[0078] The equipment used in the data processing and computing module includes a central processing unit;

[0079] The equipment used for data display and feedback includes data visualization equipment and intelligent control equipment.

[0080] In this embodiment, the system forms a closed-loop agricultural park environment perception and intelligent control system through the mutual cooperation of three algorithm units. Combining the three operation results of HZ, GG and TK, HZ is the comprehensive environmental index, which provides a quantitative standard for evaluating whether the current environment is suitable for crop growth. This index not only helps to understand the real-time environmental conditions of the park, but also provides basic data for subsequent irrigation demand calculation and intelligent control strategy evaluation. GG is the irrigation demand, and this demand indicates the amount of water supplement required for crops to maintain normal growth in the current environment. TK is the intelligent control evaluation value, which provides a quantitative evaluation value to reflect whether the current control strategy has achieved the expected effect. This evaluation value not only helps to understand the actual effect of the control strategy, but also provides guidance for subsequent strategy adjustments. The calculation results of TK can also affect the calculation of HZ and GG, and introduce a line graph to show the changing trend of the relevant values, so as to intuitively understand the system operation status, and take targeted adjustment measures according to the changing trend to achieve the optimal environmental conditions and crop growth conditions.

[0081] See also Figures 1 to 4 , the calculation formula for the unit that fully reflects the overall environmental status of the agricultural park is as follows:

[0082]

[0083] CO 2,avg =(CO 2,1 +CO 2,2 +CO 2,3 +......+CO 2,n ) / n;

[0084] in:

[0085] HZ is the comprehensive environmental index;

[0086] W is temperature;

[0087] S is humidity;

[0088] G is the light intensity;

[0089] TS is soil moisture;

[0090] CO2 is the concentration of carbon dioxide;

[0091] CO 2,avg is the reference concentration of carbon dioxide;

[0092] n is the total number of random inspections, which reflects the total number of times the reference concentration of carbon dioxide CO2 in the atmosphere is inspected;

[0093] CO 2,1 The first sampling of carbon dioxide reference concentration, CO 2,2 The second sampling carbon dioxide reference concentration, CO 2,3 The third sampling carbon dioxide reference concentration, CO 2,n It is the reference concentration of carbon dioxide for the nth random inspection.

[0094] In this embodiment: First, in this algorithm unit The calculation part is to average the four environmental parameters of temperature W, humidity S, light intensity G and soil moisture TS, and then square them. This processing method is to obtain a comprehensive environmental parameter evaluation value. These four parameters are important factors affecting crop growth. By averaging these four parameters, the differences in order of magnitude between them are eliminated, making their contributions to the comprehensive environmental index HZ more balanced. The square operation is to amplify the differences, so that small changes in environmental parameters can also be reflected in the comprehensive environmental index HZ. "(CO2-CO 2，avg ) 2 The calculation part is to calculate the carbon dioxide concentration CO2 and the carbon dioxide reference concentration CO 2,avg Carbon dioxide is an important raw material for photosynthesis, and changes in its concentration have a significant impact on crop growth. By calculating the difference and squaring it, the degree of deviation between the carbon dioxide concentration and the reference average concentration is quantified, and then incorporated into the calculation of the comprehensive environmental index HZ, so that the comprehensive environmental index HZ can more comprehensively reflect the environmental conditions;

[0095] This algorithm comprehensively reflects the overall environmental status of the agricultural park. The unit integrates these environmental parameters into a comprehensive index through weighted average and other algorithms, thereby achieving the effect of understanding the current environmental status of the park at a glance. This integration avoids the one-sidedness of single parameter evaluation and provides more comprehensive environmental information;

[0096] The changing trend of the environmental comprehensive index HZ value can provide decision support. Specifically, when the environmental comprehensive index HZ value deviates from the ideal average range, the problem can be quickly located, such as excessive temperature and insufficient humidity, so that timely measures can be taken to make adjustments;

[0097] The comprehensive environmental index HZ value is not only a reflection of the environmental conditions, but also the basis for subsequent irrigation demand calculation and intelligent control strategy evaluation. Its accuracy directly affects the precision and reliability of subsequent calculations.

