Rainwater intelligent recycling system and method for facility agriculture

Abstract

The application relates to the technical field of rainwater recycling, in particular to a rainwater intelligent recycling system and method for facility agriculture. The system comprises a shed body covering a planting area, a rain guiding and adjusting device installed at the top of the shed body and used for guiding and adjusting the flow direction of rainwater, a rainwater driving device used for driving the rain guiding and adjusting device to act, a rainwater collecting device, a sensing unit used for detecting environmental parameters in and outside the shed in real time, and a processor. The processor is provided with the information about the types of planted crops and the requirements of different growth stages of the crops, is used for calculating the utilization requirement parameters of rainwater according to the information about the types of crops and the growth stages and the environmental parameters detected by the sensing unit, and controls the rainwater driving device based on the parameters to adjust the working state of the rain guiding and adjusting device, so that the rainwater is collected in the shed body area as required. The reasonable distribution of the collection of rainwater and the soil flushing of crops in the shed is solved.

Description

Technical Field

[0001] This invention relates to the field of rainwater harvesting technology, and in particular to an intelligent rainwater harvesting system and method for facility agriculture. Background Technology

[0002] As an important form of high-efficiency agriculture, facility agriculture provides a controlled environment for crop growth through greenhouse structures, playing a crucial role in ensuring crop yield and quality. Rainwater, as a clean and renewable resource, has significant value in facility agriculture irrigation and soil salinization improvement; therefore, rainwater harvesting systems have become an important component of facility agriculture infrastructure.

[0003] Furthermore, in the relatively enclosed environment of greenhouses, unlike traditional open-field agriculture where rainwater naturally irrigates the land, not only providing moisture but, more importantly, effectively removing soil salts to maintain salinity and ensure soil health, the natural erosion effect of rainwater is blocked by the greenhouse structure. This lack of rainwater leads to the continuous accumulation of salts in the soil. After two or three years of continuous cultivation, the soil salt content gradually increases, causing soil compaction and severely impacting crop growth and yield.

[0004] Currently, most rainwater treatment solutions used in facility agriculture adopt a fixed design approach, which involves enclosing the roof to collect all rainwater. While this achieves rainwater recycling, it cannot be used to specifically flush out salinized areas of the soil inside the greenhouse.

[0005] Currently, on the one hand, we need to consider the sensitivity of crops to the intensity of rainwater when it washes over the crop planting environment, and on the other hand, we need to consider the collection of rainwater and use the collected rainwater to irrigate crops during periods of no rain or little rain. In summary, we need a system that can dynamically regulate the collection of rainwater and the distribution of rainwater within the greenhouse to avoid low utilization of rainwater resources and negative impacts on crop growth and soil conditions caused by improper rainwater regulation. Summary of the Invention

[0006] To address the rational distribution of rainwater collection and soil erosion within greenhouse crops, this invention provides an intelligent rainwater recycling system for facility agriculture.

[0007] In a first aspect, the present invention provides a smart rainwater harvesting system for facility agriculture, comprising:

[0008] The greenhouse covering the planting area;

[0009] A rain-guiding and regulating device is installed on the top of the canopy to guide and regulate the flow of rainwater;

[0010] A rainwater driving device, connected to the rain-guiding adjustment device, is used to drive the rain-guiding adjustment device to operate;

[0011] Rainwater collection devices are installed inside and outside the shed to collect rainwater that is guided into the shed by the rainwater regulating device;

[0012] Sensing units, arranged inside and outside the greenhouse, are used to detect environmental parameters inside and outside the greenhouse in real time;

[0013] The processor is communicatively connected to both the rainwater driving device and the sensing unit.

[0014] The processor includes:

[0015] Obtain information on the types of crops planted and their different growth stages;

[0016] Based on information about crop type and growth stage, as well as environmental parameters detected by the sensing unit, the rainwater utilization demand parameters are calculated. Based on these parameters, the rainwater driving device is controlled, and the working state of the rainwater guiding device is adjusted so that rainwater is collected as needed in the greenhouse area.

[0017] Furthermore, the sensing unit includes:

[0018] Soil condition detection components are installed in the soil inside the greenhouse to detect soil salinization parameters;

[0019] Rainfall detection components, installed outside the canopy, are used to detect rainfall intensity parameters;

[0020] A water storage status detection component is installed inside the PP water storage module to detect water storage parameters;

[0021] The sensing unit is used to transmit salinization-related parameters, rainfall intensity parameters, and water storage parameters to the processor in real time.

[0022] Furthermore, the rain-guiding adjustment device includes several rotatable rain-guiding blades, which are horizontally arranged on the top of the canopy to form a continuous canopy roof. The rainwater driving device is equipped with a driving component corresponding to the rain-guiding blades. The driving component is used to control the rotation angle of the corresponding rain-guiding blades to achieve relative opening and closing of the rain-guiding blades relative to each other. The rainwater collection device includes a rainwater collection trough and a PP water storage module. The rainwater collection trough is located on the outer edges of opposite sides of the canopy and extends along the laying direction of the rain-guiding blades. The PP water storage module is connected to the rainwater collection trough through a pipe. When the rain-guiding blades are relatively closed relative to each other, the rain-guiding blades guide rainwater into the rainwater collection trough and into the PP water storage module. When the rain-guiding blades are relatively open relative to each other, the rain-guiding blades guide some rainwater into the rainwater collection trough while allowing rainwater to enter the canopy through the space between the front and rear of the rain-guiding blades.

[0023] Furthermore, the processor includes a first angle determination module and a second angle determination module. The first angle determination module determines a safe threshold for the target opening and closing angle of the rain guide blade based on pre-stored tolerance characteristic parameters of the corresponding crop growth stage, matching crop type and growth stage information. The safe threshold is the maximum allowable opening and closing angle of the rain guide blade under the current crop growth stage, which is used to constrain the upper limit of the target opening and closing angle of the rain guide blade determined by the second angle determination module. Under the constraint of the safe threshold, the second angle determination module is used to call soil salinization parameters, rainfall intensity parameters, and water storage parameters to calculate and obtain a rainwater harvesting level score, and determine the target opening and closing angle of the rain guide blade under the constraint of the safe threshold based on the rainwater harvesting level score.

[0024] Furthermore, the rainwater harvesting rating includes:

[0025] An AHP hierarchical structure is constructed, which includes a target layer for determining the optimal opening and closing angle of rain guide blades; a quasi-side layer for crop tolerance characteristics and environmental parameter requirements; and an index layer including basic tolerance, growth stage, soil salinization status, rainfall intensity, and water storage.

[0026] Construct a judgment matrix, calculate the weights using the eigenvector method, and perform consistency verification.

[0027] Standardize and quantify soil salinization, rainfall intensity, and water storage;

[0028] The formula for calculating the rainwater harvesting rating is: ,in,

[0029] It is a comprehensive index of environmental parameters;

[0030] This represents the basic tolerance score for crops. The total weight of crop basic tolerance relative to the target layer;

[0031] The score is based on the crop growth stage. This represents the total weight of the crop growth stage relative to the target layer.

