Submerged plant restoration and monitoring operation and maintenance method in ecological restoration

Abstract

The invention discloses a submerged plant recovery and monitoring operation and maintenance method in ecological restoration, which belongs to the technical field of submerged plants and comprises the following steps: screening submerged plant planting cultivation materials, quickly cultivating submerged plant seedlings, determining underwater planting points and automatically planting the submerged plant seedlings by adopting an underwater robot. Inputting the plurality of initial planting point distribution results into an efficiency benefit prediction scoring model to obtain a prediction scoring value of each initial planting point distribution result, and determining underwater planting points based on the initial planting point distribution result with the maximum prediction scoring value; and monitoring and managing the recovered submerged plants. The problems that existing planting is low in efficiency, high in cost and low in survival rate are solved. By establishing a systematic system of submerged plant seedling cultivation, modular propagation, automatic efficient planting and intelligent monitoring and operation and maintenance, efficient modular cultivation of submerged plants can be achieved, the planting efficiency and the survival rate of the submerged plants are improved, and the planting cost is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of submerged plants, and in particular to a method for restoring, monitoring and maintaining submerged plants in ecological restoration. Background Art

[0002] Aquatic plants can be divided into emergent plants, floating-leaf plants and submerged plants according to their growth characteristics. As the main primary producers in the composition of the ecosystem, they play an irreplaceable role, especially submerged plants, whose specific living habits give them more ecological functions. When submerged plants are abundant, the water body exhibits high biodiversity, clear water quality, high dissolved oxygen content, low algae density, etc., which are of great value in maintaining the clear water homeostasis of rivers and lakes.

[0003] Submerged macrophytes are the foundation of biodiversity in water bodies. As primary producers, they provide essential food sources for fish and other aquatic organisms, offer refuge for small zooplankton and other fish, and maintain the integrity and complexity of ecosystem food webs. Furthermore, submerged macrophytes, living entirely in water, possess absorptive functions through their roots, stems, and leaves, playing a crucial role in controlling nitrogen and phosphorus nutrients and accumulating heavy metals. Furthermore, by absorbing both biological and non-biological suspended matter in the water, they mitigate sediment resuspension caused by currents and wind and waves, improve underwater lighting conditions, and enhance water clarity. Compared to floating algae, submerged macrophytes are larger, have longer life cycles, and possess a greater ability to absorb and store nutrients, effectively inhibiting the growth of floating algae. Submerged macrophytes play a bridging role in aquatic ecosystems, maintaining a normal ecological cycle and balance. Submerged plants are almost entirely submerged in water throughout their life cycle. Compared with terrestrial plants, submerged plants are relatively fragile, and their roots are sometimes underdeveloped or degenerate, serving only to stabilize the plant body. The fiber bundles and mechanical tissues of submerged plants are extremely underdeveloped, which also makes the plant body very soft, making planting and harvesting relatively difficult.

[0004] Currently, submerged plants are primarily planted manually, using methods such as dry-bottom cuttings, fork cuttings, cast planting, and seed-sinking bags. These methods are not only inefficient and costly, but are also often affected by water depth and wind and waves, resulting in low survival rates for submerged plants after planting. Furthermore, due to ecological restoration projects, the water bodies that require aquatic plant restoration are often polluted. This creates a high demand for submerged plants, a relatively large number of species, and complex pre-plant preparations, all of which significantly impact the rapid establishment of aquatic plants. Summary of the Invention

[0005] The purpose of the present invention is to provide a method for the restoration, monitoring and operation of submerged plants in ecological restoration. By establishing a systematic system for submerged plant seedling cultivation, modular propagation, automated and efficient planting, intelligent monitoring and operation, submerged plants can be cultivated efficiently and modularly, the planting efficiency and survival rate of submerged plants can be improved, the planting cost can be reduced, and the problems raised in the above-mentioned background technology can be solved.

[0006] To achieve the above object, the present invention provides the following technical solutions: Restoration, monitoring, and maintenance methods for submerged plants in ecological restoration include: Screening submerged plant planting and cultivation materials, rapidly cultivating submerged plant seedlings, determining underwater planting sites, and using underwater robots to automatically plant submerged plant seedlings; Among them, based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, combined with artificial intelligence, an efficiency-benefit prediction and scoring model is established; Inputting multiple initial planting point allocation results into the efficiency and benefit prediction scoring model to obtain a predicted score value for each initial planting point allocation result, and determining the underwater planting point based on the initial planting point allocation result with the largest predicted score value; Monitor the restored submerged plants, conduct analysis and prediction based on the monitoring results, and then carry out operation and maintenance management of the submerged plants.