[0098] See also Figures 1 to 4 , the calculation formula reflecting the irrigation demand unit in the current environment is as follows:

[0099]

[0100] in:

[0101] GG is the irrigation demand;

[0102] HZ opt is the optimal comprehensive environmental index, HZ opt The comprehensive environmental index HZ reflects the highest value of crop growth trend in agricultural parks;

[0103] G min is the minimum intensity of light;

[0104] G max is the maximum intensity of light;

[0105] W base is the base temperature, W base Indicates the temperature reached for irrigation.

[0106] In this embodiment, first, "(HZ-HZ opt )” calculation part is to calculate the current environmental comprehensive index HZ and the environmental comprehensive optimal index HZ opt The difference between the environmental comprehensive optimal index HZ opt It is a comprehensive index of ideal environmental parameters that determines the highest value of growth trend according to crop type and growth stage. By calculating the difference, it quantifies the gap between the current environment and the ideal environment, thereby guiding the calculation of irrigation demand GG. The larger the difference, the farther the current environment is from the ideal environment, and the greater the crop's demand for water. The calculation part is the normalization of the light intensity, G max and G minare the maximum and minimum values ​​of light intensity, respectively, and G is the current light intensity. This calculation part converts the light intensity G into a proportional value between 0 and 1. The normalization process can eliminate the difference of light intensity G in different time periods and under different weather conditions, making the calculation of irrigation demand GG more accurate. By calculating the proportional value, the influence of light intensity G on irrigation demand GG can be quantified.

[0107] The algorithm reflects the irrigation demand unit in the current environment based on the comprehensive index of environmental parameters HZ, light intensity G, and the comprehensive optimal index of the environment HZ. opt The environmental parameters of factors such as temperature W are used to calculate the irrigation demand GG of the crop. This calculation result can provide a scientific basis for precise irrigation and avoid waste of resources and stunted crop growth caused by over-irrigation and insufficient irrigation.

[0108] See also Figures 1 to 4 , the calculation formula for intelligently reflecting and regulating the strategy unit is as follows:

[0109]

[0110] HZ tanget =(HZ1+HZ2+HZ3+......+HZ m ) / m;

[0111] TS tanget =(TS1+TS2+TS3+......+TS m ) / m;

[0112] in:

[0113] TK is the intelligent control evaluation value;

[0114] HZ prev is the last comprehensive environmental index;

[0115] HZ tanget It is a comprehensive environmental benchmark index;

[0116] m is the total number of historical test results, HZ tanget In the calculation formula, m reflects the total number of historical result values ​​used to calculate the benchmark value of the comprehensive environmental index H;

[0117] HZ1 is the first historical testing environment comprehensive benchmark index, HZ2 is the second historical testing environment comprehensive benchmark index, HZ3 is the third historical testing environment comprehensive benchmark index, HZ m is the mth historical testing environment comprehensive benchmark index;

[0118] GG prev The last irrigation demand;

[0119] TStanget is the soil base moisture;

[0120] TS tanget The calculation formula m reflects the total number of historical result values ​​used to calculate the soil moisture TS benchmark value;

[0121] TS1 is the first historical soil moisture detection, TS2 is the second historical soil moisture detection, TS3 is the third historical soil moisture detection, TS m Detect soil moisture for the mth history;

[0122] TS max is the maximum soil moisture value, TS min is the minimum soil moisture value.

[0123] In this embodiment, the algorithm unit first In this calculation part, the irrigation demand GG and the last irrigation demand GG are introduced. prev ratio, specifically the last irrigation demand GG prev The ratio of the square of HZ to the current irrigation demand GG is used to evaluate the change of irrigation demand GG. By calculating the ratio, the degree of change of irrigation demand GG between two measurements is quantified, so as to evaluate the impact of the control strategy on irrigation demand GG. The larger the ratio, the more significant the impact of the control strategy on irrigation demand GG. tanget ) 2 "This calculation part is the current environmental comprehensive index HZ and the environmental comprehensive benchmark index HZ tanget The square of the difference between tanget It represents the ideal growth environment. By calculating the difference and squaring it, the gap between the current environment and the ideal environment is quantified and incorporated into the calculation of the intelligent control evaluation value TK to evaluate the effect of the control strategy on improving the environmental conditions.

