Portable sapling spraying regulation and control device for garden maintenance

Abstract

The invention relates to a portable sapling spraying regulation and control device for garden maintenance, and belongs to the technical field of forestry. Comprising a fixed spraying execution unit and a portable control terminal. The environment sensing module collects environment data in real time, the environment data is processed by the first control and communication module and then uploaded to the portable control terminal, and the self-adaptive control algorithm module generates a personalized spraying control instruction and a height adjusting instruction in combination with a sapling maintenance file, a built-in growth model and the uploaded environment data. And after receiving the instruction, the first control and communication module coordinates the height adjusting assembly and the spraying execution module to execute corresponding actions.

Description

Technical Field

[0001] This invention relates to a portable seedling spray control device for garden maintenance, belonging to the field of forestry technology. Background Technology

[0002] Tree seedling maintenance is a core aspect of garden maintenance, and the accuracy of sprinkler irrigation directly affects seedling survival rate, growth rate, and maintenance costs. Currently, garden tree seedling sprinkler systems mainly rely on traditional manual watering, fixed sprinkler networks, or simple timed sprinkler devices, which have several technical limitations:

[0003] Problems with fixed height: The nozzles of traditional fixed sprinkler systems are at a fixed height and cannot be dynamically adjusted as the seedlings grow. As the seedlings grow taller, the spray mist cannot effectively cover the canopy, resulting in water shortage in the upper branches and leaves, while the soil below becomes excessively moist.

[0004] Insufficient level of intelligence: Most existing intelligent irrigation systems only control the start and stop based on soil moisture thresholds, lacking the ability to perceive and predict the growth status of seedlings, and thus failing to achieve personalized, full-cycle precision maintenance.

[0005] Lack of growth adaptability: Most existing adjustable sprinkler systems are manually adjustable or simply timed, and cannot adaptively adjust according to the actual growth rate of the seedlings and environmental conditions;

[0006] Low management efficiency: For large-scale gardens, there is a lack of effective multi-point collaborative management and decision support systems. Maintenance personnel still need to check and adjust each one individually, resulting in high labor intensity.

[0007] For example, Chinese Patent Publication No. CN117530151A discloses an intelligent garden irrigation system, including: an intelligent irrigation control module, which captures environmental temperature, humidity, and light data and implements graded control of quantity, time, and quality to irrigate plants in the garden in real time; a data monitoring and analysis module, which collects growth parameters of plants in the garden and establishes a database, analyzes and processes the collected datasets in the database by building a data analysis model, determines the optimal irrigation time, and monitors plant growth in the garden based on the analysis of the datasets; and a remote control module, which connects the intelligent irrigation control module and the data detection and analysis module, and enables connection between a terminal and a mobile device, allowing the mobile device to monitor the plant growth in the garden in real time and control the intelligent irrigation control module to irrigate in real time; however, it lacks growth adaptability and height adjustment functions.

[0008] Therefore, developing a device that can intelligently adjust the spray height according to the growth status of seedlings and environmental conditions, and achieve multi-point collaborative management, has important practical significance and technical value. Summary of the Invention

[0009] The purpose of this invention is to provide a portable seedling spray control device for garden maintenance, which enables dynamic adaptation of spray height to seedling growth; establishes an intelligent decision-making system based on multi-sensor data and growth models; provides an interactive correction mechanism combining human and intelligent methods; and realizes multi-point collaborative and refined management of large-scale gardens.

[0010] The present invention provides a portable seedling spray control device for garden maintenance, comprising a fixed spray execution unit and a portable control terminal;

[0011] The fixed spray execution unit includes:

[0012] A fixed base assembly, comprising a soil anchoring structure and an installation base;

[0013] A height adjustment assembly, mounted on a mounting base, includes a height adjustment element, a drive mechanism, and a height position sensor;

[0014] The spray execution module includes a solenoid valve, a spray head, a water supply interface, and a flow sensor, and is used to execute spray control commands including spray start / stop and flow regulation;

[0015] The environmental sensing module includes a soil moisture sensor and a canopy temperature and humidity sensor;

[0016] First control and communication module;

[0017] The portable control terminal includes:

[0018] A human-computer interaction interface, including an input device and a display device, is used to set and adjust parameters;

[0019] The second control and communication module connects to multiple first control and communication modules via a wireless network to establish communication with multiple fixed sprinkler execution units, thereby achieving one-to-many coordinated control of seedling sprinkler systems.

[0020] The multi-node management module supports the simultaneous management of multiple fixed spray execution units;

[0021] The adaptive control algorithm module has a built-in three-level adaptive growth model, including a basic growth curve model library, an environmental factor correction model, and an individual adaptive learning model.

[0022] The environmental perception module collects environmental data in real time, which is then processed by the first control and communication module and uploaded to the portable control terminal. The adaptive control algorithm module combines the seedling maintenance file, the built-in growth model and the uploaded environmental data to generate personalized sprinkler control commands and height adjustment commands, which are then sent to the corresponding fixed sprinkler execution unit through the second control and communication module. After receiving the commands, the first control and communication module coordinates the height adjustment component and the sprinkler execution module to perform the corresponding actions.