[0032] Standardized scores for soil salinization parameters, The total weight of soil salinization index relative to the target layer;

[0033] Standardized scores for rainfall intensity parameters, The total weight of the rainfall intensity index relative to the target layer;

[0034] Standardized scores for water storage parameters, This represents the total weight of the water storage index relative to the target layer.

[0035] Furthermore, the construction of the judgment matrix, the calculation of weights using the eigenvector method, and the consistency verification include:

[0036] Using the target layer as a benchmark, determine the effectiveness of the quasi-lateral layer parameter weights;

[0037] The validity of the parameter weights in the indicator layer is judged based on the criteria layer.

[0038] The total weight of each indicator to the target layer is calculated by multiplying the parameter weights of the criterion layer and the parameter weights of the indicator layer.

[0039] Furthermore, the determination of the validity of the quasi-side layer parameter weights based on the target layer includes:

[0040] Construct the target layer judgment matrix and calculate the normalized weights of the criterion layer parameters: Formula: ,in, For the first Normalized weights of each criterion-level factor; The target layer judgment matrix is ​​the first Row product The right root; The target layer judgment matrix is ​​the first column product The root of the power.

[0041] The consistency check is performed using the following formula: ,in, For the corresponding number The characteristic values ​​of each criterion-level factor Target layer judgment matrix With the criterion layer weight vector The i-th element of the product;

[0042] Calculate the maximum eigenvalue of the target layer judgment matrix And calculate the consistency ratio. ,in, , , This serves as a consistency index for the target layer judgment matrix. As a random consistency indicator, the consistency ratio is less than The quasi-lateral layer parameter weights are effective.

[0043] Furthermore, the determination of the validity of the indicator layer parameter weights based on the criterion layer includes:

[0044] Construct the criterion layer judgment matrix and calculate the normalized weights of the target layer parameters: , For the first Normalized weights of each target layer factor; The criterion layer judgment matrix is ​​the first Row product The right root; The criterion layer judgment matrix is ​​the first column product The right root;

[0045] Perform a consistency check, calculate the largest eigenvalue of the criterion-level judgment matrix, and calculate the consistency ratio. If the consistency ratio is less than [a certain value], then [the condition is considered acceptable]. The weights of the indicator layer parameters are effective.

[0046] Furthermore, the standardized quantitative formulas for soil salinization, rainfall intensity, and water storage include:

[0047] S21 = 10 × (Measured EC - Critical EC Value) / (Severe EC - Critical EC Value), where the critical EC value is the first threshold; severe EC value is the second threshold. If the measured EC value is not greater than the first threshold, S21 = 0; if the measured EC value is not less than the second threshold, S21 = 10. The critical EC value is 2.0 mS / cm; severe EC value is 4.0 mS / cm. If the measured EC value is ≤ 2.0 mS / cm, S21 = 0; if the measured EC value is ≥ 4.0 mS / cm, S21 = 10.

[0048] S22 = 10 - 10 × |Measured Rainfall Intensity - Optimal Rainfall Intensity| / (Rainfall Intensity Heavy Rain - Rainfall Intensity Light Rain), where optimal rainfall intensity is the third threshold; light rain is the fourth threshold; and heavy rain is the fifth threshold. If the measured rainfall intensity is not greater than the fourth threshold or not less than the fifth threshold, S22 = 2. Optimal rainfall intensity = 15 mm / h; light rain = 5 mm / h; heavy rain = 30 mm / h. If the measured rainfall intensity is ≤ 5 mm / h or ≥ 30 mm / h, S22 = 2.

[0049] S23 = 10 × (total water storage - actual water storage) / total water storage. If the actual water storage is 0, S23 = 10; if the actual water storage is full, S23 = 0.

[0050] Furthermore, determining the target opening angle of the rain guide blades under the constraint of the safety threshold based on the rainwater harvesting level score includes:

[0051] When the rain-guiding adjustment device receives the target opening / closing angle information sent by the second angle determination module, it moves to the matching angle range.

[0052] In the first angle range, when the driving component drives the rain guide blade to rotate to this range, the rain guide adjustment device is in a closed state, and adjacent rain guide blades are connected front and back to form a continuous guide surface to guide all rainwater to the rain collection trough.

[0053] In the second angle range, the driving component drives the rain guide blades to rotate, the rain guide adjustment device is in a semi-open state, and the adjacent rain guide blades form a first gap to guide some rainwater to the rain collection trough, while allowing another part of the rainwater to enter the shed through the first gap.

[0054] In the third angle range, when the driving component drives the rain guide blades to rotate to this range, the rain guide adjustment device is in a high open state, and a second gap larger than the first gap is formed between adjacent rain guide blades to guide some rainwater to the rain collection trough, while allowing another part of the rainwater to enter the shed through the second gap.

[0055] Secondly, a smart rainwater harvesting method for facility agriculture includes:

[0056] Obtain information on crop types and growth stages, as well as environmental parameters inside and outside the greenhouse;

[0057] Rainwater utilization demand parameters are determined based on crop type and growth stage information and the aforementioned environmental parameters.

[0058] Control the rainwater drive device to adjust the state of the rain guide device so that rainwater is collected as needed in the shed area.

[0059] Furthermore, the environmental parameters inside and outside the greenhouse include soil salinization parameters, rainfall intensity parameters, and water storage parameters;

[0060] The process of determining rainwater utilization demand parameters based on crop type and growth stage information and environmental parameters includes matching pre-stored tolerance characteristic parameters of corresponding crop growth stages based on crop type and growth stage information, determining the safety threshold for the operation of the rain-guiding adjustment device, calculating rainwater collection level score by calling soil salinization parameters, rainfall intensity parameters and water storage parameters under the constraint of the safety threshold, and determining the angle range that matches the rainwater utilization demand parameters based on the rainwater collection level score.

[0061] Thirdly, the present invention provides a computer-readable storage medium storing a plurality of instructions adapted to be loaded and executed by a processor of a terminal device as described in the intelligent rainwater harvesting method for facility agriculture.

[0062] Fourthly, the present invention provides a terminal device, including a processor and a computer-readable storage medium, wherein the processor is used to implement various instructions; the computer-readable storage medium is used to store multiple instructions, the instructions being adapted to be loaded and executed by the processor to provide a method for intelligent rainwater harvesting in facility agriculture.

[0063] In summary, the present invention has the following beneficial technical effects:

[0064] 1. This invention proposes an intelligent rainwater harvesting system and method for facility agriculture, which dynamically regulates rainwater distribution and improves rainwater resource utilization. The invention utilizes a rainwater guiding and adjusting device composed of rotatable rain-guiding blades and corresponding drive components, combined with three-angle interval control logic output by a processor, to achieve the distribution of rainwater collection and internal flushing. When priority rainwater collection is needed, the blades close to guide all rainwater into the collection trough; when a balance between collection and flushing is required, the blades form a first gap to distribute rainwater; when priority flushing is needed, the blades form a larger second gap to ensure sufficient rainwater entering the facility. This design breaks away from the traditional fixed distribution mode, adapting rainwater utilization to actual needs and significantly improving rainwater resource utilization.

