A smart bamboo irrigation system based on the Internet of Things

Abstract

This invention belongs to the field of intelligent irrigation technology. It provides an IoT-based intelligent bamboo irrigation system, comprising: initially dividing the bamboo forest area and identifying dense bamboo areas; acquiring wind speed and soil moisture data within any dense bamboo area, and determining the wind speed scenario; in the case of strong winds, quantitatively analyzing the changes in wind speed within the dense bamboo area to determine if the wind speed is stable; if the wind speed is stable, supplementing irrigation is performed on the dense bamboo area by analyzing the difference between the actual evaporation rate and the normal evaporation rate when there is no strong wind. This invention ensures precise matching between the water requirements for bamboo growth and the irrigation amount, and achieves efficient water resource utilization, significantly improving the reliability and practicality of the IoT-based intelligent irrigation system in complex strong wind scenarios.

Description

Technical Field

[0001] This invention belongs to the field of intelligent irrigation technology, specifically an intelligent bamboo irrigation system based on the Internet of Things. Background Technology

[0002] Bamboo, as one of my country's important forest resources, possesses significant ecological, economic, and social value, playing an irreplaceable role in numerous fields such as ecological restoration, soil and water conservation, timber substitution, landscaping, and the development of specialty industries. With the continuous expansion of bamboo forest planting scale and the gradual improvement of intensive management, irrigation, as a key factor affecting bamboo growth rate, quality, and yield, is crucial, and its precision and intelligence directly impact the sustainable development of the bamboo industry. Especially in the mountainous regions of southern my country, where bamboo forests are mostly distributed in mountainous and hilly areas with complex terrain, variable climate, and frequent strong winds, the interaction between vegetation cover characteristics and wind fields in dense bamboo areas significantly alters the regional water evaporation rate, significantly affecting the water supply and demand for bamboo growth. This places higher demands on the targeted and adaptable nature of bamboo irrigation technologies.

[0003] However, existing bamboo irrigation technologies often rely on extensive flood irrigation, lacking a targeted assessment mechanism for strong wind scenarios. They fail to incorporate wind field monitoring based on vegetation characteristics (such as canopy coverage and leaf area index) in dense bamboo areas, resulting in insufficient timeliness and accuracy in scenario assessment. Furthermore, supplementary irrigation strategies largely depend on manual experience, failing to quantify the stability of wind speed and its changing trends along wind direction under strong wind conditions. The supplementary irrigation model is singular and cannot dynamically adjust the irrigation volume based on additional evaporation losses or wind speed patterns, impacting bamboo growth stability and causing inefficient water resource utilization. The reliability and practicality of IoT-based intelligent irrigation systems in complex strong wind scenarios need improvement. Therefore, the present invention provides a smart bamboo irrigation system based on the Internet of Things. Summary of the Invention

[0004] In order to overcome the shortcomings of the prior art, at least one technical problem raised in the background art is solved.

[0005] The technical solution adopted by this invention to solve its technical problem is: Region identification module: performs preliminary division of the bamboo forest area and identifies densely populated bamboo areas within the forest; Scene Judgment Module: Based on any dense bamboo area, acquire wind speed data and soil moisture data in the bamboo forest, and perform scene judgment on the wind speed data; Stability determination module: In the case of strong wind, the module performs quantitative analysis on the changes in wind speed in dense bamboo areas to determine whether the wind speed in dense bamboo areas is stable. Stable supplementary irrigation analysis module: If the wind speed is stable in the bamboo-dense area, the actual evaporation in the bamboo-dense area is analyzed in terms of difference from the normal evaporation when there is no strong wind. A strong wind evaporation correction coefficient is introduced to determine the stable supplementary irrigation amount. Based on the stable supplementary irrigation amount, supplementary irrigation is carried out in the bamboo-dense area. Fluctuation irrigation analysis module: If the wind speed fluctuates in the dense bamboo area, the irrigation amount in the dense bamboo area is adjusted based on the initial irrigation amount at the strong wind inlet.

[0006] As a further aspect of the present invention: the process of identifying dense bamboo areas in a bamboo forest is as follows: The bamboo forest was evenly divided into several sub-regions according to a grid pattern. The sub-regions were analyzed and processed to determine the canopy coverage and leaf area index of the sub-regions. The weights of canopy coverage and leaf area index of a subregion are determined by the entropy method. The canopy coverage and leaf area index of a subregion are then weighted and summed to obtain the density characterization value. If the dense representation value is greater than or equal to the dense representation threshold, the corresponding sub-region is recorded as a bamboo dense region.