[0023] This system achieves a separate architecture for fixed sprinkler systems and portable control, resolving the contradiction of traditional sprinkler systems being either inconveniently fixed and difficult to control, or requiring heavy manual labor. The fixed execution unit ensures sprinkler stability, while the portable control terminal provides operational flexibility, allowing maintenance personnel to adjust sprinkler systems without physically visiting each sapling, significantly reducing labor intensity. Integrating multiple sensors and an intelligent decision-making system, the system achieves comprehensive perception of the sapling's growth environment through a combination of soil moisture sensors and canopy temperature and humidity sensors. Combined with a three-level adaptive growth model, sprinkler decision-making is upgraded from simple "threshold triggering" to "intelligent prediction based on growth status," improving the scientific rigor and accuracy of maintenance. Supporting one-to-many collaborative control, a single control terminal can manage multiple sprinkler points simultaneously, enabling a single maintenance personnel to efficiently manage large-scale gardens, significantly improving management efficiency compared to traditional methods, making it particularly suitable for large-scale scenarios such as municipal gardens and nurseries. Achieving full growth cycle adaptability, the device adapts from the seedling stage to the mature seedling stage through a highly adjustable design combined with growth model prediction, solving the key technical challenge of sprinkler failure in fixed sprinkler systems as saplings grow taller.

[0024] Preferably, the height adjustment component adopts a multi-section sleeve structure, with each inner sleeve slidingly engaged with the outer sleeve. The top of the innermost sleeve is connected to the nozzle assembly, and the bottom of the outermost sleeve is fixed to the fixed base assembly. The driving mechanism adopts a drive motor, which is connected to the inner sleeve through a built-in electric push rod, driving the inner sleeve to extend and retract axially along the outer sleeve.

[0025] The multi-section sleeve structure is simple in design and low in cost, while ensuring sufficient structural strength and stability, making it suitable for long-term use in outdoor garden environments. The sliding fit design minimizes friction and ensures smooth lifting. Driven by an electric actuator, it offers advantages over traditional hydraulic or pneumatic methods, including faster response, higher precision, lower power consumption, and easier maintenance. The actuator is integrated into the sleeve, resulting in a clean appearance and excellent waterproof and dustproof performance.

[0026] Here, a multi-section telescopic sleeve can be used directly as the water pipe, or a separate water pipe can be installed on the height adjustment component, which will then drive the height adjustment. The solenoid valve is located at the bottom of the water pipe, and the nozzle is located at the top of the water pipe.

[0027] To ensure the casing structure is leak-proof and suitable for the humid environment of outdoor gardens, the casing connection is equipped with a double-layer anti-slip and wear-resistant sealing ring (made of nitrile rubber, which is resistant to aging and highly waterproof). The two sealing rings are spaced apart along the axial direction of the casing to form a double waterproof sealing structure. At the same time, the outer wall of the inner casing has an annular waterproof protrusion that precisely matches the sealing groove on the inner wall of the outer casing, further enhancing the sealing performance and preventing rainwater and irrigation water from seeping into the interior through the casing gaps. This also prevents the drive motor, electric push rod, and other components from being damaged by moisture, ensuring smooth expansion and contraction with good stability and waterproofness.

[0028] Of course, the height adjustment mechanism can also take other forms, such as a multi-section telescopic sleeve + ball screw transmission structure, a folding linkage lifting structure, or an electric telescopic rod direct drive structure.

[0029] Preferably, the lifting range of the height adjustment component is 0.3-2.5 meters. The height position sensor collects the current height data of the two-section sleeve structure in real time and feeds it back to the first control and communication module. It compares the data with the height adjustment command issued by the portable control terminal and adjusts the start, stop and rotation amplitude of the drive motor through closed-loop feedback to achieve control of the spray height.

[0030] Achieving precise positioning control, the system utilizes real-time feedback from a height sensor and a closed-loop control algorithm to ensure accurate delivery of the spray mist to the target area. Enhancing system reliability, the closed-loop feedback mechanism detects and corrects execution errors in real time. In case of mechanical jamming, load changes, or other issues, the system automatically adjusts drive parameters to prevent equipment damage and extend its lifespan.

[0031] Preferably, the environmental factor correction model includes a temperature response function, a soil moisture availability function, and a cumulative light effect function, and the output values ​​of the three functions are multiplied together as the environmental correction factor; the individual adaptive learning model establishes an independent parameter learning model for each seedling, including a growth rate correction factor, a water use efficiency factor, and a stress tolerance factor.

[0032] Quantitative modeling of environmental factors involves establishing mathematical models for the three key environmental factors—temperature, moisture, and light—upgrading the impact of the environment on growth from qualitative description to quantitative calculation, thus improving prediction accuracy. Precise characterization of individual differences involves establishing an independent learning model for each seedling, considering its unique growth characteristics, water use efficiency, and stress resistance, achieving truly personalized maintenance for each tree.

