A potting vegetable cultivation monitoring device and method based on layered self-irrigation

Abstract

This invention belongs to the technical field of potted plant cultivation equipment, and relates to a monitoring device and method for potted vegetable cultivation based on tiered self-irrigation. The device includes a container body, which is a rectangular trough structure. A detachable, breathable cultivation inner trough is installed inside the container body. The bottom of the breathable cultivation inner trough has several water-permeable and air-permeable holes evenly distributed. A first sensor assembly and a drip irrigation pipe assembly are installed in the breathable cultivation inner trough. The drip irrigation pipe assembly is connected to a preparation tank. A water storage base is detachably snapped onto the bottom of the container body. A water level sensor is installed in the water storage base. The detection data from the first sensor assembly and the water level sensor are transmitted to a user terminal via a LoRa wireless transmission module. This invention enables continuous optimization and intelligent management of the cultivation process.

Description

Technical Field

[0001] This invention relates to the field of potted plant cultivation equipment technology, specifically to a monitoring device and method for potted vegetable cultivation based on stratified self-irrigation. Background Technology

[0002] With the rapid development of balcony economy, home gardening, and community shared vegetable gardens, potted vegetable planting containers have been widely used in indoor cultivation, agricultural science popularization, and scientific research experiments, placing higher demands on the portability, water and fertilizer management, and professional display functions of the containers. Existing potted cultivation tools are mostly ordinary flower pots, with simple structures and single functions, which are difficult to adapt to the needs of large-scale and scenario-based potted vegetable cultivation.

[0003] Existing technologies often employ movable modular pot structures to achieve water storage and aeration, solving the problems of frequent watering and poor aeration associated with conventional flowerpots. However, the following issues still exist: Technical issues that fail to meet the standardized display requirements of scientific research and popular science scenarios.

[0004] In view of this, it is very necessary to provide a monitoring device and method for potted vegetable cultivation based on stratified self-irrigation to solve the above-mentioned defects in the prior art. Summary of the Invention

[0005] The purpose of this invention is to solve the technical problem that existing potted vegetable cultivation cannot meet the standardized display needs of scientific research and popular science scenarios, and to provide a monitoring device and method for potted vegetable cultivation based on layered self-irrigation, so as to solve the technical problems existing in the prior art.

[0006] To achieve the above objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a monitoring device for potted vegetable cultivation based on stratified self-irrigation, comprising: a container body, the container body being a rectangular trough structure, a detachably detachable aerated cultivation inner trough being provided inside the container body, the bottom of the aerated cultivation inner trough being evenly provided with a plurality of water-permeable and air-permeable holes, a first sensor assembly and a drip irrigation pipe assembly being provided in the aerated cultivation inner trough, the drip irrigation pipe assembly being connected to a preparation tank, a water storage base being detachably snapped onto the bottom of the container body, a water level sensor being provided in the water storage base, and the detection data of the first sensor assembly and the water level sensor being transmitted to a user terminal via a LoRa wireless transmission module.

[0007] Preferably, double handles are symmetrically arranged on the left and right outer walls of the container body, and an embedded logo mounting groove is opened on the front of the container body.

[0008] In addition, this application also provides a monitoring method for a potted vegetable cultivation monitoring device based on a tiered self-irrigation system, comprising the following steps: Step S1: The collected soil pH value, soil moisture and water level data are transmitted to the user terminal through the LoRa wireless transmission module. The user terminal processes the transmitted data to generate multi-source heterogeneous data. Step S2: Construct a potted vegetable evaluation model and a potted vegetable knowledge base. Input the multi-source heterogeneous data collected in real time into the trained potted vegetable evaluation model, and combine it with the potted vegetable knowledge base to determine whether the current soil environment is suitable for the planted vegetables. If it exceeds the threshold, generate adjustment suggestions. Step S3: Set the control parameters for drip irrigation time, number of drip irrigations, and amount of water per drip according to the adjustment suggestions, and send the control parameters to the drip irrigation control equipment; Step S4: The drip irrigation control equipment executes drip irrigation operations according to the received control parameters, monitors the drip irrigation operation data in real time, and triggers a remote alarm and generates alarm information if an abnormality occurs. Step S5: Record each drip irrigation operation, soil pH value, soil moisture data collected by each sensor, and water level data of the water storage base, and store them in the potted vegetable knowledge base to provide data for subsequent optimization of the potted vegetable evaluation model.