[0065] 2. This invention adapts to crop growth characteristics and effectively protects crop growth. The first angle determination module sets a safe threshold for the opening and closing of the rain guide blades based on the pre-stored tolerance parameters of crop growth stages. During the growth period of highly tolerant crops, a larger opening and closing angle is allowed to meet the scouring requirements, while the opening and closing angle is limited during the seedling stage of weakly tolerant crops to avoid rain impact damage. This design enables rainwater regulation to be deeply matched with crop characteristics, effectively reducing rainwater-related crop losses and ensuring the safety of crop growth.

[0066] 3. This invention employs multi-parameter closed-loop control to enhance soil improvement and rainwater utilization. A precision sensing unit collects real-time parameters such as soil salinization, rainfall intensity, and water storage. The processor's second angle determination module generates angle commands based on rainwater collection level scoring. Prioritizing flushing when salinization is severe, reducing rainwater collection when the tank is full, and lowering the opening angle during heavy rain to prevent flooding. Combined with the guide components of the soil flushing auxiliary device, rainwater can be directionally used to improve salinized soil and extend the effective planting cycle. This control shifts rainwater utilization from an experience-based approach to a data-driven one, significantly improving soil improvement and rainwater utilization, and providing technical support for the green and efficient development of facility agriculture. Attached Figure Description

[0067] Figure 1 This is a schematic diagram of the structure of the intelligent rainwater recycling system for facility agriculture according to Embodiment 1 of the present invention;

[0068] Figure 2 This is a top view of the intelligent rainwater harvesting system for facility agriculture according to Embodiment 1 of the present invention;

[0069] Figure 3This is a schematic diagram of the structure of the driving component driving the rain guide blade in Embodiment 1;

[0070] Figure 4 This is a side view of the rain guide blade in Embodiment 1;

[0071] Figure 5 This is a top view of the flow guide in Embodiment 1;

[0072] Figure 6 This is a flowchart of the comprehensive decision-making process in Embodiment 1.

[0073] Figure 7 This is a flowchart of the breakdown steps of step 3 in embodiment 1;

[0074] Figure 8 This is a flowchart of the breakdown steps of step 4 in embodiment 1;

[0075] Figure 9 This is a flowchart of the steps in Embodiment 2.

[0076] The components include: 1. Shed; 2. Rain guide adjustment device; 201. Rain guide blade; 202. Rain guide trough; 3. Drive assembly; 4. Rain collection trough; 5. PP water storage module; and 6. Flow guide. Detailed Implementation

[0077] To better understand the above-mentioned objectives, features, and advantages of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. It should be noted that, where there is no conflict, the embodiments of the present invention and the features thereof can be combined with each other.

[0078] Many specific details are set forth in the following description in order to provide a full understanding of the invention. However, the invention may also be practiced in other ways different from those described herein, and therefore the scope of protection of the invention is not limited to the specific embodiments disclosed below.

[0079] Reference Figure 1 The figure shows the overall structure of the invention, which mainly includes the following devices: a greenhouse 1 covering the planting area; a rain guiding and regulating device 2; a rainwater driving device; a sensing unit; a processor; a rainwater collection device; and a soil flushing auxiliary device.

[0080] The canopy 1 serves as the basic support carrier for the entire intelligent rainwater harvesting system. It not only provides shade for the planting area, preventing external environmental factors such as strong sunlight and strong winds from directly affecting crop growth, but also provides a stable installation reference surface for core components such as the rain guide adjustment device 2 and the rainwater drive device, ensuring that the assembly of each component meets the operational requirements. At the same time, its structural strength can withstand the loads of rainwater impact and snow accumulation, ensuring the long-term stable operation of the system.

[0081] Reference Figure 2 The rain-guiding adjustment device 2 is installed on the top of the shed 1 to guide and adjust the flow of rainwater; the rainwater driving device is connected to the rain-guiding adjustment device 2 to drive the rain-guiding adjustment device 2 to operate; the sensing unit is arranged inside and outside the shed 1 to detect environmental parameters inside and outside the shed in real time; the processor is communicatively connected to the rainwater driving device and the sensing unit respectively, and the processor stores the types of crops planted and their different growth stages and their requirements information. The processor is used to calculate the rainwater utilization requirements parameters based on the crop types and growth stages and the environmental parameters detected by the sensing unit, and to control the rainwater driving device based on the parameters to adjust the working state of the rain-guiding adjustment device 2 so that rainwater is collected as needed in the area of ​​the shed 1.

[0082] Reference Figure 3 The rain-guiding adjustment device 2 includes several rotatable rain-guiding blades 201, which are horizontally arranged on the top of the canopy 1 to form a continuous canopy roof. The rainwater driving device is equipped with a driving component 3 corresponding to the rain-guiding blades 201. The driving component 3 is used to control the rotation angle of the corresponding rain-guiding blades 201 to realize the relative opening and closing of the rain-guiding blades 201 relative to each other. The top of the canopy 1 can be set as a double-sided triangle or a single-sided triangle structure. The rain-guiding blades 201 are arranged on the top of the canopy 1, allowing rainwater to flow downwards along the rain-guiding blades 201, with the arrangement direction perpendicular to the rainwater flow direction. (Refer to...) Figure 4 In addition, a rain guide groove 202 is formed on the rain guide blade 201. The rain guide blade 201 can be tilted upward or rotated into the canopy 1 under the drive of the drive component 3. Regardless of the drive method, the rain guide groove 202 can guide rainwater to the rain collection groove 4 on the one hand, and on the other hand, it can largely prevent rainwater from flowing into the canopy 1 along the rain guide blade. In the best case, the rain collection groove 4 is set at one end close to the rotating shaft, and the rain guide blade 201 tilts upward.

[0083] The drive component 3 of the rainwater drive device adopts a DC servo motor, specifically model 130ST-M06025. This motor is a permanent magnet synchronous DC servo type, with a rated torque of 6 N·m and a rated speed of 1500 rpm. It also has a built-in 1000-line resolution encoder, which can provide real-time feedback on the rotation position of the motor rotor, providing data support for precise angle control. The motor housing adopts an IP65 protection rating design, which can resist the influence of external environmental factors such as rainwater splashing from the roof and dust, and is suitable for open and semi-enclosed installation scenarios in facility agriculture, ensuring long-term stable operation.