[0033] Preferably, the three-level adaptive growth model is as follows:

[0034] ,

[0035] Among them, Hbase is the basic predicted height based on the standard growth curve of the tree species; Fenv is the environmental factor correction coefficient, reflecting the impact of environmental conditions on actual growth; Find is the individual characteristic correction coefficient, reflecting the differences in the individual growth characteristics of a specific seedling.

[0036] Growth prediction is decomposed into three levels: basic genetic characteristics, environmental response, and individual adaptation. This logical breakdown facilitates separate optimization and updates, resulting in strong system scalability. It improves prediction robustness; even when data is missing or abnormal at one level (e.g., sensor failure), other levels still provide basic predictive capabilities, allowing the system to degrade without complete failure. It supports progressive learning; parameters at each level can be learned and optimized separately. Newly planted tree species only require a basic model to function, and environmental and individual models are gradually improved as data accumulates, reducing initial deployment difficulty.

[0037] Preferably, the basic predicted height in HBase is calculated using the Logistic growth function:

[0038] ,

[0039] Where Hmax is the expected maximum height of the tree species within the set period; k is the growth rate coefficient, reflecting the inherent growth rate characteristics of the tree species; t is the number of days after planting; and tm is the inflection point time of the growth curve.

[0040] The environmental correction factor is the product of multiple environmental factors:

[0041]

[0042] Where: f T (T) is the temperature response function, where T is the daily average temperature; f θ (θ) is the soil moisture availability function, where θ is the soil volumetric water content; f L (L) is the illumination effect function, and L is the daily effective illumination hours;

[0043] The individual correction coefficient Find adopts a weighted linear model:

[0044]

[0045] Wherein, GRF is the growth rate factor, calculated based on historical growth data; WUE is the water use efficiency factor; STR is the stress tolerance factor; β1, β2 and β3 are the weight coefficients of the growth rate correction factor, water use efficiency factor and stress tolerance factor, respectively, and β1+β2+β3=1.

[0046] The Logistic model accurately describes growth patterns. The Logistic function perfectly fits the "slow-fast-slow" S-shaped curve characteristic of plant growth. Compared with linear or exponential models, it reduces prediction errors and is particularly suitable for describing growth processes under limited resources. The environmental factor multiplicative model reflects synergistic effects, using a product form rather than a weighted sum, which is more in line with ecological principles—a severe deficiency of any environmental factor will become a growth limiting factor, making the model closer to reality. The weighted linear model balances multiple indicators. By adjusting the weight coefficients, strategies can be optimized for different maintenance objectives (such as rapid growth, water conservation priority, and stress-resistant cultivation), resulting in strong system adaptability.

[0047] Preferably, the adaptive growth model combines the standard growth curve corresponding to the seedling variety, the length of planting time, real-time canopy temperature and humidity data, soil moisture data collected by the environmental sensing module, and historical irrigation data. Through dynamic parameter weighting calculation, it dynamically estimates the current actual height of the seedling and the appropriate spraying height. The estimated height is compared with the current height data fed back by the height position sensor, and a height adjustment command is generated and sent to the height adjustment component to realize the adaptive adjustment of the spraying height.

[0048] Instead of adjusting height according to a fixed cycle, the system makes dynamic decisions based on real-time data and model predictions. This ensures timely adjustments during the rapid growth phase of the seedlings and reduces unnecessary adjustments during periods of stagnation. Multi-source data fusion for decision-making integrates historical data, real-time sensor data, and tree species characteristic information, providing a more comprehensive basis for decisions and avoiding misjudgments caused by a single data source. Prediction and execution form a closed loop: model predictions guide height adjustments, and actual adjustment effects provide feedback to optimize the model, creating a positive cycle of continuous improvement. The more the system is used, the smarter it becomes.

[0049] Preferably, maintenance personnel manually inspect and observe the actual growth of the seedlings, and manually fine-tune the spraying height. After the manual inspection and adjustment are completed, the portable control terminal automatically records the actual height data after the manual adjustment and feeds the data back to the adaptive control algorithm module. The model's self-updating submodule compares the deviation between the manually adjusted height and the model's estimated height, automatically calibrates the dynamic parameters, and subsequently continues to estimate the suitable spraying height for the seedlings through the updated seedling growth model, generating corresponding height adjustment commands to achieve continuous optimization of height estimation and adjustment, ensuring that the estimated height matches the actual growth height of the seedlings.

[0050] Human-machine collaboration leverages the complementary strengths of both systems. By combining the rapid computational capabilities of the model with the experienced judgment of human experts, it maximizes the advantages of each in complex or abnormal situations (such as disease outbreaks or extreme weather), resulting in decision-making quality superior to purely manual or purely automated systems. Each manual correction becomes a learning sample for the model, enabling it to adapt to the specific conditions of each park (such as microclimate and soil characteristics) and achieve localized optimization. As learning data accumulates, the system requires less human intervention, and even new employees can receive near-expert-level maintenance guidance through the system, reducing personnel training costs and experience requirements.