[0009] The beneficial effects of this invention are as follows: This invention features symmetrical double handles on the container body, making it easier to handle and move potted vegetables, thus solving the problem of inconvenient manual handling in existing technologies. The embedded label mounting slot allows for dedicated label display of potted vegetables, facilitating the differentiation of different vegetable varieties and management information, thus addressing the lack of dedicated label display structures in existing technologies.

[0010] This invention uses a first sensor component and a water level sensor to collect real-time data on soil pH, soil moisture, and water level in the water storage base. This data is then transmitted to a user terminal via a LoRa wireless transmission module for real-time data acquisition and remote monitoring. Based on the collected multi-source heterogeneous data, a potted vegetable evaluation model and knowledge base are constructed. This model can determine whether the soil environment is suitable for the current vegetable growth, generate adjustment suggestions, and enable precise management and optimization of cultivation conditions.

[0011] This invention enables automated drip irrigation by sending control parameters from the user terminal to the drip irrigation control equipment, ensuring precise water supply to vegetables. It monitors the drip irrigation process in real time and triggers remote alarms, providing timely alerts in case of abnormal soil conditions or water levels, thus improving the safety and reliability of the cultivation process. The user terminal automatically records each drip irrigation operation, sensor data, and water level status, storing this information in a potted vegetable knowledge base. This provides reliable data support for the optimization of subsequent potted vegetable evaluation models and management decisions, enabling continuous optimization and intelligent management of the cultivation process.

[0012] Therefore, it is evident that the present invention has outstanding substantive features and significant progress compared with the prior art, and the beneficial effects of its implementation are also obvious. Attached Figure Description

[0013] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0014] Figure 1 This is a schematic diagram of a monitoring device for potted vegetable cultivation based on tiered self-irrigation. Figure 2 This is a flowchart of a monitoring method for a potted vegetable cultivation monitoring device based on a tiered self-irrigation system.

[0015] Among them, 1-container body; 2-double handles; 3-embedded label mounting groove; 4-breathable cultivation inner trough; 5-water and air permeable holes; 6-first sensor assembly; 61-soil pH sensor; 62-soil moisture sensor; 7-drip irrigation pipe assembly; 71-drip irrigation pipe; 72-drip irrigation control equipment; 8-preparation tank; 9-water storage base; 10-water level sensor. Detailed Implementation

[0016] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. The following embodiments are explanations of the present invention, but the present invention is not limited to the following implementation methods.

[0017] Example 1: like Figure 1 As shown, this embodiment provides a monitoring device for potted vegetable cultivation based on tiered self-irrigation, comprising: The container body 1 is a rectangular trough structure. Double handles 2 are symmetrically arranged on the outer walls of the left and right sides of the container body 1. An embedded marking installation groove 3 is opened on the front of the container body 1. A breathable cultivation inner trough 4 is detachably installed inside the container body 1. Several water and air permeable holes 5 are evenly opened at the bottom of the breathable cultivation inner trough 4. A first sensor assembly 6 and a drip irrigation pipe assembly 7 are installed in the breathable cultivation inner trough 4. The drip irrigation pipe assembly 7 is connected to a preparation tank 8. A water storage base 9 is detachably snapped to the bottom of the container body 1. A water level sensor 10 is installed in the water storage base 9. The detection data of the first sensor assembly 6 and the water level sensor 10 are sent to the user terminal through a LoRa wireless transmission module.

[0018] The container body 1, double handles 2, water storage base 9, and breathable cultivation inner trough 4 are all made of food-grade environmentally friendly PP plastic. The double handles 2 are arc-shaped hollow handles with a thickness of 3-5mm, and are integrally injection molded with the container body 1. The double handles 2 are symmetrically distributed and have the same height.

[0019] The edge of the breathable cultivation inner trough 4 is provided with an outward-folding limiting edge, which is fixed to the inner side of the upper end of the container body 1 by snapping on the outward-folding limiting edge, so as to achieve detachable assembly and disassembly; the water storage base 9 has a hollow water storage cavity inside, and a sealing snap-fit ​​structure is provided between the water storage base 9 and the container body 1.

[0020] The embedded signage mounting slot 3 is a rectangular groove structure. Acrylic signs, stickers, or metal nameplates can be embedded inside the rectangular groove to accommodate unit logos, vegetable varieties, and science information displays.

