Collaborative management and control system for rural environment detection and environment evaluation

Abstract

The invention relates to the field of environment management and control, in particular to a rural environment detection and environment evaluation collaborative management and control system which is provided with a plurality of planting holes arranged at equal intervals, and for a single planting hole, the system comprises a shooting module used for shooting surface vegetation of the planting hole and generating corresponding vegetation information, and a soil locking module used for intercepting lost soil and generating corresponding vegetation information. The system comprises an acquisition module used for filtering lost soil, forming corresponding filtered soil and obtaining loss information, a learning module used for fitting vegetation information and loss information, generating and preprocessing corresponding fitting data, and selecting a plurality of index characteristics of preprocessed data for learning, and a collaboration module used for carrying out collaboration on the plurality of index characteristics of the preprocessed data. According to the system, loss of water in soil is prevented, a water storage effect can be achieved, the survival rate of vegetation is increased, the precision of environment evaluation and management and control is improved, and the system is of great significance to improvement of the rural environment.

Description

Technical Field

[0001] The present invention relates to the field of environmental control, and in particular to a rural environmental detection and environmental evaluation collaborative control system. Background Art

[0002] Soil erosion can lead to loss of soil fertility and thinning of the soil layer, which in turn affects land productivity and the stability of the ecosystem. Preventing soil erosion in rural areas is of far-reaching and important significance. It not only concerns the health and stability of the rural ecological environment, but also directly affects the sustainability of agricultural production, the development of the rural economy and the overall well-being of society.

[0003] Chinese patent application publication number: CN116332365A discloses an ecological water environment management system for sandy riverbeds in mountainous rivers, including an ecological green island set up in the river center area, an ecological buffer zone set up near the river bank, an ecological slope protection set up near the main river channel, and an ecological interception ditch set up along the direction of water flow; the green space of the ecological buffer zone is planted with dwarf loosestrife, yellow iris, pennisetum, and ground juniper in sequence from the water side to the river beach; two retention sedimentation zones are set in the middle of the dwarf loosestrife, and are set up in sequence from the water side as volcanic rock retention sedimentation zones and zeolite retention sedimentation zones. The water environment management system of the invention can effectively resist river scouring and soil erosion caused by large longitudinal slopes; it can coordinate water resources, improve water quality, and reduce non-point source pollution; the setting of the water environment management system is an effective measure to reduce nitrogen and phosphorus loads and can improve the rural living environment.

[0004] Chinese patent application publication number: CN113030969A discloses a method and system for monitoring deformation and soil erosion of open-pit mine dumps, the method comprising: obtaining multi-temporal synthetic aperture radar image data of the dump to obtain the total settlement distribution of the dump; dividing the dump into several areas according to the stockpile height according to the high-precision digital elevation model of the dump; combining the total settlement distribution of the dump with the divided areas, statistically calculating the settlement distribution of the area corresponding to each stockpile height, taking the minimum value in each area to obtain the consolidation settlement of the corresponding area; establishing a regression relationship between the stockpile height and the consolidation settlement of the dump; inverting the consolidation settlement distribution of the dump according to the regression relationship; and obtaining the surface erosion distribution caused by soil erosion in the dump according to the total settlement distribution and the consolidation settlement distribution of the dump. The scheme in this application can monitor and grasp the non-uniform deformation law and soil erosion development law of the open-pit mine dump respectively, and accurately evaluate its environmental impact degree, scope and long-term environmental pollution risk.

[0005] However, the above method has the following problems: it is unable to detect and intelligently control the environment in real time, which results in an inability to effectively adjust a single planting area when soil erosion is serious, thereby reducing coordination efficiency. Summary of the invention

[0006] To this end, the present invention provides a rural environmental monitoring and environmental evaluation collaborative management and control system to overcome the problem in the prior art that the environment cannot be monitored and intelligently controlled in real time, resulting in an inability to effectively adjust a single planting area when soil and water loss is serious, thereby reducing collaborative efficiency.

