Disaster prevention warning system and disaster prevention warning method based on data model

Abstract

The present invention relates to the technical field of natural disaster prevention and control, and in particular to a disaster prevention and early warning system and a disaster prevention and early warning method based on a data model, comprising: a control terminal, a design layer, a modeling layer and an analysis layer; the control terminal is the main control end of the system and is used to issue an execution command; the location information of a disaster prevention area is uploaded through the design layer to determine the disaster prevention range, the deployment position of a sensing device is designed within the disaster prevention range, environmental information of the disaster prevention range is collected based on the deployed sensing device, the modeling layer receives the disaster prevention range and the deployment position of the sensing device determined by the design layer, and a disaster prevention area model is constructed based on the disaster prevention range and the deployment position of the sensing device. The present invention brings drought monitoring and early warning effects to farmland by constructing a disaster prevention area model and a disaster state model. After constructing the disaster state model, the system can bring effective and real-time drought risk monitoring and good early warning services to the disaster prevention area based on the continuous update of the disaster state model.

Description

Technical Field

[0001] The present invention relates to the technical field of natural disaster prevention and control, and in particular to a disaster prevention and early warning system and a disaster prevention and early warning method based on a data model. Background Art

[0002] Drought is a disaster caused by insufficient soil moisture to meet the needs of crop and pasture growth, resulting in a significant reduction in or total loss of production. Drought is a universal natural disaster that not only affects agriculture, but also seriously affects industrial production, urban water supply and the ecological environment.

[0003] The invention patent with application number 201310631995.7 discloses a method for estimating regional drought risk, which is characterized in that the method comprises: obtaining at least one disaster-pregnant factor, at least one disaster-causing factor, at least one vulnerability assessment factor of a disaster-bearing body and a drought zoning index for at least one point of interest in the region of interest from different data sources; calculating a drought sensitivity index based on the at least one disaster-pregnant factor; calculating a drought risk index based on the at least one disaster-causing factor; calculating a drought vulnerability index based on the at least one vulnerability assessment factor of a disaster-bearing body; performing weighted summation on the drought zoning index, the drought sensitivity index, the drought risk index and the drought vulnerability index to calculate a drought risk index; and estimating drought risk based on the calculated drought risk index; wherein the method further comprises: grading the drought zoning index according to a grading standard and assigning a corresponding value to each grade; the disaster-causing factors comprise: a precipitation anomaly percentage index, a soil relative moisture index, a soil thermal inertia index and an anomaly vegetation index.

[0004] The application aims to solve the problem that "currently remote sensing drought monitoring technology has established a variety of monitoring models from the perspectives of soil moisture, crop growth, temperature, energy balance, water balance, etc. However, due to the complexity of the relationship between soil, moisture, and vegetation, the applicability and accuracy of various monitoring models need to be further improved and enhanced. For example, the theory of thermal inertia method for monitoring soil moisture has matured, and good monitoring results have been achieved on bare soil or land with low vegetation coverage, but the monitoring accuracy in areas with high vegetation coverage is not high; there is a certain time lag between crop growth and drought conditions, so it is difficult to monitor the early drought conditions of crops using various vegetation index methods. The drought monitoring model that combines vegetation index with temperature has relatively high requirements for the study area, and must meet the condition that the soil surface moisture content should be from the wilting moisture content to the field water holding capacity. The drought monitoring method based on regional crop evaporation requires more conventional meteorological and ground observation data, involving energy exchange and balance between crops and the atmosphere and the surface, and its real-time monitoring cannot be fully guaranteed."

[0005] However, the above drought monitoring technology must be combined with meteorological data as a basis to monitor drought disasters according to changes in meteorological data, and the amount of data in its calculation and analysis process is huge.

[0006] To this end, we proposed a disaster prevention and early warning system and a disaster prevention and early warning method based on data models. Summary of the invention

[0007] In view of the above-mentioned shortcomings of the prior art, the present invention provides a disaster prevention and early warning system and a disaster prevention and early warning method based on a data model, which solve the technical problems raised in the above-mentioned background technology.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] First, the disaster prevention and early warning system based on data models includes: control terminal, design layer, modeling layer and analysis layer;

[0010] The control terminal is the main control terminal of the system and is used to issue execution commands;

[0011] The location information of the disaster prevention area is uploaded through the design layer to determine the disaster prevention scope. The sensing device deployment location is designed within the disaster prevention scope. Environmental information of the disaster prevention scope is collected based on the deployed sensing devices. The modeling layer receives the disaster prevention scope and the sensing device deployment location determined by the design layer. A disaster prevention area model is constructed based on the disaster prevention scope and the sensing device deployment location. The environmental information collected by the sensing device is simultaneously obtained. A disaster status model of the disaster prevention area is constructed based on the environmental information collected by the sensing device and the disaster prevention area model. The analysis layer simultaneously receives the disaster prevention area model and the disaster status model. The disaster risk of the disaster prevention area is analyzed based on the disaster status model. The disaster prevention scope is determined based on the disaster prevention area model.