[0007] As a further aspect of the present invention: the process for determining the canopy coverage and leaf area index of the sub-region is as follows: A drone equipped with an RGB camera was used to take aerial photos of a bamboo forest sub-area. The percentage of vegetation pixels in the sub-area was calculated using image processing software and recorded as the canopy coverage of the sub-area. Within a sub-region, a portable leaf area index (LAI) meter is used to randomly select measurement points. The average of the measured LAIs from all measurement points is taken to obtain the LAI of the sub-region.

[0008] As a further aspect of the present invention: the process of determining the scene from the wind speed data is as follows: Wind speed data includes the average wind speed. Field wind speed sensors are evenly arranged in a grid pattern within the bamboo forest. Multiple field wind speed sensors along the wind direction are extracted, and the location of each field wind speed sensor is taken as a monitoring point. The wind speed is monitored by the field wind speed sensors to obtain the wind speed value at the monitoring point. Based on any monitoring point, a fixed sampling frequency and a preset collection period are used. All wind speed values ​​at the monitoring point within the sampling period are summed and averaged to obtain the average wind speed at the monitoring point. The average wind speed at the monitoring points was analyzed and processed to determine the compliance rate of the monitoring points; If the compliance rate of the measuring points is greater than or equal to the threshold of the compliance rate of the measuring points, it indicates that the bamboo forest is in a strong wind scenario.

[0009] As a further aspect of the present invention: the process of determining the compliance rate of the measuring points is as follows: If the average wind speed at the monitoring point is within the preset strong wind range, the corresponding monitoring point will be recorded as a qualified monitoring point. Calculate the percentage of monitoring points that meet the standards among all monitoring points, and record it as the monitoring point compliance rate.

[0010] As a further aspect of the present invention: the process of determining whether the wind speed is stable in the dense bamboo area is as follows: Based on the strong wind scenario, the average wind speed of all qualified measuring points is extracted and integrated into a wind speed average sequence according to the wind direction. The coefficient of variation of all wind speed data in the wind speed average sequence is calculated using the coefficient of variation formula to obtain the regional stability judgment value. If the regional stability judgment value is less than or equal to the regional stability judgment threshold, it indicates that the wind speed in the dense bamboo area is in a stable state; otherwise, it indicates that the wind speed in the dense bamboo area is in a fluctuating state.

[0011] As a further aspect of the present invention: the process of supplementing irrigation to dense bamboo areas based on a stable supplementary irrigation amount is as follows: By conducting a differential analysis between the actual evaporation rate in dense bamboo areas and the normal evaporation rate when there is no strong wind, the additional evaporation loss caused by strong wind in dense bamboo areas can be determined. The additional evaporation loss caused by strong winds in dense bamboo areas is used as a stable supplementary irrigation amount to irrigate these areas.

[0012] As a further aspect of the present invention: the process for determining the additional evaporation loss caused by strong winds in the dense bamboo area is as follows: Extract the canopy coverage of dense bamboo areas and calculate the actual evaporation rate of these areas. The normal evaporation rate without strong winds is calculated by multiplying the reference evaporation rate with the strong wind evaporation correction factor. The difference between the actual evaporation rate in the bamboo-dense area and the normal evaporation rate without strong winds is then calculated to obtain the additional evaporation loss caused by strong winds in the bamboo-dense area.

[0013] As a further aspect of the present invention: the process of adjusting the irrigation amount in the dense bamboo area is as follows: Based on the initial irrigation volume at the strong wind inlet, the canopy coverage of the dense bamboo area was extracted, and the actual evaporation of the dense bamboo area was calculated. The normal evaporation rate without strong winds is calculated by multiplying the reference evaporation rate with the strong wind evaporation correction factor. The difference between the actual evaporation rate in the bamboo-dense area and the normal evaporation rate without strong winds is then calculated to obtain the additional evaporation loss in the bamboo-dense area caused by strong winds. The additional evaporation loss caused by strong winds in dense bamboo areas is used as the initial re-irrigation amount at the strong wind inlet. Analyze the wind speed data in the wind speed mean series to determine the rate of change of wind speed; The initial irrigation amount at the strong wind inlet is multiplied by the wind speed change rate to obtain the variable irrigation amount. Based on the variable irrigation amount, supplementary irrigation is carried out at the monitoring point in the dense bamboo area.

