A method and system for regulating landscaping soil

Abstract

A method and system for regulating landscaping soil relates to the technical field of landscaping soil detection. A detection area is determined in response to a user's control request; a target material corresponding to the detection area is obtained; a target pH corresponding to the detection area is obtained, a first regulation measure is determined based on the target pH and target material, and the detection area is processed according to the first regulation measure; after the detection area undergoes the first regulation measure, a target temperature and light duration are obtained, a second regulation measure is determined based on the target temperature and light duration, and the detection area is processed according to the second regulation measure; after the detection area undergoes the second regulation measure, a target humidity and target thickness are obtained, a third regulation measure is determined based on the target humidity and target thickness, and the detection area is processed according to the third regulation measure. Implementing the provided technical solution addresses the limitations of conventional soil regulation methods and improves the accuracy of soil regulation.

Description

Technical Field

[0001] The present application relates to the technical field of garden soil detection, and in particular to a method and system for regulating garden soil. Background Art

[0002] In the field of landscaping projects, plant survival rate is a key indicator for evaluating project quality, and its importance is self-evident. Suitable soil conditions are the core foundation for plant survival. Soil testing can proactively identify potential soil problems and implement targeted improvement measures accordingly, creating a favorable growth environment for plants. This effectively improves plant survival rate, reduces project costs, and reduces the workload of subsequent maintenance.

[0003] Given that soil testing plays a key supporting role in the healthy growth of landscaping plants, soil testing is also required in some specific greening project scenarios, such as when planting green plants on rooftops, to ensure that the plants can achieve the expected survival rate. At present, the conventional soil adjustment method is mainly to collect soil samples regularly, then test and analyze the samples, and then implement corresponding adjustment measures based on the test results. This adjustment method has obvious limitations. Due to the single factor considered, the generated adjustment method is relatively fixed, which makes the adjustment measures not precise enough. Summary of the Invention

[0004] The present application provides a method and system for regulating landscaping soil, which can overcome the limitations of conventional soil regulation methods and improve the accuracy of soil regulation.

[0005] In a first aspect, the present application provides a method for regulating landscaping soil, the method comprising: determining a detection area in response to a user's regulation request, the detection area being the area corresponding to the roof greening soil; obtaining a target material corresponding to the detection area, the target material being the material used for each structural level in the roof greening; obtaining a target pH corresponding to the detection area, determining a first regulation measure based on the target pH and the target material, and processing the detection area according to the first regulation measure; when the detection area has undergone the first regulation measure, obtaining a target temperature and a light duration, determining a second regulation measure based on the target temperature and the light duration, and processing the detection area according to the second regulation measure, the target temperature being the soil temperature of the detection area, and the light duration being the duration corresponding to the sunlight irradiating the detection area; when the detection area has undergone the second regulation measure, obtaining a target humidity and a target thickness, determining a third regulation measure based on the target humidity and the target thickness, and processing the detection area according to the third regulation measure, the target humidity being the soil humidity of the detection area, and the target thickness being the total thickness corresponding to the soil in the roof greening.

[0006] By adopting the above technical solution, the target material corresponding to the detection area is first obtained, that is, the material used in each structural layer of the roof greening, the soil in the detection area is tested to obtain the target pH, and the target material is combined for analysis. By comprehensively considering the pH and target material, the cause of the abnormal soil pH can be judged more accurately, and a targeted first adjustment measure can be formulated. After the first adjustment measure, the target temperature and light duration are obtained, and the second adjustment measure is determined based on these two factors. By comprehensively considering these factors, the soil environmental conditions can be understood more comprehensively, and a more reasonable second adjustment measure can be formulated. After the second adjustment measure, the target humidity and target thickness are obtained, and the third adjustment measure is determined based on these two factors. By in-depth analysis of the relationship between humidity and thickness and the target material, the cause of the humidity abnormality can be found more accurately, and more effective adjustment measures can be formulated. Based on the step-by-step adjustment method, the effect of the adjustment measure can be understood in a timely manner, and dynamic adjustments can be made according to the monitoring results, thereby overcoming the limitations of conventional adjustment measures and improving the accuracy of soil adjustment.

[0007] Optionally, obtaining the target pH value corresponding to the detection area specifically includes: dividing the detection area into multiple sub-areas, and obtaining the pH values ​​corresponding to each of the multiple sub-areas, one sub-area corresponding to a depth interval, and one sub-area corresponding to a pH value; identifying the target plants in the detection area and obtaining the plant varieties, the target plants are the green plants planted in the detection area; obtaining the target duration corresponding to the target plants, and determining the growth stage according to the target duration; inputting the growth stage and plant variety into a preset root system database for query to obtain the target root system length; assigning corresponding weights to multiple sub-areas according to the target root system length; summing up the multiple pH values ​​and the weights corresponding to each pH value to obtain the target pH value.

[0008] By adopting the above technical solution, the detection area is divided into multiple sub-areas, each sub-area corresponds to a depth range and pH. Since the pH of soil at different depths may be different, and the distribution and absorption capacity of plant roots at different depths are also different, this division method can more comprehensively reflect the actual situation of soil pH, avoid the one-sidedness brought about by a single sampling point or shallow soil testing, thereby improving the accuracy of soil pH assessment, and then calculate the pH of multiple sub-areas with their corresponding weights to obtain the target pH. This comprehensive calculation method takes into account the degree of influence of soil at different depths on plant growth, so that the target pH can better represent the actual pH environment of the soil in the entire detection area for plant growth, providing a more accurate basis for subsequent soil adjustment.

[0009] Optionally, a first adjustment measure is determined based on the target pH and the target material, specifically including: performing a component usage analysis on the target material to obtain an influencing substance, which includes an acidic substance or an alkaline substance; judging whether the target pH is within a preset pH range; when the target pH is not within the preset pH range, determining an abnormal substance; determining a first adjustment measure based on the influencing substance and the abnormal substance, and processing the detection area according to the first adjustment measure.

[0010] By adopting the above technical solution, the target material is analyzed for its composition and usage, and the influencing substances such as acidic or alkaline substances contained therein are identified. After determining that the target pH is not within the preset pH range, the abnormal substances are judged in combination with the influencing substances. When the target pH exceeds this range, by comparing the influencing substances and the actual soil pH changes, it is possible to accurately determine which material released the substance that caused the abnormal soil pH, avoiding blind guesses and ineffective adjustments. The first adjustment measure is then determined based on the influencing substances and abnormal substances, and accurate adjustments can be made to the root cause of the abnormal soil pH.

[0011] Optionally, a second adjustment measure is determined based on the target temperature and the lighting duration, specifically including: determining a preset lighting duration based on the plant variety, and if the lighting duration is less than or equal to the preset lighting duration, determining that the lighting duration is in a normal state; obtaining the heat absorption coefficient corresponding to the target material; determining the target season based on the current time point, the target season includes summer or winter; determining the target season and the heat absorption coefficient as temperature influencing factors; determining the second adjustment measure based on the temperature influencing factors and the target temperature, the second adjustment measure including spraying water or laying insulation materials.

[0012] By adopting the above technical solution, there are significant differences in the heat absorption coefficients of different target materials. The heat absorption coefficient of the target material is obtained first. The impact of the target season on the soil temperature cannot be ignored. Therefore, the target season and heat absorption coefficient are taken as influencing factors. The conventional temperature adjustment method only considers a single factor and ignores the comprehensive impact of the material heat absorption coefficient and seasonal changes on the soil temperature. By comprehensively considering multiple factors, we can more comprehensively understand the changing law of soil temperature and formulate a more scientific and targeted second adjustment measure.

[0013] Optionally, target humidity and target thickness are obtained, specifically including: obtaining a target root length corresponding to the plant variety; determining a target sub-area based on the target root length, the target sub-area being the sub-area corresponding to the target root length in the detection area; obtaining a target resistance value collected by the target sensor from the target sub-area; determining the target humidity based on a linear relationship between the target resistance value and the soil moisture content; obtaining a first height and a second height, the first height being the height between the ground and the soil surface of the detection area, and the second height being the height between the ground and the roof base of the detection area; calculating the difference between the first height and the second height, and using the difference as the target thickness.

[0014] By adopting the above technical solution, the target root length corresponding to the plant variety is obtained, and the target sub-area is determined. It is possible to focus on the areas where the plant roots are most active and most sensitive to water demand. After determining the target sub-area, sensors can be arranged in these areas in a targeted manner to improve the accuracy and effectiveness of humidity monitoring. There is a certain linear relationship between the soil resistance value and the soil moisture content. The target resistance value collected by the target sensor is obtained from the target sub-area, and the target humidity is determined based on this linear relationship. The soil moisture information can be obtained quickly and accurately, and then the first height and the second height are obtained, and the difference between the two is calculated as the target thickness, which can intuitively reflect the actual thickness of the soil layer in the roof greening.

