Surface 10 h delay dead fuel moisture monitoring system

Abstract

The present application relates to a kind of surface 10h time dead combustible moisture content monitoring system, the system includes: moisture content monitoring unit and data processing unit;Wherein, moisture content monitoring unit includes: moisture content sensor, first wireless communication module;Data processing unit includes: second wireless communication module, processing module;Wherein, first wireless communication module and second wireless communication module establish communication connection;Moisture content sensor includes wood stick probe and sensing module;The wood material of wood stick probe is homologous with the wood material of surface 10h time dead combustible, and electrode piece is embedded in wood stick probe;Sensing module excites electrode piece, and corresponding electrical signal is collected by excitation;Electrical signal is sent to processing module by communication connection;Processing module processes electrical signal, and obtains surface 10h time dead combustible moisture content.The system related to the present application can accurately monitor surface 10h time dead combustible moisture content.

Description

Technical Field

[0001] This invention relates to the field of combustible material moisture content technology, and in particular to a surface 10-hour dead combustible material moisture content monitoring system. Background Technology

[0002] Dead combustibles on the ground surface after 10 hours refer to dead branches with a diameter of 0.6–2.5 cm, which belong to the type of combustibles with a moderate rate of water loss (reaching equilibrium moisture content in 10 hours).

[0003] The moisture content of stagnant combustibles on the ground (such as dead branches and fallen leaves) is a core factor determining the probability and intensity of forest fires. When the moisture content of combustibles is high, combustion requires a large amount of heat energy to evaporate the moisture, reducing the effective heat energy of combustion and making it difficult for the fire to spread; conversely, when the moisture content is low, the energy released by combustion is more concentrated, the fire intensifies and spreads faster.

[0004] For example, if the moisture content of stagnant combustibles such as dead branches of Yunnan pine decreases by 5% after 10 hours, the fire spread rate can increase by 1.5–2 times.

[0005] Therefore, it is necessary to accurately monitor the moisture content of dead combustibles on the ground surface over a 10-hour period. Summary of the Invention

[0006] (a) Technical problems to be solved

[0007] In view of the above-mentioned shortcomings and deficiencies of the prior art, the present invention provides a monitoring system for the moisture content of dead combustibles on the ground surface over a period of 10 hours.

[0008] (II) Technical Solution

[0009] To achieve the above objectives, the main technical solutions adopted by the present invention include:

[0010] This invention provides a surface 10-hour dead flammable material moisture content monitoring system, which includes: a moisture content monitoring unit and a data processing unit;

[0011] The moisture content monitoring unit includes: a moisture content sensor and a first wireless communication module;

[0012] The data processing unit includes: a second wireless communication module and a processing module;

[0013] The first wireless communication module establishes a communication connection with the second wireless communication module.

[0014] The moisture content sensor includes a wooden stick probe and a sensing module. The wood material of the wooden stick probe is of the same origin as the wood material of the surface stale combustibles that have been dead for 10 hours. An electrode plate is embedded in the wooden stick probe. The sensing module excites the electrode plate and collects the corresponding electrical signal. The electrical signal is sent to the processing module through a communication connection.

[0015] The processing module processes the electrical signals to obtain the moisture content of the dead combustibles on the ground surface after 10 hours.

[0016] Optionally, the wooden probe is 15 cm long and 1.5 cm in diameter.

[0017] Optionally, the sensing module excites the electrode plates at a fixed frequency of 100 kHz.

[0018] Optionally, the moisture content sensor also integrates a miniature temperature sensor;

[0019] The temperature sensor collects the ambient temperature of the wooden stick probe; the ambient temperature is then sent to the processing module via a communication connection.

[0020] When processing electrical signals, the processing module compensates for ambient temperature to obtain the moisture content of stagnant combustibles on the ground surface after 10 hours.

[0021] Optionally, the system also includes a protective sleeve;

[0022] The protective cover is made of a breathable and water-permeable membrane, with an arc-shaped flow guide at the top;

[0023] Protective cover for moisture content sensor.

[0024] Optionally, the moisture content monitoring unit is located on a positioning bracket at a preset position;

[0025] The positioning bracket is 3cm to 8cm above the ground.

[0026] Optionally, the preset position is determined through the following steps:

[0027] Obtain the slope aspect and number of vegetation types in the monitoring area; where vegetation types are: forest, shrubland, grassland; slope aspect is shady slope, sunny slope;

[0028] If the number of vegetation types is 1, then the target circumscribed square of the monitoring area is rasterized to obtain the first grid; wherein, the target circumscribed square is the smallest square that includes the monitoring area and whose side length is a multiple of the effective sensing distance of the moisture content sensor;

[0029] If the number of vegetation types is not 1, the target outer square of the monitoring area is rasterized to obtain an initial raster. The initial raster is then merged according to the vegetation type to obtain the first raster.

[0030] Obtain the historical temperature, historical humidity, and historical wind speed for each first grid cell;

[0031] The first grid is processed based on historical temperature, historical humidity, and historical wind speed to obtain the second grid;

[0032] Determine the preset position in each of the second grid cells.

[0033] Optionally, for any initial raster containing at least one vegetation type, merging any initial raster according to vegetation type includes:

[0034] Determine the target type; if the slope aspect of the monitoring area is a shady slope, then the target type is forest if any initial grid cell contains forest vegetation, and shrub if any initial grid cell does not contain forest vegetation but contains shrub vegetation; if the slope aspect of the monitoring area is a sunny slope, then the target type is grassland if any initial grid cell contains grassland vegetation, and shrub if any initial grid cell does not contain grassland vegetation but contains shrub vegetation.

[0035] Obtain candidate initial grids; wherein, the candidate initial grids are the upper initial grid, lower initial grid, left initial grid, and right initial grid of any initial grid;

[0036] Determine if there are any candidate initial grids that include the target type;

[0037] If there are candidate initial grids that include the target type, then any initial grid is merged with the target grid. Among them, if the target type is forest or grassland, the area of ​​the target type vegetation included in the target grid is the largest. If the target type is shrub, when the slope aspect of the monitoring area is a shady slope, the target grid does not include forest vegetation, but the area including shrub vegetation is the largest. When the slope aspect of the monitoring area is a sunny slope, the target grid does not include grassland vegetation, but the area including shrub vegetation is the largest.