[0124] This calculation part is the normalization of soil moisture TS and the last irrigation demand GG prev The product of TS max is the maximum soil moisture value, TS min TS is the minimum soil moisture value max is the maximum soil moisture value, TS min is the minimum soil moisture value, TS is the current soil moisture, and TS tangetThe soil baseline moisture content is used to evaluate the impact of soil moisture on irrigation demand. The difference in soil moisture TS under different conditions is eliminated through normalization, and it is combined with the last irrigation demand GG to evaluate the impact of current soil moisture TS on irrigation demand GG. This calculation part helps to more comprehensively evaluate the effect of the regulation strategy.

[0125] In this algorithm unit, the intelligent control evaluation value TK can reflect the effectiveness of the current control strategy. When the intelligent control evaluation value TK is low, it means that there are problems with the current strategy and it needs to be adjusted. This evaluation mechanism provides a basis for optimizing the control strategy.

[0126] The intelligent response and control strategy unit continuously evaluates and adjusts, allowing the system to gradually adapt to different environmental conditions and crop growth requirements, thereby improving its adaptability and stability. Effective control strategies can reduce operating costs and improve the economic benefits of agricultural production.

[0127] For example 2, please refer to Figures 1 to 4 , the trend analysis based on the intelligent control evaluation value TK and drawing a line graph is as follows:

[0128] If the intelligent control evaluation value TK in the line graph shows an upward trend, it means that the current intelligent control strategy is gradually being optimized, the crop growth environment is being improved, and the current control strategy should be maintained;

[0129] If the intelligent control evaluation value TK in the line chart shows a downward trend, it means that there are problems with the current control strategy and the crop growth environment is deteriorating. The control strategy should be adjusted immediately.

[0130] If the intelligent control evaluation value TK in the line chart fluctuates within a certain range and the overall trend is relatively stable, it means that the current control strategy is relatively stable;

[0131] If the intelligent control evaluation value TK continues to show an upward trend and fluctuations within a certain range in the linear graph, the data acquisition module is used to continuously perceive the agricultural park and stop the control strategy;

[0132] The control strategy is adjusted based on the trend of the intelligent control evaluation value TK on the linear graph, as well as the changes in temperature W, humidity S, light intensity G, and soil moisture TS on the linear graph. The specific adjustments are as follows:

[0133] If the intelligent control evaluation value TK shows a downward trend and is accompanied by large fluctuations in the temperature W on the line graph, the temperature W control device is adjusted;

[0134] If the intelligent control evaluation value TK shows a downward trend, accompanied by a linear downward and upward trend in humidity S on the line graph, the humidity S control device is adjusted;

[0135] If the change of the intelligent control evaluation value TK is closely related to the light intensity G, the light intensity G control device is adjusted;

[0136] If the intelligent control evaluation value TK reflects that the soil moisture TS is insufficient or excessive, the soil moisture TS control device is adjusted.

[0137] In this embodiment, when the intelligent control evaluation value TK value shows that the current control strategy is not effective, the system can provide real-time feedback to the unit that fully reflects the overall environmental conditions of the agricultural park, and adjust the parameters of temperature W, humidity S, light intensity G and soil moisture TS accordingly. This real-time feedback mechanism enables the system to respond quickly to environmental changes and improve the timeliness and accuracy of control.

[0138] The line graph can clearly show the changes of data over time, which helps to monitor the environmental parameters of the agricultural park and the effects of the intelligent control strategy in real time. When the intelligent control evaluation value TK value fluctuates and is abnormal, the line graph can quickly reflect these changes, thereby helping us to find problems in time and take corresponding adjustment measures. This rapid response capability is crucial to ensure the healthy growth of crops.

[0139] Line graphs can transform complex data information into intuitive and easy-to-understand graphical representations through simple lines and changes, which helps to easily understand the changing trends and laws of data, so as to better participate in the intelligent regulation process of agricultural parks. In addition, line graphs can also help the system more easily discover abnormal points and potential problems in the data, providing strong support for further optimization and improvement;

[0140] By displaying the changing trend of the intelligent control evaluation value TK through a line graph, the environmental parameters and intelligent control strategies of the agricultural park can be adjusted more accurately. For example, when the intelligent control evaluation value TK shows a downward trend, the temperature W, humidity S, light intensity G and soil moisture TS parameters are adjusted in a targeted manner according to the changes in the line graph to improve the growth environment of crops. This precise control helps the system quickly find the specific reasons that affect the control, thereby improving the accuracy of perception control.