[0021] The permeable and breathable holes 5 of the breathable cultivation inner trough 4 have a diameter of 2-4mm and are arranged in a matrix evenly.

[0022] The first sensor component 6 includes a soil pH sensor 61 and a soil moisture sensor 62, which detect the soil pH and soil moisture in real time to determine whether the current soil environment is suitable for the vegetable variety being planted; the water level sensor 10 detects the water level in the water storage base 9 in real time; the user terminal includes a mobile phone, tablet computer or computer.

[0023] The drip irrigation pipe assembly 7 includes a drip irrigation pipe 71 and a drip irrigation control device 72. The drip irrigation pipe 71 is laid on the soil surface of the aerated cultivation inner trough 4 or buried in the soil. The drip irrigation control device 72 is connected to the drip irrigation pipe 71. The drip irrigation control device 72 receives instructions from the user terminal through wireless communication and controls the start and stop of drip irrigation of nutrient solution and the drip irrigation volume according to the instructions.

[0024] The user terminal provides adjustment suggestions, and the staff adjusts the pH value in the preparation tank 8 according to the pH value required by the vegetable varieties being grown. The user terminal provides control parameters for drip irrigation time, drip irrigation frequency, and drip irrigation volume per drip. The drip irrigation control equipment 72 automatically executes the drip irrigation operation according to the control parameters.

[0025] The layered self-irrigation design and the detachable breathable cultivation inner trough 4 make it more convenient to transport, cultivate and manage potted vegetables. At the same time, the embedded label trough facilitates the display of vegetable varieties and management information, enabling refined management.

[0026] By real-time monitoring of soil pH, soil moisture and water level, processing data from LoRa wireless transmission modules and user terminals, and combining nutrient solution preparation suggestions and automatic drip irrigation control, precise supply of water and nutrients to vegetables can be achieved, improving cultivation efficiency and the suitability of the growing environment.

[0027] Example 2: like Figure 2 As shown in this embodiment, the monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation can achieve multi-dimensional data collection of the potted vegetable growth environment. The collected data types include soil moisture, soil pH value, and water level information of the water storage base in the breathable cultivation trough. A monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation includes the following steps: Step S1: The collected soil pH value, soil moisture and water level data are transmitted to the user terminal through the LoRa wireless transmission module. The user terminal processes the transmitted data to generate multi-source heterogeneous data. S11. The soil environment in the breathable cultivation trough is collected in real time using the first sensor component, including collecting soil pH value and soil moisture; water level data of the hollow water storage cavity is collected through the water level sensor to construct an environmental dataset; S12. The environmental dataset is sent to the user terminal via the LoRa wireless transmission module. The user terminal processes the received environmental dataset to generate multi-source heterogeneous data in a unified format.

[0028] The soil pH value and soil moisture data mentioned in step S11 are collected by soil pH sensor and soil moisture sensor, respectively; the water level data of the hollow water storage cavity is collected by water level sensor in the water storage base.

[0029] The data processing in step S12 includes: Units were standardized for the collected soil pH, soil moisture, and water level data in the hollow water storage cavity; The continuously collected environmental datasets are sorted by timestamp and missing values ​​are imputed. Detect and remove abnormal data, including burst noise values ​​or abnormal values ​​transmitted by various sensors; The processed environmental datasets are integrated according to categories such as soil environmental indicators and water storage status to generate structured multi-source heterogeneous data.

[0030] It should be noted that by collecting soil pH, soil moisture, and water level in the water storage base in real time and processing the data, multi-source heterogeneous data is generated, providing accurate and reliable soil environment information for subsequent potted vegetable evaluation models, thereby improving the precision and intelligence of cultivation management.

[0031] Step S2: Construct a potted vegetable evaluation model and a potted vegetable knowledge base. Input the multi-source heterogeneous data collected in real time into the trained potted vegetable evaluation model, and combine it with the potted vegetable knowledge base to determine whether the current soil environment is suitable for the planted vegetables. If it exceeds the threshold, generate adjustment suggestions. Step S2 specifically includes: S21. Construct a potted vegetable knowledge base and a potted vegetable evaluation model within the user terminal. The input parameters of the potted vegetable evaluation model are multi-source heterogeneous data. The potted vegetable knowledge base is used to record the appropriate growth parameter thresholds for different vegetable varieties, including the optimal soil pH range, soil moisture range, water requirements and range, and dynamically update the vegetable growth management rules.