[0015] Optionally, a third adjustment measure is determined based on the target humidity and target thickness, specifically including: judging whether the target humidity is in a preset humidity range, the preset humidity range is the soil moisture range corresponding to the plant variety; when the target humidity is not in the preset humidity range, determining that the target humidity is in abnormal humidity, and obtaining the target performance corresponding to the target material, the target performance includes waterproof performance, drainage performance and thermal insulation performance; determining the initial adjustment measure based on the target performance and abnormal humidity; determining and analyzing the target thickness to obtain the thickness grade; adjusting the initial adjustment measure based on the thickness grade to obtain the third adjustment measure.

[0016] By adopting the above technical solution, the target performance corresponding to the target material is obtained. The initial adjustment measures are determined based on the target performance and abnormal humidity. The initial adjustment measures are intended to quickly resolve the humidity anomaly problem and avoid the waste of resources caused by blind adjustment. Since soil thickness has a significant impact on soil moisture regulation, by analyzing the target thickness and obtaining a thickness grade, the water storage and drainage characteristics of the soil can be more accurately assessed. The initial adjustment measures are then adjusted according to the thickness grade, making the adjustment measures more consistent with actual conditions and improving the adjustment effect. By formulating a reasonable third adjustment measure, the soil moisture can be controlled within the range suitable for plant growth, providing a stable moisture environment for plants.

[0017] Optionally, after processing the detection area according to the third adjustment measure, the method also includes: obtaining a target image corresponding to the detection area; processing the target image to obtain the color of the plant leaves; if there is an abnormal state in the color of the plant leaves, obtaining the target position corresponding to the target image, and generating a patrol plan based on the abnormal state and the target position; and sending the patrol plan to the user terminal corresponding to the user.

[0018] By adopting the above technical solution, the color of plant leaves is an important indicator reflecting their health status. By processing the target image, the color of plant leaves can be accurately obtained, which can intuitively reflect the nutritional status of the plant and whether it is invaded by diseases. When the color of plant leaves is abnormal, the target position corresponding to the target image is obtained, and the area corresponding to the plant with the problem can be accurately located. This helps maintenance personnel to quickly find the problem, and then generate an inspection plan based on the abnormal state and target position. Corresponding inspection measures can be formulated for different problems. A reasonable inspection plan can optimize the allocation of inspection resources, concentrate manpower and material resources where they are most needed, and improve the effectiveness and efficiency of inspections.

[0019] In a second aspect of the present application, a control system for landscaping soil is provided, the system comprising an acquisition unit, a processing unit and a confirmation unit; the acquisition unit determines a detection area in response to a user's control request, the detection area being an area corresponding to the roof greening soil; acquires a target material corresponding to the detection area, the target material being the material used at each structural level in the roof greening; acquires a target pH corresponding to the detection area, the processing unit determines a first control measure based on the target pH and the target material, and processes the detection area according to the first control measure; acquiring the target pH corresponding to the detection area, specifically comprising: dividing the detection area into a plurality of sub-areas, and acquiring the pH corresponding to each of the plurality of sub-areas, one sub-area corresponding to a depth interval, and one sub-area corresponding to a pH; identifying target plants in the detection area to obtain plant varieties, the target plants being green plants planted in the detection area; acquiring target pH corresponding to the target plants the target duration is determined, and the growth stage is determined according to the target duration; the growth stage and plant variety are input into the preset root system database for query to obtain the target root system length; the corresponding weights of multiple sub-areas are assigned according to the target root system length; the multiple pH values ​​and the weights corresponding to each pH value are summed up to obtain the target pH value; when the detection area undergoes the first adjustment measure, the target temperature and illumination duration are obtained, the second adjustment measure is determined according to the target temperature and illumination duration, and the detection area is processed according to the second adjustment measure, the target temperature is the soil temperature of the detection area, and the illumination duration is the duration corresponding to the sunlight irradiating the detection area; the confirmation unit, when the detection area undergoes the second adjustment measure, the target humidity and target thickness are obtained, the third adjustment measure is determined according to the target humidity and target thickness, and the detection area is processed according to the third adjustment measure, the target humidity is the soil humidity of the detection area, and the target thickness is the total thickness corresponding to the soil in the roof greening.

[0020] In a third aspect of the present application, an electronic device is provided, which includes a processor, a memory, a user interface and a network interface, the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory, so that an electronic device executes any one of the methods described above in the present application.

[0021] In a fourth aspect of the present application, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores instructions, and when the instructions are executed, any one of the above methods of the present application is executed.

[0022] In summary, one or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0023] 1. First, obtain the target material corresponding to the test area, that is, the material used in each structural layer of the roof greening, test the soil in the test area to obtain the target pH, and analyze it in combination with the target material. By comprehensively considering the pH and target material, the cause of the abnormal soil pH can be more accurately determined, and thus a targeted first adjustment measure can be formulated. After the first adjustment measure, the target temperature and light duration are obtained, and the second adjustment measure is determined based on these two factors. By comprehensively considering these factors, a more comprehensive understanding of the soil environmental conditions can be achieved, and a more reasonable second adjustment measure can be formulated. After the second adjustment measure, the target humidity and target thickness are obtained, and the third adjustment measure is determined based on these two factors. By in-depth analysis of the relationship between humidity and thickness and the target material, the cause of the humidity abnormality can be more accurately identified, and more effective adjustment measures can be formulated. Based on the step-by-step adjustment method, the effect of the adjustment measure can be timely understood, and dynamic adjustments can be made based on the monitoring results, thereby overcoming the limitations of conventional adjustment measures and improving the accuracy of soil adjustment.

[0024] 2. The color of plant leaves is an important indicator of their health status. Processing the target image can accurately obtain the color of plant leaves, intuitively reflecting the nutritional status of the plant and whether it is invaded by diseases. When the color of plant leaves is abnormal, obtaining the target position corresponding to the target image can accurately locate the area corresponding to the plant with the problem. This helps maintenance personnel quickly find the problem, and then generate an inspection plan based on the abnormal state and target position. Corresponding inspection measures can be formulated for different problems. A reasonable inspection plan can optimize the allocation of inspection resources, concentrate manpower and material resources where they are most needed, and improve the effectiveness and efficiency of inspections. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 This is a flow chart of a method for regulating landscaping soil provided in an embodiment of the present application;

[0026] Figure 2 This is a schematic structural diagram of a landscaping soil control system provided in an embodiment of the present application;

[0027] Figure 3 This is a schematic structural diagram of an electronic device disclosed in an embodiment of the present application.

[0028] Explanation of reference numerals: 201, acquisition unit; 202, processing unit; 203, confirmation unit; 300, electronic device; 301, processor; 302, memory; 303, user interface; 304, network interface; 305, communication bus. DETAILED DESCRIPTION

[0029] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments.

[0030] In the description of the embodiments of this application, words such as "for example" or "for instance" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "for example" or "for instance" in the embodiments of this application should not be construed as being preferred or advantageous over other embodiments or designs. Rather, the use of words such as "for example" or "for instance" is intended to present the relevant concepts in a concrete manner.

[0031] In the description of the embodiments of the present application, the term "multiple" means two or more. For example, multiple systems refer to two or more systems, and multiple screen terminals refer to two or more screen terminals. In addition, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as indicating or implying relative importance or implicitly indicating the indicated technical features. Thus, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized.

[0032] In the field of landscaping projects, plant survival rate is a key indicator for evaluating project quality, and its importance is self-evident. Suitable soil conditions are the core foundation for plant survival. Soil testing can proactively identify potential soil problems and implement targeted improvement measures accordingly, creating a favorable growth environment for plants. This effectively improves plant survival rate, reduces project costs, and reduces the workload of subsequent maintenance.

[0033] Given that soil testing plays a key role in supporting the healthy growth of landscaping plants, soil testing is also required in some specific greening project scenarios, such as when planting green plants on rooftops, to ensure that the plants can achieve the expected survival rate. Currently, the conventional soil conditioning method is mainly to collect soil samples regularly, then test and analyze the samples, and then implement corresponding conditioning measures based on the test results. This conditioning method has obvious limitations and does not fully consider the comprehensive impact of the materials used in roof greening on the soil environment, resulting in inaccurate conditioning measures.