[0084] The DC servo motor can be a one-to-one independent control unit corresponding to the rain guide blade 201, or it can be driven by gears to control the rotation of a group (multiple) of rain guide blades 201 in a region. According to the target angle command issued by the processor, it can drive the corresponding blade to rotate independently or synchronously, so as to avoid the failure of a single blade affecting the operation of the overall system. The drive component 3 has a built-in angle feedback module, which can transmit the actual rotation angle of the blade back to the processor in real time, forming a closed-loop control of "command issuance-angle execution-feedback verification", correcting mechanical operation errors and ensuring that the deviation between the actual angle of the blade and the target angle meets the design requirements.

[0085] Reference Figure 1 To achieve rainwater collection and irrigate crops inside the greenhouse 1 when there is no rain, the rainwater collection device includes a rainwater collection trough 4 and a PP water storage module 5. The rainwater collection trough 4 is located on the outer edges of opposite sides of the greenhouse 1 and extends along the laying direction of the rain guide blades 201. The PP water storage module 5 is connected to the rainwater collection trough 4 through a pipe. When the rain guide blades 201 are closed relative to each other, the rain guide blades 201 guide rainwater into the rainwater collection trough 4 and into the PP water storage module 5. When the rain guide blades 201 are open relative to each other, the rain guide blades 201 guide some rainwater into the rainwater collection trough 4 while allowing rainwater to enter the greenhouse 1 through the space between the front and rear of the rain guide blades 201.

[0086] Reference Figure 5 In order to better irrigate inside the greenhouse 1, the soil scouring auxiliary device is used to irrigate and scour the planting area inside the greenhouse 1 by taking advantage of the rainwater scouring. The soil scouring auxiliary device includes a guide 6 set on the ground of the greenhouse 1. The guide 6 is used to guide the flow path of rainwater on the soil surface when the rainwater guiding adjustment device 2 is relatively open to each other. The guide 6 can be set with a certain slope according to the actual situation so that the rainwater flows to the target area.

[0087] As described above, the processor is used to calculate the rainwater utilization demand parameters based on crop type and growth stage information, as well as environmental parameters detected by the sensing unit. In specific embodiments, different types of crops have different levels of rainwater tolerance at different times.

[0088] In this embodiment, the sensing unit includes a soil condition detection component, a rainfall detection component, and a water storage condition detection component, specifically:

[0089] The soil condition monitoring component uses a soil conductivity sensor (TDR-300), arranged in a 5m×5m grid with 40 sensors installed in the planting area inside the greenhouse, buried at a depth of 20cm. The monitored parameter is soil salinization parameter (EC value), with a detection accuracy of ±0.01mS / cm and a data transmission frequency of once every 30 seconds. This distributed deployment covers the entire planting area, rather than providing localized single-point monitoring, ensuring that the acquired soil salinization parameters reflect the differences in soil health across different planting areas. This provides comprehensive data support for the processor to determine "priority erosion areas." Furthermore, the component is resistant to soil corrosion and interference, allowing for stable long-term operation buried in the soil, and preventing changes in soil moisture and temperature from affecting the detection accuracy.

[0090] The rainfall detection component, employing a tipping bucket rain gauge (JL-20), is positioned at the top center of the outer side of the canopy 1, 0.5m above the canopy roof. The detection parameter is rainfall intensity (mm / h), with a detection accuracy of ±0.1mm and a data transmission frequency of once every 10 seconds. The rainfall detection component is installed in an unobstructed area outside the canopy 1, avoiding interference from the canopy structure and blades, ensuring the capture of real-time changes in natural rainfall intensity. Its detection frequency is adapted to the processor's decision cycle, enabling rapid response to sudden changes in rainfall intensity. In the event of a sudden downpour, it triggers emergency control logic in the processor, such as adjusting the blade opening angle for flood prevention, providing real-time data support.

[0091] The water storage status detection component uses an ultrasonic level sensor (US-600) located at the top center inside the PP water storage module. The detection parameter is the water volume (corresponding to the liquid level height), with a detection accuracy of ±1cm and a data transmission frequency of once per minute. This component can monitor the liquid level changes within the PP water storage module in real time.

[0092] The raw data collected by each sensor is preprocessed (filtered and outlier removed) by the edge computing module (model STM32F407) and then uploaded to the processor via the LoRa wireless communication module (transmission distance ≤1km).

[0093] The rainwater harvesting system includes a rainwater collection trough 4 and a PP water storage module. The rainwater collection trough 4 is made of PVC-U material with a U-shaped cross-section and is laid along the outer edges of both sides of the shed 1. The bottom of the trough has a 1‰ slope, and the lowest point is connected to the PP water storage module through a DN100 PVC pipe. The PP water storage module adopts a modular splicing structure, with each module measuring 1000mm×500mm×500mm and a total volume of 50m³. The module has an internal filter screen (0.5mm aperture) to prevent impurities from entering. According to actual setup requirements, an electric butterfly valve is installed on the pipe, controlled by a processor. The modular splicing design of the PP water storage module allows for flexible adjustment of the total volume according to the rainwater demand of the planting area, adapting to different scales of facility agriculture scenarios. The module material has rainwater corrosion resistance and aging resistance properties, suitable for long-term rainwater storage environments. The internal filter structure can filter impurities such as fallen leaves and silt carried by rainwater, preventing impurities from clogging subsequent irrigation pipes and ensuring the safety of secondary reuse of recycled rainwater.

[0094] The soil flushing auxiliary component includes a flow guide 6, which is an arc-shaped flow guide channel made of PE material (150mm wide × 80mm high). It is laid along the direction of the planting rows in the greenhouse, with a spacing of 2m between adjacent flow guide channels. The bottom of the flow guide channel is equipped with water permeable holes. The slope of the flow guide channel is consistent with the slope of the ground in the greenhouse. After rainwater enters the greenhouse through the gap of the rain guide blades 201, it flows along the flow guide channel to the root area of ​​the planting rows, avoiding the irregular spread of rainwater on the soil surface and improving the efficiency of flushing saline soil by ≥30%.

[0095] The processor's hardware configuration uses an industrial control computer, model IPC-610L, equipped with a 10-inch touch screen, supporting local operation and remote cloud control;

[0096] The software has a built-in "Rainwater Utilization Decision System V1.0", which includes a first angle determination module, a second angle determination module, and a data storage module. It can realize functions such as parameter calculation, command issuance, and data log storage. The communication interface has multiple interfaces such as RS485, LoRa, and Ethernet (RJ45), and can simultaneously connect to peripherals such as rainwater drive devices, sensing units, and electric butterfly valves. The interface response speed is ≤50ms.

[0097] In this embodiment, the processor uses a fourth-order logic based on pre-judgment, parameter quantization and weighting, comprehensive decision-making, and angle output to achieve intelligent adjustment of the opening angle of the rain guide blade 201. The processor's decision logic and execution flow are as follows:

[0098] Reference Figure 6 Step 1: Preliminary judgment to determine the safety threshold of the rain guide blades.