[0014] As a further aspect of the present invention: the process for determining the rate of change of wind speed is as follows: The wind speed mean value, which is the first value in the sequence of wind speed mean values, is extracted as the wind speed mean value of the initial monitoring point. The difference between the wind speed mean value of the monitoring point and the wind speed mean value of the initial monitoring point is calculated, and then the ratio is calculated with the wind speed mean value of the initial monitoring point to obtain the wind speed change rate.

[0015] The beneficial effects of this invention are as follows: This invention divides bamboo-dense and non-dense areas; for the identified bamboo-dense areas, wind speed sensors are evenly arranged in a grid pattern, and strong wind scenarios are determined by statistically analyzing the compliance rate of measurement points. At the same time, non-strong wind scenarios are continuously monitored to ensure the timeliness and specificity of scenario judgment. This not only avoids the waste of resources caused by indiscriminate monitoring, but also improves the accuracy and reliability of dense area identification and scenario judgment, providing solid data support for subsequent precise supplementary irrigation decisions in strong wind scenarios.

[0016] This invention employs a closed-loop design for precise supplemental irrigation under varying wind conditions, based on wind speed stability assessment. This design integrates the vegetation and soil characteristics of densely populated bamboo areas from the initial stages, quantifies wind speed stability using the coefficient of variation, and analyzes wind direction trends through linear fitting, achieving a refined characterization of wind speed impact. Under stable conditions, additional evaporation losses are calculated based on a strong wind evaporation correction coefficient, while under fluctuating conditions, irrigation volume is dynamically adjusted according to the wind speed change rate, avoiding the limitations of a single supplemental irrigation mode. Furthermore, relying on the scientific method and quantitative indicators of the FAO Penman-Monteith formula, it replaces empirical judgment, ensuring a precise match between bamboo growth water requirements and irrigation volume, while also achieving efficient water resource utilization. This significantly improves the reliability and practicality of the IoT-based intelligent irrigation system under complex strong wind conditions. Attached Figure Description

[0017] The invention will now be further described with reference to the accompanying drawings.

[0018] Figure 1 This is a system block diagram of an IoT-based intelligent bamboo irrigation system according to an embodiment of the present invention; Figure 2 This is a flowchart illustrating the acquisition steps of an IoT-based smart bamboo irrigation method according to an embodiment of the present invention. Detailed Implementation

[0019] To make the technical means, creative features, objectives and effects of this invention easier to understand, the invention will be further described below in conjunction with specific embodiments.