[0051] Preferably, the height adjustment decision adopts a multi-factor weighted decision matrix:

[0052]

[0053] Where S is the comprehensive decision score, with a value range of [0,1], and the control strategy is determined based on the score; D H Here, Ew represents the height deviation, Tg represents the growth trend, Fs represents the seasonality factor, Se represents the equipment status, and w1-w5 represent the dynamic weighting coefficients of each factor, satisfying the following conditions: .

[0054] By integrating information from five dimensions—height deviation, water efficiency, growth trend, seasonal variation, and equipment status—into a comprehensive decision-making process, the limitations of relying on a single indicator are avoided, resulting in more scientific and rational decisions. The weighting coefficients can be dynamically adjusted based on the seedling's growth stage, season, and maintenance goals. For example, during rapid growth periods, emphasis is placed on growth trend, while during drought periods, emphasis is placed on water efficiency, allowing the system to flexibly adapt to various needs.

[0055] Preferably, the height adjustment instruction generation process is as follows:

[0056] When S≥0.7, a height adjustment command is automatically generated and executed;

[0057] When 0.5 ≤ S < 0.7, the system prompts maintenance personnel to observe and confirm.

[0058] When S < 0.5, maintain the current state and do not make any height adjustments.

[0059] Decisions with high confidence are executed automatically, those with medium confidence require manual confirmation, and those with low confidence maintain the status quo, achieving an optimal balance between automation efficiency and risk control. This avoids frequent misadjustments caused by sensor noise and short-term environmental fluctuations, extends the mechanical life of the equipment, and reduces unnecessary interference with the seedlings.

[0060] A portable seedling spray control device for garden maintenance has the following beneficial effects:

[0061] 1. Achieved true growth self-adaptation: Through a three-level model system, the spraying height can accurately match the actual growth status of the seedlings, rather than simply controlling the timing or threshold.

[0062] 2. Significantly improves water resource utilization efficiency: Actual measurement data shows that compared with traditional fixed sprinkler irrigation, this invention can save irrigation water.

[0063] 3. Significantly reduce labor intensity and management costs: One maintenance worker can manage more than 100 key saplings through a single control terminal, reducing daily inspection time by 80%.

[0064] 4. Possesses continuous learning and evolution capabilities: Through the continuous accumulation of manually corrected data and actual growth data, the system's model accuracy continues to improve, truly becoming smarter the more it is used.

[0065] 5. Provide scientific decision support: The system automatically generates maintenance reports, growth trend analysis and anomaly warnings, providing data-driven decision support for garden management.

[0066] 6. Strong scalability and adaptability: The model library can be easily expanded to include new tree species, and the parameters can be automatically adjusted through learning to adapt to different regional climate conditions. Attached Figure Description

[0067] Figure 1 This is a structural block diagram of a portable seedling spraying control device for garden maintenance according to the present invention.

[0068] Figure 2 This is a schematic diagram of the structure of a height adjustment component according to the present invention;

[0069] Figure 3 This is a schematic diagram of the structure of a portable control terminal according to the present invention;

[0070] Figure 4 This is a flowchart illustrating the working process of a portable tree seedling spray control device for garden maintenance, as described in this invention.

[0071] In the diagram: 1. Fixed sprinkler execution unit; 2. Portable control terminal; 3. Fixed base assembly; 31. Soil anchoring structure; 32. Mounting base; 4. Height adjustment assembly; 41. Height adjustment component; 42. Drive mechanism; 43. Height position sensor; 5. Sprinkler execution module; 51. Solenoid valve; 52. Sprinkler head; 53. Water supply interface; 54. Flow sensor; 6. Environmental sensing module; 61. Soil moisture sensor; 62. Canopy temperature and humidity sensor; 7. First control and communication module; 8. Human-machine interface; 81. Input device; 82. Display device; 9. Second control and communication module; 10. Multi-node management module; 11. Adaptive control algorithm module; 12. Data storage module. Detailed Implementation

[0072] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0073] This embodiment provides a portable tree seedling spray control device for garden maintenance, such as... Figure 1 As shown, it includes a fixed sprinkler execution unit 1 and a portable control terminal 2. There are 10 fixed sprinkler execution units 1, which are evenly distributed in the garden seedling planting area. The portable control terminal 2 communicates with the 10 fixed sprinkler execution units 1 through a LoRa wireless network to achieve collaborative control.

[0074] I. Specific Structure of Fixed Spray Actuator Unit 1

[0075] Fixed base assembly 3: Soil anchoring structure 31 adopts a spiral ground anchor made of stainless steel. The spiral blade has a diameter of 12cm, the anchor head is a sharp cone with a length of 30cm, and the top is bolted to the mounting base 32 via a flange. The mounting base 32 is a circular steel plate with a diameter of 20cm and a thickness of 1.5cm. The bottom is provided with anti-slip protrusions to enhance the adhesion to the soil and ensure that the device is firmly fixed in the soil to prevent it from tipping over in the wind.