[0099] The processor matches the tolerance characteristic parameters of the corresponding crop with the pre-stored "crop type and growth stage" information to determine the safe threshold (i.e., the maximum allowable opening angle) of the rain guide blades. In this embodiment, three typical crops are selected (strong tolerance: grape; moderate tolerance: tomato; weak tolerance: lettuce). The safe thresholds for different growth stages are shown in Table 1 below. The processor includes a first angle determination module, which matches the pre-stored tolerance characteristic parameters of the corresponding crop growth stage with the crop type and growth stage information to determine the safe threshold of the target opening angle of the rain guide blades. The maximum opening angle of the rain guide blades is 90°.

[0100] Table 1. Crop Types and Growth Stages

[0101]

[0102] Threshold adjustment rules: If the crop is affected by pests or diseases, such as late blight in tomatoes, the processor can receive a manually input "disease level" signal and further reduce the maximum allowable opening angle by 10%-20% to prevent direct rainwater impact from aggravating the disease. The specific opening angle and control range can be adjusted based on more detailed experiments and various factors in actual production. By setting a safety threshold, the processor can more safely ensure that even when the rain guide blades are at their maximum angle, the impact of rainwater on the crop remains controllable. It should be noted that the crop growth cycles in Table 1 are based on spring planting in northern greenhouses, which is also the design of the mainstream greenhouse planting mode. However, the October-November period marked in the table refers to late-maturing varieties and does not affect the rainwater harvesting system's decision-making during the rainy season.

[0103] Step 2: Determine the parameter quantization rules

[0104] Under safety threshold constraints, the processor standardizes and quantifies the "soil salinization parameters, rainfall intensity, and water storage" collected by the sensing unit (0-10 points), and assigns weights according to "crop type-growth stage" (total weights 100%), with the weights tilted towards the core needs of the current stage. Specific quantification rules are shown in Table 2 below:

[0105] Table 2: Parameter Standardization and Quantification Rules (0-10 points)

[0106]

[0107]

[0108] Reference Figure 7 Step 3. Comprehensive decision-making: Calculate the comprehensive rainwater utilization index.

[0109] Step 31. Determine the percentage of the safety threshold.

[0110] Before determining the flushing volume control ratio, it is necessary to first define the processor weighted summation formula to calculate the comprehensive rainwater utilization index (0-10 points), which is the rainwater collection level score. This index directly reflects the priority of rainwater collection or flushing. The formula is as follows:

[0111]

[0112] in, It is a comprehensive index of environmental parameters (reflecting the basic trend of "rainwater harvesting-flushing").

[0113] This represents the basic tolerance score for crops. The total weight of crop basic tolerance relative to the target layer;

[0114] The score is based on the crop growth stage. This represents the total weight of the crop growth stage relative to the target layer.

[0115] Standardized scores for soil salinization parameters, The total weight of soil salinization index relative to the target layer;

[0116] Standardized scores for rainfall intensity parameters, The total weight of the rainfall intensity index relative to the target layer;

[0117] Standardized scores for water storage parameters, This represents the total weight of the water storage index relative to the target layer.

[0118] Next, based on the comprehensive index range, we determine the core exploitation tendencies that are limited by the first-order security threshold.

[0119] The determination of the target opening angle of the rain guide blade under the constraint of the safety threshold based on the rainwater harvesting level score includes:

[0120] When the rain-guiding adjustment device receives the target opening / closing angle information sent by the second angle determination module, it moves to the matching angle range.

[0121] In the first angle range, when the driving component drives the rain guide blade to rotate to this range, the rain guide adjustment device is in a closed state, and adjacent rain guide blades are connected front and back to form a continuous guide surface to guide all rainwater to the rain collection trough.

[0122] The first angle range can be set to within 40% of the safety threshold (the comprehensive index range of 7-10 points given in Table 3) to guide most of the rainwater to the rainwater collection trough.

[0123] Similarly, the first angle zone can also be set to a fully enclosed state, preventing rainwater from entering the interior of the shed.

[0124] In the second angle range, the driving component drives the rain guide blades to rotate, the rain guide adjustment device is in a semi-open state, and the adjacent rain guide blades form a first gap to guide some rainwater to the rain collection trough, while allowing another part of the rainwater to enter the shed through the first gap.

[0125] In the third angle range, when the driving component drives the rain guide blades to rotate to this range, the rain guide adjustment device is in a high open state, and a second gap larger than the first gap is formed between adjacent rain guide blades to guide some rainwater to the rain collection trough, while allowing another part of the rainwater to enter the shed through the second gap.

[0126] Regarding the percentage set as the safety threshold corresponding to the angle range, this embodiment provides the corresponding ratios in Table 3 below.

[0127] Table 3: Core Utilization Tendency and Ratio of Flue Volume Control

[0128]

[0129] Step 32. Construct the AHP hierarchy

[0130] Before implementing the weighted summation formula to calculate the comprehensive index range of the core utilization tendency, it is necessary to determine the weight values ​​of each influencing factor. This embodiment constructs an AHP hierarchical structure through a layered design of target layer, criterion layer, and indicator layer, and verifies the rationality by calculating the weight through judgment matrix and consistency check, and finally outputs the blade target angle by combining the parameter quantification formula.

[0131] Target layer (O): Decision on the optimal opening angle of the rain guide blades;

[0132] Criterion Layer (C): 2 core criteria, namely "Crop Tolerance Characteristics (C1)" and "Environmental Parameter Requirements (C2)";

[0133] Crop tolerance characteristics (C1): Determines the safety boundary for leaf angle, including two indicator layer factors;

[0134] Environmental parameter requirements (C2): These determine the dynamic adjustment of the blade angle and include three index layers of factors.

[0135] Indicator layer (P): Sub-indicators of crop tolerance characteristics: basic tolerance (P11), growth stage (P12);

[0136] The environmental parameters required include the following sub-indicators: soil salinization status (P21), rainfall intensity (P22), and water storage (P23).

[0137] Step 33. Design the judgment matrix and calculate the weights (AHP) (criteria layer and index layer)

[0138] Design a judgment matrix (1 = equally important, 3 = slightly important, 5 = significantly important, 7 = strongly important, 9 = extremely important, and the reciprocal is the opposite of the importance), calculate the weights using the "eigenvector method", and verify the logical rationality by combining the "consistency test (CR<0.1)".

[0139] Step 331. Calculation of judgment matrices and weights for the criterion layer (C1, C2)

[0140] Using "target layer O" as the benchmark, the importance of C1 (crop tolerance characteristics) and C2 (environmental parameter requirements) is determined, and the determination matrix is ​​constructed as shown in Table 4 below:

[0141] Table 4: Target Layer Judgment Matrix

[0142]

[0143] Based on the target layer judgment matrix above, the weight calculation steps are as follows:

[0144] (1) Formula for calculating the product of elements in each row:

[0145]

[0146] in, To determine the matrix of the first The product of all elements in a row;

[0147] The row index of the judgment matrix (corresponding to the index of the criterion layer factor);

[0148] The column index of the judgment matrix (corresponding to the index of the criterion layer factor);

[0149] To determine the matrix of the first Line number The element of the column (representing the first) The factor is relative to the first (Importance scale of factors, 1-9 scale).

