Forestry intelligent supervision method and system based on edge calculation

Abstract

The invention relates to an intelligent forestry supervision method and system based on edge computing, and the method comprises the steps: carrying out the real-time monitoring of a forestry condition according to monitoring equipment, and obtaining forestry information; judging whether a disaster occurs or not according to a preset information range and the forestry information; if the temperature and the carbon dioxide concentration are both larger than the information range, information related to disaster area early warning is sent to an administrator terminal; if the temperature or the carbon dioxide concentration is larger than the information range, a rainfall record is searched in a preset rainfall database; and if the precipitation amount in the preset period is smaller than a preset threshold value, information related to disaster early warning is sent to an administrator terminal. According to the invention, forestry disasters are early warned according to the temperature and the concentration of carbon dioxide, the forest fire is monitored in real time and personnel rescue is carried out through the unmanned aerial vehicle and a fire spreading algorithm, the efficiency and convenience of forestry management are improved, and forestry areas can be continuously monitored and managed in real time.

Description

Technical Field

[0001] The present application relates to the field of forestry management technology, and in particular to a forestry intelligent supervision method and system based on edge computing. Background Art

[0002] Forestry refers to the production sector that protects the ecological environment and maintains ecological balance, cultivates and protects forests to obtain timber and other forest products, and utilizes the natural characteristics of forests to play a protective role. It is an important part of the national economy. Forestry is a basic industry and social welfare undertaking that cultivates, protects, and utilizes forest resources in the human and biosphere through advanced science and technology and management methods, fully utilizes the multiple benefits of forests, and can sustainably manage forest resources and promote the coordinated development of population, economy, society, environment, and resources.

[0003] The effective acquisition of forest environmental information is particularly important for the growth of forestry, so monitoring and maintaining forest areas is the general trend. Effective information can significantly reduce the loss of forest resources, increase forest production, and maintain the health and stability of forest development. At present, forestry management is mainly carried out through manual patrols of forestry areas, monitoring of key entry and exit points of forestry areas, and the coordinated work of multiple groups of personnel to complete the management of forestry areas.

[0004] Regarding the above-mentioned related technologies, it is believed that the above-mentioned forestry management methods require a lot of manpower and material resources for field surveys, and their monitoring is difficult and costly, and the monitoring data is scattered, making it difficult to achieve continuous real-time monitoring, which is not convenient for the management of forestry areas. Summary of the invention

[0005] In order to improve forestry management methods, a lot of manpower and material resources are needed for field surveys. The monitoring is difficult and costly, the monitoring data is scattered, it is difficult to achieve continuous real-time monitoring, and it is not convenient to manage forestry areas. This application provides a forestry intelligent supervision method and system based on edge computing.

[0006] In the first aspect, the present application provides a forestry intelligent supervision method based on edge computing, which adopts the following technical solutions: including:

[0007] Monitor forestry conditions in real time using monitoring equipment to obtain forestry information, the forestry information at least including: temperature and carbon dioxide concentration;

[0008] Determine whether a disaster has occurred based on a preset information range and the forestry information;

[0009] If the temperature and the carbon dioxide concentration are both greater than the information range, sending information related to the disaster warning to the administrator terminal;

[0010] If the temperature or the carbon dioxide concentration is greater than the information range, searching for precipitation records in a preset precipitation database;

[0011] If the precipitation is less than the preset threshold within the preset period, information related to the disaster warning is sent to the administrator terminal.

[0012] Through the above technical scheme, the system monitors the forestry area in real time according to the monitoring equipment and obtains forestry information. The system determines whether a disaster occurs in the forestry area according to the information range and forestry information. If the system detects that both the temperature and the carbon dioxide concentration are greater than the information range, the system sends information related to the disaster warning to the management. If the system detects that one of the temperature or the carbon dioxide concentration is greater than the preset information range, the system searches for precipitation records in the precipitation database. If the system detects that the precipitation within the preset period is less than the threshold, the system sends information related to the disaster warning to the administrator terminal, thereby issuing warnings for forestry disasters based on the temperature and carbon dioxide concentrations, and then further judging the disaster based on the precipitation. This greatly improves the efficiency and convenience of forestry management, reduces the waste of human resources, and enables continuous real-time monitoring and management of forestry areas.