[0020] Example 1 Please see Figure 1 As shown in the embodiment of the present invention, a smart bamboo irrigation system based on the Internet of Things includes the following modules: Region identification module: performs preliminary division of the bamboo forest area and identifies densely populated bamboo areas within the forest; The bamboo forest was evenly divided into several sub-regions in a grid pattern. A drone with an RGB camera was used to take aerial photos of the bamboo forest sub-regions at a height of 100-20 meters. The proportion of vegetation pixels in the photographed sub-regions was calculated using image processing software (such as QGIS and ENVI) and recorded as the canopy coverage of the sub-regions. Within a sub-region, randomly select measurement points using a portable leaf area index meter (such as LAI-2200), avoiding direct sunlight, and average the leaf area index measured at all measurement points to obtain the leaf area index of the sub-region. The weights of canopy coverage and leaf area index of a subregion are determined by the entropy method. The canopy coverage and leaf area index of a subregion are then weighted and summed to obtain the density characterization value. In some embodiments, the dense representation value is compared with a dense representation threshold, specifically: If the dense representation value is greater than or equal to the dense representation threshold, the corresponding sub-region is recorded as a bamboo dense region. If the dense representation value is less than the dense representation threshold, the corresponding sub-region is recorded as a non-bamboo dense region. Scene Judgment Module: Based on any dense bamboo area, acquire wind speed data and soil moisture data in the bamboo forest, and perform scene judgment on the wind speed data; The wind speed data includes the average wind speed. Field-type wind speed sensors are evenly arranged in a grid pattern within the bamboo forest. Multiple field-type wind speed sensors along the wind direction are extracted, and the arrangement position of the field-type wind speed sensors is used as a monitoring point. The wind speed is monitored by the field-type wind speed sensors to obtain the wind speed value at the monitoring point. Based on any monitoring point, a fixed sampling frequency and a preset collection period are used. All wind speed values ​​at the monitoring point within the sampling period are summed and averaged to obtain the average wind speed at the monitoring point. If the average wind speed at the monitoring point is within the preset strong wind range, the corresponding monitoring point will be recorded as a qualified monitoring point. If the average wind speed at a monitoring point is not within the preset strong wind range, the corresponding monitoring point will be recorded as a non-compliant monitoring point. It should be noted that the strong wind zone was set by those skilled in the art based on historical experience; The number of compliant monitoring points among all monitoring points is counted, and the percentage of compliant monitoring points among all monitoring points is calculated and recorded as the monitoring point compliance rate. If the compliance rate of the measuring points is greater than or equal to the threshold of the compliance rate of the measuring points, it indicates that the bamboo forest is in a strong wind scenario; If the compliance rate of the monitoring points is less than the threshold, it indicates that the bamboo forest is in a non-strong wind scenario, and the wind speed should continue to be monitored. The technical solution of this embodiment is as follows: The bamboo forest area is initially divided to identify dense bamboo areas; based on any dense bamboo area, wind speed data and soil moisture data are acquired, and scene judgment is performed on the wind speed data; this invention divides the bamboo forest into dense and non-dense areas; for the identified dense bamboo areas, wind speed sensors are evenly arranged in a grid pattern, and strong wind scenes are judged by statistically analyzing the compliance rate of measurement points. Simultaneously, non-strong wind scenes are continuously monitored to ensure the timeliness and specificity of scene judgment. This avoids resource waste caused by indiscriminate monitoring and improves the accuracy and reliability of dense area identification and scene judgment, providing solid data support for subsequent precise irrigation decisions under strong wind conditions.