[0032] S22. Input the historically collected multi-source heterogeneous data into the potted vegetable evaluation model, and train it in combination with the potted vegetable knowledge base to obtain a trained potted vegetable evaluation model.

[0033] S23. Input the real-time collected multi-source heterogeneous data into the trained potted vegetable evaluation model for judgment and generate adjustment suggestions.

[0034] It should be noted that step S2 generates adjustment suggestions by constructing a potted vegetable evaluation model and a potted vegetable knowledge base, thereby realizing intelligent environmental monitoring and cultivation management. S2 provides a scientific decision-making basis for subsequent drip irrigation operations, enabling precise irrigation and nutrient supplementation.

[0035] Step S21 specifically includes: S211. Establish a knowledge base for potted vegetables that includes suitable growth parameter thresholds and management rules for different vegetable varieties; S212. Construct an evaluation model for potted vegetables that includes regression analysis, threshold matching, and a scoring mechanism; Step S211 specifically includes: S2111. Collect growth parameter thresholds for different vegetable varieties, including optimal soil pH range, soil moisture range, and water requirement; S2112. Organize the collected vegetable growth parameter thresholds into a structured database, establish a vegetable variety index, and perform fast query and matching; S2113. Record vegetable growth management rules in the potted vegetable knowledge base, including watering frequency, nutrient solution concentration and fertilization strategy, and set up a dynamic update mechanism so as to adjust the vegetable growth management rules according to environmental changes or planting experience. S2114. Connect the potted vegetable knowledge base with the potted vegetable evaluation model so that the potted vegetable evaluation model can automatically call the growth parameter thresholds and management rules of the corresponding vegetable varieties when evaluating the real-time environment.

[0036] Step S212 specifically includes: S2121. The multiple linear regression method is used to establish the mapping relationship between soil environmental indicators and vegetable growth performance. Cross-validation is performed, and the regression coefficients are optimized to ensure that the impact of the current soil environment on vegetable growth can be accurately assessed and the predicted environmental impact value is output. S2122. Obtain suitable growth parameter thresholds for each vegetable variety from the potted vegetable knowledge base. The growth parameter thresholds include soil pH range, soil moisture range, and water requirement and range. Compare the multi-source heterogeneous data with the growth parameter thresholds item by item to determine whether the current soil environmental indicators deviate from the suitable range. Mark the degree of deviation of each indicator and output the deviation mark to provide input reference for the scoring mechanism. S2123. Combine the predicted environmental impact values ​​with deviation markers for weighted calculation to generate a scoring mechanism, standardize the scoring results, and provide adjustment suggestions based on the scoring results.

[0037] Step S21 establishes a potted vegetable evaluation model and a potted vegetable knowledge base to accurately match soil environmental indicators with vegetable growth needs, providing a reliable basis for environmental suitability assessment.

[0038] Step S22 specifically includes: S221. Call up historically collected multi-source heterogeneous data, classify them according to vegetable varieties and soil environmental indicators, and construct training sample sets and training validation sets; S222. Input the training sample set into the potted vegetable evaluation model, optimize it by minimizing the mean square error, so that the degree of deviation of the prediction result from the threshold is consistent with the actual growth performance of the potted vegetables, evaluate the accuracy of the output through the validation set, and adjust the weight parameters on the validation set using the grid search method. S223. Apply the potted vegetable evaluation model to the training and validation set, compare the predicted values ​​of each soil environmental index with the actual vegetable growth performance; adjust the weight parameters according to the validation results, and output the trained potted vegetable evaluation model.

[0039] Step S2 trains the potted vegetable evaluation model using historically collected multi-source heterogeneous data, optimizes regression coefficients, threshold matching logic, and scoring weight parameters, and improves prediction accuracy.

[0040] Step S23 specifically includes: S231. Input the multi-source heterogeneous data collected in real time by the user terminal into the trained potted vegetable evaluation model; S232. Using a potted vegetable evaluation model, assess and score deviations in soil pH, soil moisture, and water level in the water storage base, and provide adjustment suggestions; the adjustment suggestions include water level adjustment suggestions, soil moisture adjustment suggestions, and pH adjustment suggestions; S233. Integrate the adjustment suggestions and output them to the user terminal interface to provide specific operating parameters and decision-making basis for subsequent drip irrigation control equipment; Step S232 specifically includes: S2321. Assess the deviation of soil pH: If the soil pH is below the lower limit, it is recommended to add alkaline nutrient solution to adjust the soil pH; if the soil pH is above the upper limit, it is recommended to add acidic nutrient solution. S2322. Assess soil moisture deviation: If soil moisture is below the lower limit, it is recommended to increase irrigation volume or extend drip irrigation time; if soil moisture is above the upper limit, it is recommended to shorten drip irrigation time or reduce water volume. S2323. Determine the deviation of the water level in the water storage base: If the water level is lower than the minimum threshold, the user terminal will prompt to add water to prevent the drip irrigation from being interrupted; if the water level is higher than the maximum threshold, the user terminal will prompt to discharge excess water to prevent overflow or water accumulation.