[0012] The modeling layer includes a receiving module, a storage module, a building module and an evaluation module. The receiving module is used to receive the disaster prevention scope and the deployment location of the sensing device, and build the distribution topology of the sensing device based on the disaster prevention scope and the deployment location of the sensing device. The storage module is used to receive the environmental information collected by the sensing device in real time and store the environmental information. The building module is used to read the distribution topology of the sensing device built in the receiving module and the environmental information stored in the storage module, and use the distribution topology of the sensing device and the environmental information to build a disaster status model. The evaluation module is used to evaluate the effectiveness of the disaster status model built in the building module.

[0013] The evaluation logic of the disaster status model effectiveness in the evaluation module is expressed as: ;

[0014] Where: For the effectiveness of disaster status model; The size of the maximum area that can be formed by connecting corresponding points of sensing devices in the sensing device distribution topology; To sense the topological size of device distribution; The total number of topological edge corner points distributed for sensing devices; is the coordinates of the corner points of the i-th group; The total number of corresponding points of sensing devices on the edge of the largest area that can be formed by connecting corresponding points of sensing devices in the sensing device distribution topology; are the coordinates of the corresponding points of the jth group of sensing devices; is the adjustment factor; The value is 1 or -1.

[0015] When , the adjustment factor The value is -1.

[0016] When , the adjustment factor The value is 1, the disaster status model is effective The larger the value, the more accurate the disaster risk analysis results in the disaster prevention area; conversely, the less accurate the disaster risk analysis results in the disaster prevention area, and the effectiveness of the disaster status model Used to determine the scope of disaster prevention and control.

[0017] Furthermore, the design layer includes an upload module, a design module and a collection module, the upload module is used to upload the location information of the disaster prevention area, the design module is used to receive the location information of the disaster prevention area uploaded in the upload module, determine the disaster prevention range based on the location information of the disaster prevention area, design the deployment position of the sensing device within the disaster prevention range, and the collection module is used to collect environmental information within the disaster prevention range;

[0018] Among them, the upload module uploads no less than three groups of disaster prevention area location information. When determining the disaster prevention scope, the design module connects the adjacent areas based on the received disaster prevention area location information to form a group of closed areas. The closed area represents the disaster prevention scope. The area is selected within the disaster prevention scope, and the center of each area is used as the deployment location of the sensing device.

[0019] Furthermore, the sensing device is deployed at the deployment position designed by the design module, the deployment position designed by the design module is not less than five groups, and the range contained in any group of areas used for designing the deployment position is not greater than one half of the disaster prevention range;

[0020] When selecting the area, a minimum of three groups are selected. When the deployment positions designed by the design module are less than five groups, a group of line segments are determined by using the centers of two adjacent groups of areas. Based on the determined line segments as the bases, a group of isosceles right triangles are drawn within the disaster prevention range. The diagonal points opposite the right angles of the isosceles right triangles are selected as the deployment positions. The acquisition module is integrated by a sensing device, and the sensing device includes: a humidity sensor and a metal rod;

[0021] Among them, several groups of humidity sensors are arranged, and the several groups of humidity sensors are deployed equidistantly on the surface of the metal rod. The metal rod carrying the humidity sensor is inserted into the soil at the deployment position designed by the design module, and the distance between the top humidity sensor on the surface of the metal rod and the soil surface is equal to the distance between any two adjacent groups of humidity sensors on the surface of the metal rod.

[0022] Furthermore, the sensing device distribution topology constructed in the receiving module is a disaster prevention area model, and the disaster prevention area model is composed of a group of closed areas and a number of groups of sensing devices corresponding to the deployment points in the closed areas. When the storage module stores the environmental information, the stored environmental information is synchronously marked with the environmental information collection timestamp and the environmental information collection source sensing device, and after the marking is completed, each environmental information is distinguished and stored based on the environmental information collection timestamp, and each distinguished storage interval in the storage module is named according to the corresponding marking timestamp of the stored environmental information;

[0023] The storage module arranges the differentiated storage intervals based on the marked timestamp sequence of the differentiated storage intervals, and the construction module executes the construction of a disaster status model based on the environmental information stored in each differentiated storage interval in the storage module.

[0024] Furthermore, when constructing the disaster status model, the construction module divides the distribution topology of the sensing devices based on the maximum area that can be formed by the interconnection of the corresponding points of the sensing devices in the distribution topology of the sensing devices, so as to retain the corresponding area of ​​the maximum area that can be formed by the interconnection of the corresponding points of the sensing devices in the distribution topology of the sensing devices, and the construction unit runs to synchronously set the conversion scale, and further draws a line segment perpendicular to the reserved area based on the conversion scale at the position of each corresponding point of the sensing device in the reserved area, and synchronously connects the endpoints of each drawn line segment away from one end of the reserved area to construct a plurality of groups of faces, and then splices the plurality of groups of faces to obtain an unclosed figure composed of the plurality of groups of faces, and uses the unclosed figure as the top surface, the reserved area as the bottom surface and the disaster status model construction space to construct the disaster status model;

[0025] When a line segment perpendicular to the reserved area is drawn based on the conversion scale at the corresponding point position of each sensing device in the reserved area, the length of the line segment is:

[0026] ;

[0027] Where: Draw the length for the line segment; The distance between the humidity sensor used to collect humidity in the sensing device and the soil surface; Collect humidity for sensing devices; To convert the scale.