[0007] To achieve the above-mentioned purpose, the present invention provides a rural environment detection and environmental assessment collaborative management and control system, wherein the system is provided with a plurality of equally spaced planting holes, and for a single planting hole, the system comprises:

[0008] A shooting module, which is used to shoot the surface vegetation of the planting hole and generate corresponding vegetation information;

[0009] A soil locking module, which is used to intercept the lost soil and retain the lost soil in the soil locking net;

[0010] A collection module, which is connected to the soil locking module, and is used to filter the lost soil to form corresponding filtered soil, and obtain loss information of the filtered soil;

[0011] A learning module, connected to the shooting module and the acquisition module, for fitting the vegetation information and the loss information to generate corresponding fitting data, preprocessing the fitting data to generate corresponding preprocessing data, selecting several indicator features of the preprocessing data, and learning the preprocessing data according to the indicator features;

[0012] A collaboration module, connected to the learning module, for receiving the learning result of the learning module and adjusting the planting hole;

[0013] Wherein, the loss information is the water content in the lost soil;

[0014] The fitting data includes vegetation fitting data corresponding to the vegetation information and loss fitting data corresponding to the loss information;

[0015] The learning module is provided with a vegetation learning model and a loss learning model, and the loss learning model is generated by training according to the preprocessed data.

[0016] Furthermore, the shooting module is provided with a single camera, which is arranged above a single planting hole, to shoot the surface vegetation in real time, and convert the vegetation image into the vegetation information for output.

[0017] The camera is provided with a fixed time duration, which is used to poll whether the vegetation information is output at fixed time intervals.

[0018] Furthermore, four downward-inclined protection holes are drilled at equal intervals on the side wall of the soil-locking module, and the protection holes are filled with mud to fix the soil-locking net at a preset height, so that the soil-locking net intercepts the lost soil.

[0019] The preset height corresponds to the lowest position of the main trunk of the vegetation root system.

[0020] Furthermore, the filter screen in the collection module filters the lost soil, and the filtered soil automatically falls off from the filter screen to form corresponding filtered soil, and the loss information in the filtered soil is monitored.

[0021] Wherein, the filter screen is used to filter large particles of impurities in the lost soil.

[0022] Furthermore, the learning module fits the vegetation information and the loss information, and generates a plurality of fitting data with a sampling rate of a standard sampling rate.

[0023] Wherein, the fitting is to segment the vegetation information and the loss information according to the standard sampling rate;

[0024] The standard sampling rate is a sampling rate that can be recognized by the vegetation learning model and the loss learning model, and for a single sampling, the corresponding standard sampling rate is a single sampling rate.

[0025] Furthermore, the preprocessor preprocesses the vegetation fitting data to generate corresponding vegetation data, the vegetation learning model selects several indicator features of the vegetation data, uses the vegetation learning model to learn the vegetation data, and generates a loss threshold corresponding to the surface vegetation.

[0026] The index characteristics of the vegetation data include water content, weather conditions, terrain height and / or vegetation type;

[0027] The loss threshold is the maximum value of the water loss content corresponding to the surface vegetation.

[0028] Furthermore, the preprocessor preprocesses the churn fitting data to generate corresponding churn data, the churn learning model selects several indicator features of the churn data, uses the churn learning model to learn the churn data, and generates a churn coordination graph.

[0029] The churn learning model learns the churn data to convert the churn data into the churn coordination graph, extracts several indicator features from the churn coordination graph, and annotates the churn coordination graph based on the indicator features;

[0030] The indicator characteristics of the loss data include weather conditions, monitoring time and / or terrain height.

[0031] Furthermore, the coordination module receives the loss coordination diagram, and the calculator calculates the water loss content corresponding to each planting hole in real time.

[0032] Furthermore, the water loss content is compared with a loss threshold, and when the water loss content is less than the loss threshold, the collaborative module does not make any adjustment to the planting hole.

[0033] Furthermore, when the water loss content is greater than the loss threshold, the collaborative module configures the elements required for vegetation growth into a nutrient solution to irrigate the planting hole.

[0034] Compared with the prior art, the present invention is provided with a number of planting holes arranged at equal intervals. For a single planting hole, the present invention includes: a shooting module for shooting the surface vegetation of the planting hole and generating corresponding vegetation information, a soil locking module for intercepting the lost soil and retaining it in the soil locking net, a collection module for filtering the lost soil to form the corresponding filtered soil and obtain the loss information, a learning module for fitting the vegetation information and the loss information, generating the corresponding fitting data and performing preprocessing, and selecting several indicator features of the preprocessed data for learning, and a collaborative module for receiving the learning results of the learning module and adjusting the planting hole. The present invention prevents the loss of water in the soil, can play a role in water storage, increases the survival rate of vegetation, improves the accuracy of environmental evaluation and control, and plays an important role in improving the rural environment.

[0035] Furthermore, by setting up a shooting module to shoot the surface vegetation, the loss threshold corresponding to the specific vegetation can be obtained, thereby improving the accuracy of environmental assessment and control.

