An online supervision method for land consolidation

Abstract

The present invention discloses an online supervision method for land consolidation, the method comprising: obtaining a land consolidation plan, the land consolidation plan comprising a number of lands to be consolidated, original soil data of each land to be consolidated, current soil grade, target soil grade and consolidation range; confirming a number of supervision nodes based on the current soil grade, target soil grade and meteorological data of the land to be consolidated; obtaining node soil data of the land to be consolidated at each supervision node, and obtaining soil consolidation progress based on the node soil data; generating reminder information based on the soil consolidation progress of the land to be consolidated and sending it to a management terminal. The method solves the technical problem of the difficulty of supervision in the land consolidation process in the prior art.

Description

Technical Field

[0001] The invention relates to the technical field of land consolidation management, and in particular to an online supervision method for land consolidation. Background Art

[0002] In the concept of balance between cultivated land inflow and outflow, if cultivated land is converted into other agricultural land such as forest land, grassland, orchard and land for construction of agricultural facilities, it should be supplemented by the same quantity and quality of cultivated land that can be used in a long-term and stable manner through the overall improvement of forest land, grassland, orchard and land for construction of agricultural facilities into cultivated land.

[0003] Land such as forests, grasslands and gardens need to be rehabilitated in a targeted manner before they can be restored to arable land for growing crops. However, land remediation involves many types of land and the remediation process is complicated, requiring a lot of manpower to supervise and manage the land remediation process. When the area of ​​land to be rehabilitated is large and wide, the difficulty of supervision increases further.

[0004] It can be seen from this that there are technical problems in the existing technology that make supervision during land reclamation difficult. Summary of the invention

[0005] The purpose of the present invention is to provide an online supervision method for land consolidation, which solves the technical problem of great difficulty in supervision during land consolidation in the prior art.

[0006] The present invention provides an online supervision method for land consolidation, the method comprising:

[0007] Obtaining a land remediation plan, wherein the land remediation plan includes a number of lands to be remediated, original soil data of each land to be remediated, current soil grade, target soil grade, and remediation scope;

[0008] Based on the current soil grade, target soil grade and meteorological data of the land to be remediated, several monitoring nodes are identified;

[0009] Obtain node soil data of the land to be remediated at each supervision node, and obtain soil remediation progress based on the node soil data;

[0010] Based on the soil remediation progress of the land to be remediated, a reminder message is generated and sent to the management terminal.

[0011] Furthermore, based on the current soil grade, target soil grade and meteorological data of the land to be remediated, several regulatory nodes are identified, including:

[0012] S21: Based on the current soil grade and meteorological data of the land to be rehabilitated, obtain the theoretical rehabilitating time of the land to be rehabilitated to the next soil grade;

[0013] S22: repeat step S21 until the next soil level is the target soil level;

[0014] S23: Based on the theoretical remediation time between adjacent soil grades of the land to be remediated, the time nodes corresponding to each soil grade in the process of the land to be remediated from the current soil grade to the target soil grade are obtained as supervision nodes, and each soil grade is the theoretical soil grade of the corresponding supervision node.

[0015] Furthermore, before each supervision node obtains the node soil data of the land to be remediated and obtains the soil remediation progress based on the node soil data, it also includes:

[0016] Based on the remediation scope of the land to be remediated, a number of detection locations corresponding to the land to be remediated are determined, and a number of soil sensors are set at each detection location;

[0017] Each soil sensor collects corresponding soil data at each supervision node as node soil data of the corresponding supervision node; the node soil data includes several items of soil sensor data; the several soil sensors include pH sensors, temperature sensors, humidity sensors, heavy metal sensors and soil nutrient sensors.

[0018] Furthermore, node soil data of the land to be remediated is obtained at each supervision node, and soil remediation progress is obtained based on the node soil data, including:

[0019] Based on the node soil data of the land to be remediated at the current supervision node, confirm the actual soil grade of the land to be remediated at the current supervision node;

[0020] Compare the actual soil level at the current monitoring node with the theoretical soil level to obtain the soil remediation progress; the soil remediation progress includes advanced, lagging and normal;

[0021] If the actual soil grade is higher than the theoretical soil grade, the soil remediation progress is ahead of schedule; if the actual soil grade is lower than the theoretical soil grade, the soil remediation progress is behind schedule; if the actual soil grade is equal to the theoretical soil grade, the soil remediation progress is normal.