[0150] Calculate the product of elements in each row: ; .

[0151] (2) Calculate the nth root of the product of each row (n=2, number of criteria layer factors):

[0152]

[0153] in, To determine the matrix of the first Row product The power root (the element of the unnormalized weight vector). To determine the order of a matrix;

[0154] ;

[0155] (3) Normalization formula:

[0156]

[0157] in, For the first Normalized weights of each criterion layer factor (final criterion layer weight vector) (elements)

[0158] ;

[0159] (4) Formula for calculating the product of the judgment matrix and the weight vector:

[0160]

[0161] in, To determine the matrix With the criterion layer weight vector The i-th element of the product;

[0162] The judgment matrix (n-order square matrix) for the criteria layer factors.

[0163] The normalized weight vector (n-dimensional column vector) of the criteria layer factors.

[0164] is the normalized weight of the j-th criterion layer factor.

[0165]

[0166]

[0167] (5) Eigenvalue calculation formula:

[0168] ,

[0169] in, For the corresponding number Eigenvalues ​​of each criterion layer factor (judgment matrix) (local eigenvalues)

[0170]

[0171] (6) Calculate the maximum eigenvalue λmax of the judgment matrix:

[0172]

[0173] in, To determine the matrix The largest eigenvalue (core parameter for consistency test).

[0174]

[0175] (7) Formula for calculating the Consistency Index (CI):

[0176]

[0177] in, CI is used to determine the consistency index of a matrix (measures the degree to which a matrix deviates from perfect consistency; CI=0 indicates perfect consistency).

[0178]

[0179] (8) Formula for calculating the conformity ratio (CR):

[0180]

[0181] in, To determine the consistency ratio of the matrix (final consistency test index, CR<0.1 indicates that the matrix is ​​logically consistent and the weights are effective);

[0182] The random consistency index (RI) is a standard value obtained by looking up the order n of the judgment matrix; when n=2, RI=0; when n=3, RI=0.58, etc.; the random consistency index RI (RI=0 when n=2).

[0183] Consistency ratio The judgment matrix is ​​consistent with the logic, and the weights are valid.

[0184] Step 332. Calculation of judgment matrix and weights for indicator layer (P11, P12) (belonging to C1)

[0185] Based on the "criterion layer C1 (crop tolerance characteristics)", the importance of P11 (basic tolerance) and P12 (growth stage) is determined, and the judgment matrix is ​​constructed as shown in Table 5 below:

[0186] Table 5 Crop Tolerance Characteristic Judgment Matrix

[0187]

[0188] Weight calculation steps:

[0189] Product per row: ;

[0190] nth root (n=2): ;

[0191] Normalization: ;

[0192] Consistency check: , 0, The weights are effective.

[0193] Step 333. Calculation of judgment matrices and weights for the indicator layer (P21, P22, P23) (belonging to C2)

[0194] Based on the "criterion layer C2 (environmental parameter requirements)", the importance of P21 (soil salinization), P22 (rainfall intensity), and P23 (water storage) is determined, and the judgment matrix is ​​constructed as shown in Table 6 below:

[0195] Table 6 Environmental Parameter Demand Judgment Matrix

[0196]

[0197] Weight calculation steps:

[0198] Product per row: ; ;

[0199] nth root (n=3): ; ;

[0200] Normalization: ; 0.258; 0.105.

[0201] Consistency check: , (3.038-3) / (3-1)=0.019, The weights are effective. λmax≈3.038 , (when n=3) ), The judgment matrix is ​​consistent with the logic, and the weights are valid.

[0202] Step 34. Calculate the total weight (index layer relative to target layer)

[0203] The total weight (Wtotal) of each indicator to the target layer is calculated by multiplying the weight of the criterion layer by the weight of the indicator layer. The results are shown in Table 7 below.

[0204] Table 7 Total Weights of the Target Layer

[0205]

[0206] Step 35. Parameter standardization and quantization:

[0207] Table 2 provides one quantitative standard, and step 35 provides another quantitative standard:

[0208] For the three dynamic parameters in the indicator layer, namely "soil salinization (P21), rainfall intensity (P22), and water storage (P23)," a standardized quantitative formula was designed (score S∈[0,10], with higher scores indicating a stronger tendency to "prioritize meeting the requirements of this parameter"), as follows:

[0209] (1) Soil salinization quantification formula (S21)

[0210] Based on soil EC values ​​(electrical conductivity, reflecting the degree of salinization), the following formula was designed: S21 = 10 × (measured EC - critical EC value) / (specific EC - critical EC value).

[0211] Defined parameters: EC critical value (upper limit of crop tolerance) = 2.0 mS / cm; EC severe (requiring emergency flushing) = 4.0 mS / cm;

[0212] Boundary conditions: If the measured EC is ≤2.0 mS / cm (no salinization), S21=0; if the measured EC is ≥4.0 mS / cm (severe salinization), S21=10.

[0213] (2) Formula for quantifying rainfall intensity (S22)

[0214] S22 = 10 - 10 × |Measured Rainfall Intensity - Optimal Rainfall Intensity| / (Rainfall Intensity - Heavy Rainfall Intensity - Light Rainfall)

[0215] Define parameters: Optimal rainfall intensity (suitable for flushing and harvesting) = 15 mm / h; Light rain rainfall intensity (prioritizes harvesting) = 5 mm / h; Heavy rain rainfall intensity (requires control) = 30 mm / h;

[0216] Boundary conditions: If the measured rainfall intensity is 15 mm / h, S22 = 10; if the measured rainfall intensity is ≤5 mm / h or ≥30 mm / h, S22 = 2.

[0217] (3) Formula for quantifying water storage (S23)

[0218] S23 = 10 × (Total water storage - Actual water storage) / Total water storage

[0219] Define parameters: Total water storage = 50m³ (total volume of PP water storage modules);

[0220] Boundary conditions: If the measured water storage is 0 (empty tank), S23 = 10; if the measured water storage is 50 m³ (full tank), S23 = 0.

[0221] Step 36. Calculation of Comprehensive Rainwater Utilization Index

[0222] Combining the "total weight (W_total)" and the "parameter standardized score (S)", the "rainwater utilization comprehensive index (I)" is calculated using the following formula:

[0223] illustrate: (Basic tolerance score) (Growth stage score) is a qualitative parameter quantification (S∈[0,10]), with specific rules as follows:

[0224] Basic tolerance Strong tolerance = 10, moderate tolerance = 6, weak tolerance = 2;

[0225] growth stage Seedling stage = 3, growth stage = 8, fruiting stage = 5.

[0226] Index range: I∈[0,10]. The larger I is, the stronger the tendency of "priority rainwater collection" and the smaller I is, the stronger the tendency of "priority flushing".