[0038] If no candidate initial grid includes the target type, then any initial grid is merged with the target grid; wherein the target grid and any initial grid include the same vegetation type, and the area of ​​the vegetation of the same type included in the target grid is the largest.

[0039] Optionally, the first grid is processed based on historical temperature, historical humidity, and historical wind speed to obtain a second grid, including:

[0040] The temperature threshold, humidity threshold, and wind speed threshold are determined based on the slope aspect corresponding to each first grid cell.

[0041] The processing value for each first grid cell is determined by the temperature threshold, humidity threshold, and wind speed threshold based on the slope aspect corresponding to each first grid cell.

[0042] The first grid is split based on the processed value to obtain the second grid.

[0043] Optionally, the temperature threshold, humidity threshold, and wind speed threshold are determined based on the slope aspect corresponding to any first grid cell, including:

[0044] If the slope direction corresponding to any first grid is a shady slope, then the temperature threshold is determined to be the average temperature of the monitoring area, the humidity threshold is determined to be the average humidity of the monitoring area, and the wind speed threshold is determined to be the average wind speed of the monitoring area.

[0045] If the slope corresponding to any first grid cell is a sunny slope, then the temperature threshold is determined as the nighttime average temperature of the monitoring area, the humidity threshold is determined as the nighttime average humidity of the monitoring area, and the wind speed threshold is determined as the afternoon average wind speed of the monitoring area.

[0046] (III) Beneficial Effects

[0047] The beneficial effects of this invention are as follows: This invention relates to a system for monitoring the moisture content of surface dead combustibles over a 10-hour period. The system includes a moisture content monitoring unit and a data processing unit. The moisture content monitoring unit includes a moisture content sensor and a first wireless communication module. The data processing unit includes a second wireless communication module and a processing module. The first wireless communication module and the second wireless communication module establish a communication connection. The moisture content sensor includes a wooden probe and a sensing module. The wood material of the wooden probe is homologous to the wood material of the surface dead combustibles over a 10-hour period, and an electrode is embedded within the wooden probe. The sensing module excites the electrode and collects the corresponding electrical signal. The electrical signal is sent to the processing module via the communication connection. The processing module processes the electrical signal to obtain the moisture content of the surface dead combustibles over a 10-hour period. The system of this invention can accurately monitor the moisture content of surface dead combustibles over a 10-hour period. Attached Figure Description

[0048] Figure 1 This is a schematic diagram of a surface 10-hour dead flammable material moisture content monitoring system provided by the present invention;

[0049] Figure 2 A schematic diagram of a wooden stick probe provided by the present invention;

[0050] Figure 3 A schematic diagram of a sensing module provided by the present invention;

[0051] Figure 4 A schematic diagram of a positioning bracket provided by the present invention;

[0052] Figure 5 A schematic diagram of an initial grid provided by the present invention;

[0053] Figure 6 A schematic diagram of an initial grid merging provided by the present invention;

[0054] Figure 7This is a schematic diagram of a first grid splitting method provided by the present invention. Detailed Implementation

[0055] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0056] The moisture content of dead combustibles on the ground (such as dead branches and fallen leaves) is a core factor determining the probability and intensity of forest fires. When the moisture content of combustibles is high, combustion requires a large amount of heat energy to evaporate the moisture, reducing the effective heat of combustion and making it difficult for the fire to spread. Conversely, when the moisture content is low, the energy released by combustion is more concentrated, intensifying the fire and accelerating its spread. Therefore, accurate monitoring of the moisture content of dead combustibles on the ground over 10 hours is necessary.

[0057] This invention relates to a system for monitoring the moisture content of surface dead combustibles over a 10-hour period. The system includes a moisture content monitoring unit and a data processing unit. The moisture content monitoring unit includes a moisture content sensor and a first wireless communication module. The data processing unit includes a second wireless communication module and a processing module. The first wireless communication module and the second wireless communication module establish a communication connection. The moisture content sensor includes a wooden probe and a sensing module. The wood material of the wooden probe is homologous to the wood material of the surface dead combustibles over a 10-hour period, and an electrode is embedded within the probe. The sensing module excites the electrode to collect the corresponding electrical signal. The electrical signal is transmitted to the processing module via the communication connection. The processing module processes the electrical signal to obtain the moisture content of the surface dead combustibles over a 10-hour period. The system of this invention can accurately monitor the moisture content of surface dead combustibles over a 10-hour period.

[0058] See Figure 1 This embodiment provides a surface 10-hour dead combustible moisture content monitoring system, which includes at least one moisture content monitoring unit and a data processing unit.

[0059] 1. Moisture content monitoring unit

[0060] The moisture content monitoring unit includes: a moisture content sensor and a first wireless communication module.

[0061] The first wireless communication module supports the LoRa / NB-IoT protocol, and the first wireless communication module establishes a communication connection with the second wireless communication module.

[0062] The moisture content sensor includes a wooden stick probe and a sensing module.

[0063] 1) Wooden stick probe

[0064] The wood material of the wooden stick probe is of the same origin as the wood material of the stale combustible material on the ground surface after 10 hours, and an electrode plate is embedded in the wooden stick probe.

[0065] The wooden probe is 15cm long and 1.5cm in diameter.

[0066] For example, the rod probe uses wood of the same origin as the 10-hour dead combustible material (such as pine or oak), and its size matches the target combustible material (15cm in length and 1.5cm in diameter). An electrode plate is embedded inside (to measure changes in resistance / capacitance). Figure 2 As shown.

[0067] 2) Sensing module

[0068] The sensing module excites the electrode plates and acquires the corresponding electrical signals. For example, the sensing module excites the electrode plates at a fixed frequency of 100 kHz (kilohertz) and acquires the corresponding electrical signals.

[0069] Electrical signals are transmitted to the data processing unit via a communication connection. In specific implementation, the electrical signals are transmitted to the processing module within the data processing unit via the communication connection.

[0070] In practical implementation, the sensing module can be as follows: Figure 3 As shown.

[0071] In addition, the moisture content sensor also integrates a miniature temperature sensor.

[0072] A temperature sensor collects the ambient temperature of the wooden stick probe. This ambient temperature is then transmitted to the processing module via a communication connection.

[0073] For example, the sensing module excites the electrodes at a fixed frequency of 100kHz to collect the electrical signal (voltage ratio) corresponding to the moisture content of the wooden stick, and simultaneously integrates a miniature temperature sensor (for temperature compensation).