[0022] Furthermore, based on the node soil data of the land to be remediated at the current supervision node, the actual soil grade of the land to be remediated at the current supervision node is confirmed, including:

[0023] Acquire a soil grade relationship database, wherein the soil grade relationship database includes a plurality of soil sensor data, soil grades, and mapping relationships between the plurality of soil sensor data and soil grades;

[0024] The neural network model is trained through the soil grade relationship database to obtain the soil analysis model;

[0025] The node soil data of the current supervision node is input into the soil analysis model to obtain the actual soil grade of the land to be rehabilitated at the current supervision node.

[0026] Furthermore, based on the soil remediation progress of the land to be remediated, a reminder message is generated and sent to the management terminal, including:

[0027] When the soil remediation progress of the land to be remediated is lagging behind, a remediation strategy is generated based on the soil data of the current node as a reminder information;

[0028] When the soil remediation progress of a piece of land to be remediated is ahead of schedule and the actual soil grade is not lower than the target soil grade, a stop remediation signal is generated as a reminder message. After the management terminal receives the stop remediation signal and verifies it, it confirms that the land to be remediated is remediated land.

[0029] Further, obtaining land remediation plans includes:

[0030] Based on the land balance requirement, a number of constraint conditions are obtained; the land balance requirement includes a number of outflow lands, the soil grade and area of ​​each outflow land;

[0031] Based on the current data of the land to be flowed in and several constraints, several candidate plans are randomly obtained as the initial population; the data of the land to be flowed in includes the current soil grade, remediation potential and area of ​​the land to be flowed in; the candidate plans include the original soil data, current soil grade, target soil grade and area of ​​each land to be flowed in;

[0032] Based on the preset fitness function, several candidate schemes of the initial population are iteratively optimized until the preset iteration conditions are met to obtain the land consolidation scheme.

[0033] Furthermore, the several constraints include:

[0034] The soil grade of each land to be flowed into after remediation is not higher than the remediation potential and the soil grade span is within the set span;

[0035] The total area of ​​the land to be flowed into corresponding to each soil grade after remediation shall not be less than the preset percentage of the total area of ​​the land to be flowed out;

[0036] The total area of ​​the land to be flowed into corresponding to all soil levels after remediation is greater than or equal to the total area of ​​the land to be flowed out;

[0037] The first area change of a number of lands to be flowed in whose soil grade after remediation is higher than the set grade is greater than or equal to the second area change of a number of lands to be flowed in whose soil grade is not higher than the set grade.

[0038] Furthermore, based on a preset fitness function, several candidate solutions of the initial population are iteratively optimized until a preset iteration condition is met to obtain a land consolidation solution, including:

[0039] SS31: Based on the preset fitness function, calculate the fitness of each candidate solution in the initial population;

[0040] SS32: Based on the fitness of each candidate solution, several target candidate solutions are identified;

[0041] SS33: mutate and crossover several target candidate solutions, obtain several genetic solutions as candidate solutions in the next generation population and calculate the fitness;

[0042] SS34: Repeat steps SS32 to SS33 until a preset iteration condition is met, and the genetic scheme with the highest fitness in the contemporary population is obtained as the land reclamation scheme; the preset iteration condition includes that the number of iterations is greater than or equal to the preset number of iterations, or the fitness is greater than or equal to the set fitness.

[0043] Furthermore, in step SS33, before taking several genetic schemes as candidate schemes in the next generation population, the method further includes:

[0044] Based on several constraints, several genetic schemes are screened, and the genetic schemes that meet the constraints are used as candidates in the next generation population.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] In the present invention, by analyzing the current soil grade, target soil grade and meteorological data, several supervision nodes of the land to be remediated are obtained, so that soil data can be collected and analyzed in time during the land remediation process, avoiding inaccurate analysis results caused by disorderly data collection. By analyzing the node soil data corresponding to each supervision node, the progress of soil remediation is obtained, and corresponding reminder information is further generated according to the progress of soil remediation and sent to the management terminal. So that the management terminal can timely obtain the progress of land remediation of each land to be mediated and take corresponding measures, so that the difficulty of land remediation management of multiple lands to be mediated at the same time is reduced. The technical problem of high difficulty in supervision during land remediation in the prior art is solved. . BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A method step diagram of an online supervision method for land reclamation provided in an embodiment of the present invention.