[0227] Reference Figure 8 Step 4. Specific application scenario calculation examples

[0228] Taking "medium-tolerant crop (tomato) - growth period" as an example, the complete calculation process is completed by combining actual environmental parameters, and the target opening and closing angle of the rain guide blade is output.

[0229] Step 41. Collection and Determination of Basic Scene Parameters

[0230] Crop parameters: moderately tolerant (S11=6), growth period (S12=8);

[0231] Environmental parameters: measured soil EC = 3.0 mS / cm, measured rainfall intensity = 15 mm / h, measured water storage = 20 m³;

[0232] Safety threshold: Maximum permissible leaf opening angle for moderately tolerant - growing season = 60°.

[0233] Step 42. Calculate the standardized scores of the dynamic parameters (S21, S22, S23).

[0234] S21 (soil salinization): S21 = 10 × (3.0 - 2.0) / (4.0 - 2.0) = 10 × 0.5 = 5 points

[0235] S22 (Rainfall Intensity): S22 = 10 - 10 × |15 - 15| / (30 - 5) = 10 - 0 = 10 points

[0236] S23 (water storage capacity): S23 = 10 × (50 - 20) / 50 = 10 × 0.6 = 6 points

[0237] Step 43. Calculate the comprehensive rainwater utilization index (I).

[0238] Substituting the total weight (Table 7) and the scores of each parameter: I = (6 × 0.5) + (8 × 0.25) + (5 × 0.159) + (10 × 0.064) + (6 × 0.026) = 3 + 2 + 0.795 + 0.64 + 0.156 = 6.591 points (≈ 6.6 points)

[0239] Step 44. Map the target opening angle of the rain guide blades.

[0240] Based on the comprehensive index (I=6.6 points, indicating a tendency towards "balanced rainwater harvesting and scour"), and under the constraint of a safety threshold of 60°:

[0241] When the exponent I∈[4,7], the angle = safety threshold × angle range (the angle range is 40%-60% of the safety threshold).

[0242] The lower limit of the target angle is: 60° × 40% = 24°

[0243] The upper limit of the target angle is: 60° × 60% = 36°

[0244] Step 45. Execute and record the data log.

[0245] After determining the angle range of "24° to 36°", the processor can calculate the unique fixed angle within the range through a dynamic weight bias algorithm, enabling the servo motor to execute a single angle command.

[0246] The specific steps are as follows:

[0247] The standardized scores of the calculated dynamic parameters are called, and the contribution of each dynamic parameter to the angular bias is calculated using the formula "Parameter demand intensity = Parameter score × Parameter weight".

[0248] The formula is:

[0249] Bias coefficient = (S21×W21+S23×W23) / (S21×W21+S22×W22+S23×W23);

[0250] Substituting the data, we get: Bias coefficient = (5×0.159+6×0.026) / (5×0.159+10×0.064+6×0.026) = (0.795+0.156) / (0.795+0.64+0.156)≈0.951 / 1.591≈0.6;

[0251] The bias coefficient ∈ [0,1], the closer the coefficient is to 0, the more the angle is biased towards the lower limit of the interval 24° (prioritizing rainwater collection); the closer the coefficient is to 1, the more the angle is biased towards the upper limit of the interval 36° (prioritizing scouring).

[0252] Based on the bias coefficient and the angle interval span (36°-24°=12°), the fixed angle is calculated using the formula: Fixed angle = lower limit of angle interval + bias coefficient × interval span. Substituting the data, we get: Fixed angle = 24° + 0.6 × 12° = 24° + 7.2° = 31.2°. The processor rounds the calculation result (or retains one decimal place), and finally determines the fixed angle to be 31°.

[0253] The processor calls the safety threshold of 60°, verifies whether the calculated fixed angle of 31° is within the "24°-36°" range and does not exceed the safety threshold, and generates a single angle instruction of "open 31°" after confirming that there is no error.

[0254] Similarly, an angle command can be randomly selected within this range (24°-36°) to drive the rain guide blades to swing within that range. Furthermore, the rain guide blade angle is adjusted by recalculating the score at intervals during rainfall, allowing for timely adjustments based on the current situation.

[0255] The servo motor drives the blades to rotate to 31°, while simultaneously recording data in a log.

[0256]

[0257] Example 2

[0258] Reference Figure 9 This embodiment provides a smart rainwater harvesting method for facility agriculture, specifically as follows:

[0259] S1. Obtain information on crop type and growth stage, as well as environmental parameters inside and outside the greenhouse;

[0260] S2. Determine the rainwater utilization demand parameters based on crop type and growth stage information and the aforementioned environmental parameters;

[0261] S3. Control the rainwater drive device to adjust the state of the rain guide device so that rainwater is collected as needed in the shed area.

[0262] The environmental parameters inside and outside the greenhouse include soil salinization parameters, rainfall intensity parameters, and water storage parameters.

[0263] The process of determining rainwater utilization demand parameters based on crop type and growth stage information and environmental parameters includes matching pre-stored tolerance characteristic parameters of corresponding crop growth stages based on crop type and growth stage information, determining the safety threshold for the operation of the rain-guiding adjustment device, calculating rainwater collection level score by calling soil salinization parameters, rainfall intensity parameters and water storage parameters under the constraint of the safety threshold, and determining the angle range that matches the rainwater utilization demand parameters based on the rainwater collection level score.

[0264] Example 3

[0265] This embodiment provides:

[0266] A computer-readable storage medium storing a plurality of instructions adapted for loading and execution by a processor of a terminal device, the aforementioned intelligent rainwater harvesting method for facility agriculture.

[0267] A terminal device includes a processor and a computer-readable storage medium, the processor being used to implement various instructions; the computer-readable storage medium being used to store multiple instructions adapted to be loaded and executed by the processor as described in the intelligent rainwater harvesting method for facility agriculture.

[0268] The above are all preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. Therefore, all equivalent changes made in accordance with the structure, shape and principle of the present invention should be covered within the scope of protection of the present invention.