[0036] Furthermore, by providing a soil locking net in the soil locking module, the lost soil can be intercepted, thereby ensuring the real-time collection of the lost soil and improving the accuracy of moisture monitoring in the lost soil.

[0037] Furthermore, by setting up a filter screen, large particles of impurities in the lost soil can be filtered out, avoiding errors in the learning results caused by large particles of impurities and improving the accuracy of the system's environmental detection.

[0038] Furthermore, the fitting data is fitted and preprocessed through the learning module to obtain the corresponding preprocessed data, so that the effective features of the preprocessed data can be quickly selected, which facilitates the learning of the preprocessed data by the vegetation learning model and the loss learning model, and further improves the efficiency of the system's collaborative work with the environment.

[0039] Furthermore, by obtaining the loss threshold through the vegetation learning model and making corresponding adjustment measures for the corresponding planting holes, it can play a role in water storage, prevent water loss in the soil, increase the survival rate of vegetation, and further improve the rural environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a structural schematic diagram of a single planting hole in a rural environment detection and environmental assessment collaborative management and control system of the present invention;

[0041] Figure 2 A schematic diagram of a shooting area of ​​a shooting module of the present invention;

[0042] Figure 3 This is a schematic diagram of the structure of the soil locking module of the present invention;

[0043] Figure 4 This is a schematic diagram of the fixing position of the soil locking net of the present invention;

[0044] Among them: 1. Main root trunk; 2. Planting hole; 3. Soil locking net; 4. Shooting area; 5. Other vegetation; 6. Protection hole. DETAILED DESCRIPTION

[0045] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0046] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0047] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0048] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0049] See also Figure 1 As shown, it is a structural schematic diagram of a single planting hole in a rural environment detection and environmental assessment collaborative management and control system of the present invention, including:

[0050] A shooting module is used to shoot the surface vegetation of the planting hole and generate corresponding vegetation information;

[0051] A soil locking module, which is used to intercept the lost soil and retain the lost soil in the soil locking net;

[0052] A collection module, which is connected to the soil locking module, is used to filter the lost soil to form corresponding filtered soil and obtain the loss information of the filtered soil;

[0053] A learning module, which is connected to the shooting module and the acquisition module, is used to fit vegetation information and loss information, generate corresponding fitting data, pre-process the fitting data, generate corresponding pre-processed data, select several indicator features of the pre-processed data, and learn the pre-processed data according to the indicator features;

[0054] A collaboration module, which is connected to the learning module, is used to receive the learning result of the learning module and adjust the planting hole;

[0055] Among them, the loss information is the water content in the lost soil;

[0056] The fitting data includes vegetation fitting data corresponding to the vegetation information and loss fitting data corresponding to the loss information;

[0057] The learning module is provided with a vegetation learning model and a loss learning model, and the loss learning model is generated by training based on the preprocessed data.

[0058] A number of equally spaced planting holes are provided, and for a single planting hole, the system includes: a shooting module for shooting the surface vegetation of the planting hole and generating corresponding vegetation information, a soil locking module for intercepting the lost soil and retaining it in the soil locking net, a collection module for filtering the lost soil to form corresponding filtered soil and obtain loss information, a learning module for fitting vegetation information and loss information, generating corresponding fitting data and performing preprocessing, and selecting several indicator features of the preprocessed data for learning, and a collaborative module for receiving the learning results of the learning module and adjusting the planting hole. The present invention prevents the loss of water in the soil, can play a role in water storage, increases the survival rate of vegetation, improves the accuracy of environmental evaluation and control, and plays an important role in improving the rural environment.

[0059] See also Figure 2As shown, it is a schematic diagram of the shooting area of ​​the shooting module of the present invention, wherein a single camera is provided in the shooting area 4, and the camera is arranged above the root trunk 1, and the surface vegetation is photographed in real time, and other vegetation 5 that does not belong to the root trunk 1 is filtered to form a vegetation image, and the vegetation image is converted into vegetation information for output.

[0060] Among them, the camera is set with a fixed time length, which is used to poll whether the vegetation information is output at fixed intervals.

[0061] By setting up a shooting module to shoot the surface vegetation, the loss threshold corresponding to the specific vegetation can be obtained, thereby improving the accuracy of environmental assessment and control.

[0062] See also Figure 3 As shown, it is a schematic diagram of the structure of the soil locking module of the present invention, wherein four downward-inclined protective holes 6 are drilled at equal intervals on the side wall of the planting hole 2, and the protective holes 6 are filled with mud to fix the soil locking net 3 at a preset height, and the soil locking net 3 intercepts the lost soil.