[0007] Preferably, determining the underwater planting site includes: The camera obtains images of the underwater planting area, and the AI ​​algorithm is used to identify the bottom type of the underwater planting area image to obtain the underwater bottom type, and based on the underwater bottom type, the type of plants cultivated in the underwater planting area is obtained; Obtaining historical planting conditions and historical planting situations of the plant type, and training an artificial intelligence model based on the historical planting conditions and historical planting situations to obtain a planting point allocation model; Obtaining a plurality of frames of underwater planting area images continuously captured by a camera, determining the water depth, water flow velocity and bottom depth of the underwater planting area based on the plurality of frames of underwater planting area images, and obtaining the lighting characteristics of the underwater planting area; The water depth, water flow velocity, bottom depth and light characteristics of the underwater planting area, as well as the planting requirements are input into the planting point allocation model to obtain multiple initial planting point allocation results for the underwater planting area; Obtaining historical growth conditions corresponding to historical planting conditions of the plant type, determining historical planting efficiencies of the historical planting conditions, obtaining historical cost-effectiveness of the historical growth conditions, and establishing an efficiency weight for the historical planting efficiency and a benefit weight for the historical cost-effectiveness based on actual needs; Based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, combined with artificial intelligence, an efficiency-benefit prediction and scoring model is established; Inputting multiple initial planting point allocation results into the efficiency and benefit prediction scoring model to obtain the predicted score value of each initial planting point allocation result; The underwater planting point is determined based on the initial planting point allocation result with the largest predicted score value.

[0008] Preferably, based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, combined with artificial intelligence, an efficiency-benefit prediction scoring model is established, including: Based on the historical growth conditions corresponding to the historical planting conditions, the historical planting conditions are divided to obtain different planting areas, each of which corresponds to different local growth conditions; Set the efficiency coefficient and profit coefficient of the corresponding planting area based on the local growth situation; Establishing efficiency prediction rules and benefit prediction rules for the planting conditions to be tested based on the efficiency coefficient and the benefit coefficient; Based on the efficiency prediction rules and the benefit prediction rules, the planting efficiency and the planting benefit of the planting situation to be tested are obtained; Establish prediction scoring rules based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight; Based on efficiency prediction rules, benefit prediction rules and prediction scoring rules, combined with artificial intelligence, an efficiency and benefit prediction scoring model is established.

[0009] Preferably, the automated planting of submerged plant seedlings using an underwater robot includes: Divide the planting grid according to the underwater planting site, and adopt a modular design combining woven grids and planting baskets to divide the underwater planting site into multiple grid units. Establish a four-level grid of water area-division-unit-point, and manage multiple grid units through a combination of physical isolation and digital monitoring. The water quality and bottom quality are detected by sensors to evaluate the submerged plant planting environment. When the submerged plant planting environment is suitable for submerged plant seedlings, the operator sends instructions to the underwater robot through the computer and sends the underwater planting point to the underwater robot; Place submerged plant seedlings into the seedling container of the underwater robot, use GPS and sonar systems to locate the underwater planting point, and the underwater robot will find the underwater planting point according to the planned movement path; The underwater robot uses a robotic arm to dig a hole and places submerged plant seedlings into the hole. It uses the cutting method to plant the seedlings, implants them into the bottom mud, and covers them with soil to fix them, completing the underwater planting task of submerged plants. After the community stabilizes, it enters the maintenance stage.

[0010] Preferably, screening submerged plant planting and cultivation materials includes: Based on the differences in plant growth conditions, submerged plants commonly used in ecological restoration were selected as typical representative species, with easy-to-obtain plant seeds, stone buds, dormant buds and broken stems as the main focus; Choose environmentally friendly embedding materials suitable for plant cultivation; Through germination experiments, the advantages and disadvantages of different cultivation materials are compared, and high-quality cultivation materials that can be used for submerged plant cultivation are screened out.

[0011] Preferably, the method of rapidly cultivating submerged plant seedlings comprises: Select submerged plants with faster rooting from Vallisneria, Potamogeton serrata and Myriophyllum paniculatum; According to the selected submerged plants, the bottom type, water level, light intensity and water temperature conditions are regulated, and inducing hormones are appropriately added. The germination experiment is used to quantify the various environmental indicators for submerged plant cultivation and establish a submerged plant cultivation site; Combined with the selected high-quality cultivation materials, the selected submerged plants are cultivated in a submerged plant cultivation site, so that the submerged plants can be cultivated in a modular manner and submerged plant seedlings can be cultivated quickly.