[0141] The application of line graphs in the agricultural intelligent control system can also provide a basis for auxiliary decision-making. By comparing the changing trends of the intelligent control evaluation value TK value under different time periods and different control strategies, the effects of various strategies can be evaluated, and a more scientific and reasonable control plan can be formulated accordingly. In addition, the line graph can also continuously track and monitor the implementation of the control strategy, discover and solve problems in a timely manner, and thus achieve continuous improvement and optimization;

[0142] This unit uses a line graph to display the changing trend of the intelligent control evaluation value TK, and monitors the environmental conditions of the agricultural park in real time. When the intelligent control evaluation value TK shows a downward trend, it can quickly identify potential problems and immediately start the adjustment program. According to the changing trend and specific value of the intelligent control evaluation value TK, the temperature W, humidity S, light intensity G and soil moisture TS parameters are adjusted in a targeted manner. This precise control can avoid waste of resources and ensure that crops grow in the best growth environment. By comprehensively considering the effects of multiple environmental parameters and control strategies, the stability and reliability of the system are enhanced. This comprehensive control method can cope with various complex environmental changes and crop growth needs, and ensure the long-term stable operation of the agricultural park.

[0143] In summary, the unit that comprehensively reflects the overall environmental status of the agricultural park, the unit that reflects the irrigation demand under the current environment, and the intelligent reflection and regulation strategy unit play a vital role in the distributed digital agricultural park environmental perception system. The three algorithm units calculate the irrigation demand GG and the intelligent regulation strategy evaluation value TK by comprehensively considering the key environmental parameters and crop growth needs, and realize real-time monitoring and intelligent regulation of the environmental parameters of the agricultural park according to the intelligent regulation evaluation value TK and the changing trends of temperature W, humidity S, light intensity G, and soil moisture TS. The temperature W, humidity S, light intensity G, and soil moisture TS in the unit that comprehensively reflects the overall environmental status of the agricultural park can be specifically fed back for targeted regulation. This feedback mechanism and targeted adjustment method can enhance the stability and reliability of the system. At the same time, by introducing a line graph to show the changing trend of the relevant values, the system operation status can be intuitively understood, and targeted adjustment measures can be taken according to the changing trend. This closed-loop regulation mechanism enables the system to continuously optimize the environmental conditions and improve agricultural production efficiency.

[0144] 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. Distributed digital agricultural park environment perception system, characterized by: The specific implementation steps are as follows: Step 1: Use the data acquisition module deployed in the agricultural park to collect environmental parameters such as temperature W, humidity S, light intensity G, soil moisture TS and carbon dioxide concentration CO2 in real time; Step 2: collecting historical data of relevant environmental parameters from the storage unit of the data collection module; Step 3: Use the data processing and calculation module to calculate and output the comprehensive environmental index HZ, irrigation demand GG and intelligent control evaluation value TK; Step 4: Use data display and feedback, and draw a trend chart in combination with the results of the intelligent control evaluation value TK. According to the change trends of the intelligent control evaluation value TK and temperature W, humidity S, light intensity G, and soil moisture TS, adjust the temperature W / humidity S / light intensity G / soil moisture TS in a targeted manner; The data processing and calculation module includes a unit for comprehensively reflecting the overall environmental conditions of the agricultural park, a unit for reflecting the irrigation demand under the current environment, and a unit for intelligently reflecting and regulating strategies.

2. The distributed digital agricultural park environment perception system according to claim 1 is characterized in that: The equipment used in the data acquisition module includes a temperature sensor, a humidity sensor, a light intensity sensor, a soil moisture sensor and a carbon dioxide concentration sensor; The equipment used in the data processing and computing module includes a central processing unit; The equipment used for data display and feedback includes data visualization equipment and intelligent control equipment.