[0021] Example 2 Please see Figure 1 As shown in the embodiment of the present invention, a smart bamboo irrigation system based on the Internet of Things further includes the following modules: Stability determination module: In the case of strong wind, the module performs quantitative analysis on the changes in wind speed in dense bamboo areas to determine whether the wind speed in dense bamboo areas is stable. It should be noted that in strong wind scenarios, the interaction between airflow and the vegetation and topography of dense bamboo areas, coupled with the natural characteristics of the wind field itself, leads to turbulent airflow and uneven energy distribution, resulting in fluctuations in wind speed in dense bamboo areas. The necessity of analyzing whether the wind speed in dense bamboo areas is stable is that strong winds directly accelerate surface water evaporation, and the stability of wind speed determines the persistence and fluctuation range of evaporation loss. The conclusion directly leads to the precise adjustment of supplementary irrigation strategies. This analysis not only connects the basic vegetation and soil conditions of dense bamboo areas (after preliminary division by number of bamboo plants, canopy coverage, etc., and correction by soil characteristics), but also avoids the supplementary irrigation deviation caused by relying solely on strong wind scenarios. Ultimately, it achieves efficient water resource utilization and precise matching of water requirements for bamboo growth, providing key data support for IoT-based intelligent irrigation decisions and ensuring irrigation effectiveness and bamboo growth stability. Based on the strong wind scenario, the average wind speed of all qualified measuring points is extracted and integrated into a wind speed average sequence according to the wind direction. The coefficient of variation of all wind speed data in the wind speed average sequence is calculated using the coefficient of variation formula to obtain the regional stability judgment value. If the regional stability judgment value is less than or equal to the regional stability judgment threshold, it indicates that the wind speed in the dense bamboo area is in a stable state. If the regional stability judgment value is greater than the regional stability judgment threshold, it indicates that the wind speed fluctuates in the bamboo-dense area. It should be noted that the beneficial effect of determining the regional stability judgment value is that it effectively avoids the bias of relying solely on experience-based judgment, reflects the actual amplitude of wind speed fluctuations in dense bamboo areas under strong winds, connects with the basic vegetation characteristics of dense bamboo areas previously defined by the proportion of bamboo plants, canopy coverage, and leaf area index, and clarifies the persistence and fluctuation patterns of water evaporation loss, providing a core quantitative basis for adjusting supplementary irrigation strategies; under stable conditions, water can be precisely supplemented according to evaporation loss; under fluctuating conditions, the trend of wind speed changes can be analyzed to make targeted adjustments to irrigation supplementation; at the same time, this indicator provides a clear decision input for IoT smart irrigation systems, ensuring that supplementary irrigation operations are adapted to the water demand characteristics of dense bamboo areas and the depth of the impact of strong winds, ultimately achieving a synergy between precise and controllable irrigation and healthy bamboo growth, and improving the practicality and reliability of smart irrigation systems in complex strong wind scenarios; Stable supplementary irrigation analysis module: If the wind speed is stable in the bamboo-dense area, the actual evaporation in the bamboo-dense area is analyzed in terms of difference from the normal evaporation when there is no strong wind. A strong wind evaporation correction coefficient is introduced to determine the stable supplementary irrigation amount. Based on the stable supplementary irrigation amount, supplementary irrigation is carried out in the bamboo-dense area. Canopy cover in dense bamboo areas is extracted using the formula: The actual evaporation rate in densely bamboo-grown areas was calculated. , This indicates the reference evaporation rate for areas with dense bamboo populations. Indicates the canopy coverage of dense bamboo areas; It should be noted that the reference evaporation rate is calculated based on the FAO Penman-Monteith formula, focusing on the impact of strong winds on evaporation; The strong wind evaporation correction factor is usually determined through correlation analysis between historical meteorological data and measured evaporation. The specific steps are as follows: Data Acquisition: Collect long-term meteorological data such as wind speed, temperature, humidity, and radiation for the target area. Simultaneously, measure the normal evaporation (ET) under conditions of no strong wind using an eddy covariance meter or lysimeter. n ; Regression modeling: Using the reference evaporation calculated by FAO Penman-Monteith as a benchmark, an ET model is established. n = ET0 × strong wind evaporation correction coefficient linear regression model; for example, studies have shown that in the Qinhuai River Basin, after correcting the strong wind evaporation correction coefficient of the Makkink method by monthly regression, the annual-scale average relative error decreased from more than 10% to 1.4%; Error calibration: The model accuracy was verified using indicators such as coefficient of variation (CV) and mean absolute error (MAE), and the Wilcoxon nonparametric test was used to ensure that the corrected results were not significantly different from the measured values. The normal evaporation rate without strong winds is calculated by multiplying the reference evaporation rate with the strong wind evaporation correction factor. The difference between the actual evaporation rate in the bamboo-dense area and the normal evaporation rate without strong winds is then calculated to obtain the additional evaporation loss in the bamboo-dense area caused by strong winds. It should be noted that the reference evaporation is calculated using the FAO Penman-Monteith formula. Under strong wind conditions, the actual evaporation differs significantly from the normal evaporation under calm conditions. The introduction of the strong wind evaporation correction factor is essentially an adaptive adjustment of the FAO formula to specific environments. Its