[0012] Preferably, monitoring of restored submerged macrophytes includes: Based on remote sensing technology and sensors, the community composition, coverage and biomass of underwater submerged plants are monitored and collected in real time to obtain plant growth data; Based on remote sensing technology and sensors, the water temperature, pH and dissolved oxygen in the living environment of underwater submerged plants are monitored and collected in real time to obtain water quality change data; Based on remote sensing technology and sensors, real-time monitoring and collection of changes in fish and plankton in the living environment of underwater submerged plants are carried out to obtain ecological response data; Among them, the real-time monitoring data of submerged plants after the recovery of submerged plants in ecological restoration is determined based on plant growth data, water quality change data and ecological response data.

[0013] Preferably, analysis and prediction are performed based on the monitoring situation, including: Clean the real-time monitoring data of submerged plants, remove noise in the real-time monitoring data of submerged plants, identify and delete duplicate values, missing values ​​and outliers in the real-time monitoring data of submerged plants; Convert the real-time monitoring data of submerged plants, remove the dimensional differences between the real-time monitoring data of submerged plants, and determine the standardized real-time monitoring data of submerged plants; Feature extraction is performed on the real-time monitoring data of submerged plants, feature vectors related to submerged plant monitoring and operation are extracted from the real-time monitoring data of submerged plants, and the characteristic monitoring data of submerged plants is determined.

[0014] Preferably, the analysis and prediction based on the monitoring situation also includes: Collect historical data on submerged plant growth, and use deep learning technology to train and optimize the deep learning model using this data to determine a submerged plant growth risk prediction model. The submerged plant characteristic monitoring data is input into the submerged plant growth risk prediction model, the submerged plant characteristic monitoring data is analyzed according to the submerged plant growth risk prediction model, and the growth risk behavior of the submerged plants is predicted to determine the submerged plant growth risk prediction results.

[0015] Preferably, the operation and maintenance of submerged plants includes: When risky growth of submerged plants is predicted, maintenance and control of the submerged plants are carried out, alien species are removed, overcrowded plants are pruned, and the growth environment is optimized. At the same time, the submerged plant restoration plan is dynamically adjusted according to the submerged plant monitoring situation to restore the submerged plants during ecological restoration.

[0016] Compared with the prior art, the present invention has the following beneficial effects: The present invention adopts germination experiment to screen submerged plant planting and cultivation materials, quantifies various environmental indicators of submerged plant cultivation, establishes submerged plant cultivation sites, carries out modular cultivation of submerged plants, quickly cultivates submerged plant seedlings, adopts underwater robots to carry out automatic planting of submerged plant seedlings, completes the underwater planting task of submerged plants, enters the maintenance stage after the community stabilizes, monitors the recovered submerged plants, collects real-time monitoring data of submerged plants and determines submerged plant characteristic monitoring data after processing, analyzes and predicts the submerged plant characteristic monitoring data, and performs operation and maintenance management of submerged plants according to the prediction results. By establishing a systematic system of submerged plant seedling cultivation, modular expansion, automated and efficient planting, intelligent monitoring and operation and maintenance, submerged plants can be cultivated efficiently and modularly, the planting efficiency and submerged plant survival rate can be improved, and the planting cost can be reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a flow chart of the method for restoring, monitoring, and maintaining submerged plants in ecological restoration according to the present invention; Figure 2 The figure is a flow chart of determining underwater planting points according to the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0019] In order to solve the problems of low efficiency, high cost and low survival rate of submerged plants after planting, please refer to Figure 1-2 , this embodiment provides the following technical solutions: Restoration, monitoring, and maintenance methods for submerged plants in ecological restoration include: Use germination experiment to screen submerged plant planting and cultivation materials; In this embodiment, germination experiments were used to screen submerged plant planting and cultivation materials, including: Based on the differences in plant growth conditions, submerged plants commonly used in ecological restoration were selected as typical representative species, with easy-to-obtain plant seeds, stone buds, dormant buds and broken stems as the main focus; Select environmentally friendly embedding materials suitable for plant cultivation. Environmentally friendly embedding materials should be environmentally friendly, pollution-free, biodegradable, low-cost, easily available, permeable, and have a certain strength. Through germination experiments, the advantages and disadvantages of different cultivation materials are compared, and high-quality cultivation materials that can be used for submerged plant cultivation are screened out.