[0048] Figure 2 A step diagram of a method for obtaining a supervisory node provided in an embodiment of the present invention.

[0049] Figure 3 A method step diagram for obtaining a land reclamation plan provided in an embodiment of the present invention.

[0050] Figure 4 Shown Figure 3 An exemplary flow chart of step SS3 in FIG. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0052] like Figure 1 As shown, an online supervision method for land consolidation includes:

[0053] S1: Obtain a land remediation plan, which includes a number of lands to be remediated, original soil data of each land to be remediated, current soil grade, target soil grade and remediation scope;

[0054] In this embodiment, the soil grade is divided into 10 grades from high to low, namely, grade A, grade B, grade C, ..., grade J. In the process of land consolidation, it is necessary to use corresponding consolidation means to consolidate the land with lower soil grade into land with higher soil grade. Since the boundaries of the land to be consolidated in some areas are not clear, it is easy to have insufficient or missed consolidation during the consolidation process. Therefore, the land consolidation plan also includes the consolidation scope.

[0055] In this embodiment, the actual soil grade of the land to be remediated after remediation is not lower than the corresponding target soil grade. If the actual soil grade is lower than the corresponding target soil grade, the land to be remediated is prohibited from flowing in.

[0056] The land consolidation plan includes a number of lands to be consolidated distributed in various locations. The current soil grade at various locations of the same piece of land to be consolidated is the same, and the actual soil grade at various locations after consolidation is the same.

[0057] S2: Based on the current soil grade, target soil grade and meteorological data of the land to be remediated, confirm several supervision nodes;

[0058] In this embodiment, several supervision nodes are set in the process of improving the land to be improved from the current soil grade to the target soil grade to supervise the improvement progress of the land to be improved, so as to obtain the improvement status of the land to be improved in time.

[0059] Meteorological data is an important factor affecting the progress of land reclamation. For example, the progress of land reclamation in a region in winter is slower than that in summer. In this embodiment, the meteorological data includes the temperature, wind speed, rainfall, etc. of the area where the land to be renovated is located.

[0060] S3: Obtain node soil data of the land to be remediated at each supervision node, and obtain soil remediation progress based on the node soil data;

[0061] In this embodiment, soil remediation progress is obtained by analyzing the node soil data at each monitoring node. The soil remediation progress includes advanced, lagging and normal.

[0062] S4: Based on the soil remediation progress of the land to be remediated, a reminder message is generated and sent to the management terminal.

[0063] In this embodiment, the management terminal includes a manager's smartphone, laptop, tablet computer, and supervisory computer, so that the manager can obtain the soil remediation progress of each land to be remediated in a timely manner, thereby reducing the inconvenience of land remediation process management caused by the large number and wide distribution of land to be remediated.

[0064] The specific implementation process of this embodiment includes:

[0065] In this embodiment, by analyzing the current soil grade, target soil grade and meteorological data, several supervision nodes of the land to be remediated are obtained, so that soil data can be collected and analyzed in time during the land remediation process, avoiding inaccurate analysis results caused by disorderly data collection. By analyzing the node soil data corresponding to each supervision node, the progress of soil remediation is obtained, and corresponding reminder information is further generated according to the progress of soil remediation and sent to the management terminal. So that the management terminal can obtain the progress of land remediation of each land to be mediated in time and take corresponding measures, so that the difficulty of land remediation management of multiple lands to be mediated at the same time is reduced. The technical problem of the difficulty of supervision in the land remediation process in the prior art is solved.

[0066] In this embodiment, Figure 2 As shown in the figure, based on the current soil grade of the land to be remediated, the target soil grade and meteorological data, several regulatory nodes are identified, including:

[0067] S21: Based on the current soil grade and meteorological data of the land to be rehabilitated, obtain the theoretical rehabilitating time of the land to be rehabilitated to the next soil grade;

[0068] S22: repeat step S21 until the next soil level is the target soil level;

[0069] S23: Based on the theoretical remediation time between adjacent soil grades of the land to be remediated, the time nodes corresponding to each soil grade in the process of the land to be remediated from the current soil grade to the target soil grade are obtained as supervision nodes, and each soil grade is the theoretical soil grade of the corresponding supervision node.