theoretical basis includes: the accelerating effect of wind speed on evaporation: strong winds directly increase the evaporation rate by enhancing air turbulence and reducing canopy boundary layer resistance. The correction factor needs to quantify the relationship between this effect and wind speed; the buffering effect of vegetation canopy: high canopy coverage in dense bamboo areas can partially weaken the impact of wind speed on surface evaporation, therefore the correction factor needs to be dynamically adjusted in conjunction with canopy structure parameters. The additional evaporation loss caused by strong winds in dense bamboo areas is used as a stable supplementary irrigation amount to supplement the irrigation in dense bamboo areas. Fluctuation irrigation analysis module: If the wind speed fluctuates in the bamboo-dense area, the irrigation amount in the bamboo-dense area is adjusted based on the initial irrigation amount at the strong wind inlet. Based on the initial irrigation volume at the strong wind inlet, the canopy coverage of the dense bamboo area was extracted, and the actual evaporation of the dense bamboo area was calculated. It should be noted that the initial irrigation volume at the strong wind inlet is determined in the same way as the stable irrigation volume when the wind speed is stable in the bamboo-dense area; The normal evaporation rate without strong winds is calculated by multiplying the reference evaporation rate with the strong wind evaporation correction factor. The difference between the actual evaporation rate in the bamboo-dense area and the normal evaporation rate without strong winds is then calculated to obtain the additional evaporation loss in the bamboo-dense area caused by strong winds. The additional evaporation loss caused by strong winds in dense bamboo areas is used as the initial re-irrigation amount at the strong wind inlet. Extract the first wind speed mean value in the wind speed mean value sequence as the initial monitoring point wind speed mean value. Subtract the wind speed mean value of the monitoring point from the initial monitoring point wind speed mean value, and then compare the wind speed mean value of the monitoring point with the initial monitoring point wind speed mean value to obtain the wind speed change rate. The initial irrigation amount at the strong wind inlet is multiplied by the wind speed change rate to obtain the variable irrigation amount. Based on the variable irrigation amount, supplementary irrigation is carried out at the monitoring point in the dense bamboo area. For example, the actual evaporation ET a =ET0×CCstd=6.0 mm / d×0.90=5.4mm / d; Normal evaporation rate (ET) without strong winds n=ET0×strong wind evaporation correction factor=6.0 mm / d×0.75=4.5mm / d; Initial makeup water volume (strong wind inlet M1) = Additional evaporation loss = ET a - ET n =5.4 mm / d - 4.5 mm / d = 0.9 mm / d; Calculate the rate of change of wind speed at each monitoring point: Wind speed change rate formula = (Current average wind speed at monitoring points - Initial average wind speed at monitoring points) ÷ Initial average wind speed at monitoring points: M1 (initial point): Wind speed change rate = (5.5 - 5.5) ÷ 5.5 = 0; M2: Wind speed change rate = (6.2 - 5.5) ÷ 5.5 ≈ 0.127 (12.7%); M3: Wind speed change rate = (4.8-5.5) ÷ 5.5 ≈ -0.127 (-12.7%); M4: Wind speed change rate = (5.9-5.5) ÷ 5.5 ≈ 0.073 (7.3%); Calculate the change in supplemental irrigation amount at each monitoring point: The formula for variable irrigation amount is: Initial irrigation amount × Wind speed change rate (Note: If the result is negative, take 0 to avoid excessive reduction of irrigation leading to water shortage). M1 (Initial supplementary irrigation baseline): 0.9 mm / d × 0.00 = 0.9 mm / d (maintaining initial supplementary irrigation amount); M2: 0.9 mm / d × 0.127 ≈ 0.114 mm / d → Actual supplementary irrigation amount = Initial supplementary irrigation amount + Variable supplementary irrigation amount = 0.9 + 0.114 = 1.014 mm / d (Increased wind speed leads to increased evaporation, requiring additional supplementary irrigation) M3: 0.9 mm / d × (-0.127) ≈ -0.114 mm / d → Actual supplementary irrigation amount = 0.9 - 0.114 = 0.786 mm / d (Frequency decreases, evaporation weakens, and supplementary irrigation is reduced). M4: 0.9 mm / d × 0.073 ≈ 0.066 mm / d → Actual supplementary irrigation amount = 0.9 + 0.066 = 0.966 mm / d (slight increase in wind speed leads to a slight increase in supplementary irrigation). The technical solution of this invention is as follows: In the case of strong winds, the wind speed variation in dense bamboo areas is quantitatively analyzed to determine whether the wind speed is stable in the dense bamboo areas. If the wind speed is stable, the actual evaporation rate in the dense bamboo areas is compared with the normal evaporation rate when there is no strong wind. A strong wind evaporation correction coefficient is introduced to determine a stable supplementary irrigation amount, and supplementary irrigation is carried out in the dense bamboo areas based on the stable supplementary irrigation amount. If the wind speed fluctuates in the dense bamboo areas, the irrigation amount in the dense bamboo areas is adjusted based on the initial supplementary irrigation amount at the strong wind inlet. This invention, through the determination of wind speed stability in strong wind scenarios and the closed-loop design of precise supplementary irrigation in different states, connects... The study established the basic characteristics of vegetation and soil in dense bamboo areas in the early stages. It also quantified the stable state of wind speed through the coefficient of variation and analyzed the trend of wind direction changes through linear fitting, thus achieving a refined characterization of the impact of wind speed. Under stable conditions, it calculated additional evaporation loss based on the strong wind evaporation correction coefficient, and under fluctuating conditions, it dynamically adjusted the irrigation amount according to the rate of change of wind speed, avoiding the limitations of a single supplementary irrigation mode. At the same time, relying on the scientific method and quantitative indicators of the FAO Penman-Monteith formula, it replaced empirical judgment, which not only ensured the accurate matching of water requirements for bamboo growth and irrigation amount, but also achieved efficient use of water resources, significantly improving the reliability and practicality of the IoT smart irrigation system in complex strong wind scenarios.