[0074] In addition, in practical implementation, the moisture content monitoring unit is located on a positioning bracket at a preset position, and this positioning bracket can be used as follows: Figure 4 As shown.

[0075] The positioning bracket is 3cm to 8cm above the ground.

[0076] For example, the positioning bracket can adjust the insertion depth (3cm-8cm) to ensure that the probe is in the 10-hour time-delay combustible material concentration layer and avoids the soil layer.

[0077] In addition, the preset position is determined through the following steps:

[0078] 101, obtain the number of slope aspects and vegetation types in the monitoring area.

[0079] The vegetation types are: forest, shrubland, and grassland.

[0080] The slope is shady and sunny.

[0081] In practice, a general survey and dynamic monitoring of basic data such as topography and vegetation conditions in the monitored area will be conducted regularly. In step 101, the slope aspect and number of vegetation types in the monitored area obtained from the latest survey and monitoring can be directly obtained.

[0082] Different types of vegetation have different water content and water content changes, so the number of vegetation types will be determined in step 101.

[0083] 102. If the number of vegetation types is 1, it means that the vegetation in the monitoring area is monolithic. The moisture content and moisture content change of the surface dead combustibles in the entire area over 10 hours are similar and can be considered as a whole. Therefore, the target outer square of the monitoring area is rasterized to obtain the first grid.

[0084] The target circumscribed square is the smallest square that includes the monitoring area and has a side length that is a multiple of the effective sensing distance r of the moisture content sensor. In other words, the target circumscribed square is a square, and it is the smallest circumscribed square of the monitoring area whose side length is a multiple of r.

[0085] The process of rasterizing the outer square of the target in the monitoring area to obtain the first grid can be as follows: rasterize the outer square of the target in the monitoring area with length r to obtain the first grid, and then the first grid is a square with length r.

[0086] Because the wood material of the stick probe in the moisture content sensor is of the same origin as the wood material of the dead combustibles on the ground surface after 10 hours, and although the types of wood in the monitoring area are the same, there may be differences in specific varieties, the moisture content sensor can only reflect the moisture content of dead combustibles on the ground surface after 10 hours of the same wood material. It cannot accurately reflect the moisture content of dead combustibles on the ground surface after 10 hours of different wood materials. Therefore, the moisture content sensor has an effective sensing distance, which can be set by relevant personnel based on the material of the stick probe in the moisture content sensor and the specific vegetation conditions in the monitoring area.

[0087] Therefore, with r as the length of the first grid, it is possible to equip each first grid with a moisture content monitoring unit to accurately monitor the moisture content of dead combustibles on the surface within the entire first grid over 10 hours.

[0088] 103. If the number of vegetation types is not 1, the target outer square of the monitoring area is rasterized to obtain an initial raster. The initial raster is then merged according to the vegetation type to obtain the first raster.

[0089] The target circumscribed square is the smallest square that includes the monitoring area and has a side length that is a multiple of the effective sensing distance r of the moisture content sensor. In other words, the target circumscribed square is a square, and it is the smallest circumscribed square of the monitoring area whose side length is a multiple of r.

[0090] The process of rasterizing the target circumscribed square of the monitoring area to obtain the initial grid is as follows: rasterize the target circumscribed square of the monitoring area with length r to obtain the initial grid, and then the initial grid is a square with length r.

[0091] Therefore, using r as the initial grid length allows for accurate monitoring of the 10-hour dead combustible surface moisture content within an initial grid containing only one vegetation type, with just one moisture content monitoring unit. However, for initial grids containing two or three vegetation types, the diversity of vegetation makes it impossible to accurately monitor the 10-hour dead combustible surface moisture content within the entire initial grid using only one moisture content monitoring unit.

[0092] Therefore, after obtaining the initial raster, the number of vegetation types included in each initial raster is determined. Initial rasters with only one vegetation type are left unprocessed. For initial rasters with more than one vegetation type, they are merged according to the vegetation type to obtain the first raster.

[0093] The process of merging any initial raster containing at least one vegetation type according to the vegetation type is as follows:

[0094] 201. Determine the target type.

[0095] If the slope of the monitoring area is a shady slope, then when any initial grid cell contains forest-type vegetation, the target type is forest type; when any initial grid cell does not contain forest-type vegetation but contains shrub-type vegetation, the target type is shrub type.

[0096] If the slope of the monitored area is a sunny slope, then the target type is grassland if any initial grid cell contains grassland vegetation, and the target type is shrub if any initial grid cell does not contain grassland vegetation but contains shrub vegetation.

[0097] The target type characterizes the main vegetation type in the monitoring area that causes uneven moisture content of dead combustibles on the ground surface over 10 hours.

[0098] For example, on shady slopes, the shorter sunshine hours, lower temperatures, and lower evaporation rates result in higher vegetation and soil moisture, leading to slower drying of combustibles. Consequently, the surface moisture content of dead combustibles on shady slopes is higher over 10 hours. Furthermore, the impact of external environmental factors on the surface moisture content of dead combustibles on shady slopes is relatively smaller. Given the limited impact of the external environment on vegetation, shrub and grassland vegetation types, due to their lower height and poor shading, cannot effectively block the influence of the external environment. This means that changes in the external environment have a relatively small impact on shrub and grassland vegetation in various locations. Forest vegetation, however, provides significant shading due to its varied height and foliage. Different levels of shading reduce the impact of external environmental changes on the surface moisture content of dead combustibles over 10 hours. Therefore, the effect of external environmental changes on the surface moisture content of dead combustibles varies depending on the effectiveness of the shading.

[0099] In other words, regardless of their location within the monitoring area, the difference in surface dead combustible moisture content over 10 hours for shrub and grassland vegetation is smaller than that for forest vegetation at different locations. Forest vegetation is the main vegetation type causing the uneven distribution of surface dead combustible moisture content over 10 hours.

[0100] If forest types are excluded and only shrub and grassland types are included, based on the above analysis, shrub vegetation provides a relatively higher degree of shading from external factors due to its height and branches compared to sub-grassland vegetation. This means that for grassland vegetation, regardless of its location within the monitoring area, the difference in surface dead combustible moisture content over 10 hours is smaller than that of shrub vegetation at different locations. Shrub vegetation is the main vegetation type causing the uneven distribution of surface dead combustible moisture content over 10 hours.