[0070] In this embodiment, the land remediation process needs to last for a long time to fundamentally improve the soil grade of the land to be remediated. This is related to the fact that the organic matter in the soil needs to be fully decomposed, the chemicals added for remediation need to fully act, and the growth of beneficial bacteria.

[0071] Through expert experience and big data analysis, the theoretical remediation time between adjacent soil grades is obtained when using standard remediation methods to upgrade the land to be remediated from the current soil grade to the target soil grade under the meteorological data of the area where the land to be remediated is located. Standard remediation methods include land leveling, fertilization, pesticide application, and fungus application.

[0072] Then, further, the time nodes corresponding to each soil grade in the process of the land to be rehabilitated rising from the current soil grade to the target soil grade are obtained as supervision nodes.

[0073] In this embodiment, before each supervision node obtains the node soil data of the land to be remediated and obtains the soil remediation progress based on the node soil data, it also includes:

[0074] Based on the remediation scope of the land to be remediated, a number of detection locations corresponding to the land to be remediated are determined, and a number of soil sensors are set at each detection location;

[0075] Each soil sensor collects corresponding soil data at each supervision node as node soil data of the corresponding supervision node; the node soil data includes several items of soil sensor data; the several soil sensors include pH sensors, temperature sensors, humidity sensors, heavy metal sensors and soil nutrient sensors.

[0076] In this embodiment, the plurality of detection positions include a plurality of random positions in the land to be rehabilitated whose distance from the land boundary is greater than a set distance.

[0077] In this embodiment, node soil data of the land to be remediated is obtained at each supervision node, and the soil remediation progress is obtained based on the node soil data, including:

[0078] Based on the node soil data of the land to be remediated at the current supervision node, confirm the actual soil grade of the land to be remediated at the current supervision node;

[0079] Compare the actual soil level at the current monitoring node with the theoretical soil level to obtain the soil remediation progress; the soil remediation progress includes advanced, lagging and normal;

[0080] If the actual soil grade is higher than the theoretical soil grade, the soil remediation progress is ahead of schedule; if the actual soil grade is lower than the theoretical soil grade, the soil remediation progress is behind schedule; if the actual soil grade is equal to the theoretical soil grade, the soil remediation progress is normal.

[0081] In this embodiment, based on the node soil data of the land to be remediated at the current supervision node, the actual soil grade of the land to be remediated at the current supervision node is confirmed, including:

[0082] Acquire a soil grade relationship database, the soil grade relationship database including a plurality of soil sensor data, soil grades, and a mapping relationship between the plurality of soil sensor data and soil grades;

[0083] The neural network model is trained through the soil grade relationship database to obtain the soil analysis model;

[0084] The node soil data of the current supervision node is input into the soil analysis model to obtain the actual soil grade of the land to be rehabilitated at the current supervision node.

[0085] The neural network model in this embodiment includes: an input layer, an output layer and a hidden layer;

[0086] The input layer includes a number of input neurons, and the number of input neurons corresponds one-to-one to a number of soil sensor data;

[0087] The hidden layer includes several hidden neurons;

[0088] The output layer includes a number of output neurons, and the output neurons correspond to a number of soil grades. In this embodiment, there are 10 soil grades, that is, there are 10 corresponding output neurons. The activation function uses the Softmax function.

[0089] During training, the data in the soil grade relationship database is divided into a training set and a verification set; the neural network model is trained with the training set, and after the training is completed, it is verified with the verification set, and the soil analysis model is obtained after the verification passes.

[0090] In this embodiment, based on the soil remediation progress of the land to be remediated, a reminder message is generated and sent to the management terminal, including:

[0091] When the soil remediation progress of the land to be remediated is lagging behind, a remediation strategy is generated based on the soil data of the current node as a reminder information;

[0092] When the soil remediation progress of a piece of land to be remediated is ahead of schedule and the actual soil grade is not lower than the target soil grade, a stop remediation signal is generated as a reminder message. After the management terminal receives the stop remediation signal and verifies it, it confirms that the land to be remediated is remediated land.

[0093] In this embodiment, when the land to be remediated is confirmed as remediated land, the remediated land is confirmed to flow in. The remediation progress of the remaining land to be remediated is continuously supervised.

[0094] In this embodiment, based on the soil data of the current node, generating a remediation strategy includes:

[0095] Based on the current node soil data and current soil grade, obtain several abnormal data;

[0096] Based on several abnormal data, obtain several processing methods;

[0097] Through big data analysis, the processing sequence and interval time of each treatment method can be used as a remediation strategy when the progress of soil remediation lags behind.