[0076] Height Adjustment Component 4: The height adjustment component 41 adopts a three-section telescopic sleeve made of aluminum alloy. The inner sleeve has a diameter of 2cm, the middle sleeve has a diameter of 2.5cm, and the outer sleeve has a diameter of 3cm, with a length of 80cm for each. The maximum total height after extension is 2.5m, and the minimum total height is 0.3m. A self-locking protrusion is provided every 10cm on the outer wall of the middle sleeve, and a positioning groove matching the self-locking protrusion is provided on the inner wall of the outer sleeve. The self-locking protrusion is made of elastic rubber and can be retracted by pressing, facilitating locking after height adjustment. Drive... Mechanism 42 uses a small DC drive motor with a power of 50W and a speed of 100r / min. The drive motor is connected to the bottom of the inner sleeve through an electric push rod. The extension stroke of the electric push rod is 100cm, which drives the inner sleeve to extend and retract along the axial direction of the middle and outer sleeves. The height position sensor 43 uses an infrared displacement sensor, model GP2Y0A21YK, which is fixed to the top of the outer sleeve. The measurement accuracy is ±0.1cm. It collects the actual height data after the sleeve extends and retracts in real time and feeds it back to the first control and communication module 7.

[0077] Sprinkler execution module 5: Solenoid valve 51 is a normally closed solenoid ball valve, model 2W-160-15, with a working voltage of 12V and a flow rate adjustment range of 0.5-5L / min; Sprinkler head 52 is a rotatable atomizing nozzle with an atomization particle size of 50-100μm, a rotation angle of 360°, and a spray radius of 0.5-1.5m, suitable for the size of tree seedling canopy; Water supply interface 53 is a quick connector, model PC8-02, which can be quickly connected to the garden water supply network or portable water tank; Flow sensor 54 is a turbine flow sensor, model LWGY-15, with a measurement accuracy of ±1%, which is connected in series between solenoid valve 51 and sprinkler head 52 to collect sprinkler flow data in real time and form a flow closed-loop control.

[0078] Environmental sensing module 6: Soil moisture sensor 61, model YL-69, with a measurement range of 0-100%RH and an accuracy of ±2%RH, is embedded in the bottom of the fixed base component 3, extending to 10cm below the soil surface, to collect soil moisture data around the seedling roots; Canopy temperature and humidity sensor 62, model DHT11, with a measurement range of temperature 0-50℃ and humidity 20-90%RH, and an accuracy of temperature ±1℃ and humidity ±5%RH, is fixed to the top of the middle sleeve of the height adjustment component 4, flush with the seedling canopy, to collect temperature and humidity data around the seedling canopy.

[0079] The first control and communication module 7 uses an STM32F103 microcontroller as the main control chip, with a working frequency of 72MHz. It integrates a LoRa wireless communication module, model SX1278, with a communication frequency of 433MHz and a communication distance of up to 800m. It supports multi-channel communication and is used to receive control commands issued by the portable control terminal 2, coordinate the height adjustment component 4 and the sprinkler execution module 5 to perform corresponding actions, and simultaneously collect data from the environmental perception module 6, the height position sensor 43, and the flow sensor 54. After filtering and amplification, the data is uploaded to the portable control terminal 2.

[0080] II. Specific Structure of Portable Control Terminal 2

[0081] Human-machine interface 8: It adopts a 3.5-inch touch LCD display screen with a resolution of 480×320, supports multi-touch, and the input device 81 is a touch keyboard, which can set the spraying duration (0-60min), flow range (0.5-5L / min), height parameters (0.3-2.5m), maintenance cycle (1-7 days) and other adjustment parameters; the display device 82 can display the working status (normal, fault, low battery) of each fixed spraying execution unit 1, the collected environmental data (soil moisture, canopy temperature and humidity), model prediction results (suitable spraying height, suitable flow rate) and control command records in sections.

[0082] The second control and communication module 9 adopts the SX1278LoRa wireless communication module matched with the first control and communication module 7. It supports simultaneous communication on 10 channels and can connect to 10 fixed spray execution units 1 at the same time to realize one-to-many collaborative control. The communication delay is ≤1s, ensuring the rapid issuance of control commands and the real-time uploading of data.

[0083] Multi-node management module 10: Built-in node registration function. After the fixed sprinkler execution unit 1 is installed, a registration command is sent through the portable control terminal 2 to complete the node binding. It supports group management, which can divide 10 fixed sprinkler execution units 1 into 2 groups, each corresponding to different varieties of seedlings. It monitors the equipment status of each node in real time. When the equipment malfunctions (such as sensor failure, solenoid valve 51 failure) or has low power, it will issue an audible and visual alarm in time to remind maintenance personnel to handle the situation.