[0101] However, on sunny slopes, due to longer hours of sunshine and stronger solar radiation, the moisture content of dead combustibles on the surface over 10 hours is higher. Furthermore, the influence of the external environment on the moisture content of dead combustibles on the surface over 10 hours is also relatively greater. Given the significant impact of the external environment on vegetation, grassland vegetation, due to its lower height and poor shading, cannot effectively block the influence of the external environment. This makes grassland vegetation highly sensitive to changes in the external environment; that is, changes in external factors will affect the moisture content of dead combustibles on the surface over 10 hours. In contrast, shrub and forest vegetation, due to their varied heights and foliage, provides greater shading. This shading reduces the impact of external environmental changes on the moisture content of dead combustibles on the surface over 10 hours. Therefore, shrub and forest vegetation are less sensitive to changes in the external environment, and changes in the external environment may have a smaller impact on the moisture content of dead combustibles on the surface over 10 hours.

[0102] In other words, the degree to which the surface 10-hour dead combustible moisture content of grassland vegetation changes with the external environment is greater than that of shrub and forest vegetation. Grassland is the main vegetation type causing the uneven surface 10-hour dead combustible moisture content.

[0103] If we exclude grassland and only include shrub and forest types, based on the above analysis, shrub vegetation has significantly smaller height, branches, and leaves than forest vegetation. Therefore, shrub vegetation provides less shielding against external factors than subforest vegetation. Consequently, the surface moisture content of dead combustibles in shrub vegetation changes more significantly with environmental changes than that in forest vegetation. Shrub vegetation is the main vegetation type causing uneven surface moisture content of dead combustibles over 10 hours.

[0104] Based on the above analysis, if the slope aspect of the monitoring area is a shady slope, then when any initial grid cell contains forest-type vegetation, the target type is forest type; when any initial grid cell does not contain forest-type vegetation but contains shrub-type vegetation, the target type is shrub type.

[0105] If the slope of the monitored area is a sunny slope, then the target type is grassland if any initial grid cell contains grassland vegetation, and the target type is shrub if any initial grid cell does not contain grassland vegetation but contains shrub vegetation.

[0106] 202, Obtain candidate initial grids.

[0107] Among them, the candidate initial grid is the initial grid above, the initial grid below, the initial grid to the left, and the initial grid to the right of any initial grid.

[0108] like Figure 5 As shown, if any initial grid cell is grid cell i, the initial grid cell above it is grid cell j, the initial grid cell below it is grid cell k, the initial grid cell to its left is grid cell u, and the initial grid cell to its right is grid cell v.

[0109] It is possible that any initial grid does not have all of the top, bottom, left, and right initial grids. For example, if any initial grid is grid k and it does not have a bottom initial grid, then the initial grids in the missing directions can be disregarded as candidate initial grids. If any initial grid is grid k, the only candidate initial grids are its top, left, and right initial grids.

[0110] 203. Determine if there are any candidate initial grids that include the target type.

[0111] 204. If there are candidate initial rasters that include the target type, then merge any initial raster with the target raster.

[0112] Among them, if the target type is forest or grassland, the area of ​​vegetation of the target type included in the target grid is the largest.

[0113] If the target type is shrubland, then when the slope aspect of the monitoring area is a shady slope, the target grid does not include forest type vegetation, but the area including shrubland type vegetation is the largest. When the slope aspect of the monitoring area is a sunny slope, the target grid does not include grassland type vegetation, but the area including shrubland type vegetation is the largest.

[0114] 205. If there are no candidate initial rasters that include the target type, then merge any initial raster with the target raster.

[0115] Among them, the target grid and any initial grid include the same vegetation type, and the area of ​​the vegetation of the same vegetation type included in the target grid is the largest.

[0116] For example, A. If the target type is forest, then:

[0117] a.1 Determine whether there are candidate initial rasters that include forest-type vegetation.

[0118] a.2 If there are no candidate initial rasters including forest type, then:

[0119] (1) Determine whether there are candidate initial rasters with the same vegetation type as any initial raster.

[0120] (2) If there is no candidate initial grid with the same vegetation type as any initial grid, there is no target grid and therefore no initial grid will be merged with the target grid.

[0121] (3) If there is a candidate initial grid with the same vegetation type as any initial grid, then:

[0122] ① If there is only one candidate initial grid (e.g., grid u) with the same vegetation type as any initial grid, then grid u is determined as the target grid. Therefore, any initial grid (e.g., grid i) will be merged with the target grid (e.g., grid u) to form... Figure 6 The grid shown.

[0123] ② If there are multiple candidate initial graticles (such as graticles u and graticles v) that contain the same vegetation type as any initial graticle, then determine the area Su of the vegetation of the same type included in graticle u, and determine the area Sv of the vegetation of the same type included in graticle v.

[0124] If Su > Sv, then raster u is selected as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster u). If Sv > Su, then raster v is selected as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster v). If Sv = Su, then raster u and raster v are randomly selected as the target raster, and any initial raster will be merged with the target raster.

[0125] a.3 If there is only one candidate initial raster (e.g., raster u) that includes the forest type, then raster u is determined as the target raster, and therefore any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster u).

[0126] a.4 If there are multiple candidate initial rasters containing forest type (e.g., raster u and raster v), then determine the area Su of forest type vegetation included in raster u, and determine the area Sv of forest type vegetation included in raster v. If Su > Sv, then raster u is determined as the target raster, and therefore any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster u). If Sv > Su, then raster v is determined as the target raster, and therefore any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster v). If Sv = Su, then raster u and raster v are randomly selected as the target raster, and therefore any initial raster will be merged with the target raster.

[0127] B. If the target type is grassland, then:

[0128] b.1 Determine whether there are candidate initial rasters that include grassland-type vegetation among the candidate initial rasters.

[0129] b.2 If there are no candidate initial rasters including grassland type, then:

[0130] (1) Determine whether there are candidate initial rasters with the same vegetation type as any initial raster.

[0131] (2) If there is no candidate initial grid with the same vegetation type as any initial grid, there is no target grid and therefore no initial grid will be merged with the target grid.

[0132] (3) If there is a candidate initial grid with the same vegetation type as any initial grid, then:

[0133] ① If there is only one candidate initial grid (such as grid u) that has the same vegetation type as any initial grid, then grid u is determined as the target grid, and thus any initial grid (such as grid i) will be merged with the target grid (such as grid u).