[0098] According to another embodiment of the present invention, Figure 3 As shown, the land acquisition and remediation options include:

[0099] SS1: Based on the land balance requirement, obtain several constraints; the land balance requirement includes several outflow lands, soil grade and area of ​​each outflow land;

[0100] SS2: Based on the current data of the land to be flowed in and several constraints, several candidate schemes are randomly obtained as the initial population; the data of the land to be flowed in include the current soil grade, remediation potential and area of ​​the land to be flowed in; the candidate schemes include the original soil data, current soil grade, target soil grade and area of ​​each land to be flowed in;

[0101] SS3: Based on the preset fitness function, several candidate schemes of the initial population are iteratively optimized until the preset iteration conditions are met to obtain the land consolidation scheme.

[0102] The specific implementation process of this embodiment includes:

[0103] In this embodiment, all outflow lands within a period of time are obtained, and the soil grade and area of ​​each outflow land are counted; given the soil grades and areas of several outflow lands, several soil grades of the outflow lands and the land area corresponding to each soil grade are obtained. In this embodiment, the land balance requirement also requires that the area and quality of the newly inflow land cannot be lower than the area and quality of the outflow land.

[0104] Therefore, in this embodiment, it is necessary to obtain a number of constraints according to the land balance requirements, and screen the land improvement plans through the constraints to improve the scientificity and rationality of the land balance.

[0105] In this embodiment, several constraints include:

[0106] The soil grade of each land to be flowed into after remediation is not higher than the remediation potential and the soil grade span is within the set span;

[0107] The total area of ​​the land to be flowed into corresponding to each soil grade after remediation shall not be less than the preset percentage of the total area of ​​the land to be flowed out;

[0108] The total area of ​​the land to be flowed into corresponding to all soil levels after remediation is greater than or equal to the total area of ​​the land to be flowed out;

[0109] The first area change of a number of lands to be flowed in whose soil grade after remediation is higher than the set grade is greater than or equal to the second area change of a number of lands to be flowed in whose soil grade is not higher than the set grade.

[0110] In this embodiment, some land that is not currently used as farmland is used as land to be flowed in, and the land to be flowed in includes forest land, grassland, garden land, etc. The land to be flowed in becomes land to be rectified after entering the land consolidation plan.

[0111] Due to various factors such as geographical factors, it is difficult for each land to reach a very high soil grade through short-term remediation measures. When entering the land to be relocated, managers or experts should confirm the corresponding remediation potential of the land to be relocated. The remediation potential includes the highest soil grade that the land to be relocated can reach within a preset time through standard remediation measures. The preset time includes the remediation cycle preset by the manager.

[0112] In this embodiment, in order to control the cost of remediation, requirements are also put forward for the soil grade span of each land to be flowed in during the remediation process. When the soil grade span is too large, the manpower, material resources and time costs required increase exponentially. Therefore, setting the constraint condition that the soil grade of each land to be flowed in after remediation is not higher than the remediation potential and the soil grade span is within the set span can control the land remediation cost.

[0113] In the land reclamation scheme, the land area corresponding to each soil grade is not less than the set percentage relative to the outflow land. In this embodiment, each soil grade is set with a corresponding set percentage. In some embodiments, the higher the soil grade, the larger the corresponding set percentage, which is more conducive to ensuring the improvement of the overall soil quality after land reclamation.

[0114] In this embodiment, the first area change of a number of lands to be flowed in whose soil grade after remediation is higher than the set grade is greater than or equal to the second area change of a number of lands to be flowed in whose soil grade is not higher than the set grade.

[0115] The first area change amount of the several lands to be flowed in whose soil grade after remediation is higher than the set grade includes the difference between the total area of ​​the several lands to be flowed in whose soil grade is higher than the set grade and the total area of ​​the outflowing lands which are higher than the set grade and have actually flowed out;

[0116] The second area change of the several lands to be flowed in with soil grades not higher than the set grade includes the difference between the total area of ​​the several lands to be flowed in with soil grades not higher than the set grade and the total area of ​​the outflowing lands which actually flowed out and were not higher than the set grade.