[0084] Adaptive control algorithm module 11: Built-in three-level adaptive growth model, as detailed below:

[0085] (1) Basic growth curve model library: Pre-stored standard growth curve data of two common garden tree seedlings, camphor and osmanthus, and the basic predicted height is calculated using the Logistic growth function in HBase:

[0086]

[0087] Wherein, Hmax is the expected maximum height of the tree species within the set period (2.0m for apples and 2.0m for osmanthus); k is the growth rate coefficient (k=0.022 for apples and k=0.018 for osmanthus), reflecting the inherent growth rate characteristics of the tree species; t is the number of days after planting; tm is the inflection point time of the growth curve (tm=150 days for apples and tm=160 days for osmanthus).

[0088] (2) Environmental factor correction model: including temperature response function, soil moisture availability function and cumulative light effect function, the output values ​​of the three functions are multiplied together as the environmental correction factor Fenv:

[0089]

[0090] Where: f T (T) is the temperature response function, where T is the daily average temperature, and it corresponds to the suitable temperature range for seedling growth (15-30℃). When T < 15℃ or T > 30℃, f T (T) decreases linearly with the degree of temperature deviation; when 15℃≤T≤30℃, f T (T)=1, and the specific expression is:

[0091]

[0092] fθ (θ) is the soil moisture availability function, where θ is the soil volumetric water content, and it is suitable for the appropriate soil moisture range (20-60%) for seedling growth. When θ < 20% or θ > 60%, f θ (θ) decreases linearly with the degree of humidity deviation; when 20% ≤ θ ≤ 60%, f θ (θ)=1, and the specific expression is:

[0093]

[0094] f L (L) is the light effect function, where L is the daily effective light hours, and it is used to determine the suitable light range for seedling growth (4-10h). When L < 4h or L > 10h, f L (L) decreases linearly with the degree of deviation from the light duration; when 4h≤L≤10h, f L (L)=1, and the specific expression is:

[0095]

[0096] (3) Individual adaptive learning model: An independent parameter learning model is established for each seedling, and the individual correction coefficient Find adopts a weighted linear model:

[0097]

[0098] Among them, GRF is the growth rate factor, calculated based on historical growth data (plant height is measured once a week), GRF = actual growth rate / standard growth rate; WUE is the water use efficiency factor, WUE = seedling height increment / total spraying water volume; STR is the stress tolerance factor, calculated based on historical environmental stress data (such as high temperature, drought) and seedling growth status; β1, β2 and β3 are the weight coefficients of growth rate correction factor, water use efficiency factor and stress tolerance factor, respectively, β1+β2+β3=1, initial values ​​β1=0.4, β2=0.3, β3=0.3, which can be manually fine-tuned and self-updated by data.

[0099] The final output of the three-level adaptive growth model is the estimated value of the actual suitable seedling height, Hpred.

[0100]

[0101] The adaptive control algorithm module 11 determines the appropriate spraying height based on Hpred, and determines the appropriate spraying flow rate and spraying duration by combining soil moisture and canopy temperature and humidity data, and generates personalized control instructions.

[0102] 5. Data storage module 12: Uses an SD card as the storage medium with a storage capacity of 16GB. It is used to store seedling maintenance records (variety, planting time, initial plant height, historical maintenance records), environmental perception data (collected every 10 minutes, with a storage period of 1 year), model parameters, control command records, and other data. It supports data export via USB interface and automatic backup to avoid data loss.

[0103] Work process

[0104] 1. Device installation: Screw the spiral anchor of the fixed sprinkler execution unit 1 into the soil around the roots of the sapling to ensure a stable installation. Connect the water supply interface 53 to the garden water supply network through the quick connector. Bind the 10 fixed sprinkler execution units 1 to the portable control terminal 2 through the LoRa wireless network to complete the node registration. Enter the maintenance file information such as the sapling variety, planting time, and initial plant height corresponding to each node into the portable control terminal 2.

[0105] Data Acquisition: The soil moisture sensor 61 and the canopy temperature and humidity sensor 62 of the environmental sensing module 6 collect soil moisture and canopy temperature and humidity data every 10 minutes. The height position sensor 43 collects sprinkler height data in real time, and the flow sensor 54 collects sprinkler flow data in real time. All collected data are filtered and amplified by the first control and communication module 7 and then uploaded to the portable control terminal 2 via the LoRa wireless network.

[0106] Command generation: The adaptive control algorithm module 11 of the portable control terminal 2 calls the three-level adaptive growth model, combines the seedling maintenance file and the uploaded environmental data, calculates the appropriate spraying height, spraying flow rate and spraying duration for each fixed spraying execution unit 1, and generates personalized spraying control commands and height adjustment commands; at the same time, the multi-node management module 10 monitors the working status of each node in real time to ensure the relevance of the commands issued.

[0107] Specifically, the portable control terminal 2 receives data from each node and updates the electronic maintenance file of the corresponding seedling; the adaptive control algorithm module 11 calls the seedling's growth model, and calculates the comprehensive predicted height Hpred and height deviation D by combining the current number of days since planting, historical growth trajectory, and real-time environmental data. H =Hact / Hpred; Calculate the comprehensive decision score using a multi-factor weighted decision matrix:

[0108]

[0109] Where S is the comprehensive decision score, with a value range of [0,1], and the control strategy is determined based on the score; w1 to w5 are the dynamic weight coefficients of each factor, satisfying D HEw is the height deviation, defined as the ratio of the actual measured height of the seedling to the predicted height of the model; Ew is the water use efficiency, calculated by the increase in seedling growth per unit of irrigation water; Tg is the growth trend index, based on the comparison of recent growth rate with historical average; Fs is the seasonality factor, which comprehensively considers the influence of seasonal changes and phenological periods; Se is the equipment status factor, reflecting the current working status of the execution unit.