[0022] Example 3 Based on the same inventive concept as the IoT-based smart bamboo irrigation system described in the foregoing embodiments, such as Figure 2 As shown, this application provides a smart bamboo irrigation method based on the Internet of Things, wherein the system specifically includes: Step 1: Make a preliminary division of the bamboo forest area and identify the dense bamboo areas within the forest; Step 2: Based on any dense bamboo area, obtain wind speed data and soil moisture data in the bamboo forest, and make scene judgments based on the wind speed data; Step 3: In the case of strong winds, quantitative analysis of wind speed changes in dense bamboo areas is conducted to determine whether the wind speed remains stable in these areas. Step 4: If the wind speed is stable in the dense bamboo area, the actual evaporation in the dense bamboo area is compared with the normal evaporation when there is no strong wind. A strong wind evaporation correction coefficient is introduced to determine the stable supplementary irrigation amount. Based on the stable supplementary irrigation amount, supplementary irrigation is carried out in the dense bamboo area. Step 5: If the wind speed fluctuates in the dense bamboo area, adjust the irrigation amount in the dense bamboo area based on the initial supplementary irrigation amount at the strong wind inlet.

[0023] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the present invention as claimed. The scope of protection of the present invention is defined by the appended claims and their equivalents.

Claims

1. A smart bamboo irrigation system based on the Internet of Things, characterized in that: include: Region identification module: performs preliminary division of the bamboo forest area and identifies densely populated bamboo areas within the forest; Scene Judgment Module: Based on any dense bamboo area, acquire wind speed data and soil moisture data in the bamboo forest, and perform scene judgment on the wind speed data; Stability determination module: In the case of strong wind, the module performs quantitative analysis on the changes in wind speed in dense bamboo areas to determine whether the wind speed in dense bamboo areas is stable. Stable supplementary irrigation analysis module: If the wind speed is stable in the bamboo-dense area, the actual evaporation in the bamboo-dense area is analyzed in terms of difference from the normal evaporation when there is no strong wind. A strong wind evaporation correction coefficient is introduced to determine the stable supplementary irrigation amount. Based on the stable supplementary irrigation amount, supplementary irrigation is carried out in the bamboo-dense area. Fluctuation irrigation analysis module: If the wind speed fluctuates in the dense bamboo area, the irrigation amount in the dense bamboo area is adjusted based on the initial irrigation amount at the strong wind inlet.

2. The smart bamboo irrigation system based on the Internet of Things according to claim 1, characterized in that: The process of identifying dense bamboo areas in a bamboo forest is as follows: The bamboo forest was evenly divided into several sub-regions according to a grid pattern. The sub-regions were analyzed and processed to determine the canopy coverage and leaf area index of the sub-regions. The weights of canopy coverage and leaf area index of a subregion are determined by the entropy method. The canopy coverage and leaf area index of a subregion are then weighted and summed to obtain the density characterization value. If the dense representation value is greater than or equal to the dense representation threshold, the corresponding sub-region is recorded as a bamboo dense region.

3. The smart bamboo irrigation system based on the Internet of Things according to claim 2, characterized in that: The process for determining the canopy coverage and leaf area index of the sub-region is as follows: A drone equipped with an RGB camera was used to take aerial photos of a bamboo forest sub-area. The percentage of vegetation pixels in the sub-area was calculated using image processing software and recorded as the canopy coverage of the sub-area. Within a sub-region, a portable leaf area index (LAI) meter is used to randomly select measurement points. The average of the measured LAIs from all measurement points is taken to obtain the LAI of the sub-region.