[0020] Carry out modular cultivation of submerged plants and quickly cultivate submerged plant seedlings; In this embodiment, the rapid cultivation of submerged plant seedlings includes: Select submerged plants with faster rooting from Vallisneria, Potamogeton serrata and Myriophyllum paniculatum; According to the selected submerged plants, the bottom type, water level, light intensity and water temperature conditions are regulated, and inducing hormones are appropriately added. The germination experiment is used to quantify the various environmental indicators for submerged plant cultivation and establish a submerged plant cultivation site; Combined with the selected high-quality cultivation materials, the selected submerged plants are cultivated in a submerged plant cultivation site, so that the submerged plants can be cultivated in a modular manner and submerged plant seedlings can be cultivated quickly.

[0021] It should be noted that in order to germinate seeds more quickly, realize seed recovery in polluted water bodies, and enable them to self-restore the density of submerged plants, a large number of artificial seed studies have been carried out based on different test methods according to the seed forms and germination methods of different submerged plants. By quantitatively adding various types of hormone substances, the rapid germination, sprouting and rooting of seeds are promoted, and a variety of embedding materials are made to enable seeds to resist the influence of adverse environments, enhance the storage, transportation and germination ability of seeds under suitable conditions, and study the optimal germination of different plant seeds. Suitable growth conditions, such as water temperature, water depth, transparency and light conditions. Studies have shown that the optimum temperature for seed germination of submerged plants is generally around 20°C. The germination rate generally increases with increasing temperature, but the germination rate decreases. For example, the germination rate of water chestnuts, giant algae and water chestnuts is the highest at 20°C, but the germination rate is 28°C>20°C>10°C. Light intensity is another important factor affecting the cultivation of submerged plants. Studies have shown that germination can occur when the light intensity in the water reaches 5-10% of the incident light intensity, and the light intensity is 40μmol / m 2 ·s, and also carried out a lot of tissue culture research, using the fixed point addition of nutrient solution, plant fragments or tissue structures to quickly cultivate submerged plants indoors.

[0022] Use underwater robots to automate the planting of submerged plant seedlings; In this embodiment, an underwater robot is used to automatically plant submerged plant seedlings, including: Cameras and AI algorithms are used to identify underwater substrate types. Based on the identified underwater substrate types, underwater planting sites are determined and divided into planting grids. A modular design combining woven grids and planting baskets is used to divide underwater planting sites into multiple grid cells. A four-level grid system is established: water area-zone-cell-point. Multiple grid cells are managed through a combination of physical isolation and digital monitoring. The water quality and bottom quality are detected by sensors to evaluate the submerged plant planting environment. When the submerged plant planting environment is suitable for submerged plant seedlings, the operator sends instructions to the underwater robot through the computer and sends the underwater planting point to the underwater robot; Place submerged plant seedlings into the seedling container of the underwater robot, use GPS and sonar systems to locate the underwater planting point, and the underwater robot will find the underwater planting point according to the planned movement path; The underwater robot uses a robotic arm to dig a hole and places submerged plant seedlings into the hole. It uses the cutting method to plant the seedlings, implants them into the bottom mud, covers them with soil to fix them, and stabilizes the seedlings. This completes the underwater planting task of submerged plants. After the community stabilizes, it enters the maintenance stage.

[0023] It should be noted that the cutting planting method is more conducive to the rapid rooting, establishment and growth of plants than other methods. Although the throwing planting method reduces the impact of wind, waves and water flow on the planted seedlings, the roots cannot effectively break through the wrapped net or non-woven fabric to contact the bottom mud, resulting in a sharp drop in plant survival rate, making it more difficult to grow quickly and unable to guarantee the recovery effect. The sowing method and the sinking bag method are the most efficient planting methods. They use plant seeds, stone buds, dormant buds, etc. with the help of other auxiliary methods to directly spread into the water body. This method is suitable for water bodies with shallow water depth and no wind and wave interference. The germination rate is low, but the plant establishment is more stable. For the cutting planting method, in order to promote the rapid growth of plants, the forward cutting, reverse cutting and horizontal cutting planting methods of different plants were studied and compared. The results showed that horizontal cutting increased the number of adventitious roots and branches. Therefore, when planting cuttings, it is necessary to distinguish the morphological upper and lower ends, and make the contact area with the bottom mud as large as possible, which is conducive to enhancing the establishment and propagation ability.

[0024] It should be noted that the traditional seedling raising method is relatively extensive and the planting cost is 60-150 yuan / m 2 , planting efficiency per person per hour 2-5 m 2 The efficiency of this automated planting method is 3-6 times that of pure manual labor, which can reduce 2-5 man-hours of labor input. The planting cost is about 20-30 yuan / m 2 In addition, most restoration projects have a short construction period and the optimal planting time is limited. Automated mechanical planting can cope with a variety of working conditions and can ensure good planting efficiency and survival rate. It can not only save a lot of costs, but also effectively improve planting efficiency and plant survival rate, reduce rework, and achieve restoration effects faster. It is the best choice at present.