[0028] Furthermore, when a line segment perpendicular to the reserved area is drawn based on the conversion scale at the corresponding point position of each sensing device in the reserved area, in the stage of obtaining the length of the line segment, the humidity collected by each humidity sensor on the same metal rod is obtained and the humidity average is calculated, and the humidity collected by a group of humidity sensors with the smallest difference between the humidity collected by the humidity sensor and the humidity average is further selected as and distance Source.

[0029] Furthermore, the analysis layer includes an analysis module and a capture module, the analysis module is used to continuously receive the disaster prevention area model and the disaster status model constructed by the modeling layer, and analyze the disaster risk of the disaster prevention area based on the disaster status model, and the capture module is used to obtain the disaster prevention area model received by the analysis module, and capture the disaster prevention scope in the disaster prevention area model;

[0030] The disaster risk analysis logic of the disaster prevention area is expressed as:

[0031] ;

[0032] Where: To prevent regional disaster risks; A collection of hazard status models built for continuous operation of the modeling layer; is the volume of the disaster state model of group p; is the volume of the p+1th group of disaster state models; The maximum humidity value of the model construction source in the disaster state model of group p or group p+1;

[0033] The minimum humidity value of the model construction source in the disaster state model of group p or group p+1; is the adjustment factor;

[0034] Among them, the adjustment factor The value is 1 or -1. , , Disaster Risk in Disaster Prevention Areas The larger the value, the lower the disaster risk in the disaster prevention area. Conversely, the smaller the value, the higher the disaster risk in the disaster prevention area. , , Disaster Risk in Disaster Prevention Areas The larger it is, the higher the disaster risk in the disaster prevention area; conversely, the smaller it is, the lower the disaster risk in the disaster prevention area.

[0035] Furthermore, the analysis module is provided with a risk determination threshold, and the analysis module is based on the risk determination threshold and the disaster risk of the disaster prevention area. Compare and determine whether there is a disaster risk in the current disaster prevention area;

[0036] When the analysis module determines that there is a disaster risk in the disaster prevention area, the capture module is triggered to run;

[0037] The disaster prevention and control scope capture logic is: ;

[0038] Where: It is the disaster prevention area; The area corresponding to the distribution topology of the sensing device;

[0039] Among them, the disaster prevention area After obtaining, the disaster prevention area is captured in the corresponding area of ​​the sensing device distribution topology The area with the same size, the same topological center as the sensing device distribution, the same topological shape as the sensing device distribution and containing the most sensing device deployment points is recorded as the disaster prevention and control scope.

[0040] Furthermore, the receiving module is interactively connected to the storage module, the construction module and the evaluation module through the local area network, the receiving module is interactively connected to the acquisition module through the local area network, the acquisition module is interactively connected to the design module and the upload module through the local area network, the evaluation module is interactively connected to the analysis module through the local area network, and the analysis module is interactively connected to the capture module through the local area network.

[0041] Second, the disaster prevention and early warning method based on the data model includes the following steps:

[0042] Step 1: Upload the location information of the disaster prevention area, determine the disaster prevention scope, deploy humidity sensing equipment within the disaster prevention scope, and collect the humidity of the equipment deployment location in the disaster prevention area in real time based on the humidity sensing equipment;

[0043] Step 11: Design phase of humidity sensing device deployment logic;

[0044] Step 2: Build a disaster prevention area model based on the disaster prevention scope and the deployment location of the sensing device, and continuously build a disaster status model based on the humidity information of the deployment location collected by the humidity sensing device and the disaster prevention area model;

[0045] Step 21: Setting stage of disaster status model construction logic;

[0046] Step 3: Traverse the continuously constructed disaster status model and analyze the disaster risk in the disaster prevention area based on the disaster status model;

[0047] Step 31: Setting stage of disaster risk analysis logic for disaster prevention areas;

[0048] Step 4: Obtain the disaster risk analysis results of the disaster prevention area, set the risk determination threshold, and compare the risk determination threshold with the disaster risk analysis results of the disaster prevention area to determine whether there is a disaster risk in the disaster prevention area;

[0049] Step 5: If the result of the determination of whether there is a disaster risk in the disaster prevention area is no, then the process ends; if the result of the determination of whether there is a disaster risk in the disaster prevention area is yes, then the disaster prevention and control scope is captured.

[0050] Compared with the known public technology, the technical solution provided by the present invention has the following beneficial effects:

[0051] The present invention provides a disaster prevention and early warning system based on a data model. During operation, the system brings drought monitoring and early warning effects to farmland by constructing a disaster prevention area model and a disaster state model. After constructing the disaster state model, the system can provide effective and real-time drought risk monitoring and good early warning services to the disaster prevention area based on the continuous updating of the disaster state model, so that the disaster prevention area managers can have visual reading conditions and accurate and effective predictability for the management of the disaster prevention area based on the system. At the same time, when the drought risk is monitored, the area with severe drought in the disaster prevention area can be captured, so that the disaster prevention area managers can maintain the "severely affected area" in the disaster prevention area more quickly and accurately.