4. The smart bamboo irrigation system based on the Internet of Things according to claim 1, characterized in that: The process of determining the scene from the wind speed data is as follows: Wind speed data includes the average wind speed. Field wind speed sensors are evenly arranged in a grid pattern within the bamboo forest. Multiple field wind speed sensors along the wind direction are extracted, and the location of each field wind speed sensor is taken as a monitoring point. The wind speed is monitored by the field wind speed sensors to obtain the wind speed value at the monitoring point. Based on any monitoring point, a fixed sampling frequency and a preset collection period are used. All wind speed values ​​at the monitoring point within the sampling period are summed and averaged to obtain the average wind speed at the monitoring point. The average wind speed at the monitoring points was analyzed and processed to determine the compliance rate of the monitoring points; If the compliance rate of the measuring points is greater than or equal to the threshold of the compliance rate of the measuring points, it indicates that the bamboo forest is in a strong wind scenario.

5. The smart bamboo irrigation system based on the Internet of Things according to claim 4, characterized in that: The process for determining the compliance rate of the measuring points is as follows: If the average wind speed at the monitoring point is within the preset strong wind range, the corresponding monitoring point will be recorded as a qualified monitoring point. Calculate the percentage of monitoring points that meet the standards among all monitoring points, and record it as the monitoring point compliance rate.

6. The smart bamboo irrigation system based on the Internet of Things according to claim 5, characterized in that: The process for determining whether the wind speed remains stable in dense bamboo areas is as follows: Based on the strong wind scenario, the average wind speed of all qualified measuring points is extracted and integrated into a wind speed average sequence according to the wind direction. The coefficient of variation of all wind speed data in the wind speed average sequence is calculated using the coefficient of variation formula to obtain the regional stability judgment value. If the regional stability judgment value is less than or equal to the regional stability judgment threshold, it indicates that the wind speed in the dense bamboo area is in a stable state; otherwise, it indicates that the wind speed in the dense bamboo area is in a fluctuating state.

7. The smart bamboo irrigation system based on the Internet of Things according to claim 1, characterized in that: The process of supplementing irrigation to dense bamboo areas based on a stable supplemental irrigation amount is as follows: By conducting a differential analysis between the actual evaporation rate in dense bamboo areas and the normal evaporation rate when there is no strong wind, the additional evaporation loss caused by strong wind in dense bamboo areas can be determined. The additional evaporation loss caused by strong winds in dense bamboo areas is used as a stable supplementary irrigation amount to irrigate these areas.

8. The smart bamboo irrigation system based on the Internet of Things according to claim 7, characterized in that: The process for determining the additional evaporation loss caused by strong winds in the dense bamboo area is as follows: Extract the canopy coverage of dense bamboo areas and calculate the actual evaporation rate of these areas. The normal evaporation rate without strong winds is calculated by multiplying the reference evaporation rate with the strong wind evaporation correction factor. The difference between the actual evaporation rate in the bamboo-dense area and the normal evaporation rate without strong winds is then calculated to obtain the additional evaporation loss caused by strong winds in the bamboo-dense area.

9. A smart bamboo irrigation system based on the Internet of Things according to claim 7, characterized in that: The process of adjusting the irrigation amount in dense bamboo areas is as follows: Based on the initial irrigation volume at the strong wind inlet, the canopy coverage of the dense bamboo area was extracted, and the actual evaporation of the dense bamboo area was calculated. The normal evaporation rate without strong winds is calculated by multiplying the reference evaporation rate with the strong wind evaporation correction factor. The difference between the actual evaporation rate in the bamboo-dense area and the normal evaporation rate without strong winds is then calculated to obtain the additional evaporation loss in the bamboo-dense area caused by strong winds. The additional evaporation loss caused by strong winds in dense bamboo areas is used as the initial re-irrigation amount at the strong wind inlet. Analyze the wind speed data in the wind speed mean series to determine the rate of change of wind speed; The initial irrigation amount at the strong wind inlet is multiplied by the wind speed change rate to obtain the variable irrigation amount. Based on the variable irrigation amount, supplementary irrigation is carried out at the monitoring point in the dense bamboo area.

10. A smart bamboo irrigation system based on the Internet of Things according to claim 9, characterized in that: The process for determining the rate of change of wind speed is as follows: The wind speed mean value, which is the first value in the sequence of wind speed mean values, is extracted as the wind speed mean value of the initial monitoring point. The difference between the wind speed mean value of the monitoring point and the wind speed mean value of the initial monitoring point is calculated, and then the ratio is calculated with the wind speed mean value of the initial monitoring point to obtain the wind speed change rate.

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