[0134] ② If there are multiple candidate initial graticets (e.g., graticets u and v) that contain the same vegetation type as any initial graticet, then determine the area Su of the vegetation of the same type in graticet u, and the area Sv of the vegetation of the same type in graticet v. If Su > Sv, then graticet u is determined as the target graticet, and thus any initial graticet (e.g., graticet i) will be merged with the target graticet (e.g., graticet u). If Sv > Su, then graticet v is determined as the target graticet, and thus any initial graticet (e.g., graticet i) will be merged with the target graticet (e.g., graticet v). If Sv = Su, then graticet u and graticet v are randomly selected as the target graticet, and thus any initial graticet will be merged with the target graticet.

[0135] b.3 If there is only one candidate initial raster (such as raster u) that includes the grassland type, then raster u is determined as the target raster, and any initial raster (such as raster i) will be merged with the target raster (such as raster u).

[0136] b.4 If there are multiple candidate initial rasters containing grassland type (e.g., raster u and raster v), determine the area Su of grassland type vegetation in raster u, and determine the area Sv of grassland type vegetation in raster v. If Su > Sv, then raster u is determined as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster u). If Sv > Su, then raster v is determined as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster v). If Sv = Su, then raster u and raster v are randomly selected as the target raster, and any initial raster will be merged with the target raster.

[0137] C. If the target type is shrub type, then:

[0138] c.1 When the slope aspect of the monitored area is a shady slope, it means that any initial grid cell includes shrub and grassland types, that is, no initial grid cell has forest type vegetation. If any initial grid cell is merged with an initial grid cell that has forest type vegetation, the merged grid cell will be affected by the forest type vegetation. Therefore, the target grid cell cannot have forest type vegetation.

[0139] (1) Determine whether there are candidate initial grids that include shrub type vegetation but not forest type vegetation.

[0140] (2) If there are no candidate initial grids that include shrub-type vegetation but exclude forest-type vegetation, then:

[0141] ① Determine whether there are any candidate initial rasters with the same vegetation type as any initial raster.

[0142] ② If there is no candidate initial raster with the same vegetation type as any initial raster, there is no target raster, and therefore no initial raster will be merged with the target raster.

[0143] ③ If there is a candidate initial raster with the same vegetation type as any initial raster, then:

[0144] If there is only one candidate initial grid (e.g., grid u) that has the same vegetation type as any initial grid, then grid u is determined as the target grid, and thus any initial grid (e.g., grid i) will be merged with the target grid (e.g., grid u).

[0145] If there are multiple candidate initial graticets (e.g., graticets u and v) that contain the same vegetation type as any initial graticet, then the area Su of the vegetation of the same type in graticet u is determined, and the area Sv of the vegetation of the same type in graticet v is determined. If Su > Sv, then graticet u is determined as the target graticet, and thus any initial graticet (e.g., graticet i) is merged with the target graticet (e.g., graticet u). If Sv > Su, then graticet v is determined as the target graticet, and thus any initial graticet (e.g., graticet i) is merged with the target graticet (e.g., graticet v). If Sv = Su, then graticet u and graticet v are randomly selected as the target graticet, and thus any initial graticet is merged with the target graticet.

[0146] (3) If there is only one candidate initial grid (such as grid u) that includes shrub type vegetation but does not include forest type vegetation, then grid u will be determined as the target grid, and any initial grid (such as grid i) will be merged with the target grid (such as grid u).

[0147] (4) If there are multiple candidate initial rasters (e.g., raster u and raster v) that include shrub-type vegetation but not forest-type vegetation, then determine the area Su of shrub-type vegetation included in raster u, and determine the area Sv of shrub-type vegetation included in raster v. If Su > Sv, then raster u is determined as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster u). If Sv > Su, then raster v is determined as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster v). If Sv = Su, then raster u and raster v are randomly selected as the target raster, and any initial raster will be merged with the target raster.

[0148] c.2 When the slope aspect of the monitored area is a sunny slope, it means that any initial grid cell includes shrub and forest types, that is, no initial grid cell has grassland type vegetation. If any initial grid cell is merged with an initial grid cell that has grassland type vegetation, the merged grid cell will be affected by grassland type vegetation. Therefore, the target grid cell cannot have grassland type vegetation.

[0149] (1) Determine whether there are candidate initial grids that include shrub-type vegetation but not grassland-type vegetation.

[0150] (2) If there are no candidate initial grids that include shrub-type vegetation but exclude grassland-type vegetation, then:

[0151] ① Determine whether there are any candidate initial rasters with the same vegetation type as any initial raster.

[0152] ② If there is no candidate initial raster with the same vegetation type as any initial raster, there is no target raster, and therefore no initial raster will be merged with the target raster.

[0153] ③ If there is a candidate initial raster with the same vegetation type as any initial raster, then:

[0154] If there is only one candidate initial grid (e.g., grid u) that has the same vegetation type as any initial grid, then grid u is determined as the target grid, and thus any initial grid (e.g., grid i) will be merged with the target grid (e.g., grid u).

[0155] If there are multiple candidate initial graticets (e.g., graticets u and v) that contain the same vegetation type as any initial graticet, then the area Su of the vegetation of the same type in graticet u is determined, and the area Sv of the vegetation of the same type in graticet v is determined. If Su > Sv, then graticet u is determined as the target graticet, and thus any initial graticet (e.g., graticet i) is merged with the target graticet (e.g., graticet u). If Sv > Su, then graticet v is determined as the target graticet, and thus any initial graticet (e.g., graticet i) is merged with the target graticet (e.g., graticet v). If Sv = Su, then graticet u and graticet v are randomly selected as the target graticet, and thus any initial graticet is merged with the target graticet.

[0156] (3) If there is only one candidate initial grid (such as grid u) that includes shrub type vegetation but not grassland type vegetation, then grid u will be determined as the target grid, and any initial grid (such as grid i) will be merged with the target grid (such as grid u).

[0157] (4) If there are multiple candidate initial rasters (e.g., raster u and raster v) that include shrub-type vegetation but not grassland-type vegetation, then determine the area Su of shrub-type vegetation included in raster u, and determine the area Sv of shrub-type vegetation included in raster v. If Su > Sv, then raster u is determined as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster u). If Sv > Su, then raster v is determined as the target raster, and any initial raster (e.g., raster i) will be merged with the target raster (e.g., raster v). If Sv = Su, then raster u and raster v are randomly selected as the target raster, and any initial raster will be merged with the target raster.