[0052] At the same time, a disaster prevention and early warning method based on a data model is provided, and the steps in the method are executed to provide operation logic support for the operation of the above system to ensure the stable operation of the above system. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the prior art descriptions. Obviously, the drawings described below are only some embodiments of the present invention, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 It is a structural diagram of a disaster prevention and early warning system based on a data model;

[0055] Figure 2 It is a flowchart of a disaster prevention and early warning method based on a data model;

[0056] Figure 3 Design a logical schematic diagram for the deployment location of the sensing device in the present invention;

[0057] Figure 4 This is a schematic diagram of an example of a disaster state model in the present invention;

[0058] Figure 5 This is a schematic diagram of an example of the results of capturing the scope of disaster prevention and control in the present invention;

[0059] The numbers in the figure represent: 1. Disaster prevention scope; 2. Area selected for deploying sensing devices; 3. Center point of selected area; 4. Topological center of sensing device distribution; 5. Disaster prevention scope. DETAILED DESCRIPTION

[0060] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are 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 creative work are within the scope of protection of the present invention.

[0061] The present invention will be further described below in conjunction with the embodiments. Example

[0062] The disaster prevention and early warning system based on the data model of this embodiment is as follows: Figure 1 As shown, it includes: control terminal, design layer, modeling layer and analysis layer;

[0063] The control terminal is the main control terminal of the system and is used to issue execution commands;

[0064] The location information of the disaster prevention area is uploaded through the design layer to determine the disaster prevention scope. The sensing device deployment location is designed within the disaster prevention scope. Environmental information of the disaster prevention scope is collected based on the deployed sensing devices. The modeling layer receives the disaster prevention scope and the sensing device deployment location determined by the design layer. A disaster prevention area model is constructed based on the disaster prevention scope and the sensing device deployment location. The environmental information collected by the sensing device is simultaneously obtained. A disaster status model of the disaster prevention area is constructed based on the environmental information collected by the sensing device and the disaster prevention area model. The analysis layer simultaneously receives the disaster prevention area model and the disaster status model. The disaster risk of the disaster prevention area is analyzed based on the disaster status model. The disaster prevention scope is determined based on the disaster prevention area model.

[0065] The design layer includes an upload module, a design module and a collection module. The upload module is used to upload the location information of the disaster prevention area. The design module is used to receive the location information of the disaster prevention area uploaded by the upload module, determine the disaster prevention scope based on the location information of the disaster prevention area, and design the deployment location of the sensing equipment within the disaster prevention scope. The collection module is used to collect environmental information within the disaster prevention scope.

[0066] The uploading module uploads no less than three groups of disaster prevention area location information. When determining the disaster prevention range, the design module connects adjacent areas to each other based on the received disaster prevention area location information to form a group of closed areas. The closed area represents the disaster prevention range. Areas are selected within the disaster prevention range, and the center of each area is used as the deployment position of the sensing device.

[0067] The modeling layer includes a receiving module, a storage module, a building module and an evaluation module. The receiving module is used to receive the disaster prevention scope and the deployment location of the sensing device, and build the distribution topology of the sensing device based on the disaster prevention scope and the deployment location of the sensing device. The storage module is used to receive the environmental information collected by the sensing device in real time and store the environmental information. The building module is used to read the distribution topology of the sensing device built in the receiving module and the environmental information stored in the storage module, and use the distribution topology of the sensing device and the environmental information to build a disaster status model. The evaluation module is used to evaluate the effectiveness of the disaster status model built in the building module.

[0068] The evaluation logic of the disaster status model effectiveness in the evaluation module is expressed as:

[0069] ;

[0070] Where: For the effectiveness of disaster status model; The size of the maximum area that can be formed by connecting corresponding points of sensing devices in the sensing device distribution topology; To sense the topological size of device distribution; The total number of topological edge corner points distributed for sensing devices; is the coordinates of the corner points of the i-th group; The total number of corresponding points of sensing devices on the edge of the largest area that can be formed by connecting corresponding points of sensing devices in the sensing device distribution topology; are the coordinates of the corresponding points of the jth group of sensing devices; is the adjustment factor; The value is 1 or -1.

[0071] When , the adjustment factor The value is -1.

[0072] When , the adjustment factor The value is 1, the disaster status model is effective The larger the value, the more accurate the disaster risk analysis results in the disaster prevention area; conversely, the less accurate the disaster risk analysis results in the disaster prevention area, and the effectiveness of the disaster status model Used to determine the scope of disaster prevention and control;

[0073] The analysis layer includes an analysis module and a capture module. The analysis module is used to continuously receive the disaster prevention area model and disaster status model constructed by the modeling layer, and analyze the disaster risk in the disaster prevention area based on the disaster status model. The capture module is used to obtain the disaster prevention area model received by the analysis module, and capture the disaster prevention scope in the disaster prevention area model.

[0074] The logical representation of disaster risk analysis in disaster prevention areas is:

[0075] ;

[0076] Where: To prevent regional disaster risks; A collection of hazard status models built for continuous operation of the modeling layer; is the volume of the disaster state model of group p; is the volume of the p+1th group of disaster state models; The maximum humidity value of the model construction source in the disaster state model of group p or group p+1;

[0077] The minimum humidity value of the model construction source in the disaster state model of group p or group p+1; is the adjustment factor;

[0078] Among them, the adjustment factor The value is 1 or -1. , , Disaster Risk in Disaster Prevention Areas The larger the value, the lower the disaster risk in the disaster prevention area. Conversely, the smaller the value, the higher the disaster risk in the disaster prevention area. , , Disaster Risk in Disaster Prevention Areas The larger the value, the higher the disaster risk in the disaster prevention area; conversely, the smaller the value, the lower the disaster risk in the disaster prevention area.