[0025] Specifically, the method of identifying underwater substrate types based on cameras and AI algorithms, and determining underwater planting sites based on the identified underwater substrate types, includes: The camera obtains images of the underwater planting area, and the AI ​​algorithm is used to identify the bottom type of the underwater planting area image to obtain the underwater bottom type, and based on the underwater bottom type, the type of plants cultivated in the underwater planting area is obtained; Obtaining historical planting conditions and historical planting situations of the plant type, and training an artificial intelligence model based on the historical planting conditions and historical planting situations to obtain a planting point allocation model; Obtaining a plurality of frames of underwater planting area images continuously captured by a camera, determining the water depth, water flow velocity and bottom depth of the underwater planting area based on the plurality of frames of underwater planting area images, and obtaining the lighting characteristics of the underwater planting area; The water depth, water flow velocity, bottom depth and light characteristics of the underwater planting area, as well as the planting requirements are input into the planting point allocation model to obtain multiple initial planting point allocation results for the underwater planting area; Obtaining historical growth conditions corresponding to historical planting conditions of the plant type, determining historical planting efficiencies of the historical planting conditions, obtaining historical cost-effectiveness of the historical growth conditions, and establishing an efficiency weight for the historical planting efficiency and a benefit weight for the historical cost-effectiveness based on actual needs; Based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, combined with artificial intelligence, an efficiency-benefit prediction and scoring model is established; Inputting multiple initial planting point allocation results into the efficiency and benefit prediction scoring model to obtain the predicted score value of each initial planting point allocation result; The underwater planting point is determined based on the initial planting point allocation result with the largest predicted score value.

[0026] In this embodiment, the planting requirements are set according to the actual situation, and the actual demand is also pre-set according to the actual situation, which can be achieved by adjusting the model parameters.

[0027] In this embodiment, a higher efficiency benefit prediction score indicates that the actual needs are better met.

[0028] The beneficial effects of the above design scheme are: by obtaining images of underwater planting areas based on cameras, identifying the bottom types of underwater planting area images based on AI algorithms, obtaining the underwater bottom types, and based on the underwater bottom types, obtaining the types of plants cultivated in the underwater planting areas, thereby determining the types of planted plants, and combining the historical planting conditions and historical growth conditions of the planted plant types with artificial intelligence models to determine the planting points and evaluate the efficiency at the planting points. Finally, the initial planting point allocation result with the largest predicted score value is selected to determine the underwater planting point, thereby achieving the optimal determination of the underwater planting point and providing a basis for efficient modular cultivation of submerged plants.

[0029] Specifically, the efficiency and benefit prediction scoring model is established based on historical planting efficiency and its efficiency weight, historical cost-benefit and its benefit weight, combined with artificial intelligence, including: Based on the historical growth conditions corresponding to the historical planting conditions, the historical planting conditions are divided to obtain different planting areas, each of which corresponds to different local growth conditions; Set the efficiency coefficient and profit coefficient of the corresponding planting area based on the local growth situation; Establish efficiency prediction rules and benefit prediction rules for the planting situation to be analyzed based on the efficiency coefficient and the benefit coefficient; The calculation formula of the efficiency prediction rule is as follows:

[0030] in, σ arepresents the planting efficiency of the planting situation to be analyzed, n represents the number of divided areas of the planting situation to be analyzed, τ i represents the area weight of the i-th divided area, M i represents the efficiency coefficient of the historical planting area with the greatest similarity to the i-th divided area, α i It represents the similarity value between the ith divided area and its corresponding historical planting area with the greatest similarity. C represents a constant with a value less than α i , when the i-th divided area and its corresponding historical planting area with the greatest similarity are similar in efficiency upward, Take +, when the efficiency of the i-th divided area and its corresponding historical planting area with the greatest similarity is downward similar, Take -, M0 represents the reference efficiency coefficient; The calculation formula of the benefit prediction rule is as follows:

[0031] in, K a represents the planting efficiency of the planting situation to be analyzed, β i It represents the similarity value between the i-th divided area and its corresponding historical planting area with the greatest similarity. Y i represents the benefit coefficient of the historical planting area with the greatest similarity to the i-th divided area, Z Represents a constant, with a value less than β i , when the i-th divided area and its corresponding historical planting area with the greatest similarity are similar in benefits upward, Take +, when the i-th divided area and its corresponding historical planting area with the greatest similarity are similar in benefits downward, Take -, Y 0 represents the reference benefit coefficient; Based on the efficiency prediction rules and the benefit prediction rules, the planting efficiency and the planting benefit of the planting situation to be tested are obtained; Establish prediction scoring rules based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight; The calculation formula of the prediction scoring rule is as follows:

[0032] Among them, H represents the predicted score value, σ represents the unified historical planting efficiency value, K represents the unified historical cost-effectiveness value, δ0 represents the efficiency weight, ε K represents the benefit weight; Based on efficiency prediction rules, benefit prediction rules and prediction scoring rules, combined with artificial intelligence, an efficiency and benefit prediction scoring model is established.