[0158] At this point, all initial rasters containing multiple vegetation types will be merged with their adjacent target rasters, and the merged rasters will all be the first rasters.

[0159] The first grid either contains only one type of vegetation, or mainly contains vegetation of the target type, or is composed of merging vegetation of the same type.

[0160] 104. Obtain the historical temperature, historical humidity, and historical wind speed of each first grid cell.

[0161] In step 104, the historical temperature, historical humidity, and historical wind speed of each first grid can be obtained from data such as temperature, humidity, and wind speed released by meteorological departments, etc.

[0162] Alternatively, a large number of temperature, humidity, and wind speed sensors can be evenly distributed within the monitoring area using the Internet of Things (IoT) to ensure that, regardless of the division, there will always be at least one temperature, humidity, and wind speed sensor in the first grid. Each temperature, humidity, and wind speed sensor collects temperature, humidity, and wind speed data at various locations within the monitoring area. In step 104, the temperature, humidity, and wind speed data collected by the temperature, humidity, and wind speed sensors located in each of the first grids are obtained. If there are multiple temperature, humidity, and wind speed sensors in a single first grid, then in step 104, the average temperature, average humidity, and average wind speed data collected by all the temperature, humidity, and wind speed sensors in that first grid at the same time are obtained.

[0163] 105. Based on historical temperature, historical humidity, and historical wind speed, the first grid is processed to obtain the second grid.

[0164] The implementation process of step 105 is as follows:

[0165] 105-1, Determine the temperature threshold, humidity threshold, and wind speed threshold based on the slope direction corresponding to each first grid.

[0166] The process of determining the temperature threshold T0, humidity threshold M0, and wind speed threshold W0 based on the slope aspect corresponding to each first grid cell is as follows:

[0167] If the slope corresponding to any first grid cell is a shady slope, then the temperature threshold is determined to be the average temperature of the monitoring area, the humidity threshold is determined to be the average humidity of the monitoring area, and the wind speed threshold is determined to be the average wind speed of the monitoring area.

[0168] If the slope corresponding to any first grid cell is a sunny slope, then the temperature threshold is determined as the nighttime average temperature of the monitoring area, the humidity threshold is determined as the nighttime average humidity of the monitoring area, and the wind speed threshold is determined as the afternoon average wind speed of the monitoring area.

[0169] For example, if any first grid cell is grid cell a, and the slope corresponding to grid cell a is a shady slope, and the shady slope has short sunshine hours, lower temperature, and relatively small temperature difference, then the average temperature of the monitoring area can be determined as the temperature threshold T0, the average humidity of the monitoring area can be determined as the humidity threshold M0, and the average wind speed of the monitoring area can be determined as the wind speed threshold W0.

[0170] Let grid a be any first grid cell. If the slope corresponding to grid cell a is a sunny slope, and sunny slopes have long hours of sunshine, strong solar radiation, and relatively large temperature differences, then the average nighttime temperature of the monitoring area can be determined as the temperature threshold T0, the average nighttime humidity of the monitoring area can be determined as the humidity threshold M0, and the average nighttime wind speed of the monitoring area can be determined as the wind speed threshold W0.

[0171] 105-2, Based on the slope aspect corresponding to each first grid, determine the temperature threshold, humidity threshold, and wind speed threshold to determine the processing value of each first grid.

[0172] The processing value for each first grid cell is determined to be (α). T +α M )×α W .

[0173] Where, α T This is the value affected by temperature. Then α T =0, otherwise, α T =1,T max T0 is the maximum historical temperature, and T1 is the temperature threshold.

[0174] α M This is the value affected by humidity. Then α M =1, otherwise, α M =0, M max M0 represents the maximum historical humidity value, and M0 is the humidity threshold.

[0175] α W This is the wind speed influence value, if Then α W =1, otherwise, α W =2, W max W0 is the maximum historical wind speed, and W0 is the wind speed threshold.

[0176] For any first grid cell (e.g., grid cell a), This represents the ratio between the historical maximum temperature of grid a and the temperature threshold of grid a. This is a floor function. Increased temperature significantly reduces the moisture content of stagnant combustibles on the surface over 10 hours. This means In other words, if the historical maximum temperature of grid a is less than the temperature threshold of grid a, the temperature of grid a will not have a different impact on the surface moisture content of dead combustibles over 10 hours compared to other grids. This "no different impact" does not mean "no impact," but rather that the effect of temperature on grid a is not significantly different from the effect of temperature on other grids. Therefore, α T =0. If This means In other words, the historical maximum temperature of grid a is not less than the temperature threshold of grid a. The temperature of grid a may have a different impact on the surface moisture content of dead combustibles over 10 hours compared to other grids. Therefore, α T =1. α T This characterizes whether temperature has a different effect on grid a than on other grids.

[0177] This represents the ratio between the historical maximum humidity of grid a and the humidity threshold of grid a. A decrease in humidity significantly reduces the moisture content of dead combustibles on the surface over 10 hours. If... This means In other words, if the historical maximum humidity of grid a is less than the humidity threshold of grid a, the humidity of grid a will significantly reduce the moisture content of the 10-hour dead combustible material at the surface of grid a, meaning it has a different impact on grid a than on other grids. This "different impact" does not mean no impact, but rather that the impact of humidity on grid a is greater than its impact on other grids; therefore, α M =1. If This means In other words, the historical maximum humidity of grid a is not less than the humidity threshold of grid a. The humidity of grid a may not have a different impact on the surface moisture content of dead combustibles over 10 hours compared to other grids. Therefore, α M =0. α M This characterizes whether humidity has a different effect on grid a than on other grids.