[0034] Therefore, how to solve the limitations of conventional soil conditioning methods to improve the accuracy of soil conditioning is an urgent problem to be solved. The embodiment of the present application provides a method for regulating landscaping soil, which is applied to a server. The server of the present application can be a platform that provides soil detection and regulation services for landscaping. Figure 1 This is a flow chart of a method for regulating landscaping soil provided in the embodiment of the present application, with reference to Figure 1 The method includes the following steps S101-S105.

[0035] S101: Determine a detection area in response to a user's control request, where the detection area is an area corresponding to the rooftop greening soil.

[0036] In S101 above, the application scenario of this embodiment is rooftop greening, specifically testing the soil of a rooftop greening and formulating adjustment measures based on the test results to ensure that the conditioned soil is suitable for plant survival. A user initiates a control request via a mobile app or webpage. In this case, the user is the staff performing daily maintenance on the rooftop greening. Upon receiving the control request, the server parses it to determine the area of ​​the rooftop greening to be tested. The detection area can be used to represent the area of ​​the rooftop greening to be tested.

[0037] For example, the user can select the area to be regulated in the app and obtain the corresponding number for the area. If the area is numbered A-01, the corresponding green roof area is found based on the number, the soil range corresponding to A-01 is determined, and the soil range is defined as the detection area. The green roof mentioned in this embodiment can be the green roof of a commercial building or the green roof of other buildings, but does not refer to greening in other scenarios.

[0038] S102: Acquire target materials corresponding to the detection area, where the target materials are materials used in each structural layer of the roof greening.

[0039] In S102 above, after determining the detection area, the location corresponding to the detection area can be retrieved. Based on the location, the structural layer information of the rooftop greening system can be retrieved from the database. This information was initially entered when the rooftop greening system was constructed. For example, before implementing a green roof, the roof's structural layers must be constructed. Typically, three layers are constructed: a waterproof layer, a drainage layer, and a planting layer. The waterproof layer is a key structural layer in a green roof, preventing moisture from penetrating the roof structure. By trapping moisture in the planting layer and any accumulated water from rainfall, it prevents damage to the roof's load-bearing structure, insulation layer, and other components, thereby ensuring the roof's safety and durability. The drainage layer, located above the waterproof layer and below the planting layer, primarily functions to promptly remove excess moisture from the planting layer, preventing accumulated water from harming plant roots while ensuring the stability and air permeability of the green roof system. It acts like a network of drainage pipes, quickly directing excess water to the drain outlet for discharge. The planting layer serves as the substrate for plant growth in a green roof, providing essential nutrients, water, and air for plants, and providing a fundamental environment for their survival and growth. Then, the materials used in each layer are recorded separately. After the detection area is determined, the materials used in each structural layer in the area, i.e., the target materials, can be directly extracted from the database.

[0040] For example, for the "A-01" area, the database shows that its waterproof layer is a polyethylene polypropylene composite waterproof membrane with a thickness of 1.2 mm, the drainage layer is a plastic drainage board with a height of 30 mm, and the planting soil layer is improved humus soil with an organic matter content of 30%.

[0041] S103: Obtain a target pH value corresponding to the detection area, determine a first adjustment measure according to the target pH value and the target material, and process the detection area according to the first adjustment measure.

[0042] In S103 above, after determining the target material, a soil pH sensor can be deployed in the soil of the detection area in advance to measure the soil pH in real time. Since soil at different depths corresponds to different pH values, to accurately obtain the target pH, the final pH value can be determined based on the root length of the plants in the detection area. Obtaining the target pH value corresponding to the detection area specifically includes: dividing the detection area into multiple sub-areas and obtaining the pH values ​​corresponding to each of the multiple sub-areas, with each sub-area corresponding to a depth interval and a pH value; identifying the target plant in the detection area to obtain the plant species, where the target plant is the green plant planted in the detection area; obtaining the target duration corresponding to the target plant, and determining the growth stage based on the target duration; inputting the growth stage and plant species into a preset root database for query to obtain the target root length; assigning weights to each of the multiple sub-areas based on the target root length; and summing the multiple pH values ​​with the weights corresponding to each pH value to obtain the target pH value.

[0043] Specifically, the detection area is first divided vertically into multiple sub-areas based on soil depth and actual needs, with each sub-area corresponding to a specific depth range. For example, the detection area can be divided into multiple sub-areas with depth ranges such as 0-10cm, 10-20cm, and 20-30cm. During division, each depth range can be marked as a location to ensure clear boundaries within each sub-area. For example, in a rooftop garden detection area, to more accurately understand the pH level of soil at different depths, it is divided into three sub-areas: 0-10cm (topsoil), 10-20cm (middle soil), and 20-30cm (deep soil). Soil pH sensors are then deployed in each sub-area, inserted at the corresponding sub-area depth, and pH readings are taken after a period of time. In the above example, a soil pH sensor inserted into the soil within a 0-10 cm sub-area for 5 minutes reads a pH of 6.5. Within a 10-20 cm sub-area, the pH sensor reads a pH of 6.2. Within a 20-30 cm sub-area, the pH is 6.0. A high-definition camera or drone is then used to capture images of the detection area, obtaining clear images of the target plants. During acquisition, consideration should be given to factors such as lighting and angle to ensure image quality meets recognition requirements. A drone is flown over the detection area of ​​the roof garden to capture images of different plants. These images are then fed into a plant recognition model, a convolutional neural network (CNN) based on deep learning. This model first collects and trains images of a large number of plant species, accurately identifying them based on the images. After receiving the captured images, the plant recognition model analyzes and processes them to identify the plant species. The plant's planting date (i.e., the planting date) is recorded. The current date is then obtained. The difference between the current date and the planting date is calculated, and the target root length is determined based on this difference. After obtaining the target root length for the plant, the target plant's current growth stage is determined based on the target length and the plant's growth cycle. This growth cycle can be referenced in botanical literature or professional gardening manuals, which detail the time ranges required for different plant varieties at different growth stages. A pre-built root database is constructed, containing root length information for different plant varieties at different growth stages. This pre-built root database can be collected through field measurements, literature research, and other methods, and then organized and categorized. The determined growth stage and plant variety are entered into the pre-built root database for querying. The database matches the corresponding record based on the input information and returns the target root length. For example, if the target plant is a rose, the recorded planting date is March 1, 2023, and the current date is September 1, 2023, the target root length is six months.After consulting the growth cycle table of roses, it was found that roses are usually in the transition stage from the vegetative growth period to the reproductive growth period 3-6 months after planting. Combined with the target duration of 6 months, it was determined that the rose was in the early reproductive growth period. In the preset root database, the plant variety was entered as rose, and the growth stage was the early reproductive growth period. It was found that the target root length of the rose at this stage was about 25cm. Based on the target root length and the depth range of each sub-area, the distribution ratio of the root system in each sub-area was determined, and the corresponding weight was assigned. Generally speaking, the roots are more distributed in the sub-areas close to the surface, and the weight is relatively large; the roots are less distributed in the deeper sub-areas, and the weight is relatively small. The weight can be calculated using linear interpolation or other mathematical methods based on the relationship between the target root length and the depth range of the sub-area. In the above example, since the target root length for roses is 25 cm, and it's assumed that the roots are most concentrated in the 0-10 cm depth range, followed by the 10-20 cm depth range, and the least concentrated in the 20-30 cm depth range, the 0-10 cm subregion is assigned a weight of 0.4, the 10-20 cm subregion a weight of 0.35, and the 20-30 cm subregion a weight of 0.25. After determining the weights for each subregion, the pH values ​​for each subregion are calculated and the target pH value is calculated using a weighted average method. This involves multiplying the pH value of each subregion by its corresponding weight and then adding the results for all subregions to arrive at the final target pH value.

[0044] For example, if the pH value of the 0-10 cm subregion is 6.5 with a weight of 0.4, the pH value of the 10-20 cm subregion is 6.2 with a weight of 0.35, and the pH value of the 20-30 cm subregion is 6.0 with a weight of 0.25, then the target pH value = 6.5 × 0.4 + 6.2 × 0.35 + 6.0 × 0.25 = 2.6 + 2.17 + 1.5 = 6.27.