[0110] Based on the threshold range into which the comprehensive decision score S falls, the system executes the corresponding action:

[0111] If S≥0.7: Automatically generate height adjustment instructions, including target height value and lifting / lowering speed parameters;

[0112] If 0.5 ≤ S < 0.7: A prompt message will be pushed to the interface, and manual observation and confirmation are recommended;

[0113] If S < 0.5: Maintain the current state and do not generate any instructions.

[0114] The instructions are sent to the corresponding execution unit through the second control and communication module 9.

[0115] 4. Command Execution: The second control and communication module 9 sends control commands to the first control and communication module 7 of the corresponding fixed sprinkler execution unit 1. After receiving the command, the first control and communication module 7 controls the drive motor to start, which drives the electric push rod to extend and retract, thereby driving the inner and middle sleeves of the height adjustment component 41 to extend and retract, adjusting the sprinkler height to a suitable value. The height position sensor 43 provides real-time feedback of height data. When the target height is reached, the drive motor stops, and the self-locking mechanism locks the sleeve position, completing the height adjustment. At the same time, the solenoid valve 51 is controlled to open and the opening degree is adjusted to control the sprinkler flow rate and sprinkler duration. The flow sensor 54 provides real-time feedback of flow data, forming a closed-loop flow control to ensure that the sprinkler parameters accurately match the needs of the seedlings.

[0116] 5. Manual Fine-tuning and Model Self-Update: When maintenance personnel conduct manual inspections, if they find that the actual growth of the seedlings does not match the model's prediction, they can manually fine-tune the spray height and spray flow rate through the touch input device 81 of the portable control terminal 2. After the fine-tuning is completed, the data storage module 12 automatically records the parameter data after this manual adjustment. The self-updating submodule of the adaptive control algorithm module 11 compares the deviation between the manually adjusted parameters and the model's predicted parameters, automatically calibrates the weight coefficients of β1, β2, and β3 in the model, updates the growth model, and ensures that the control commands generated subsequently are more in line with the actual growth needs of the seedlings.

[0117] 6. Anomaly Handling: When a fixed spray unit 1 experiences an anomaly such as sensor malfunction, solenoid valve 51 failure, or low battery, the first control and communication module 7 uploads the anomaly signal to the portable control terminal 2. The multi-node management module 10 of the portable control terminal 2 issues an audible and visual alarm, and simultaneously displays the anomaly node number and anomaly type on the LCD display device 82, reminding maintenance personnel to handle the situation promptly and ensure the normal operation of the device.

[0118] This specific embodiment is merely an explanation of the present invention and is not intended to limit the invention. After reading this specification, those skilled in the art can make modifications to this embodiment without contributing any inventive step, but such modifications are protected by patent law as long as they are within the scope of the claims of the present invention.

Claims

1. A portable seedling sprinkler control device for garden maintenance, characterized in that, It includes a fixed spraying actuator (1) and a portable control terminal (2); The fixed spray execution unit (1) includes: The fixed base assembly (3) has a soil anchoring structure (31) and an mounting base (32); The height adjustment assembly (4) is mounted on the mounting base (32) and includes a height adjustment element (41), a drive mechanism (42) and a height position sensor (43); The spray execution module (5) includes a solenoid valve (51), a nozzle (52), a water supply interface (53), and a flow sensor (54), and is used to execute spray control commands including spray start / stop and flow regulation. The environmental sensing module (6) includes a soil moisture sensor (61) and a canopy temperature and humidity sensor (62); First control and communication module (7); The portable control terminal (2) includes: The human-computer interaction interface (8) includes an input device (81) and a display device (82) for setting adjustment parameters; The second control and communication module (9) connects to multiple first control and communication modules (7) via a wireless network to establish communication with multiple fixed spray execution units (1) and realize one-to-many seedling spraying collaborative control. A multi-node management module (10) supports the simultaneous management of multiple fixed spray execution units (1); The adaptive control algorithm module (11) has a built-in three-level adaptive growth model, including a basic growth curve model library, an environmental factor correction model and an individual adaptive learning model. The environmental perception module (6) collects environmental data in real time, and after processing by the first control and communication module (7), it is uploaded to the portable control terminal (2). The adaptive control algorithm module (11) combines the seedling maintenance file, the built-in growth model and the uploaded environmental data to generate personalized sprinkler control instructions and height adjustment instructions, which are then sent to the corresponding fixed sprinkler execution unit (1) through the second control and communication module (9). After receiving the instructions, the first control and communication module (7) coordinates the height adjustment component (4) and the sprinkler execution module (5) to perform the corresponding actions.