[0117] In this embodiment, the first area change of several lands to be flowed in and whose soil grade after remediation is higher than the set grade is greater than or equal to the second area change of several lands to be flowed in and whose soil grade is not higher than the set grade, including: the first area change must be greater than or equal to 0, and the first area change is greater than or equal to the absolute value of the second area change.

[0118] Through the above constraints, it can be ensured that the land to be flowed in through the land consolidation plan is no worse than the outflowing land in terms of quantity and quality.

[0119] In this embodiment, Figure 4 As shown, based on the preset fitness function, several candidate solutions of the initial population are iteratively optimized until the preset iteration conditions are met to obtain a land consolidation solution, including:

[0120] SS31: Based on the preset fitness function, calculate the fitness of each candidate solution in the initial population;

[0121] SS32: Based on the fitness of each candidate solution, several target candidate solutions are identified;

[0122] SS33: mutate and crossover several target candidate solutions, obtain several genetic solutions as candidate solutions in the next generation population and calculate the fitness;

[0123] SS34: Repeat steps SS32 to SS33 until the preset iteration conditions are met, and the genetic scheme with the highest fitness in the contemporary population is obtained as the land reclamation scheme; the preset iteration conditions include the number of iterations being greater than or equal to the preset number of iterations, or the fitness being greater than or equal to the set fitness.

[0124] In this embodiment, in step SS33, before taking several genetic schemes as candidate schemes in the next generation population, the following steps are also included:

[0125] Based on several constraints, several genetic schemes are screened, and the genetic schemes that meet the constraints are used as candidates in the next generation population.

[0126] In this embodiment, the candidate solutions are denoted as [S1(X1, Y1), S2(X2, Y2), ..., Si (X i , Y i ), …, S n (X n , Y n )], where S i represents the i-th piece of land to be flowed in; X i represents the current soil level of the i-th land to be flowed into; Y i Represents the target soil grade of the i-th piece of land to be flowed into.

[0127] In this embodiment, the calculation formula of the preset fitness function is as follows:

[0128]

[0129] W i =P(X i , Y i )*S i

[0130] Among them, F is the fitness; a is the weight coefficient; Wi is the cost of remediation of the i-th piece of land to be flowed into; p(X i , Y i ) indicates that the i-th piece of land to be flowed into is from the current soil i The soil level is raised to the target soil level Y i The unit area cost of the level; S i Represents the area of ​​land flowing into the i-th belt.

[0131] It should be noted that, in this article, relational terms such as "first" and "second" are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0132] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. An online supervision method for land consolidation, characterized in that: The method comprises: Obtaining a land remediation plan, wherein the land remediation plan includes a number of lands to be remediated, original soil data of each land to be remediated, current soil grade, target soil grade, and remediation scope; Based on the current soil grade, target soil grade and meteorological data of the land to be remediated, several monitoring nodes are identified; Obtain node soil data of the land to be remediated at each supervision node, and obtain soil remediation progress based on the node soil data; Based on the soil remediation progress of the land to be remediated, a reminder message is generated and sent to the management terminal.

2. The online supervision method for land consolidation according to claim 1, characterized in that: Based on the current soil grade of the land to be remediated, the target soil grade and meteorological data, several regulatory nodes are identified, including: S21: Based on the current soil grade and meteorological data of the land to be rehabilitated, obtain the theoretical rehabilitating time of the land to be rehabilitated to the next soil grade; S22: repeat step S21 until the next soil level is the target soil level; S23: Based on the theoretical remediation time between adjacent soil grades of the land to be remediated, the time nodes corresponding to each soil grade in the process of the land to be remediated from the current soil grade to the target soil grade are obtained as supervision nodes, and each soil grade is the theoretical soil grade of the corresponding supervision node.

3. The online supervision method for land consolidation according to claim 2, characterized in that: Before obtaining node soil data of the land to be remediated at each supervision node and obtaining the soil remediation progress based on the node soil data, it also includes: Based on the remediation scope of the land to be remediated, a number of detection locations corresponding to the land to be remediated are determined, and a number of soil sensors are set at each detection location; Each soil sensor collects corresponding soil data at each supervision node as node soil data of the corresponding supervision node; the node soil data includes several items of soil sensor data; the several soil sensors include pH sensors, temperature sensors, humidity sensors, heavy metal sensors and soil nutrient sensors.