[0045] In addition, although the present embodiment can directly know the acidity and alkalinity of the soil through soil pH detection, knowing the pH value alone is not enough to formulate accurate adjustment measures. The core purpose of introducing a technical solution for analyzing the composition of target materials and judging abnormal substances is to find out the root cause of abnormal soil pH, so as to formulate more targeted and sustainable first adjustment measures. After determining the target pH corresponding to the detection area, the first adjustment measure is determined according to the target pH and target material, specifically including: analyzing the composition of the target material to obtain the influencing substance, which includes acidic substances or alkaline substances; judging whether the target pH is in the preset acid-base range; determining the abnormal substance when the target pH is not in the preset acid-base range; determining the first adjustment measure based on the influencing substance and the abnormal substance, and processing the detection area according to the first adjustment measure.

[0046] Specifically, when abnormal soil pH is detected, if adjustments are made based solely on the pH value, such as adding calcareous substances if the soil is acidic, this approach can temporarily change the soil pH, but because the root cause of the abnormal pH is not identified and addressed, the adjustment effect is often short-lived. This embodiment, however, analyzes the composition of the target material to determine the influencing substance, then determines the abnormal substance based on the soil pH, and determines whether the two are consistent. This method can clearly identify the specific source of the soil pH. The corresponding components of each target material are first obtained, and then each component is analyzed in turn to determine whether it will affect the soil after long-term use, namely, whether it is acidic or alkaline. For example, for drainage layers, common drainage layer materials include plastic drain boards, ceramsite, and gravel. Plastic drain boards may age and degrade over time due to factors such as ultraviolet radiation and oxidation. For example, the molecular chains of PVC drain boards may break under the influence of ultraviolet light, releasing acidic substances such as hydrogen chloride. Ceramsite is typically made from raw materials such as clay and shale, which are fired at high temperatures. During the firing process, if the raw materials contain some minerals, such as sulfur-containing minerals, the ceramsite may react with moisture and oxygen in the air over long-term use, producing acidic substances such as sulfuric acid. Gravel is primarily composed of various rock fragments, such as limestone and granite. Limestone is primarily composed of calcium carbonate, which, over long-term use, may react with carbon dioxide and water in the air to produce calcium bicarbonate. Although calcium bicarbonate solutions are weakly alkaline, some intermediate products or impurities during the reaction may affect the pH value. Common waterproofing materials include polymer waterproof membranes and waterproof coatings. The aging and degradation process of polymer waterproof membranes is similar to that of PVC drainage boards, releasing acidic substances such as hydrogen chloride. Polyurethane waterproof coatings may leave some unreacted monomers or oligomers during the curing process. These substances may further react or decompose with long-term use, producing acidic or alkaline substances. After analyzing the target material and obtaining the influencing substance, and then obtaining the target pH corresponding to the detection area based on the above calculation method, according to the growth requirements and soil type of the target plant, consult relevant information or consult a professional gardener to determine the soil pH range suitable for the growth of the plant, that is, the preset pH range. Then compare the target pH with the preset pH range. If the target pH is within the preset pH range, it means that the soil pH is suitable for plant growth; if the target pH is not within the preset pH range, it means that there is a problem with the soil pH and needs to be adjusted. For example, when it is detected that the pH value of a rooftop greening soil is 5.8, which is lower than the preset pH range (6.0-7.5) required for plant growth, the traditional method may directly choose to apply calcareous substances to increase the pH value. However, the embodiment will first analyze the materials used for the rooftop greening, such as checking the plastic drainage board used in the drainage layer.Through component analysis, it was found that the plastic drainage board will age and degrade under long-term ultraviolet radiation, releasing acidic substances such as hydrogen chloride (influencing substances). At the same time, based on the acidity of the soil and chemical analysis, it was determined that the abnormal substance causing soil acidification was also hydrogen chloride. In this case, the influencing substance is consistent with the abnormal substance, indicating that soil acidification is indeed caused by the aging of the drainage board material. Based on this judgment result, the first adjustment measure cannot be limited to neutralizing the soil acidity, but also considering replacing or protecting the drainage board material. Otherwise, even if the soil pH value is temporarily adjusted, the soil will soon become acidic again due to the continuous release of acidic substances.

[0047] This first-line regulatory approach, addressing the root cause, can achieve more lasting regulatory effects. By comparing influencing and anomalous substances to determine regulatory action, this technical approach establishes a causal analysis framework, avoiding the potential blindness associated with simple adjustments based on pH values. While this process may seem like an additional step, it helps identify the true cause of abnormal soil pH, providing a basis for developing more targeted regulatory measures, ultimately enhancing the durability of regulatory effects. In practical application, this analytical approach can significantly reduce the number of repeated adjustments, lower maintenance costs, and improve regulatory efficiency. This is particularly true in the unique context of green roofs, where the use of multiple artificial materials creates a more complex environment impacting the soil environment. This systematic analytical approach can better identify and address various potential influencing factors, ensuring the accuracy and effectiveness of soil regulatory measures.

[0048] Furthermore, when the abnormal substance and the influencing substance are inconsistent, it indicates that the abnormal soil pH may be caused by multiple factors, or that the primary influencing factor is not the material issue initially suspected. Quantitative analysis of the detected abnormal substances should be performed to determine their specific content and distribution in the soil. For example, if soil testing reveals alkaline soil and material analysis indicates sodium ions (the influencing substance) in the waterproofing layer, but soil chemical analysis indicates that the alkalinity is primarily derived from calcium carbonate (the abnormal substance), further analysis of the source and distribution of the calcium carbonate is necessary. A stratified analysis of the soil profile reveals that calcium carbonate is primarily concentrated in the surface soil layer, suggesting its origin may be irrigation water or atmospheric deposition; if it is primarily concentrated in deeper layers, it may be related to the substrate material. A multi-factor assessment model can be developed that comprehensively considers factors such as the potential impact of the material influencing substance, the actual content of the abnormal substance, and the plant's tolerance to pH. For example, if the sodium ion content released by the waterproofing layer is low, but the calcium carbonate content is significantly above the standard, the first regulatory measure should be to control the calcium carbonate content. Specifically, measures such as improving irrigation water quality, increasing soil organic matter content, and selecting appropriate soil amendments can be taken. Once the initial adjustment plan is determined, a graded adjustment strategy can be generated based on the evaluation model's results. For primary influencing factors (such as excess calcium carbonate), direct control measures are implemented, such as neutralization with sulfur-containing compounds. For secondary influencing factors (such as sodium ions released from the waterproofing layer), preventative measures are taken, such as adding an isolation layer or using ion exchange resins for isolation. This graded adjustment strategy ensures effective control while avoiding the potential negative impacts of overtreatment. During the adjustment process, changes in soil pH are continuously monitored. A real-time feedback mechanism allows for timely adjustments to the intensity and duration of the initial adjustment measure. For example, if the initial adjustment measure fails to improve soil pH as expected, the intensity of the adjustment will be automatically increased; if the improvement exceeds the target value, the intensity will be appropriately reduced. This dynamic adjustment mechanism ensures the accuracy and controllability of the adjustment process. After the initial adjustment measure is determined, corresponding operational instructions are issued to address the monitored area.

[0049] S104: After the detection area has undergone the first adjustment measure, a target temperature and a lighting duration are obtained, a second adjustment measure is determined according to the target temperature and the lighting duration, and the detection area is processed according to the second adjustment measure.

[0050] In S104, after determining that the detection area should be adjusted according to the first adjustment measure, a temperature sensor is installed in the detection area to monitor soil temperature in real time. Data can be collected at preset intervals, and temperature changes within the preset period are recorded. The average value is taken as the target temperature. The target temperature is the temperature obtained by monitoring the soil temperature in the detection area. A light sensor is then used to calculate the duration of sunlight exposure to the detection area. Alternatively, the daily sunlight duration can be calculated based on weather data provided by the meteorological department and the detection area's geographic location. A second adjustment measure is then determined based on the target temperature and sunlight duration. Specifically, the following steps are performed: determining a preset sunlight duration based on the plant species; if the sunlight duration is less than or equal to the preset duration, determining that the sunlight duration is normal; obtaining the heat absorption coefficient corresponding to the target material; determining a target season based on the current time point, which can be summer or winter; determining the target season and heat absorption coefficient as temperature influencing factors; and determining a second adjustment measure based on the temperature influencing factors and the target temperature. The second adjustment measure can include spraying water or laying down thermal insulation materials.