[0041] Step S23 involves inputting real-time collected multi-source heterogeneous data into the trained potted vegetable evaluation model and comparing it with suitable thresholds in the potted vegetable knowledge base to achieve intelligent adjustment suggestions for nutrient solution preparation and water storage level.

[0042] Step S3: Set the control parameters for drip irrigation time, number of drip irrigations, and amount of water per drip according to the adjustment suggestions, and send the control parameters to the drip irrigation control equipment; Step S3 specifically includes: S31. Receive adjustment suggestions generated by the potted vegetable evaluation model and integrate the adjustment suggestions into operable parameters; S32. Based on the adjustment recommendations, check the current soil pH value, soil moisture, and existing water volume in the water storage base. If the water level in the water storage base is lower than the set lower limit, no operation is required; if the water level in the water storage base is higher than the upper limit, drain the excess water.

[0043] S33. Based on the soil pH value configured for the vegetable variety and the current soil moisture deviation, set the drip irrigation parameters, including drip irrigation time, number of drip irrigations, and drip volume per irrigation; encapsulate the drip irrigation parameters into control instructions, including start time, duration, drip irrigation interval, and flow rate per irrigation, and prepare to send them to the drip irrigation control equipment.

[0044] S34. The user terminal sends the drip irrigation control command to the drip irrigation control device through the LoRa wireless transmission module. After receiving the command, the drip irrigation control device starts the water pump and valve and performs the drip irrigation operation according to the set drip irrigation time and drip irrigation amount. The drip irrigation control device monitors the drip irrigation process in real time, including water flow, drip irrigation time and water level in the water storage base, and feeds back the execution status to the user terminal. The user terminal records the actual execution data of each drip irrigation, providing a data foundation for subsequent optimization of nutrient solution preparation and drip irrigation strategies.

[0045] It should be noted that by converting the nutrient solution preparation suggestions and water level prompts generated by the potted vegetable evaluation model into executable drip irrigation control parameters, precise control of drip irrigation time, frequency, and irrigation volume per irrigation can be achieved. Real-time monitoring of the drip irrigation process and the water level in the storage tank, along with feedback of the execution status to the user terminal, ensures the accuracy and safety of irrigation operations. Simultaneously, recording the actual execution data for each drip irrigation provides reliable data support for subsequent optimization of nutrient solution preparation and drip irrigation strategies.

[0046] Step S4: The drip irrigation control equipment executes drip irrigation operations based on the received control parameters, monitors the drip irrigation operation data in real time, and triggers a remote alarm and generates alarm information if an abnormality occurs.

[0047] Step S4 specifically includes: S41. The drip irrigation control equipment controls the drip irrigation pump and valve to perform drip irrigation operations. The water level sensor continuously collects water level data from the water storage base and sends it to the user terminal at fixed time intervals. S42. The user terminal compares the water level data with the upper limit of the water level of the water storage base. When the water level is higher than the upper limit threshold, the user terminal issues an alarm prompt to discharge the excess water. S43. The user terminal monitors the duration of soil moisture, soil pH value, and water level deviation in real time; if any indicator deviates from the threshold for a duration exceeding the preset threshold, a remote alarm is triggered, generating alarm information. The alarm information includes the type of abnormal indicator, the degree of deviation, and a recommended adjustment plan. The recommended adjustment plan includes adjusting the drip irrigation volume, adjusting the soil pH value, or supplementing the water volume; the alarm information is sent to the user terminal.

[0048] It should be noted that step S4 enables the automatic execution and real-time monitoring of drip irrigation operations. Key data is continuously collected through water level and soil environment sensors to ensure a safe and reliable irrigation process. When the water level in the water storage base or soil environment indicators deviate from the threshold and remain there for an extended period, the user terminal automatically triggers a remote alarm and provides specific adjustment solutions, helping to promptly correct abnormal conditions and ensure the healthy growth of vegetables.