[0079] The receiving module is interactively connected to the storage module, the construction module and the evaluation module through the local area network, the receiving module is interactively connected to the acquisition module through the local area network, the acquisition module is interactively connected to the design module and the upload module through the local area network, the evaluation module is interactively connected to the analysis module through the local area network, and the analysis module is interactively connected to the capture module through the local area network.

[0080] In this embodiment, the control terminal controls the operation of the system, the upload module uploads the location information of the disaster prevention area, the design module synchronously receives the location information of the disaster prevention area uploaded in the upload module, determines the disaster prevention scope based on the disaster prevention area location information, designs the deployment position of the sensing device within the disaster prevention scope, the acquisition module further acquires environmental information within the disaster prevention scope, the receiving module post-operates to receive the disaster prevention scope and the deployment position of the sensing device, and constructs the distribution topology of the sensing device based on the disaster prevention scope and the deployment position of the sensing device, the storage module synchronously receives the environmental information collected by the sensing device in real time, stores the environmental information, and then the construction module reads the distribution topology of the sensing device constructed in the receiving module and the environmental information stored in the storage module, and uses the distribution topology of the sensing device and the environmental information to construct a disaster status model, the evaluation module evaluates the effectiveness of the disaster status model constructed in the construction module, the analysis module runs to continuously receive the disaster prevention area model and the disaster status model constructed by the modeling layer, analyzes the disaster risk of the disaster prevention area based on the disaster status model, and the capture module finally obtains the disaster prevention area model received by the analysis module, and captures the disaster prevention scope in the disaster prevention area model.

[0081] Through the operation of the system in the above embodiment, fast, accurate and real-time disaster warning and monitoring are provided for drought problems in agricultural planting scenarios, assisting system users to grasp the drought situation in the planting area in real time and respond in time.

[0082] See also Figure 3 As shown in the figure, based on the marks in the figure, the design logic of the sensing device deployment location is further demonstrated:

[0083] The two groups of marked points in the figure that are not in the area 2 selected for deploying the sensing equipment are also recorded as the center points 3 of the selected area. A group of line segments are determined by the centers of the two adjacent groups of areas. Based on the determined line segments as the bases, a group of isosceles right triangles are drawn within the disaster prevention range, and the right angle points of the isosceles right triangles are determined;

[0084] See also Figure 4 , based on the arrow indication, the distributed topology of the sensing device and the environmental information stored in the storage module further determine the unclosed figure as the top surface and the bottom surface and the reserved area of ​​the disaster state model construction space, and then complete the construction of the disaster state model with this limited condition;

[0085] See also Figure 5 As shown, based on the marks in the figure, the results of capturing the scope of disaster prevention and control are further displayed;

[0086] The capture conditions of the disaster prevention and control scope are met in this figure:

[0087] Disaster prevention area Equal in size, with the same center as the sensing device distribution topology, with the same shape as the sensing device distribution topology, and containing the most sensing device deployment points. Example

[0088] In terms of specific implementation, based on Example 1, this example refers to Figure 1 The disaster prevention and early warning system based on the data model in Example 1 is further described in detail:

[0089] The sensing equipment is deployed at the deployment locations designed by the design module. The deployment locations designed by the design module are not less than five groups, and the area contained in any group of areas used for the designed deployment locations is not greater than one-half of the disaster prevention range;

[0090] When selecting the area, no less than three groups are selected. When the deployment positions designed by the design module are less than five groups, a group of line segments are determined by the centers of two adjacent groups of areas. Based on the determined line segments as the base, a group of isosceles right triangles are drawn within the disaster prevention range. The diagonal points opposite the right angles of the isosceles right triangles are selected as the deployment positions. The acquisition module is integrated by the sensing device, and the sensing device includes: humidity sensor, metal rod;

[0091] Among them, several groups of humidity sensors are arranged, and the several groups of humidity sensors are deployed equidistantly on the surface of the metal rod. The metal rod carrying the humidity sensor is inserted into the soil at the deployment position designed by the design module, and the distance between the top humidity sensor on the surface of the metal rod and the soil surface is equal to the distance between any two adjacent groups of humidity sensors on the surface of the metal rod.

[0092] Through the above settings, detailed auxiliary logic is provided for the deployment of the sensing device of the system in Example 1, and the specific structure of the sensing device is limited, so that the sensing device can stably operate to collect humidity information, and provide necessary operation data support for the operation of subsequent modules in the system.

[0093] like Figure 1 As shown, the sensing device distribution topology constructed in the receiving module is a disaster prevention area model, which is composed of a group of closed areas and a number of groups of sensing devices corresponding to deployment points in the closed areas. When the storage module stores the environmental information, it synchronously performs environmental information collection timestamps and environmental information collection source sensing device markings on the stored environmental information, and after the marking is completed, each environmental information is distinguished and stored based on the environmental information collection timestamp. Each distinguished storage interval in the storage module is named according to the marking timestamp corresponding to the stored environmental information;

[0094] The storage module arranges the differentiated storage intervals based on the marked timestamp sequence of the differentiated storage intervals, and the construction module executes the construction of a disaster status model based on the environmental information stored in each differentiated storage interval in the storage module.