[0051] Specifically, the optimal light duration ranges for different plant species at different growth stages are first collected to construct a comprehensive light duration database. This data can be obtained by consulting botanical textbooks, horticultural research materials, and agricultural experts. A light sensor is installed in the detection area to monitor the duration of sunlight in real time. The preset light duration for the plant species in the detection area is then queried from the light duration database and compared with the preset duration. If the monitored light duration is less than or equal to the preset duration, the light duration is determined to be normal. For example, suppose the plant species planted in the detection area are roses, and during their peak growth season, consulting the light duration database reveals that the optimal light duration for roses during their peak growth season is 6-10 hours per day. The light sensor monitors that the area has 8 hours of sunlight that day, which falls within the 6-10 hour range, thus confirming that the light duration is normal. A certain amount of samples are then collected for target materials, such as waterproofing materials, drainage materials, and planting soil used in green roofs. Samples collected should be representative and reflect the overall material properties. For example, for waterproofing materials, multiple small samples can be collected from different locations. These samples should be sent to a professional materials testing laboratory, where specialized thermal testing equipment (such as a heat flow meter or guarded hot plate method) should be used to measure the thermal absorption coefficient. The thermal absorption coefficient reflects the material's ability to absorb heat, and this varies significantly among materials. The measured thermal absorption coefficients should be recorded and stored in a database for future reference and use. Therefore, the target material's name can be directly entered into the database for query purposes to obtain its corresponding thermal absorption coefficient. The current time point (date information) is then obtained. The target season is determined based on this date, using conventional seasonal classification criteria (e.g., March-May as spring, June-August as summer, September-November as autumn, and December-February as winter). The impact of the target season and thermal absorption coefficient on soil temperature in the testing area should be analyzed. In summer, when solar radiation is strong and temperatures are high, the target material absorbs a significant amount of heat, causing soil temperatures to rise. In winter, when solar radiation is weak and temperatures are low, the target material's heat absorption coefficient also affects soil temperature fluctuations. Materials with higher heat absorption coefficients may cause soil temperatures to cool relatively slowly. Therefore, the target season and heat absorption coefficient are key factors influencing soil temperature. A normal soil temperature range, or temperature threshold, is then set based on the growth requirements of the plant species. For example, the optimal soil temperature range for most plants is 15-30°C. When the target temperature exceeds the upper temperature threshold, the soil temperature is too high, potentially affecting plant growth. Watering can be used as a control measure. Watering reduces soil temperature through evaporative heat absorption. The watering volume and frequency are calculated based on the difference between the target temperature and the upper temperature threshold, as well as the area of ​​the monitoring area.For example, if the target temperature is 5°C higher than the upper temperature threshold, and the detection area is 50 square meters, it may be necessary to spray 50-100L of water daily, divided into 2-3 times. If the target temperature continues to be too high and the water spraying effect is not ideal, or considering factors such as long-term energy conservation, you can choose to lay insulation materials as a regulatory measure. Insulation materials can reduce the heating effect of solar radiation on the soil and lower the soil temperature. Based on the area of ​​the detection area and the performance of the insulation material, select the appropriate insulation material and determine the laying thickness. For example, for a 50-square-meter detection area, you can choose to lay polystyrene foam boards with a thickness of 3-5 cm as insulation material.

[0052] Furthermore, when the target temperature falls below the lower temperature threshold, indicating that the soil temperature is too low, water spraying can be used to increase humidity and raise the temperature. Water absorbs heat during evaporation, but after spraying, the mist or droplets form a protective film on the plant surface and the surrounding environment, reducing heat loss. At this time, the water spray temperature needs to be adjusted based on actual conditions to avoid plant frost damage caused by low temperatures. In addition to water spraying, insulating materials can also be laid on the surface of the target plants to reduce heat loss.

[0053] S105: After the detection area has undergone the second adjustment measure, a target humidity and a target thickness are obtained, a third adjustment measure is determined according to the target humidity and the target thickness, and the detection area is processed according to the third adjustment measure.

[0054] In the above S105, after determining that the soil in the detection area has been adjusted according to the second adjustment measure, a soil sensor is inserted into the soil in the detection area to measure the soil moisture in real time; the total thickness of the soil in the roof greening, that is, the target thickness, is measured to obtain the target humidity and target thickness, specifically including: obtaining the target root length corresponding to the plant variety; determining the target sub-area based on the target root length, the target sub-area being the sub-area corresponding to the target root length in the detection area; obtaining the target resistance value collected by the target sensor from the target sub-area; determining the target humidity based on the linear relationship between the target resistance value and the soil moisture content; obtaining a first height and a second height, the first height being the height between the ground and the soil surface of the detection area, and the second height being the height between the ground and the roof base of the detection area; calculating the difference between the first height and the second height, and using the difference as the target thickness.

[0055] Specifically, the growth stage corresponding to the target plant is obtained. The growth stage and plant variety are then entered into a pre-set root database for query to obtain the target root length. The soil depth is divided within the detection area, vertically dividing the soil into multiple sub-regions. The soil can be divided into sub-regions such as 0-10cm, 10-20cm, 20-30cm, and 30-40cm. Based on the target root length, the depth interval where the target root length is primarily distributed is determined. The sub-region corresponding to this depth interval is the target sub-region. Generally speaking, roots are more concentrated in sub-regions close to the surface, and the root distribution gradually decreases with increasing depth. If the target root length is 30cm, then the sub-region within the 0-30cm depth range is the target sub-region. Since the detection interval has been pre-divided by 10cm depth, the 0-30cm depth range corresponds to 0-10cm, 10-20cm, and 20-30cm, respectively. These three sub-regions are then determined to represent the target sub-regions. If the root distribution is more concentrated, the range can be further narrowed to determine a more precise target sub-region. Soil resistance sensors are pre-buried in each sub-area of ​​the detection area to ensure they can accurately measure the soil resistance in the corresponding sub-area. The sensor's burial depth should match the sub-area's depth range. For example, a sensor in a 10-20 cm sub-area should be buried at a depth of 10-20 cm. The resistance value collected by the sensor corresponding to the target sub-area is obtained; this resistance value serves as the target resistance value. If the target sub-area contains multiple sub-areas, the resistance values ​​corresponding to each sub-area are obtained separately and then averaged. The resulting resistance value serves as the target resistance value. Alternatively, a weight can be determined for each sub-area based on the distribution ratio of the target root system in each sub-area. The target resistance value is then calculated by combining the resistance value of each sub-area with the weight. The specific method used to calculate the target resistance value depends on actual circumstances and is not specified here. A linear relationship model between soil resistance and soil moisture content is then established through experiments or by consulting relevant literature. Generally speaking, soil resistance and soil moisture content are negatively correlated; that is, higher soil moisture content indicates lower soil resistance. By measuring soil resistance at different moisture contents and then performing linear regression analysis, you can obtain a linear equation, such as y=ax+b, where y represents the soil moisture content, x represents the soil resistance, and a and b are the regression coefficients. Substituting the target resistance value into the linear equation, the corresponding soil moisture content is calculated, which is the target humidity.

[0056] For example, the linear relationship between soil resistance and soil moisture content is experimentally determined as y = −0.002x + 1.2, where y is the soil moisture content (%) and x is the soil resistance (Ω). Assuming the target resistance is 550Ω, substituting this into the equation yields the target humidity y = −0.002 × 550 + 1.2 = 0.1 (%), which translates to a target humidity of 10%.

[0057] In addition, use a measuring tool (such as a laser rangefinder or tape measure) to measure the height between the ground and the soil surface in the inspection area. This height is the first height. Carefully select the measurement points to ensure that the overall height of the inspection area is accurately reflected. You can measure multiple locations in the inspection area and take the average value as the final first height. In this case, the first height is the height from the soil surface of the planting layer to the roof surface. Similarly, use a measuring tool to measure the height between the ground and the roof base in the inspection area. This height is the second height, which is the height from the planting layer to the roof surface. Ensure that the measuring tool is perpendicular to the ground and roof base to minimize measurement errors. Using simple subtraction, subtract the first height from the second height to obtain the difference. This difference is the soil thickness in the planting layer. The calculation formula is: Target Thickness = Second Height - First Height. For example, if the first height is 1.21m and the second height is 1.52m, the target thickness is 0.31m.

[0058] Furthermore, after obtaining the target thickness and target humidity corresponding to the detection area, a third adjustment measure is determined based on the target humidity and target thickness, specifically including: judging whether the target humidity is in a preset humidity range, which is the soil moisture range corresponding to the plant variety; when the target humidity is not in the preset humidity range, determining that the target humidity is in abnormal humidity, and obtaining the target performance corresponding to the target material, which includes waterproof performance, drainage performance, and thermal insulation performance; determining initial adjustment measures based on the target performance and abnormal humidity; determining and analyzing the target thickness to obtain a thickness grade; and adjusting the initial adjustment measures based on the thickness grade to obtain a third adjustment measure.