Claims

1. A rainwater intelligent recycling system for facility agriculture, characterized in that, include: The greenhouse covering the planting area; A rain-guiding and regulating device is installed on the top of the canopy to guide and regulate the flow of rainwater; A rainwater driving device, connected to the rain-guiding adjustment device, is used to drive the rain-guiding adjustment device to operate; Rainwater collection devices are installed inside and outside the shed to collect rainwater that is guided into the shed by the rainwater regulating device; Sensing units, arranged inside and outside the greenhouse, are used to detect environmental parameters inside and outside the greenhouse in real time; The rain-guiding adjustment device includes several rotatable rain-guiding blades, which are horizontally arranged on the top of the canopy to form a continuous canopy roof. The rainwater driving device is equipped with a driving component corresponding to the rain-guiding blades. The driving component is used to control the rotation angle of the corresponding rain-guiding blades to realize the relative opening and closing of the rain-guiding blades. The rainwater collection device includes a rainwater collection trough and a PP water storage module. The rainwater collection trough is located on the outer edges of opposite sides of the canopy and extends along the laying direction of the rain-guiding blades. The PP water storage module is connected to the rainwater collection trough through a pipe. When the rain-guiding blades are relatively closed, the rain-guiding blades guide rainwater into the rainwater collection trough and into the PP water storage module. When the rain-guiding blades are relatively open, the rain-guiding blades guide some rainwater into the rainwater collection trough while allowing rainwater to enter the canopy through the space between the front and rear of the rain-guiding blades. The processor is communicatively connected to both the rainwater driving device and the sensing unit. The processor includes: Obtain information on the types of crops planted and their different growth stages; Based on information about crop type and growth stage, and environmental parameters detected by the sensing unit, the rainwater utilization demand parameters are calculated. Based on these parameters, the rainwater driving device is controlled, and the working state of the rainwater guiding device is adjusted so that rainwater is collected as needed in the greenhouse area. The processor includes a first angle determination module and a second angle determination module. The first angle determination module determines a safe threshold for the target opening and closing angle of the rain guide blade based on pre-stored tolerance characteristic parameters of the corresponding crop growth stage, matching crop type and growth stage information. The safe threshold is the maximum allowable opening and closing angle of the rain guide blade under the current crop growth stage, which is used to constrain the upper limit of the target opening and closing angle of the rain guide blade determined by the second angle determination module. Under the constraint of the safe threshold, the second angle determination module is used to call soil salinization parameters, rainfall intensity parameters, and water storage parameters to calculate and obtain a rainwater harvesting level score, and determine the target opening and closing angle of the rain guide blade under the constraint of the safe threshold based on the rainwater harvesting level score.

2. The intelligent rainwater harvesting system for facility agriculture according to claim 1, characterized in that, The rainwater harvesting rating includes: An AHP hierarchical structure is constructed, which includes a target layer for determining the optimal opening angle of the rain guide blades; a criterion layer for crop tolerance characteristics and environmental parameter requirements; and an index layer including basic tolerance, growth stage, soil salinization status, rainfall intensity, and water storage. Construct a judgment matrix, calculate the weights using the eigenvector method, and perform consistency verification. Standardize and quantify soil salinization, rainfall intensity, and water storage; The formula for calculating the rainwater harvesting rating is: ,in, This represents the basic tolerance score for crops. The total weight of crop basic tolerance relative to the target layer; The score is based on the crop growth stage. This represents the total weight of the crop growth stage relative to the target layer. Standardized scores for soil salinization parameters, The total weight of soil salinization index relative to the target layer; Standardized scores for rainfall intensity parameters, The total weight of the rainfall intensity index relative to the target layer; Standardize the score for the water storage parameter. This represents the total weight of the water storage index relative to the target layer.

3. The intelligent rainwater harvesting system for facility agriculture according to claim 2, characterized in that, The process of constructing the judgment matrix, calculating weights using the eigenvector method, and performing consistency verification includes: Using the target layer as a benchmark, determine the effectiveness of the parameter weights in the criterion layer; The validity of the parameter weights in the indicator layer is judged based on the criteria layer. The total weight of each indicator to the target layer is calculated by multiplying the parameter weights of the criterion layer and the parameter weights of the indicator layer.

4. The intelligent rainwater harvesting system for facility agriculture according to claim 3, characterized in that, The determination of the validity of the parameter weights of the criterion layer based on the target layer includes: Construct the target layer judgment matrix and calculate the normalized weights of the criterion layer parameters: Formula: ,in, For the first Normalized weights of each criterion-level factor; The target layer judgment matrix is ​​the first Row element product The right root; The target layer judgment matrix is ​​the first Column element product The right root; The consistency check is performed using the following formula: ,in, For the corresponding number The characteristic values ​​of each criterion-level factor Target layer judgment matrix With the criterion layer weight vector The i-th element of the product; Calculate the maximum eigenvalue of the target layer judgment matrix And calculate the consistency ratio. ,in, , , This serves as a consistency index for the target layer judgment matrix. As a random consistency indicator, the consistency ratio is less than The weights of the criteria layer parameters are valid.

5. The intelligent rainwater harvesting system for facility agriculture according to claim 4, characterized in that, The determination of the validity of the indicator layer parameter weights based on the criterion layer includes: Construct the criterion layer judgment matrix and calculate the normalized weights of the target layer parameters: , For the first Normalized weights of each target layer factor; The criterion layer judgment matrix is ​​the first Row element product The right root; The criterion layer judgment matrix is ​​the first Column element product The right root; Perform a consistency check, calculate the largest eigenvalue of the criterion-level judgment matrix, and calculate the consistency ratio. If the consistency ratio is less than [a certain value], then [the condition is considered acceptable]. The weights of the indicator layer parameters are effective.

6. The intelligent rainwater harvesting system for facility agriculture according to claim 5, characterized in that, The determination of the target opening angle of the rain guide blade under the constraint of the safety threshold based on the rainwater harvesting level score includes: When the rain-guiding adjustment device receives the target opening / closing angle information sent by the second angle determination module, it moves to the matching angle range. In the first angle range, when the driving component drives the rain guide blade to rotate to this range, the rain guide adjustment device is in a closed state, and adjacent rain guide blades are connected front and back to form a continuous guide surface to guide all rainwater to the rain collection trough. In the second angle range, the driving component drives the rain guide blades to rotate, the rain guide adjustment device is in a semi-open state, and the adjacent rain guide blades form a first gap to guide some rainwater to the rain collection trough, while allowing another part of the rainwater to enter the shed through the first gap. In the third angle range, when the driving component drives the rain guide blades to rotate to this range, the rain guide adjustment device is in a high open state, and a second gap larger than the first gap is formed between adjacent rain guide blades to guide some rainwater to the rain collection trough, while allowing another part of the rainwater to enter the shed through the second gap.

7. A method for intelligent rainwater harvesting in facility agriculture, based on the intelligent rainwater harvesting system for facility agriculture as described in any one of claims 1-6, characterized in that, include: Obtain information on crop types and growth stages, as well as environmental parameters inside and outside the greenhouse; Rainwater utilization demand parameters are determined based on crop type and growth stage information and the aforementioned environmental parameters. Control the rainwater drive device to adjust the state of the rainwater guiding device so that rainwater can be collected as needed in the canopy area; The environmental parameters inside and outside the greenhouse include soil salinization parameters, rainfall intensity parameters, and water storage parameters.

8. The intelligent rainwater harvesting method for facility agriculture according to claim 7, characterized in that, The process of determining rainwater utilization demand parameters based on crop type and growth stage information and environmental parameters includes matching pre-stored tolerance characteristic parameters of corresponding crop growth stages based on crop type and growth stage information, determining the safety threshold for the operation of the rain-guiding adjustment device, calculating rainwater collection level score by calling soil salinization parameters, rainfall intensity parameters and water storage parameters under the constraint of the safety threshold, and determining the angle range that matches the rainwater utilization demand parameters based on the rainwater collection level score.

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