[0095] Through the above settings, the construction source of the disaster prevention area model and the logic of the storage module running the storage environment information are further limited;

[0096] It should be noted that the environmental information here refers to the humidity information collected by the collection module of the system in Example 1.

[0097] like Figure 1 As shown, when constructing the disaster state model, the construction module divides the distribution topology of the sensing devices based on the maximum area that can be formed by the interconnection of the corresponding points of the sensing devices in the distribution topology of the sensing devices, so as to retain the corresponding area of ​​the maximum area that can be formed by the interconnection of the corresponding points of the sensing devices in the distribution topology of the sensing devices, and the construction unit runs to synchronously set the conversion scale, and further draws a line segment perpendicular to the reserved area based on the conversion scale at the position of each corresponding point of the sensing device in the reserved area, and synchronously connects the endpoints of each drawn line segment away from one end of the reserved area to construct a plurality of groups of faces, and then splices the plurality of groups of faces to obtain an unclosed figure composed of the plurality of groups of faces, and uses the unclosed figure as the top surface, the reserved area as the bottom surface and the disaster state model construction space to construct the disaster state model;

[0098] When a line segment perpendicular to the reserved area is drawn based on the conversion scale at the corresponding point position of each sensing device in the reserved area, the length of the line segment is:

[0099] ;

[0100] Where: Draw the length for the line segment; The distance between the humidity sensor used to collect humidity in the sensing device and the soil surface; Collect humidity for sensing devices; To convert the scale;

[0101] When a line segment perpendicular to the reserved area is drawn based on the conversion scale at the corresponding point position of each sensing device in the reserved area, in the stage of obtaining the length of the line segment, the humidity collected by each humidity sensor on the same metal rod is obtained and the humidity average is calculated, and the humidity collected by a group of humidity sensors with the smallest difference between the humidity collected by the humidity sensor and the humidity average is further selected as and distance Source.

[0102] Through the above settings, the necessary construction parameter sources are provided for the construction module when constructing the disaster status model.

[0103] like Figure 1 As shown in the figure, a risk determination threshold is set in the analysis module. The analysis module is based on the risk determination threshold and the disaster risk of the disaster prevention area. Compare and determine whether there is a disaster risk in the current disaster prevention area;

[0104] When the analysis module determines that there is a disaster risk in the disaster prevention area, the capture module is triggered to run;

[0105] The logic of capturing the scope of disaster prevention and control is:

[0106] ;

[0107] Where: It is the disaster prevention area; The area corresponding to the distribution topology of the sensing device;

[0108] Among them, the disaster prevention area After obtaining, the disaster prevention area is captured in the corresponding area of ​​the sensing device distribution topology The area with the same size, the same topological center as the sensing device distribution, the same topological shape as the sensing device distribution and containing the most sensing device deployment points is recorded as the disaster prevention and control scope.

[0109] Through the above settings, the disaster prevention and control scope capture logic is further limited to ensure that the information in Example 1 is stably output for the disaster prevention and control scope. Example

[0110] In terms of specific implementation, based on Example 1, this example refers to Figure 2 The disaster prevention and early warning system based on the data model in Example 1 is further described in detail:

[0111] The disaster prevention and early warning method based on the data model includes the following steps:

[0112] Step 1: Upload the location information of the disaster prevention area, determine the disaster prevention scope, deploy humidity sensing equipment within the disaster prevention scope, and collect the humidity of the equipment deployment location in the disaster prevention area in real time based on the humidity sensing equipment;

[0113] Step 11: Design phase of humidity sensing device deployment logic;

[0114] Step 2: Build a disaster prevention area model based on the disaster prevention scope and the deployment location of the sensing device, and continuously build a disaster status model based on the humidity information of the deployment location collected by the humidity sensing device and the disaster prevention area model;

[0115] Step 21: Setting stage of disaster status model construction logic;

[0116] Step 3: Traverse the continuously constructed disaster status model and analyze the disaster risk in the disaster prevention area based on the disaster status model;

[0117] Step 31: Setting stage of disaster risk analysis logic for disaster prevention areas;

[0118] Step 4: Obtain the disaster risk analysis results of the disaster prevention area, set the risk determination threshold, and compare the risk determination threshold with the disaster risk analysis results of the disaster prevention area to determine whether there is a disaster risk in the disaster prevention area;

[0119] Step 5: If the result of the determination of whether there is a disaster risk in the disaster prevention area is no, then the process ends; if the result of the determination of whether there is a disaster risk in the disaster prevention area is yes, then the disaster prevention and control scope is captured.

[0120] In summary, during the operation of the system in the above embodiment, the system brings drought monitoring and early warning effects to farmland through the construction of disaster prevention area models and disaster status models. After constructing the disaster status model, the system can provide effective and real-time drought risk monitoring and good early warning services to the disaster prevention area based on the continuous update of the disaster status model, so that disaster prevention area managers can have visual reading conditions and accurate and effective predictability for the management of disaster prevention areas based on the system. At the same time, when drought risks are monitored, areas with severe droughts in the disaster prevention area can be captured, so that disaster prevention area managers can maintain the "severely affected areas" in the disaster prevention area more quickly and accurately.