[0049] Step S5: Record each drip irrigation operation, soil pH value, soil moisture data collected by each sensor, and water level data of the water storage base, and store them in the potted vegetable knowledge base to provide data for subsequent optimization of the potted vegetable evaluation model.

[0050] In this document, relational terms such as "first" are used merely to distinguish one entity or operation from another, without necessarily requiring or implying any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0051] The above-disclosed embodiments are merely preferred embodiments of the present invention, but the present invention is not limited thereto. Any non-creative variations that can be conceived by those skilled in the art, as well as any improvements and modifications made without departing from the principles of the present invention, should fall within the protection scope of the present invention.

Claims

1. A monitoring device for potted vegetable cultivation based on tiered self-irrigation, characterized in that, include: The container body is a rectangular trough structure. A breathable cultivation inner trough is detachably installed inside the container body. Several water and air permeable holes are evenly opened at the bottom of the breathable cultivation inner trough. A first sensor assembly and a drip irrigation pipe assembly are installed in the breathable cultivation inner trough. The drip irrigation pipe assembly is connected to a preparation tank. A water storage base is detachably snapped to the bottom of the container body. A water level sensor is installed in the water storage base. The detection data of the first sensor assembly and the water level sensor are sent to the user terminal through a LoRa wireless transmission module.

2. The monitoring device for potted vegetable cultivation based on tiered self-irrigation according to claim 1, characterized in that, The edge of the breathable cultivation trough is provided with an outward-folding limiting edge, which is fixed to the inner side of the upper end of the container body by snapping on the outward-folding limiting edge. The water storage base has a hollow water storage cavity inside, and a sealing snap-fit ​​structure is provided between the water storage base and the container body. The first sensor assembly includes a soil pH sensor and a soil moisture sensor to detect the soil pH and soil moisture in real time, and a water level sensor to detect the water level in the water storage base in real time. The drip irrigation assembly includes drip irrigation pipes and drip irrigation control equipment. The drip irrigation pipes are laid on the soil surface of the aerated cultivation trough or buried in the soil, and the drip irrigation control equipment is connected to the drip irrigation pipes.

3. A monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation as described in claim 1 or 2, characterized in that, Includes the following steps: Step S1: The collected soil pH value, soil moisture and water level data are transmitted to the user terminal through the LoRa wireless transmission module. The user terminal processes the transmitted data to generate multi-source heterogeneous data. Step S2: Construct a potted vegetable evaluation model and a potted vegetable knowledge base. Input the multi-source heterogeneous data collected in real time into the trained potted vegetable evaluation model, and combine it with the potted vegetable knowledge base to determine whether the current soil environment is suitable for the planted vegetables. If it exceeds the threshold, generate adjustment suggestions. Step S3: Set the control parameters for drip irrigation time, number of drip irrigations, and amount of water per drip according to the adjustment suggestions, and send the control parameters to the drip irrigation control equipment; Step S4: The drip irrigation control equipment executes drip irrigation operations according to the received control parameters, monitors the drip irrigation operation data in real time, and triggers a remote alarm and generates alarm information if an abnormality occurs. Step S5: Record each drip irrigation operation, soil pH value, soil moisture data collected by each sensor, and water level data of the water storage base, and store them in the potted vegetable knowledge base to provide data for subsequent optimization of the potted vegetable evaluation model.

4. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 3, characterized in that, Step S2 specifically includes: S21. Construct a knowledge base and evaluation model for potted vegetables. The input parameters for the evaluation model for potted vegetables are multi-source heterogeneous data. S22. Input the historically collected multi-source heterogeneous data into the potted vegetable evaluation model and combine it with the potted vegetable knowledge base for training to obtain a trained potted vegetable evaluation model. S23. Input the real-time collected multi-source heterogeneous data into the trained potted vegetable evaluation model, combine it with the potted vegetable knowledge base to make judgments, and generate adjustment suggestions.

5. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 4, characterized in that, Step S21 specifically includes: S211. Establish a knowledge base for potted vegetables that includes suitable growth parameter thresholds and management rules for different vegetable varieties; S212. Construct an evaluation model for potted vegetables that includes regression analysis, threshold matching, and a scoring mechanism.

6. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 5, characterized in that, Step S211 specifically includes: S2111. Collect growth parameter thresholds for different vegetable varieties; S2112. Organize the collected vegetable growth parameter thresholds into a structured database, establish a vegetable variety index, and perform fast query and matching; S2113. Record vegetable growth management rules in the potted vegetable knowledge base, set up a dynamic update mechanism, and adjust the vegetable growth management rules according to environmental changes or planting experience; S2114. Connect the potted vegetable knowledge base with the potted vegetable evaluation model so that the potted vegetable evaluation model can automatically call the growth parameter thresholds and management rules of the corresponding vegetable varieties when evaluating the real-time environment. Step S212 specifically includes: S2121. The mapping relationship between soil environmental indicators and vegetable growth performance was established by using multiple linear regression, cross-validation was performed, regression coefficients were optimized, and predicted environmental impact values ​​were output. S2122. Obtain suitable growth parameter thresholds for each vegetable variety from the potted vegetable knowledge base, compare the multi-source heterogeneous data with the growth parameter thresholds item by item, and determine whether the current soil environmental indicators deviate from the suitable range; mark the degree of deviation for each indicator and output the deviation marker. S2123. Combine the predicted environmental impact values ​​with deviation markers for weighted calculation to generate a scoring mechanism, standardize the scoring results, and provide adjustment suggestions based on the scoring results.

7. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 6, characterized in that, Step S22 specifically includes: S221. Call up historically collected multi-source heterogeneous data, classify them according to vegetable varieties and soil environmental indicators, and construct training sample sets and training validation sets; S222. Input the training sample set into the potted vegetable evaluation model, optimize it by minimizing the mean square error, and evaluate the accuracy of the output using the validation set; use the grid search method to adjust the weight parameters on the validation set; S223. Apply the potted vegetable evaluation model to the training and validation set, compare the predicted values ​​of each soil environmental index with the actual vegetable growth performance; adjust the weight parameters according to the validation results, and output the trained potted vegetable evaluation model.

8. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 7, characterized in that, Step S23 specifically includes: S231. Input the multi-source heterogeneous data collected in real time by the user terminal into the trained potted vegetable evaluation model; S232. Use a potted vegetable evaluation model to judge the deviation of soil pH, soil moisture and water level in the water storage base and give adjustment suggestions, including water level adjustment suggestions, soil moisture adjustment suggestions and pH adjustment suggestions. S233. Integrate the adjustment suggestions into the output.

9. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 8, characterized in that, Step S3 specifically includes: S31. Receive adjustment suggestions generated by the potted vegetable evaluation model and integrate the adjustment suggestions into operable parameters; S32. Based on the adjustment recommendations, check the current soil pH value, soil moisture, and the existing water level in the water storage base. If the water level in the water storage base is below the set lower limit, no operation is required; if the water level in the water storage base is above the upper limit, drain the excess water. S33. Based on the soil pH value configured for the vegetable variety and the current soil moisture deviation, set the drip irrigation parameters, including drip irrigation time, number of drips, and drip volume per drip; encapsulate the drip irrigation parameters into control instructions, including start time, duration, drip interval, and flow rate per drip, and prepare to send them to the drip irrigation control equipment; S34. The user terminal sends the drip irrigation control command to the drip irrigation control device through the LoRa wireless transmission module. After receiving the command, the drip irrigation control device starts the water pump and valve and performs the drip irrigation operation according to the set drip irrigation time and drip irrigation amount. The drip irrigation control device monitors the drip irrigation process in real time, including water flow, drip irrigation time and water level in the water storage base, and feeds back the execution status to the user terminal. The user terminal records the actual execution data for each drip irrigation cycle.

10. The monitoring method for a potted vegetable cultivation monitoring device based on tiered self-irrigation according to claim 9, characterized in that, Step S4 specifically includes: S41. The drip irrigation control equipment controls the drip irrigation pump and valve to perform drip irrigation operations. The water level sensor continuously collects water level data from the water storage base and sends it to the user terminal at fixed time intervals. S42. The user terminal compares the water level data with the upper limit of the water level of the water storage base. When the water level is higher than the upper limit threshold, the user terminal issues an alarm prompt to discharge excess water. S43. The user terminal monitors the soil moisture, soil pH value, and water level deviation in real time for the duration; if any indicator deviates from the threshold for a duration exceeding the preset threshold, a remote alarm is triggered, an alarm message is generated, and the alarm message is sent to the user terminal.

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