[0063] See also Figure 4 As shown, it is a schematic diagram of the fixed position of the soil-locking net of the present invention. The root trunk 1 is placed in the planting hole 2, and the preset height of the soil-locking net 3 should not be higher than the lowest position of the root trunk 1.

[0064] By setting a soil locking net in the soil locking module, the lost soil can be intercepted, ensuring the real-time collection of the lost soil and improving the accuracy of moisture monitoring in the lost soil.

[0065] Specifically, the filter screen in the collection module filters the lost soil, and the filtered soil automatically falls off the filter screen to form the corresponding filtered soil, and the loss information in the filtered soil is monitored.

[0066] Among them, the filter screen is used to filter out large particles of impurities in the lost soil.

[0067] By setting up a filter screen, large particles of impurities in the lost soil can be filtered out, avoiding errors in the learning results caused by large particles of impurities and improving the accuracy of the system's environmental detection.

[0068] Specifically, the learning module fits the vegetation information and the loss information, and generates a number of fitting data with a sampling rate of the standard sampling rate.

[0069] Among them, fitting is to segment the vegetation information and loss information according to the standard sampling rate;

[0070] The standard sampling rate is a sampling rate that can be recognized by the vegetation learning model and the loss learning model, and for a single sampling, the corresponding standard sampling rate is a single sampling rate.

[0071] In a specific implementation, the preferred standard sampling rate is set to 10 per second, and the learning result of the learning module is the most accurate.

[0072] Specifically, the preprocessor preprocesses the vegetation fitting data to generate corresponding vegetation data. The vegetation learning model selects several indicator features of the vegetation data, uses the vegetation learning model to learn the vegetation data, and generates a loss threshold corresponding to the surface vegetation.

[0073] Among them, the indicator characteristics of vegetation data include water content, weather conditions, terrain height and / or vegetation type;

[0074] The loss threshold is the maximum value of the water loss content corresponding to the surface vegetation.

[0075] Embodiment 1:

[0076] For a certain planting hole, the shooting module shoots the surface vegetation and converts it into vegetation information. The indicator features selected by the vegetation learning model are: "water content: 15%, weather conditions: sunny, terrain: 0m, vegetation type: poplar", and the loss threshold of the generated surface vegetation is 5%.

[0077] By obtaining the loss threshold through the vegetation learning model and making corresponding adjustment measures for the corresponding planting holes, it can play a role in water storage, prevent water loss in the soil, increase the survival rate of vegetation, and further improve the rural environment.

[0078] Specifically, the preprocessor preprocesses the churn fitting data to generate corresponding churn data. The churn learning model selects several indicator features of the churn data, uses the churn learning model to learn the churn data, and generates a churn coordination graph.

[0079] The churn learning model learns the churn data by converting the churn data into a churn synergy graph, extracts several indicator features from the churn synergy graph, and annotates the churn synergy graph based on the indicator features;

[0080] Indicator characteristics of loss data include weather conditions, monitoring time and / or terrain elevation.

[0081] The fitting data is fitted and preprocessed through the learning module to obtain the corresponding preprocessed data, so that the effective features of the preprocessed data can be quickly selected, which facilitates the learning of the preprocessed data by the vegetation learning model and the loss learning model, and further improves the efficiency of the system's collaborative work with the environment.

[0082] Specifically, the coordination module receives the loss coordination diagram, and the calculator calculates the real-time corresponding water loss content of various planting holes.

[0083] Specifically, the water loss content is compared with the loss threshold, and when the water loss content is less than the loss threshold, the collaborative module does not make adjustments to the planting hole.

[0084] Embodiment 2:

[0085] The loss threshold is set to 5%. If the calculator calculates that the corresponding water loss content in the loss coordination diagram of planting hole A is 4% in real time, and 4% is less than the loss threshold of 5%, the coordination module will not make any adjustment to planting hole A.

[0086] Specifically, when the water loss content is greater than the loss threshold, the collaborative module configures the elements required for vegetation growth into a nutrient solution to irrigate the planting hole.

[0087] Embodiment 3:

[0088] The loss threshold is set to 5%. If the calculator calculates that the corresponding water loss content in the loss coordination diagram of planting hole B is 10%, and 10% is greater than the loss threshold of 5%, the coordination module will configure the elements nitrogen, phosphorus, and potassium required for vegetation growth into a nutrient solution in a ratio of 3:1:1 to irrigate the planting hole.