[0013] Optionally, the forestry information also includes: wind speed and wind direction;

[0014] After determining whether a disaster has occurred according to the preset information range and the forestry information, the method further includes:

[0015] Determine the direction of fire spread according to the wind direction;

[0016] Calculating the fire area according to the temperature variation;

[0017] Control the drone to go to the fire area to find the fire location;

[0018] Searching a preset fire database for a fire spread grade corresponding to the wind speed;

[0019] The fire spread direction, the fire location and the fire spread level are sent to an administrator terminal.

[0020] Through the above technical scheme, the system determines the direction of fire spread according to the wind direction, and estimates the location of the fire area according to the temperature changes of different monitoring devices. That is, according to the location of the monitoring equipment and the detected temperature changes, the direction of the fire and the distance from the monitoring equipment can be obtained. Then the system controls the drone to go to the fire area to find the specific location of the fire. The system then searches the fire database for the fire spread level corresponding to the wind speed. The system sends the fire spread level, fire location and fire spread direction to the administrator terminal, so as to quickly determine the fire situation according to the wind speed, wind direction and temperature changes, so as to facilitate firefighters to quickly have a preliminary understanding of the fire situation, so as to quickly deal with the fire and reduce the harm caused by the fire.

[0021] After sending the fire spreading direction, the fire location and the fire spreading level to the administrator terminal, the method further includes:

[0022] Retrieving the forestry personnel entry and exit table according to the edge computing platform, and judging whether there are people in distress according to the forestry personnel entry and exit table and the fire location;

[0023] If it is determined that there are people in distress or a rescue order is received, the risk area is calculated according to the fire spread direction, the fire location and the fire spread level;

[0024] Control the drone group to conduct a carpet search of the risk area and take photos at preset intervals to obtain pictures of the risk area;

[0025] Performing real-time person recognition on the risk area image according to the edge computing platform, determining and uploading the rescue location;

[0026] According to the fire spreading direction and the fire location, dynamically planning a rescue guidance route based on a preset fire route algorithm;

[0027] The drone is controlled to guide the trapped persons along the rescue guidance route.

[0028] Through the above technical solution, whether there are trapped persons can be quickly detected according to the entry and exit table of forestry personnel. Through the rapid response of the edge computing platform, the location of trapped persons or special objects such as vehicles can be timely determined, and rescue personnel can be searched for in time. According to factors such as the direction of fire spread, the rescue route is quickly calculated based on the fire route algorithm and real-time dynamic adjustments are made according to the changes in the fire, so that drones can safely guide trapped persons and rescue personnel from fire-hazardous areas in time to improve the safety of forestry management.

[0029] Optionally, the tree density and the forest area are detected by monitoring equipment according to a preset detection cycle, and the tree density and the forest area are stored in a preset forestry database;

[0030] When a forestry report request is received, the forestry report request includes: a requested year, and retrieving the forestry area and the forest density corresponding to the requested year in the forestry database;

[0031] Filling the forest area, the tree density and the corresponding time into a preset statistical chart according to a preset statistical chart component;

[0032] The statistical graph is sent to a user terminal.

[0033] Through the above technical solution, the system regularly detects the forest density and forest area according to the monitoring period, and stores the detected data in the forestry database. When receiving a forestry report request, the system retrieves the forest area and forest density corresponding to the requested year from the forestry database. The system fills the forest area, tree density and corresponding time into the statistical chart according to the statistical chart component, and finally sends the statistical chart to the user end, so that the user can intuitively see the changes in forestry and plan the forestry according to the statistical chart.

[0034] Optionally, before filling the forest area, the forest density and the corresponding time into a preset statistical chart according to a preset statistical chart component, the method further includes:

[0035] Calculate the number of trees based on the tree density and the forest area;

[0036] Calculate the trend of changes in the requested years based on the number of trees;

[0037] Excluding the target years with a decreasing trend from the requested years, to obtain the increasing years;

[0038] Searching the forestry database for forestry logging information corresponding to the increase years, wherein the forestry logging information includes: logging years, logging areas, and logging quantities;

[0039] According to the said increase years, the number of trees corresponding to the said felling years is compared with the said felling number to calculate the average felling relative value;

[0040] Calculate the estimated felling quantity based on the number of trees corresponding to the current year and the average felling relative value;

[0041] The estimated felling quantity is sent to the user terminal.