[0059] Specifically, based on the growth characteristics of the plant species, relevant botanical data is consulted, and horticultural experts are consulted to determine the soil moisture range suitable for plant growth, known as the preset humidity range. For example, the ideal soil moisture range for the common pothos is generally between 40% and 70%. The target humidity, acquired in real time, is then compared with the preset humidity range. If the target humidity is below the lower limit of the preset humidity range, the soil is too dry; if it is above the upper limit, the soil is too moist. In both cases, the target humidity is considered abnormal, which can include excessive moisture or excessive dryness. Product specifications, technical manuals, and test reports are then collected for target materials (such as waterproofing, drainage, and insulation materials used in green roofs). These materials typically provide detailed information on parameters such as the material's waterproofing, drainage, and insulation properties. From this collected data, specific parameters for the target material's waterproofing, drainage, and insulation properties are extracted. Based on the target material's waterproofing, drainage, and insulation properties, the potential causes of the abnormal target humidity are analyzed. Poor waterproofing can allow external moisture to penetrate the soil, causing excessively high soil moisture. Poor drainage can prevent soil moisture from draining away quickly, also leading to abnormal humidity. Thermal insulation can affect soil temperature, indirectly affecting the rate of evaporation. Poor insulation can lead to rapid evaporation in hot weather, potentially causing low soil moisture. If the target humidity is too high and analysis reveals poor drainage, initial adjustments may include improving drainage facilities, such as increasing the number or diameter of drain pipes or clearing debris from drainage channels to ensure smooth drainage. If the waterproofing issue is a problem, the waterproofing layer may need to be inspected for damage and repaired or replaced. If any damage is found, consider increasing the insulation thickness or replacing it with a better-performing material to reduce soil evaporation. Additionally, irrigation can be appropriately increased. Consult relevant industry codes and standards, such as those for construction and gardening, and draw upon previous project experience to develop a grading standard for target thickness. For example, soil thickness is divided into three levels: thin (less than 20cm), medium (20-40cm), and thick (greater than 40cm). The actual measured target thickness is then compared with the established thickness classification standard to determine the level to which the target thickness belongs. If the target thickness level is thin, the impact on the structural bearing capacity needs to be considered when taking adjustment measures. If the soil thickness level is thin and the initial adjustment measure is to increase the irrigation amount, the irrigation amount can be appropriately reduced, or precision irrigation methods such as drip irrigation can be used to avoid excessive water. If the initial adjustment measure is to increase the thickness of the insulation material, the roof bearing capacity can be evaluated first. If the bearing capacity is limited, choose to replace the material with better insulation performance but thinner thickness. In other words, the third adjustment measure is to choose to replace the material with better insulation performance but thinner thickness.If the target thickness is thick, the implementation of adjustment measures may be limited. If the soil thickness is thick and the initial adjustment measure is to clear drainage channels, specialized soil drilling equipment can be used to conduct deep soil cleaning. If the initial adjustment measure is to add drainage facilities, due to limited space, a more compact drainage system design, i.e., the third adjustment measure, may be considered.

[0060] For example, if the plant being planted is a pothos, the humidity threshold is set between 40% and 70%, and the real-time target humidity is 80%, exceeding the upper threshold. Therefore, the target humidity is determined to be abnormal (too humid). The target materials used in the green roof are then obtained, including the polyvinyl chloride waterproofing membrane (waterproof layer), plastic drain board (drainage layer), and polystyrene foam board (insulation layer). By consulting the product specifications and test reports, the PVC waterproofing membrane is rated as Class I, the plastic drain board has a drainage rate of 5 cm³ / s and a drainage volume of 2000 cm³ / m², and the polystyrene foam board has a thermal conductivity of 0.03 W / (m·K), indicating good insulation performance. These parameters represent the target performance of the target materials. Since the target humidity is 80%, it is too high. Analysis reveals that the plastic drain board's low drainage rate may be due to soil particle blockage in the drainage channel. Therefore, the initial adjustment measures are to clean debris from the drain board and check that the drainage pipes are unobstructed, clearing any blockages promptly. Real-time soil thickness measurements show a value of 25cm. According to established soil thickness classification standards, a soil thickness of 20-40cm is considered medium, so the thickness grade is medium. If the thickness grade is medium, the initial adjustment measures are to clean debris from the drain board and check that the drainage pipes are unobstructed. Because the soil thickness is moderate, conventional soil cleaning tools, such as small shovels and brushes, can be used to clean the surface of the drain board when cleaning debris from the drain board. For inspection of the drainage pipes, equipment such as a pipe endoscope can be used to check for blockages inside the pipes. If a minor blockage is found in the pipe, a high-pressure water gun can be used to flush and unclog it. The resulting third adjustment measure is to use conventional tools to clean debris from the drain board and to inspect and unclog the drainage pipes with a pipe endoscope and a high-pressure water gun. After the third adjustment measure, the soil moisture in the test area can be ensured to meet the requirements for plant growth.

[0061] In one possible implementation, in addition to daily monitoring of the soil, the growth status of plants can also be monitored, and plants with abnormal leaf color can be identified in a timely manner, and then a patrol plan can be formulated so that users can deal with plants with abnormal leaves in a timely manner to avoid affecting other surrounding plants due to untreated conditions. Specifically, the plan includes: obtaining a target image corresponding to the detection area; processing the target image to obtain the color of the plant leaves; if the color of the plant leaves is abnormal, obtaining the target position corresponding to the target image, and generating a patrol plan based on the abnormal state and the target position; sending the patrol plan to the user's corresponding user terminal so that the user can view the patrol plan.

[0062] Specifically, cameras should be strategically installed within the monitoring area. The cameras should be positioned to cover the entire monitoring area, ensuring clear images of plant growth. Camera acquisition parameters, such as resolution, frame rate, and shooting angle, should be set according to actual needs. Higher resolutions provide clearer image detail, but increase the data storage and processing burden. An appropriate frame rate ensures accurate dynamic monitoring. Timed acquisition can be used to automatically capture images at preset intervals (e.g., hourly or daily). Alternatively, trigger conditions can be set to trigger image capture when certain events (such as changes in light intensity or temperature) are detected. For example, in a rooftop garden, to monitor plant growth, high-definition cameras were installed at the four corners and the center of the garden. The cameras were set to a resolution of 2560×1440, a frame rate of 30 fps, and a bird's-eye view to cover the entire garden area. Timed acquisition is used to capture images daily at 9:00 AM, 12:00 PM, and 3:00 PM. These captured images are designated as target images. Image denoising algorithms (such as Gaussian filtering or median filtering) are used to remove noise from the target images and improve image quality. Noise can arise from camera sensors, transmission processes, and other factors, affecting subsequent color recognition accuracy. Histogram equalization and other methods are used to enhance image contrast, making the color characteristics of plant leaves more distinct. If the overall image is too dark or too bright, contrast enhancement can more clearly highlight the color differences within the leaves. The target image is then converted from the common RCB color space to a color space more suitable for color analysis, such as the HSV (hue, saturation, value) color space. In the HSV color space, hue (H) more intuitively represents color type, facilitating the classification and identification of plant leaf colors. A color threshold is then set based on the normal color range of plant leaves. An image segmentation algorithm is then used to extract the color region of the plant leaves from the image using the set color threshold. The extracted leaf color is then compared with a pre-set normal color range. If the leaf color exceeds the normal range, such as yellowing, whitishness, or spots, it is considered abnormal. For example, the hue of a normal green plant leaf is between 80° and 120°. If the hue of a leaf falls below 80° or rises above 120°, the leaf is considered abnormal. The severity of the anomaly is assessed based on the degree of difference between the leaf color and the normal color. The greater the difference, the greater the anomaly. For example, a color distance formula (such as Euclidean distance) can be used to calculate the distance between the leaf color and the normal color center value. The greater the distance, the more severe the anomaly. The camera's installation position and shooting angle information, combined with image processing coordinate transformation algorithms, can be used to determine the actual geographic location of the plant leaf in the target image. For example, by establishing a transformation relationship between the camera coordinate system and the world coordinate system, pixel coordinates in the image can be converted to actual geographic coordinates.Mark the area where abnormal leaves appear in the target image and record its location. Marking methods such as rectangular boxes and circles can be used, and the center coordinates and size of the marked area are recorded. Based on the abnormality status and target location, patrol tasks are assigned to the appropriate patrol personnel or equipment. Based on the target location, a reasonable patrol route is planned to improve patrol efficiency. A path planning algorithm can be used to consider factors such as the patrol personnel's or equipment's movement speed and obstacles to optimize the patrol route. The patrol plan details the inspection content, such as observing the specific signs of leaf abnormalities, checking the plant's growing environment (light, temperature, humidity, etc.), and recording relevant information. The patrol plan is then sent to the user via text message or email. Abnormality status can also be categorized into multiple levels. When abnormalities are detected at multiple locations, the patrol plan is sent to patrol personnel via text message, allowing them to promptly conduct inspections at the target locations. You can set a processing time in the inspection plan. The more locations with abnormal conditions, the shorter the processing time. The fewer locations with abnormal conditions, the more appropriate the processing time. This processing time can be set based on the area the inspector is actually responsible for. For example, if four abnormal conditions are found in the inspection area at the same time, the processing time can be set to 4 hours. If one abnormal condition is found in the inspection area at the same time, the processing time can be set to 24 hours.