[0033] In this embodiment, upward efficiency similarity indicates that the efficiency coefficient of the i-th divided area is greater than the efficiency coefficient of the historical planting area with the greatest similarity corresponding to it, and downward efficiency similarity indicates that the efficiency coefficient of the i-th divided area is less than or equal to the efficiency coefficient of the historical planting area with the greatest similarity corresponding to it.

[0034] In this embodiment, upward similarity in efficiency indicates that the efficiency coefficient of the i-th divided area is greater than the efficiency coefficient of the historical planting area with the greatest similarity to it, and downward similarity in efficiency indicates that the efficiency coefficient of the i-th divided area is less than or equal to the efficiency coefficient of the historical planting area with the greatest similarity to it.

[0035] In this embodiment, The smaller the value, the more synchronized the historical planting efficiency and historical cost-effectiveness are, and the higher the corresponding prediction score.

[0036] In this embodiment, the division of the planting conditions to be analyzed is obtained based on the matching between artificial intelligence and the corresponding planting areas in history.

[0037] The beneficial effects of the above design scheme are: by dividing the historical planting conditions based on the historical growth conditions corresponding to the historical planting conditions, different planting areas are obtained, each planting area corresponds to a different local growth condition, and the efficiency coefficient and benefit coefficient of the corresponding planting area are set based on the local growth condition, and efficiency prediction rules and benefit prediction rules for the planting conditions to be tested are established based on the efficiency coefficient and the benefit coefficient, and the planting efficiency and planting benefit of the planting conditions to be tested are obtained based on the efficiency prediction rules and the benefit prediction rules, and based on the historical planting efficiency and its efficiency weight, the historical cost-effectiveness and its benefit weight, a prediction scoring rule is established, and based on the efficiency prediction rule, the benefit prediction rule and the established prediction scoring rule, combined with artificial intelligence, an efficiency and benefit prediction scoring model is established, and based on the prediction calculation of efficiency and benefit and the calculation of prediction score based on artificial intelligence, and the advance division of the planting area is added to ensure the accuracy of the obtained efficiency and benefit prediction scoring model, which provides a basis for determining the optimal underwater planting point.

[0038] Specifically, we will restore submerged plants in ecological restoration, carry out water pollution control and water ecological restoration work, reduce nutrients in water bodies, improve the water environment, restore aquatic plants, and rebuild a healthy ecosystem.

[0039] Monitor the restored submerged macrophytes, collect real-time monitoring data of submerged macrophytes and process it to determine the characteristic monitoring data of submerged macrophytes; In this embodiment, monitoring of the restored submerged macrophytes and collection of real-time monitoring data of the submerged macrophytes include: Based on remote sensing technology and sensors, the community composition, coverage and biomass of underwater submerged plants are monitored and collected in real time to obtain plant growth data; Based on remote sensing technology and sensors, the water temperature, pH and dissolved oxygen in the living environment of underwater submerged plants are monitored and collected in real time to obtain water quality change data; Based on remote sensing technology and sensors, real-time monitoring and collection of changes in fish and plankton in the living environment of underwater submerged plants are carried out to obtain ecological response data; Among them, the real-time monitoring data of submerged plants after the recovery of submerged plants in ecological restoration is determined based on plant growth data, water quality change data and ecological response data.

[0040] In this embodiment, the collected real-time monitoring data of submerged plants is processed, including: Clean the real-time monitoring data of submerged plants, remove noise in the real-time monitoring data of submerged plants, identify and delete duplicate values, missing values ​​and outliers in the real-time monitoring data of submerged plants; Convert the real-time monitoring data of submerged plants, remove the dimensional differences between the real-time monitoring data of submerged plants, and determine the standardized real-time monitoring data of submerged plants; Feature extraction is performed on the real-time monitoring data of submerged plants, feature vectors related to submerged plant monitoring and operation are extracted from the real-time monitoring data of submerged plants, and the characteristic monitoring data of submerged plants is determined.