2. The portable seedling sprinkler control device for garden maintenance according to claim 1, characterized in that, The height adjustment component (41) adopts a multi-section sleeve structure. Each inner sleeve is slidably fitted with the outer sleeve. The top of the innermost sleeve is connected to the nozzle (52), and the bottom of the outermost sleeve is fixed to the fixed base assembly (3). The drive mechanism (42) adopts a drive motor. The drive motor is connected to the inner sleeve through a built-in electric push rod, which drives the inner sleeve to extend and retract axially along the outer sleeve.

3. A portable seedling sprinkler control device for garden maintenance according to claim 2, characterized in that, The height adjustment component (41) has a lifting range of 0.3-2.5 meters. The height position sensor (43) collects the current height data of the multi-section sleeve structure in real time and feeds it back to the first control and communication module (7). It compares the height adjustment command issued by the portable control terminal (2) with the height adjustment command. The start, stop and rotation amplitude of the drive mechanism (42) are adjusted through closed-loop feedback to realize the control of the spray height.

4. The portable seedling sprinkler control device for garden maintenance according to claim 1, characterized in that, The environmental factor correction model includes a temperature response function, a soil moisture availability function, and a cumulative light effect function. The output values ​​of the three functions are multiplied together to form the environmental correction factor. The individual adaptive learning model establishes an independent parameter learning model for each seedling, including a growth rate correction factor, a water use efficiency factor, and a stress tolerance factor.

5. A portable seedling sprinkler control device for garden maintenance according to claim 1, characterized in that, The three-level adaptive growth model is as follows: ， Among them, Hbase is the basic predicted height based on the standard growth curve of the tree species; Fenv is the environmental factor correction coefficient, reflecting the impact of environmental conditions on actual growth; Find is the individual characteristic correction coefficient, reflecting the differences in the individual growth characteristics of a specific seedling.

6. A portable seedling spray control device for garden maintenance according to claim 5, characterized in that, The basic predicted height is calculated using the Logistic growth function in HBase: ， Where Hmax is the expected maximum height of the tree species within the set period; k is the growth rate coefficient, reflecting the inherent growth rate characteristics of the tree species; t is the number of days after planting; and tm is the inflection point time of the growth curve. The environmental correction factor is the product of multiple environmental factors: Where: f T (T) is the temperature response function, where T is the daily average temperature; f θ (θ) is the soil moisture availability function, where θ is the soil volumetric water content; f L (L) is the illumination effect function, and L is the daily effective illumination hours; The individual correction coefficient Find adopts a weighted linear model: Wherein, GRF is the growth rate factor, calculated based on historical growth data; WUE is the water use efficiency factor; STR is the stress tolerance factor; β1, β2 and β3 are the weight coefficients of the growth rate correction factor, water use efficiency factor and stress tolerance factor, respectively, and β1+β2+β3=1.

7. A portable seedling sprinkler control device for garden maintenance according to claim 1, characterized in that, The adaptive growth model combines the standard growth curve corresponding to the seedling variety, the length of planting time, the real-time canopy temperature and humidity, soil moisture data collected by the environmental sensing module (6), and historical irrigation data. Through dynamic parameter weighting calculation, it dynamically estimates the current actual height of the seedling and the appropriate spraying height. The estimated height is compared with the current height data fed back by the height position sensor (43), and a height adjustment command is generated and sent to the height adjustment component (4) to realize the adaptive adjustment of the spraying height.

8. A portable seedling spray control device for garden maintenance according to claim 7, characterized in that, Maintenance personnel manually inspect and observe the actual growth of the seedlings, and manually fine-tune the spraying height. After the manual inspection and adjustment is completed, the portable control terminal (2) automatically records the actual height data after the manual adjustment and feeds the data back to the adaptive control algorithm module (11). The self-updating submodule of the model compares the deviation between the height after manual adjustment and the height estimated by the model, automatically calibrates the dynamic parameters, and continues to estimate the appropriate spraying height for the seedlings through the updated seedling growth model, generating corresponding height adjustment instructions to achieve continuous optimization of height estimation and adjustment, and ensure that the estimated height matches the actual growth height of the seedlings.

9. A portable seedling sprinkler control device for garden maintenance according to claim 7, characterized in that, The height adjustment decision adopts a multi-factor weighted decision matrix: Where S is the comprehensive decision score, with a value range of [0,1], and the control strategy is determined based on the score; D H Here, Ew represents the height deviation, Tg represents the growth trend, Fs represents the seasonality factor, Se represents the equipment status, and w1-w5 represent the dynamic weighting coefficients of each factor, satisfying the following conditions: .

10. A portable seedling spray control device for garden maintenance according to claim 9, characterized in that, The process for generating the height adjustment command is as follows: When S≥0.7, a height adjustment command is automatically generated and executed; When 0.5 ≤ S < 0.7, the system prompts maintenance personnel to observe and confirm. When S < 0.5, maintain the current state and do not make any height adjustments.

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