[0063] Based on the above method, through a step-by-step adjustment approach, corresponding monitoring and evaluation will be carried out after each step of adjustment. Based on real-time monitoring of various soil indicators, the effects of adjustment measures can be understood in a timely manner, and dynamic adjustments can be made according to the monitoring results. Adjustment measures are continuously optimized to ensure that the soil environment is always kept within a range suitable for plant growth. The mechanism of dynamic adjustment and continuous optimization can improve the accuracy and effectiveness of soil adjustment and overcome the limitations of conventional adjustment methods.

[0064] The present application also provides a landscaping soil control system. Figure 2 This is a schematic diagram of a control system for landscaping soil provided in an embodiment of the present application, with reference to Figure 2 The system includes an acquisition unit 201, a processing unit 202 and a confirmation unit 203.

[0065] The acquisition unit 201 determines a detection area in response to a user's control request. The detection area is the area corresponding to the roof greening soil; obtains the target material corresponding to the detection area. The target material is the material used in each structural layer of the roof greening; and obtains the target pH value corresponding to the detection area.

[0066] The processing unit 202 determines a first adjustment measure based on the target pH and target material, and processes the detection area according to the first adjustment measure; obtains the target pH corresponding to the detection area, specifically including: dividing the detection area into multiple sub-areas, and obtaining the pH corresponding to each of the multiple sub-areas, where each sub-area corresponds to a depth range and a pH; identifies the target plant in the detection area to obtain the plant variety, where the target plant is a green plant planted in the detection area; obtains the target duration corresponding to the target plant, and determines the growth stage based on the target duration; inputs the growth stage and plant variety into a preset root system database for query to obtain the target root length; assigns corresponding weights to each of the multiple sub-areas based on the target root system length; sums the multiple pH values ​​and the weights corresponding to each pH value to obtain the target pH; after the detection area undergoes the first adjustment measure, obtains the target temperature and light duration, determines a second adjustment measure based on the target temperature and light duration, and processes the detection area according to the second adjustment measure, where the target temperature is the soil temperature of the detection area, and the light duration is the duration corresponding to sunlight irradiating the detection area.

[0067] The confirmation unit 203 obtains the target humidity and target thickness after the detection area undergoes the second adjustment measure, determines the third adjustment measure based on the target humidity and target thickness, and processes the detection area according to the third adjustment measure. The target humidity is the soil humidity of the detection area, and the target thickness is the total thickness of the soil in the roof greening.

[0068] In one possible embodiment, the processing unit 202 is used to perform a composition analysis on the target material to obtain an influencing substance, which includes an acidic substance or an alkaline substance; determine whether the target pH is within a preset pH range; the confirmation unit 203 is used to determine an abnormal substance when the target pH is not within the preset pH range; determine a first adjustment measure based on the influencing substance and the abnormal substance, and process the detection area based on the first adjustment measure.

[0069] In one possible embodiment, the acquisition unit 201 is used to determine a preset illumination duration based on the plant variety. If the illumination duration is less than or equal to the preset illumination duration, it is determined that the illumination duration is in a normal state; the heat absorption coefficient corresponding to the target material is obtained; the processing unit 202 is used to determine the target season based on the current time point, and the target season includes summer or winter; the target season and the heat absorption coefficient are determined as temperature influencing factors; and a second adjustment measure is determined based on the temperature influencing factor and the target temperature, and the second adjustment measure includes spraying water or laying insulation materials.

[0070] In one possible embodiment, the acquisition unit 201 is used to obtain the target root length corresponding to the plant variety; the processing unit 202 is used to determine the target sub-area based on the target root length, and the target sub-area is the sub-area corresponding to the target root length in the detection area; the acquisition unit 201 is used to obtain the target resistance value collected by the target sensor from the target sub-area; the processing unit 202 is used to determine the target humidity based on the linear relationship between the target resistance value and the soil moisture content; the acquisition unit 201 is used to obtain a first height and a second height, the first height being the height between the ground and the soil surface of the detection area, and the second height being the height between the ground and the roof base of the detection area; the processing unit 202 is used to calculate the difference between the first height and the second height, and use the difference as the target thickness.

[0071] In one possible embodiment, the acquisition unit 201 is used to determine whether the target humidity is within a preset humidity range, which is the soil moisture range corresponding to the plant variety; when the target humidity is not within the preset humidity range, it is determined that the target humidity is at abnormal humidity, and the target performance corresponding to the target material is obtained, which includes waterproof performance, drainage performance, and thermal insulation performance; the processing unit 202 is used to determine the initial adjustment measures based on the target performance and abnormal humidity; determine and analyze the target thickness to obtain a thickness grade; adjust the initial adjustment measures based on the thickness grade to obtain a third adjustment measure.

[0072] In one possible implementation, the acquisition unit 201 is used to acquire a target image corresponding to the detection area; the processing unit 202 is used to process the target image to obtain the color of the plant leaves; if there is an abnormal state in the color of the plant leaves, the target position corresponding to the target image is acquired, and a patrol plan is generated based on the abnormal state and the target position; the patrol plan is sent to the user terminal corresponding to the user so that the user can view the patrol plan.

[0073] It should be noted that the above embodiments provide systems that implement their functions using only the division of the above functional modules as an example. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments are based on the same concept. The specific implementation process is detailed in the method embodiment and will not be repeated here.

[0074] This application also discloses an electronic device. Figure 3 , Figure 3 The electronic device 300 may include: at least one processor 301 , at least one network interface 304 , a user interface 303 , a memory 302 , and at least one communication bus 305 .

[0075] The communication bus 305 is used to realize the connection and communication between these components.

[0076] The user interface 303 may include a display screen (Display) and a camera (Camera). Optionally, the user interface 303 may also include a standard wired interface and a wireless interface.

[0077] The network interface 304 may optionally include a standard wired interface or a wireless interface (such as a WI-FI interface).

[0078] The processor 301 may include one or more processing cores. Using various interfaces and circuits, the processor 301 connects to various components within the server. It executes instructions, programs, code sets, or instruction sets stored in the memory 302, as well as accesses data stored in the memory 302, to perform various server functions and process data. Optionally, the processor 301 may be implemented using at least one of the following hardware forms: a digital signal processing (DSP), a field-programmable gate array (FPGA), or a programmable logic array (PLA). The processor 301 may integrate one or a combination of a central processing unit (CPU), a graphics processing unit (GPU), and a modem. The CPU primarily processes the operating system, user interface, and application requests; the GPU is responsible for rendering and drawing content displayed on the display screen; and the modem handles wireless communications. It is understood that the modem may also be implemented independently of the processor 301 and implemented as a separate chip.

[0079] Memory 302 may include random access memory (RAM) or read-only memory (ROM). Optionally, memory 302 may include non-transitory computer-readable storage medium. Memory 302 may be used to store instructions, programs, codes, code sets, or instruction sets. Memory 302 may include a program storage area and a data storage area. The program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the aforementioned method embodiments, and the data storage area may store data involved in the aforementioned method embodiments. Memory 302 may also optionally be at least one storage device located remotely from the aforementioned processor 301.

[0080] like Figure 3 As shown, the memory 302 as a computer storage medium may include an operating system, a network communication module, a user interface module, and an application program for regulating landscaping soil.

[0081] exist Figure 3 In the electronic device 300 shown, the user interface 303 is mainly used to provide an input interface for the user and obtain data input by the user; and the processor 301 can be used to call the application for regulating landscaping soil stored in the memory 302. When executed by one or more processors, the electronic device executes one or more methods described in the above embodiments.