[0089] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0090] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A rural environmental detection and environmental assessment collaborative management and control system, characterized in that: The system is provided with a plurality of planting holes arranged at equal intervals, and for a single planting hole, it includes: A shooting module, which is used to shoot the surface vegetation of the planting hole and generate corresponding vegetation information; A soil locking module, which is used to intercept the lost soil and retain the lost soil in the soil locking net; A collection module, which is connected to the soil locking module, and is used to filter the lost soil to form corresponding filtered soil, and obtain loss information of the filtered soil; A learning module, connected to the shooting module and the acquisition module, for fitting the vegetation information and the loss information to generate corresponding fitting data, preprocessing the fitting data to generate corresponding preprocessing data, selecting several indicator features of the preprocessing data, and learning the preprocessing data according to the indicator features; A collaboration module, connected to the learning module, for receiving the learning result of the learning module and adjusting the planting hole; Wherein, the loss information is the water content in the lost soil; The fitting data includes vegetation fitting data corresponding to the vegetation information and loss fitting data corresponding to the loss information; The learning module is provided with a vegetation learning model and a loss learning model, and the loss learning model is generated by training according to the preprocessed data.

2. The rural environmental detection and environmental assessment collaborative management and control system according to claim 1 is characterized in that: The shooting module is provided with a single camera, which is arranged above a single planting hole, to shoot the surface vegetation in real time, and convert the vegetation image into the vegetation information for output. The camera is provided with a fixed time duration, which is used to poll whether the vegetation information is output at fixed time intervals.

3. The rural environmental detection and environmental assessment collaborative management and control system according to claim 2 is characterized in that: Four downward-inclined protective holes are drilled at equal intervals on the side wall of the soil-locking module, and the protective holes are filled with mud to fix the soil-locking net at a preset height. The soil-locking net intercepts the lost soil. The preset height corresponds to the lowest position of the main trunk of the vegetation root system.

4. The rural environmental detection and environmental assessment collaborative management and control system according to claim 3 is characterized in that: The filter screen in the collection module filters the lost soil, and the filtered soil automatically falls off from the filter screen to form corresponding filtered soil, and the loss information in the filtered soil is monitored. Wherein, the filter screen is used to filter large particles of impurities in the lost soil.

5. The rural environment detection and environmental assessment collaborative management and control system according to claim 4 is characterized in that: The learning module fits the vegetation information and the loss information and generates a plurality of fitting data with a sampling rate of a standard sampling rate. Wherein, the fitting is to segment the vegetation information and the loss information according to the standard sampling rate; The standard sampling rate is a sampling rate that can be recognized by the vegetation learning model and the loss learning model, and for a single sampling, the corresponding standard sampling rate is a single sampling rate.

6. The rural environment detection and environmental assessment collaborative management and control system according to claim 5 is characterized in that: The preprocessor preprocesses the vegetation fitting data to generate corresponding vegetation data, the vegetation learning model selects several indicator features of the vegetation data, uses the vegetation learning model to learn the vegetation data, and generates a loss threshold corresponding to the surface vegetation. The index characteristics of the vegetation data include water content, weather conditions, terrain height and / or vegetation type; The loss threshold is the maximum value of the water loss content corresponding to the surface vegetation.

7. The rural environment detection and environmental assessment collaborative management and control system according to claim 6 is characterized in that: The preprocessor preprocesses the churn fitting data to generate corresponding churn data, the churn learning model selects several indicator features of the churn data, uses the churn learning model to learn the churn data, and generates a churn coordination graph, The churn learning model learns the churn data to convert the churn data into the churn coordination graph, extracts several indicator features from the churn coordination graph, and annotates the churn coordination graph based on the indicator features; The indicator characteristics of the loss data include weather conditions, monitoring time and / or terrain height.

8. The rural environment detection and environmental assessment collaborative management and control system according to claim 7 is characterized in that: The coordination module receives the loss coordination diagram, and the calculator calculates the real-time corresponding water loss content of each planting hole.

9. The rural environment detection and environmental assessment collaborative management and control system according to claim 8 is characterized in that: The water loss content is compared with a loss threshold, and when the water loss content is less than the loss threshold, the collaborative module does not make any adjustment to the planting hole.

10. The rural environment detection and environmental assessment collaborative management and control system according to claim 9 is characterized in that: When the water loss content is greater than the loss threshold, the collaborative module configures the elements required for vegetation growth into a nutrient solution to irrigate the planting hole.

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