[0041] It should be noted that by monitoring the restored submerged plants, collecting real-time monitoring data of submerged plants and determining the characteristic monitoring data of submerged plants after processing, it will be convenient to analyze and predict the characteristic monitoring data of submerged plants in the future, and it will be possible to better manage the operation and maintenance of submerged plants and improve the survival rate of submerged plants.

[0042] Analyze and predict the monitoring data of submerged plant characteristics, and carry out operation and maintenance management of submerged plants based on the prediction results.

[0043] In this embodiment, the analysis and prediction of submerged plant characteristic monitoring data includes: Collect historical data on submerged plant growth, and use deep learning technology to train and optimize the deep learning model using this data to determine a submerged plant growth risk prediction model. The submerged plant characteristic monitoring data is input into the submerged plant growth risk prediction model, the submerged plant characteristic monitoring data is analyzed according to the submerged plant growth risk prediction model, and the growth risk behavior of the submerged plants is predicted to determine the submerged plant growth risk prediction results.

[0044] In this embodiment, the operation and maintenance management of submerged plants is performed according to the prediction results, including: When risky growth of submerged plants is predicted, maintenance and control of the submerged plants are carried out, alien species are removed, overcrowded plants are pruned, and the growth environment is optimized. At the same time, the submerged plant restoration plan is dynamically adjusted according to the submerged plant monitoring situation to restore the submerged plants during ecological restoration.

[0045] Specifically, by establishing a systematic system for submerged plant seedling cultivation, modular propagation, automated and efficient planting, and intelligent monitoring and operation and maintenance, submerged plants can be cultivated efficiently and modularly, improving planting efficiency and the survival rate of submerged plants and reducing planting costs.

[0046] It should be noted that, in this document, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that includes a list of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus.

[0047] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.

Claims

1. The method for restoring, monitoring and maintaining submerged plants in ecological restoration is characterized by: include: Screening submerged plant planting and cultivation materials, rapidly cultivating submerged plant seedlings, determining underwater planting sites, and using underwater robots to automatically plant submerged plant seedlings; Among them, based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, combined with artificial intelligence, an efficiency-benefit prediction and scoring model is established; Inputting multiple initial planting point allocation results into the efficiency and benefit prediction scoring model to obtain a predicted score value for each initial planting point allocation result, and determining the underwater planting point based on the initial planting point allocation result with the largest predicted score value; Monitor the restored submerged plants, conduct analysis and prediction based on the monitoring results, and then carry out operation and maintenance management of the submerged plants.

2. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: Identify underwater planting sites, including: The camera obtains images of the underwater planting area, and the AI ​​algorithm is used to identify the bottom type of the underwater planting area image to obtain the underwater bottom type, and based on the underwater bottom type, the type of plants cultivated in the underwater planting area is obtained; Obtaining historical planting conditions and historical planting situations of the plant type, and training an artificial intelligence model based on the historical planting conditions and historical planting situations to obtain a planting point allocation model; Obtaining a plurality of frames of underwater planting area images continuously captured by a camera, determining the water depth, water flow velocity and bottom depth of the underwater planting area based on the plurality of frames of underwater planting area images, and obtaining the lighting characteristics of the underwater planting area; The water depth, water flow velocity, bottom depth and light characteristics of the underwater planting area, as well as the planting requirements are input into the planting point allocation model to obtain multiple initial planting point allocation results for the underwater planting area; Obtaining historical growth conditions corresponding to historical planting conditions of the plant type, determining historical planting efficiencies of the historical planting conditions, obtaining historical cost-effectiveness of the historical growth conditions, and establishing an efficiency weight for the historical planting efficiency and a benefit weight for the historical cost-effectiveness based on actual needs; Based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, combined with artificial intelligence, an efficiency-benefit prediction and scoring model is established; Inputting multiple initial planting point allocation results into the efficiency and benefit prediction scoring model to obtain the predicted score value of each initial planting point allocation result; The underwater planting point is determined based on the initial planting point allocation result with the largest predicted score value.

3. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: Based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight, and combined with artificial intelligence, an efficiency-benefit prediction scoring model is established, including: Based on the historical growth conditions corresponding to the historical planting conditions, the historical planting conditions are divided to obtain different planting areas, each of which corresponds to different local growth conditions; Set the efficiency coefficient and profit coefficient of the corresponding planting area based on the local growth situation; Establishing efficiency prediction rules and benefit prediction rules for the planting conditions to be tested based on the efficiency coefficient and the benefit coefficient; Based on the efficiency prediction rules and the benefit prediction rules, the planting efficiency and the planting benefit of the planting situation to be tested are obtained; Establish prediction scoring rules based on historical planting efficiency and its efficiency weight, historical cost-effectiveness and its benefit weight; Based on efficiency prediction rules, benefit prediction rules and prediction scoring rules, combined with artificial intelligence, an efficiency and benefit prediction scoring model is established.

4. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: The use of underwater robots to automatically plant submerged plant seedlings includes: Divide the planting grid according to the underwater planting site, and adopt a modular design combining woven grids and planting baskets to divide the underwater planting site into multiple grid units. Establish a four-level grid of water area-division-unit-point, and manage multiple grid units through a combination of physical isolation and digital monitoring. The water quality and bottom quality are detected by sensors to evaluate the submerged plant planting environment. When the submerged plant planting environment is suitable for submerged plant seedlings, the operator sends instructions to the underwater robot through the computer and sends the underwater planting point to the underwater robot; Place submerged plant seedlings into the seedling container of the underwater robot, use GPS and sonar systems to locate the underwater planting point, and the underwater robot will find the underwater planting point according to the planned movement path; The underwater robot uses a robotic arm to dig a hole and places submerged plant seedlings into the hole. It uses the cutting method to plant the seedlings, implants them into the bottom mud, and covers them with soil to fix them, completing the underwater planting task of submerged plants. After the community stabilizes, it enters the maintenance stage.

5. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: Screening of submerged plant planting and cultivation materials, including: Based on the differences in plant growth conditions, submerged plants commonly used in ecological restoration were selected as typical representative species, with easy-to-obtain plant seeds, stone buds, dormant buds and broken stems as the main focus; Choose environmentally friendly embedding materials suitable for plant cultivation; Through germination experiments, the advantages and disadvantages of different cultivation materials are compared, and high-quality cultivation materials that can be used for submerged plant cultivation are screened out.

6. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: Rapid cultivation of submerged plant seedlings, including: Select submerged plants with faster rooting from Vallisneria, Potamogeton serrata and Myriophyllum paniculatum; According to the selected submerged plants, the bottom type, water level, light intensity and water temperature conditions are regulated, and inducing hormones are appropriately added. The germination experiment is used to quantify the various environmental indicators for submerged plant cultivation and establish a submerged plant cultivation site; Combined with the selected high-quality cultivation materials, the selected submerged plants are cultivated in a submerged plant cultivation site, so that the submerged plants can be cultivated in a modular manner and submerged plant seedlings can be cultivated quickly.

7. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: Monitoring of restored submerged plants, including: Based on remote sensing technology and sensors, the community composition, coverage and biomass of underwater submerged plants are monitored and collected in real time to obtain plant growth data; Based on remote sensing technology and sensors, the water temperature, pH and dissolved oxygen in the living environment of underwater submerged plants are monitored and collected in real time to obtain water quality change data; Based on remote sensing technology and sensors, real-time monitoring and collection of changes in fish and plankton in the living environment of underwater submerged plants are carried out to obtain ecological response data; Among them, the real-time monitoring data of submerged plants after the recovery of submerged plants in ecological restoration is determined based on plant growth data, water quality change data and ecological response data.

8. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 7, wherein: Analysis and prediction based on monitoring results, including: Clean the real-time monitoring data of submerged plants, remove noise in the real-time monitoring data of submerged plants, identify and delete duplicate values, missing values ​​and outliers in the real-time monitoring data of submerged plants; Convert the real-time monitoring data of submerged plants, remove the dimensional differences between the real-time monitoring data of submerged plants, and determine the standardized real-time monitoring data of submerged plants; Feature extraction is performed on the real-time monitoring data of submerged plants, feature vectors related to submerged plant monitoring and operation are extracted from the real-time monitoring data of submerged plants, and the characteristic monitoring data of submerged plants is determined.

9. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 8, characterized in that: Analysis and prediction based on monitoring results also include: Collect historical data on submerged plant growth, and use deep learning technology to train and optimize the deep learning model using this data to determine a submerged plant growth risk prediction model. The submerged plant characteristic monitoring data is input into the submerged plant growth risk prediction model, the submerged plant characteristic monitoring data is analyzed according to the submerged plant growth risk prediction model, and the growth risk behavior of the submerged plants is predicted to determine the submerged plant growth risk prediction results.

10. The method for restoring, monitoring and maintaining submerged plants in ecological restoration according to claim 1, wherein: Operation and maintenance of submerged plants, including: When risky growth of submerged plants is predicted, maintenance and control of the submerged plants are carried out, alien species are removed, overcrowded plants are pruned, and the growth environment is optimized. At the same time, the submerged plant restoration plan is dynamically adjusted according to the submerged plant monitoring situation to restore the submerged plants during ecological restoration.

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