[0082] It should be noted that for the aforementioned method embodiments, for simplicity of description, they are all expressed as a series of action combinations, but those skilled in the art should be aware that this application is not limited by the order of the actions described, because according to this application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all preferred embodiments, and the actions and modules involved are not necessarily required for this application.

[0083] In the above embodiments, the description of each embodiment has its own focus. For parts that are not described in detail in a certain embodiment, reference can be made to the relevant descriptions of other embodiments.

[0084] In the several embodiments provided in this application, it should be understood that the disclosed devices can be implemented in other ways. For example, the device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. In actual implementation, there may be other division methods, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some service interfaces, and the indirect coupling or communication connection of the devices or units can be electrical or other forms.

[0085] The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of these units may be selected to achieve the purpose of this embodiment according to actual needs.

[0086] In addition, the functional units in the various embodiments of the present application may be integrated into a single processing unit, or each unit may exist physically separately, or two or more units may be integrated into a single unit. The aforementioned integrated units may be implemented in the form of hardware or software functional units.

[0087] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable memory. Based on this understanding, the technical solution of this application, or the portion that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions for causing a computer device (which can be a personal computer, server, or network device, etc.) to execute all or part of the steps of the method described in each embodiment of this application. The aforementioned memory includes various media that can store program code, such as USB flash drives, mobile hard drives, magnetic disks, or optical disks.

[0088] The above is only an exemplary embodiment of the present disclosure and cannot be used to limit the scope of the present disclosure. That is, any equivalent changes and modifications made according to the teachings of the present disclosure are still within the scope of the present disclosure. After considering the disclosure of the specification and the truth of practice, those skilled in the art will easily think of other embodiments of the present disclosure. This application is intended to cover any variation, use or adaptive change of the present disclosure, which follows the general principles of the present disclosure and includes common knowledge or customary technical means in the technical field not recorded in the present disclosure.

Claims

1. A method for regulating landscaping soil, characterized in that: The method comprises: Determining a detection area in response to a user's control request, the detection area being an area corresponding to the roof greening soil; Obtaining a target material corresponding to the detection area, wherein the target material is a material used in each structural layer of the green roof; Obtain a target pH value corresponding to the detection area, determine a first adjustment measure based on the target pH value and the target material, and process the detection area according to the first adjustment measure; obtaining the target pH value corresponding to the detection area specifically includes: dividing the detection area into multiple sub-areas, and obtaining the pH values ​​corresponding to each of the multiple sub-areas, one sub-area corresponding to a depth interval, and one sub-area corresponding to one pH value; identifying the target plants in the detection area to obtain plant varieties, wherein the target plants are green plants planted in the detection area; obtaining a target duration corresponding to the target plants, and determining a growth stage based on the target duration; inputting the growth stage and the plant variety into a preset root system database for query to obtain a target root system length; assigning corresponding weights to each of the multiple sub-areas based on the target root system length; summing the multiple pH values ​​with the weights corresponding to each pH value to obtain the target pH value; After the detection area has undergone the first adjustment measure, a target temperature and a duration of sunlight exposure are obtained, a second adjustment measure is determined based on the target temperature and the duration of sunlight exposure, and the detection area is processed according to the second adjustment measure, where the target temperature is the soil temperature of the detection area, and the duration of sunlight exposure is the duration corresponding to the sunlight exposure to the detection area; After the detection area undergoes the second adjustment measure, the target humidity and target thickness are obtained, and a third adjustment measure is determined based on the target humidity and the target thickness. The detection area is processed according to the third adjustment measure. The target humidity is the soil moisture of the detection area, and the target thickness is the total thickness corresponding to the soil in the roof greening.

2. The method according to claim 1, characterized in that The determining of the first adjustment measure according to the target pH and the target material specifically includes: Performing a component analysis on the target material to obtain an influencing substance, wherein the influencing substance includes an acidic substance or an alkaline substance; Determining whether the target pH is within a preset pH range; When the target pH is not within the preset pH range, determining an abnormal substance; The first adjustment measure is determined according to the influencing substance and the abnormal substance, and the detection area is processed according to the first adjustment measure.

3. The method according to claim 1, characterized in that The determining of the second adjustment measure according to the target temperature and the illumination duration specifically includes: Determining a preset illumination duration according to the plant variety, and if the illumination duration is less than or equal to the preset illumination duration, determining that the illumination duration is in a normal state; Obtaining a heat absorption coefficient corresponding to the target material; Determine a target season according to the current time point, wherein the target season includes summer or winter; Determining the target season and the heat absorption coefficient as temperature influencing factors; The second regulating measure is determined according to the temperature influencing factor and the target temperature, and the second regulating measure includes spraying water or laying heat insulating materials.

4. The method according to claim 1, wherein The obtaining of the target humidity and target thickness specifically includes: Obtaining the target root length corresponding to the plant variety; Determine a target sub-region according to the target root length, where the target sub-region is a sub-region corresponding to the target root length in the detection area; Acquire a target resistance value collected by a target sensor from the target sub-area; determining the target humidity based on a linear relationship between the target resistance value and soil moisture content; Obtaining a first height and a second height, wherein the first height is the height between the ground and the soil surface of the detection area, and the second height is the height between the ground and the roof base of the detection area; The difference between the first height and the second height is calculated, and the difference is used as the target thickness.

5. The method according to claim 4, characterized in that The determining of the third adjustment measure according to the target humidity and the target thickness specifically includes: Determining whether the target humidity is within a preset humidity range, where the preset humidity range is a soil humidity range corresponding to the plant variety; When the target humidity is not within the preset humidity range, determining that the target humidity is at an abnormal humidity, and obtaining target properties corresponding to the target material, the target properties including waterproof performance, drainage performance, and thermal insulation performance; determining an initial adjustment measure based on the target performance and the abnormal humidity; Determining and analyzing the target thickness to obtain a thickness grade; The initial adjustment measure is adjusted according to the thickness grade to obtain the third adjustment measure.

6. The method according to claim 5, characterized in that After processing the detection area according to the third adjustment measure, the method further includes: Acquire a target image corresponding to the detection area; Processing the target image to obtain the color of plant leaves; If the color of the plant leaves is abnormal, obtaining the target position corresponding to the target image, and generating an inspection plan based on the abnormal state and the target position; The inspection plan is sent to the user terminal corresponding to the user.

7. A landscaping soil control system, characterized in that: The system comprises an acquisition unit (201), a processing unit (202) and a confirmation unit (203); The acquisition unit (201) determines a detection area in response to a user's control request, the detection area being an area corresponding to the roof greening soil; acquires a target material corresponding to the detection area, the target material being a material used in each structural layer of the roof greening; acquires a target pH value corresponding to the detection area, The processing unit (202) determines a first adjustment measure according to the target pH and the target material, and processes the detection area according to the first adjustment measure; The obtaining of the target pH value corresponding to the detection area specifically includes: dividing the detection area into a plurality of sub-areas, and obtaining the pH values ​​corresponding to the plurality of sub-areas, wherein one sub-area corresponds to a depth interval, and one sub-area corresponds to one pH value; identifying the target plant in the detection area to obtain the plant variety, wherein the target plant is a green plant planted in the detection area; obtaining the target duration corresponding to the target plant, and determining the growth stage according to the target duration; inputting the growth stage and the plant variety into a preset root system database for query to obtain the target root length; assigning weights corresponding to the plurality of sub-areas according to the target root length; summing the plurality of pH values ​​and the weights corresponding to each pH value to obtain the target pH value; after the detection area undergoes the first adjustment measure, obtaining the target temperature and illumination duration, determining the second adjustment measure according to the target temperature and illumination duration, and processing the detection area according to the second adjustment measure, wherein the target temperature is the soil temperature of the detection area, and the illumination duration is the duration corresponding to sunlight irradiating the detection area; The confirmation unit (203) obtains a target humidity and a target thickness after the detection area has passed the second adjustment measure, determines a third adjustment measure based on the target humidity and the target thickness, and processes the detection area according to the third adjustment measure, wherein the target humidity is the soil humidity of the detection area, and the target thickness is the total thickness of the soil in the green roof.

8. An electronic device, characterized in that: The electronic device (300) comprises a processor (301), a memory (302), a user interface (303) and a network interface (304), wherein the memory (302) is used to store instructions, the user interface (303) and the network interface (304) are used to communicate with other devices, and the processor (301) is used to execute the instructions stored in the memory (302) so that the electronic device (300) executes the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores instructions, and when the instructions are executed, the method according to any one of claims 1 to 6 is executed.

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