[0178] The ratio between the historical maximum wind speed of grid a and the wind speed threshold of grid a shows that increased wind speed significantly reduces the moisture content of dead combustibles on the surface over 10 hours. This means In other words, if the historical maximum wind speed of grid a is less than the wind speed threshold for grid a, the wind speed of grid a will not have a different impact on the surface moisture content of the dead combustible material at grid a compared to other grids over 10 hours. "No different impact" here does not mean "no impact," but rather that the impact of wind speed on grid a is not significantly different from the impact on other grids. However, wind speed also has a promoting effect on temperature and humidity. Even though the impact of wind speed on grid a is not significantly different from the impact on other grids, the promoting effect of wind speed on temperature and humidity will be considered, resulting in α. W =1. If This means In other words, the historical maximum wind speed of grid a is not less than the wind speed threshold of grid a. The wind speed of grid a may have a different impact on the surface moisture content of dead combustibles over 10 hours compared to other grids. Considering the promoting effect of wind speed on temperature and humidity, α... W =2. α T This characterizes whether wind speed has a different effect on grid a than on other grids.

[0179] By using the temperature threshold T0, humidity threshold M0, and wind speed threshold W0, the degree of anomaly of the first grid cell compared to other first grid cells can be obtained regarding the main factors affecting moisture content, namely temperature, humidity, and wind speed. T +αM )×α W .

[0180] Due to α T =0 or α T =1, α M =0 or α M =1, then (α) T +α M The value of α can be 0, 1, or 2. W =1 or α W =2, then (α) T +α M )×α W The value can be 0, 1, 2 or 4.

[0181] The larger the processing value, the higher the degree of anomaly of the first grid compared to other first grids. Grids with higher degree of anomaly need to be accurately monitored by multiple moisture content monitoring units to avoid the monitoring value obtained by a single moisture content monitoring unit failing to accurately reflect the moisture content problem in the first grid.

[0182] 105-3, split the first grid according to the processing value to obtain the second grid.

[0183] A. For the first grid cell with a processing value of 0, it indicates that the environment's influence on it is similar to its influence on other first grid cells. Therefore:

[0184] If the first grid is the grid obtained in step 102 (i.e., the value in the first grid includes a type of vegetation, and the length of the first grid is the effective sensing distance r of the moisture content sensor), this first grid can accurately monitor the moisture content of the dead combustibles on the ground surface in the grid over 10 hours through a moisture content sensor. Therefore, this first grid is directly identified as the second grid.

[0185] If the first grid is the grid obtained directly from the initial grid in step 103 because there is no target grid (i.e., without merging two initial grids), this type of first grid may not be able to accurately monitor the surface moisture content of stagnant combustibles over 10 hours using a single moisture content sensor due to its inclusion of multiple vegetation types. Therefore, this type of first grid is split into four grids, each of which becomes a second grid. Each second grid has a length of [missing information]. A square, such as Figure 7 As shown.

[0186] B. For the first grid cell with a non-zero value, it is split into P×P grid cells.

[0187] If the value to be processed is not greater than 3, then P = 2; otherwise, P = 3.

[0188] In other words, the first grid cell with a non-zero value will be split. If the value is 1 or 2, the first grid cell will be split into 4 grid cells, each of which will be a second grid cell. If the value is 4, the first grid cell will be split into 9 grid cells, each of which will be a second grid cell.

[0189] When splitting, the length of the first grid is divided into 3 equal segments, and the width is also divided into 3 equal segments, forming 9 grids.

[0190] By dividing the first grid with a higher degree of anomaly into more second grids, and then installing more moisture content monitoring units in the first grid with a higher degree of anomaly, the moisture content of the first grid can be accurately monitored.

[0191] 106. Determine the preset position in each of the second grid cells.

[0192] For example, the center position of the second grid can be set as the preset position.

[0193] The first grid is obtained based on the vegetation type, with a side length equal to the effective sensing distance r of the moisture content sensor. After obtaining the first grid, it is further divided into second grids according to the external environmental conditions that mainly affect the moisture content within the grid. This ensures that each second grid has a relatively stable external environment. A moisture content monitoring unit is placed in each second grid, and the moisture content of each second grid can be obtained through this monitoring unit.

[0194] 2. Data Processing Unit

[0195] The data processing unit includes: a second wireless communication module and a processing module.

[0196] The second wireless communication module supports the LoRa / NB-IoT protocol and establishes communication connections with each of the first wireless communication modules.

[0197] The processing module processes the electrical signals to obtain the moisture content of the dead combustibles on the ground surface after 10 hours.

[0198] If the moisture content sensor also integrates a miniature temperature sensor, and the temperature sensor collects the ambient temperature of the wooden stick probe, and this ambient temperature is sent to the processing module through a communication connection, then the processing module can compensate for the ambient temperature when processing the electrical signal to obtain the moisture content of the dead combustible material on the ground surface after 10 hours.

[0199] For example, the processing module receives electrical signals transmitted by each moisture content monitoring unit (if the moisture content monitoring unit also transmits ambient temperature, the processing module also receives the ambient temperature transmitted by the moisture content monitoring unit), and converts them into moisture content through a built-in algorithm (if there is ambient temperature, it will also be combined with a temperature compensation model) to obtain the moisture content of dead combustibles on the surface over 10 hours.

[0200] The processing module processes the electrical signals to obtain the moisture content of the dead combustibles on the ground surface after 10 hours. The processing module also compensates for the ambient temperature when processing the electrical signals to obtain the moisture content of the dead combustibles on the ground surface after 10 hours. The processing process adopts existing processes, such as calculating the moisture content by detecting the change in the dielectric constant between the electrodes, which will not be elaborated on here.

[0201] In addition, the surface 10-hour dead combustible moisture content monitoring system provided in this embodiment may also include: a protective cover.

[0202] The protective cover is a breathable and water-permeable membrane (allowing water exchange while blocking soil particles), and the top is equipped with an arc-shaped deflector (to prevent direct erosion by rainfall).

[0203] The moisture content sensor is covered with a protective sleeve. For example, the outer layer of the wooden stick probe is wrapped with a protective sleeve (i.e., the outer layer of the wooden stick probe is wrapped with a breathable and water-permeable membrane). This protective sleeve allows the wooden stick probe to exchange moisture, blocks soil particles, and has an arc-shaped guide shroud on top to prevent rainwater from directly washing over the wooden stick probe.

[0204] This embodiment relates to a surface 10-hour dead combustible material moisture content monitoring system. The system includes a moisture content monitoring unit and a data processing unit. The moisture content monitoring unit includes a moisture content sensor and a first wireless communication module. The data processing unit includes a second wireless communication module and a processing module. The first wireless communication module and the second wireless communication module establish a communication connection. The moisture content sensor includes a wooden probe and a sensing module. The wood material of the wooden probe is homologous to the wood material of the surface 10-hour dead combustible material, and an electrode is embedded within the probe. The sensing module excites the electrode and collects the corresponding electrical signal. The electrical signal is sent to the processing module via the communication connection. The processing module processes the electrical signal to obtain the surface 10-hour dead combustible material moisture content. The system described in this embodiment can accurately monitor the surface 10-hour dead combustible material moisture content.