3. The distributed digital agricultural park environment perception system according to claim 2 is characterized by: The calculation formula for the unit that fully reflects the overall environmental status of the agricultural park is as follows: WHAT 2,avg =(WHAT 2,1 +WHAT 2,2 +WHAT 2,3 +......+WHAT 2,n ) / n; in: HZ is the comprehensive environmental index; W is temperature; S is humidity; G is the light intensity; TS is soil moisture; CO2 is the concentration of carbon dioxide; CO 2,avg is the reference concentration of carbon dioxide; n is the total number of random inspections, which reflects the total number of times the reference concentration of carbon dioxide CO2 in the atmosphere is inspected; CO 2,1 The first sampling of carbon dioxide reference concentration, CO 2,2 The second sampling carbon dioxide reference concentration, CO 2,3 The third sampling carbon dioxide reference concentration, CO 2,n It is the reference concentration of carbon dioxide for the nth random inspection.

4. The distributed digital agricultural park environment perception system according to claim 3 is characterized by: The calculation formula reflecting the irrigation demand unit under the current environment is as follows: in: GG is the irrigation demand; HZ opt is the optimal comprehensive environmental index, HZ opt The comprehensive environmental index HZ reflects the highest value of crop growth trend in agricultural parks; G min is the minimum intensity of light; G max is the maximum intensity of light; W base is the base temperature, W base Indicates the temperature reached for irrigation.

5. The distributed digital agricultural park environment perception system according to claim 4 is characterized in that: The calculation formula of the intelligent reflection and regulation strategy unit is as follows: HZ tanget =(HZ1+HZ2+HZ3+......+HZ m ) / m; TS tanget =(TS1+TS2+TS3+......+TS m ) / m; in: TK is the intelligent control evaluation value; HZ prev is the last comprehensive environmental index; HZ tanget It is a comprehensive environmental benchmark index; m is the total number of historical test results, HZ tanget In the calculation formula, m reflects the total number of historical result values ​​used to calculate the benchmark value of the comprehensive environmental index H; HZ1 is the first historical testing environment comprehensive benchmark index, HZ2 is the second historical testing environment comprehensive benchmark index, HZ3 is the third historical testing environment comprehensive benchmark index, HZ m is the mth historical testing environment comprehensive benchmark index; GG prev The last irrigation demand; TS tanget is the soil base moisture; TS tanget The calculation formula m reflects the total number of historical result values ​​used to calculate the soil moisture TS benchmark value; TS1 is the first historical soil moisture detection, TS2 is the second historical soil moisture detection, TS3 is the third historical soil moisture detection, TS m Detect soil moisture for the mth history; TS max is the maximum soil moisture value, TS min is the minimum soil moisture value.

6. The distributed digital agricultural park environment perception system according to claim 5 is characterized by: The trend analysis based on the intelligent control evaluation value TK and drawing a line graph is as follows: If the intelligent control evaluation value TK in the line graph shows an upward trend, it means that the current intelligent control strategy is gradually being optimized, the crop growth environment is being improved, and the current control strategy should be maintained; If the intelligent control evaluation value TK in the line chart shows a downward trend, it means that there are problems with the current control strategy and the crop growth environment is deteriorating. The control strategy should be adjusted immediately. If the intelligent control evaluation value TK in the line chart fluctuates within a certain range and the overall trend is relatively stable, it means that the current control strategy is relatively stable.

7. The distributed digital agricultural park environment perception system according to claim 6 is characterized by: The control strategy is adjusted based on the trend of the intelligent control evaluation value TK on the linear graph, as well as the changes in the temperature W, humidity S, light intensity G, and soil moisture TS on the linear graph. The specific adjustments are as follows: If the intelligent control evaluation value TK shows a downward trend and is accompanied by large fluctuations in the temperature W on the line graph, the temperature W control device is adjusted; If the intelligent control evaluation value TK shows a downward trend, accompanied by a linear downward and upward trend in humidity S on the line graph, the humidity S control device is adjusted; If the change of the intelligent control evaluation value TK is closely related to the light intensity G, the light intensity G control device is adjusted; If the intelligent control evaluation value TK reflects that the soil moisture TS is insufficient or excessive, the soil moisture TS control device is adjusted.

8. The distributed digital agricultural park environment perception system according to claim 7 is characterized by: If the intelligent control evaluation value TK continues to show an upward trend and fluctuations within a certain range in the linear graph, the data acquisition module is used to continuously sense the agricultural park and stop the control strategy.

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