4. The online supervision method for land consolidation as claimed in claim 3, characterized in that: Obtain node soil data of the land to be remediated at each supervision node, and obtain soil remediation progress based on the node soil data, including: Based on the node soil data of the land to be remediated at the current supervision node, confirm the actual soil grade of the land to be remediated at the current supervision node; Compare the actual soil level at the current monitoring node with the theoretical soil level to obtain the soil remediation progress; the soil remediation progress includes advanced, lagging and normal; If the actual soil grade is higher than the theoretical soil grade, the soil remediation progress is ahead of schedule; if the actual soil grade is lower than the theoretical soil grade, the soil remediation progress is behind schedule; if the actual soil grade is equal to the theoretical soil grade, the soil remediation progress is normal.

5. The online supervision method for land consolidation according to claim 4, characterized in that: Based on the node soil data of the land to be remediated at the current supervision node, the actual soil grade of the land to be remediated at the current supervision node is confirmed, including: Acquire a soil grade relationship database, wherein the soil grade relationship database includes a plurality of soil sensor data, soil grades, and mapping relationships between the plurality of soil sensor data and soil grades; The neural network model is trained through the soil grade relationship database to obtain the soil analysis model; The node soil data of the current supervision node is input into the soil analysis model to obtain the actual soil grade of the land to be rehabilitated at the current supervision node.

6. The online supervision method for land consolidation according to claim 4, characterized in that: Based on the soil remediation progress of the land to be remediated, generate reminder information and send it to the management terminal, including: When the soil remediation progress of the land to be remediated is lagging behind, a remediation strategy is generated based on the soil data of the current node as a reminder information; When the soil remediation progress of a piece of land to be remediated is ahead of schedule and the actual soil grade is not lower than the target soil grade, a stop remediation signal is generated as a reminder message. After the management terminal receives the stop remediation signal and verifies it, it confirms that the land to be remediated is remediated land.

7. The online supervision method for land consolidation according to claim 1, characterized in that: Acquisition of land remediation options includes: Based on the land balance requirement, a number of constraint conditions are obtained; the land balance requirement includes a number of outflow lands, the soil grade and area of ​​each outflow land; Based on the current data of the land to be flowed in and several constraints, several candidate plans are randomly obtained as the initial population; the data of the land to be flowed in includes the current soil grade, remediation potential and area of ​​the land to be flowed in; the candidate plans include the original soil data, current soil grade, target soil grade and area of ​​each land to be flowed in; Based on the preset fitness function, several candidate schemes of the initial population are iteratively optimized until the preset iteration conditions are met to obtain the land consolidation scheme.

8. An online monitoring method for land consolidation as claimed in claim 7, characterized in that: The constraints include: The soil grade of each land to be flowed into after remediation is not higher than the remediation potential and the soil grade span is within the set span; The total area of ​​the land to be flowed into corresponding to each soil grade after remediation shall not be less than the preset percentage of the total area of ​​the land to be flowed out; The total area of ​​the land to be flowed into corresponding to all soil levels after remediation is greater than or equal to the total area of ​​the land to be flowed out; The first area change of a number of lands to be flowed in whose soil grade after remediation is higher than the set grade is greater than or equal to the second area change of a number of lands to be flowed in whose soil grade is not higher than the set grade.

9. An online supervision method for land consolidation as claimed in claim 8, characterized in that: Based on the preset fitness function, several candidate solutions of the initial population are iteratively optimized until the preset iteration conditions are met to obtain the land consolidation solution, including: SS31: Based on the preset fitness function, calculate the fitness of each candidate solution in the initial population; SS32: Based on the fitness of each candidate solution, several target candidate solutions are identified; SS33: mutate and crossover several target candidate solutions, obtain several genetic solutions as candidate solutions in the next generation population and calculate the fitness; SS34: Repeat steps SS32 to SS33 until a preset iteration condition is met, and the genetic scheme with the highest fitness in the contemporary population is obtained as the land reclamation scheme; the preset iteration condition includes that the number of iterations is greater than or equal to the preset number of iterations, or the fitness is greater than or equal to the set fitness.

10. An online monitoring method for land consolidation as claimed in claim 9, characterized in that: In step SS33, before using several genetic schemes as candidate schemes in the next generation population, the method further includes: Based on several constraints, several genetic schemes are screened, and the genetic schemes that meet the constraints are used as candidates in the next generation population.

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