[0205] Since the systems / devices described in the above embodiments of the present invention are systems / devices used to implement the methods of the above embodiments of the present invention, those skilled in the art can understand the specific structure and modifications of the systems / devices based on the methods described in the above embodiments of the present invention, and therefore will not be repeated here. All systems / devices used in the methods of the above embodiments of the present invention fall within the scope of protection of the present invention.

[0206] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0207] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions.

[0208] It should be noted that any reference numerals placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In claims that enumerate several means, several of these means may be embodied by the same hardware. The use of the terms first, second, third, etc., is merely for convenience of expression and does not indicate any order. These terms can be understood as part of the component names.

[0209] Furthermore, it should be noted that in the description of this specification, the terms "one embodiment," "some embodiments," "embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of the present invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Furthermore, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of different embodiments or examples.

[0210] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the claims should be interpreted to include both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0211] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, then this invention should also include these modifications and variations.

Claims

1. A surface 10-hour time-delayed moisture content monitoring system for combustible materials, characterized in that, The system includes: a moisture content monitoring unit and a data processing unit; The moisture content monitoring unit includes: a moisture content sensor and a first wireless communication module; The data processing unit includes: a second wireless communication module and a processing module; The first wireless communication module establishes a communication connection with the second wireless communication module. The moisture content sensor includes a wooden probe and a sensing module; the wood material of the wooden probe is of the same origin as the wood material of the dead combustible material on the ground surface after 10 hours, and an electrode plate is embedded in the wooden probe; the sensing module excites the electrode plate and collects the corresponding electrical signal; the electrical signal is sent to the processing module through the communication connection; the processing module processes the electrical signal to obtain the moisture content of the dead combustible material on the ground surface after 10 hours; The moisture content monitoring unit is located on a positioning bracket at a preset position; The positioning bracket is 3cm to 8cm above the ground; The preset position is determined through the following steps: The slope aspect and vegetation type of the monitoring area are obtained; the vegetation types are: forest, shrubland, and grassland; the slope aspect is shady slope and sunny slope. If the number of vegetation types is 1, then the target circumscribed square of the monitoring area is rasterized to obtain the first grid; wherein, the target circumscribed square is the smallest square that includes the monitoring area and whose side length is a multiple of the effective sensing distance of the moisture content sensor; If the number of vegetation types is not 1, the target circumscribed square of the monitoring area is rasterized to obtain an initial raster. The initial raster is then merged according to the vegetation type to obtain the first raster, which includes: Determine the target type; wherein, if the slope aspect of the monitoring area is a shady slope, then when any initial grid cell includes forest type vegetation, the target type is forest type; when any initial grid cell does not include forest type vegetation but includes shrub type vegetation, the target type is shrub type; if the slope aspect of the monitoring area is a sunny slope, then when any initial grid cell includes grassland type vegetation, the target type is grassland type; when any initial grid cell does not include grassland type vegetation but includes shrub type vegetation, the target type is shrub type. Obtain candidate initial grids; wherein, the candidate initial grids are the upper initial grid, lower initial grid, left initial grid, and right initial grid of any initial grid; Determine if there are any candidate initial grids that include the target type; If there are candidate initial grids that include the target type, then any of the initial grids is merged with the target grid; wherein, if the target type is forest or grassland, the area of ​​the target type vegetation included in the target grid is the largest; if the target type is shrub, then when the slope aspect of the monitoring area is a shady slope, the target grid does not include forest vegetation, but the area including shrub vegetation is the largest; when the slope aspect of the monitoring area is a sunny slope, the target grid does not include grassland vegetation, but the area including shrub vegetation is the largest. If no candidate initial grid includes the target type, then any initial grid is merged with the target grid; wherein the target grid and any initial grid include the same vegetation type, and the area of ​​the vegetation of the same type included in the target grid is the largest; Obtain the historical temperature, historical humidity, and historical wind speed for each first grid cell; The first grid is processed based on historical temperature, historical humidity, and historical wind speed to obtain the second grid; Determine the preset position in each of the second grid cells; The process of processing the first grid based on historical temperature, historical humidity, and historical wind speed to obtain the second grid includes: The temperature threshold, humidity threshold, and wind speed threshold are determined based on the slope aspect corresponding to each first grid cell. The processing value for each first grid cell is determined based on the temperature threshold, humidity threshold, and wind speed threshold determined by the slope aspect corresponding to each first grid cell. The first grid is split based on the processed value to obtain the second grid.

2. The system according to claim 1, characterized in that, The wooden probe is 15cm long and 1.5cm in diameter.

3. The system according to claim 1, characterized in that, The sensing module excites the electrode sheet at a fixed frequency of 100kHz.

4. The system according to claim 1, characterized in that, The moisture content sensor also integrates a miniature temperature sensor; The temperature sensor collects the ambient temperature of the wooden stick probe; the ambient temperature is transmitted to the processing module via the communication connection. When the processing module processes the electrical signal, it compensates for the ambient temperature to obtain the moisture content of the stagnant combustibles on the ground surface after 10 hours.

5. The system according to claim 1, characterized in that, The system also includes a protective sleeve; The protective sleeve is a breathable and water-permeable membrane with an arc-shaped flow guide at the top; The moisture content sensor is covered by the protective sleeve.

6. The system according to claim 1, characterized in that, The temperature threshold, humidity threshold, and wind speed threshold are determined based on the slope aspect corresponding to any first grid cell, including: If the slope direction corresponding to any first grid is a shady slope, then the temperature threshold is determined to be the average temperature of the monitoring area, the humidity threshold is determined to be the average humidity of the monitoring area, and the wind speed threshold is determined to be the average wind speed of the monitoring area. If the slope corresponding to any first grid cell is a sunny slope, then the temperature threshold is determined to be the nighttime average temperature of the monitoring area, the humidity threshold is determined to be the nighttime average humidity of the monitoring area, and the wind speed threshold is determined to be the afternoon average wind speed of the monitoring area.

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