[0121] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A disaster prevention and early warning system based on a data model, characterized in that: include: Control terminal, design layer, modeling layer and analysis layer; The control terminal is the main control terminal of the disaster prevention and early warning system, used to issue execution commands; The location information of the disaster prevention area is uploaded through the design layer to determine the disaster prevention scope. The sensing device deployment location is designed within the disaster prevention scope. Environmental information of the disaster prevention scope is collected based on the deployed sensing devices. The modeling layer receives the disaster prevention scope and the sensing device deployment location determined by the design layer. A disaster prevention area model is constructed based on the disaster prevention scope and the sensing device deployment location. The environmental information collected by the sensing device is simultaneously obtained. A disaster status model of the disaster prevention area is constructed based on the environmental information collected by the sensing device and the disaster prevention area model. The analysis layer simultaneously receives the disaster prevention area model and the disaster status model. The disaster risk of the disaster prevention area is analyzed based on the disaster status model. The disaster prevention scope is determined based on the disaster prevention area model. The modeling layer includes a receiving module, a storage module, a building module and an evaluation module. The receiving module is used to receive the disaster prevention scope and the deployment location of the sensing device, and build the distribution topology of the sensing device based on the disaster prevention scope and the deployment location of the sensing device. The storage module is used to receive the environmental information collected by the sensing device in real time and store the environmental information. The building module is used to read the distribution topology of the sensing device built in the receiving module and the environmental information stored in the storage module, and use the distribution topology of the sensing device and the environmental information to build a disaster status model. The evaluation module is used to evaluate the effectiveness of the disaster status model built in the building module. The evaluation logic of the disaster status model effectiveness in the evaluation module is expressed as: ； Where: For the effectiveness of disaster status model; The size of the maximum area that can be formed by connecting corresponding points of sensing devices in the sensing device distribution topology; To sense the topological size of device distribution; The total number of topological edge corner points distributed for sensing devices; is the coordinates of the corner points of the i-th group; The total number of corresponding points of sensing devices on the edge of the largest area that can be formed by connecting corresponding points of sensing devices in the sensing device distribution topology; are the coordinates of the corresponding points of the jth group of sensing devices; is the adjustment factor; The value is 1 or -1. When The value is -1. When The value is 1, the disaster status model is effective The larger the value, the more accurate the disaster risk analysis results in the disaster prevention area; conversely, the less accurate the disaster risk analysis results in the disaster prevention area, and the effectiveness of the disaster status model Used to determine the scope of disaster prevention and control.

2. The disaster prevention and early warning system based on data model according to claim 1, characterized in that: The design layer includes an upload module, a design module and a collection module. The upload module is used to upload the location information of the disaster prevention area. The design module is used to receive the location information of the disaster prevention area uploaded by the upload module, determine the disaster prevention range based on the location information of the disaster prevention area, and design the deployment position of the sensing device within the disaster prevention range. The collection module is used to collect environmental information within the disaster prevention range. Among them, the upload module uploads no less than three groups of disaster prevention area location information. When determining the disaster prevention scope, the design module connects the adjacent disaster prevention area location information received to form a group of closed areas. The closed area represents the disaster prevention scope. The area is selected within the disaster prevention scope, and the center of each area is used as the deployment location of the sensing device.

3. The disaster prevention and early warning system based on data model according to claim 2, characterized in that: The sensing device is deployed based on the deployment positions designed by the design module, the deployment positions designed by the design module are not less than five groups, and the range contained in any group of areas used for designing the deployment positions is not greater than one half of the disaster prevention range; When selecting the area, a minimum of three groups are selected. When the deployment positions designed by the design module are less than five groups, a group of line segments are determined by using the centers of two adjacent groups of areas. Based on the determined line segments as the bases, a group of isosceles right triangles are drawn within the disaster prevention range. The diagonal points opposite the right angles of the isosceles right triangles are selected as the deployment positions. The acquisition module is integrated by a sensing device, and the sensing device includes: a humidity sensor and a metal rod; Among them, several groups of humidity sensors are arranged, and the several groups of humidity sensors are deployed equidistantly on the surface of the metal rod. The metal rod carrying the humidity sensor is inserted into the soil at the deployment position designed by the design module, and the distance between the top humidity sensor on the surface of the metal rod and the soil surface is equal to the distance between any two adjacent groups of humidity sensors on the surface of the metal rod.

4. The disaster prevention and early warning system based on data model according to claim 1, characterized in that: The sensing device distribution topology constructed in the receiving module is a disaster prevention area model, which is composed of a group of closed areas and a number of groups of sensing devices corresponding to deployment points in the closed areas. When the storage module stores the environmental information, it simultaneously performs environmental information collection timestamps and environmental information collection source sensing device markings on the stored environmental information, and after the marking is completed, the environmental information is differentiated and stored based on the environmental information collection timestamp. Each differentiated storage interval in the storage module is named according to the corresponding marking timestamp of the stored environmental information; The storage module arranges the differentiated storage intervals based on the marked timestamp sequence of the differentiated storage intervals, and the construction module executes the construction of a disaster status model based on the environmental information stored in each differentiated storage interval in the storage module.

5. The disaster prevention and early warning system based on data model according to claim 1, characterized in that: When constructing the disaster state model, the construction module divides the distribution topology of the sensing devices based on the maximum area that can be formed by the interconnection of the corresponding points of the sensing devices in the distribution topology of the sensing devices, so as to retain the corresponding area of ​​the maximum area that can be formed by the interconnection of the corresponding points of the sensing devices in the distribution topology of the sensing devices, and the construction unit runs to synchronously set the conversion scale, and further draws a line segment perpendicular to the reserved area based on the conversion scale at the position of each corresponding point of the sensing device in the reserved area, and synchronously connects the endpoints of each drawn line segment away from one end of the reserved area to construct a plurality of groups of faces, and then splices the plurality of groups of faces to obtain an unclosed figure composed of the plurality of groups of faces, and uses the unclosed figure as the top surface, the reserved area as the bottom surface and the disaster state model construction space to construct the disaster state model; When a line segment perpendicular to the reserved area is drawn based on the conversion scale at the corresponding point position of each sensing device in the reserved area, the length of the line segment is: ； Where: Draw the length for the line segment; The distance between the humidity sensor used to collect humidity in the sensing device and the soil surface; Collect humidity for sensing devices; To convert the scale.

6. The disaster prevention and early warning system based on data model according to claim 5, characterized in that: When a line segment perpendicular to the reserved area is drawn based on the conversion scale at the corresponding point position of each sensing device in the reserved area, in the stage of obtaining the length of the line segment, the humidity collected by each humidity sensor on the same metal rod is obtained and the humidity average is calculated, and the humidity collected by a group of humidity sensors with the smallest difference between the humidity collected by the humidity sensor and the humidity average is further selected as and distance Source.

7. The disaster prevention and early warning system based on data model according to claim 1, characterized in that: The analysis layer includes an analysis module and a capture module. The analysis module is used to continuously receive the disaster prevention area model and the disaster status model constructed by the modeling layer, and analyze the disaster risk of the disaster prevention area based on the disaster status model. The capture module is used to obtain the disaster prevention area model received by the analysis module, and capture the disaster prevention scope in the disaster prevention area model. The disaster risk analysis logic of the disaster prevention area is expressed as: ； Where: To prevent regional disaster risks; A collection of hazard status models built for continuous operation of the modeling layer; is the volume of the disaster state model of group p; is the volume of the p+1th group of disaster state models; The maximum humidity value of the model construction source in the disaster state model of group p or group p+1; The minimum humidity value of the model construction source in the disaster state model of group p or group p+1; is the adjustment factor; Among them, the adjustment factor The value is 1 or -1. , , Disaster Risk in Disaster Prevention Areas The larger the value, the lower the disaster risk in the disaster prevention area. Conversely, the smaller the value, the higher the disaster risk in the disaster prevention area. , , Disaster Risk in Disaster Prevention Areas The larger it is, the higher the disaster risk in the disaster prevention area; conversely, the smaller it is, the lower the disaster risk in the disaster prevention area.

8. The disaster prevention and early warning system based on data model according to claim 7, characterized in that: The analysis module is set with a risk determination threshold, and the analysis module is based on the risk determination threshold and the disaster risk of the disaster prevention area. Compare and determine whether there is a disaster risk in the current disaster prevention area; When the analysis module determines that there is a disaster risk in the disaster prevention area, the capture module is triggered to run; The disaster prevention and control scope capture logic is: ; Where: It is the disaster prevention area; The area corresponding to the distribution topology of the sensing device; Among them, the disaster prevention area After obtaining, the disaster prevention area is captured in the corresponding area of ​​the sensing device distribution topology The area with the same size, the same topological center as the sensing device distribution, the same topological shape as the sensing device distribution and containing the most sensing device deployment points is recorded as the disaster prevention and control scope.

9. The disaster prevention and early warning system based on data model according to claim 1, characterized in that: The receiving module is interactively connected to the storage module, the construction module and the evaluation module through the local area network, the receiving module is interactively connected to the acquisition module through the local area network, the acquisition module is interactively connected to the design module and the upload module through the local area network, the evaluation module is interactively connected to the analysis module through the local area network, and the analysis module is interactively connected to the capture module through the local area network.

10. A disaster prevention and early warning method based on a data model, the method being an implementation method of a disaster prevention and early warning system based on a data model as claimed in any one of claims 1 to 9, characterized in that: The following steps are involved: Step 1: Upload the location information of the disaster prevention area, determine the disaster prevention scope, deploy humidity sensing equipment within the disaster prevention scope, and collect the humidity of the equipment deployment location in the disaster prevention area in real time based on the humidity sensing equipment; Step 2: Build a disaster prevention area model based on the disaster prevention scope and the deployment location of the sensing device, and continuously build a disaster status model based on the humidity information of the deployment location collected by the humidity sensing device and the disaster prevention area model; Step 3: Traverse the continuously constructed disaster status model and analyze the disaster risk in the disaster prevention area based on the disaster status model; Step 4: Obtain the disaster risk analysis results of the disaster prevention area, set the risk determination threshold, and compare the risk determination threshold with the disaster risk analysis results of the disaster prevention area to determine whether there is a disaster risk in the disaster prevention area; Step 5: If the result of the determination of whether there is a disaster risk in the disaster prevention area is no, then the process ends; If the result of the determination of whether there is a disaster risk in the disaster prevention area is yes, the disaster prevention and control scope is captured.

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