[0042] Through the above technical solution, the system calculates the number of trees according to the forestry density and forestry area, and then calculates the changing trend of forestry in the requested years according to the number of trees. The system excludes the years with reduced changing trend in the requested years, and the remaining years are increasing years. The system searches the forestry database for forestry logging information corresponding to the increasing years, and then divides the number of loggings in the same year by the number of trees to calculate the relative value of logging in the same year, and then averages the relative values ​​of loggings for all increasing years to obtain the average relative value of logging. The system then calculates the expected number of loggings this year according to the number of trees corresponding to the current year and the average relative value of logging, and sends the expected number of loggings to the user end, so as to estimate the number of loggings based on the changes in forestry in recent years, thereby reducing the situation where excessive logging affects forestry development, so that users can quickly determine the number of trees that can be logged this year.

[0043] Optionally, when receiving a logging application, searching a preset regional database for a logging area with the highest tree density;

[0044] Sending the logging area to a user terminal;

[0045] When it is detected that the tree density in the fellable area is lower than a preset threshold, a fellable area with the largest tree density is searched again and sent to the user end.

[0046] Through the above technical solution, when the system receives a logging application, the system searches for the logging area with the highest forest density and sends the logging area to the user end. When the system detects that the forest density in the logging area is lower than the threshold, it searches for the logging area with the highest forest density again and sends it to the user end, thereby reducing the situation where the forest density in some areas is too low, so as to reasonably arrange the logging quantity in each area.

[0047] Optionally, the logging application includes an application quantity;

[0048] When it is detected that the tree density in the fellable area is lower than a preset threshold, the fellable area with the largest tree density is searched again and sent to the user end, the method further includes:

[0049] Searching the area database for the area corresponding to the logging area;

[0050] Real-time detection of the regional density of the fellable area, and calculation of the number of felled trees according to the change of the regional density and the area of ​​the area;

[0051] When it is detected that the number of trees cut down reaches the number of trees applied for, a prompt related to the completion of the number of trees cut down is sent to the user terminal.

[0052] Through the above technical solution, the system searches for the area of ​​the fellable area, detects the regional density of the fellable area in real time, and calculates the number of felled trees based on the changes in regional density and regional area. When it is detected that the number of felled trees has reached the applied number, the system sends a prompt related to the completion of the felling quantity to the user end, thereby reducing the situation where the number of felled trees seriously exceeds the standard, so as to protect forestry in accordance with regulations.

[0053] Optionally, searching a preset protection database for protected tree information corresponding to the fellable area, the protected tree information including: tree coordinates, tree pictures, and tree types;

[0054] Marking the locations of the tree coordinates on a preset forestry area map;

[0055] The marked forestry area map, the tree pictures and the tree types are sent to the user end.

[0056] By adopting the above technical solution, the system searches for the information of protected trees in the logging area and marks them on the forest area map according to the tree coordinates. At the same time, the system sends the marked forest area map, tree pictures and tree types to the user end, thereby reducing the occurrence of accidental felling of protected tree species and facilitating the protection of key trees.

[0057] In the second aspect, the present application provides a forestry intelligent supervision device based on edge computing, which adopts the following technical solutions: including:

[0058] A monitoring module, used to monitor forestry conditions in real time according to monitoring equipment and obtain forestry information, wherein the forestry information includes at least: temperature and carbon dioxide concentration;

[0059] An analysis module, used to determine whether a disaster has occurred based on a preset information range and the forestry information;

[0060] A detection module, configured to send information related to disaster warning to an administrator terminal if both the temperature and the carbon dioxide concentration are greater than the information range;

[0061] A precipitation module, configured to search for precipitation records in a preset precipitation database if the temperature or the carbon dioxide concentration is greater than the information range;

[0062] The output module is used to send information related to disaster warning to the administrator terminal if the precipitation within a preset period is less than a preset threshold.

[0063] Through the above technical scheme, the system monitors the forestry area in real time according to the monitoring equipment and obtains forestry information. The system determines whether a disaster occurs in the forestry area according to the information range and forestry information. If the system detects that both the temperature and the carbon dioxide concentration are greater than the information range, the system sends information related to the disaster warning to the management. If the system detects that one of the temperature or the carbon dioxide concentration is greater than the preset information range, the system searches for precipitation records in the precipitation database. If the system detects that the precipitation within the preset period is less than the threshold, the system sends information related to the disaster warning to the administrator terminal, thereby issuing warnings for forestry disasters based on the temperature and carbon dioxide concentrations, and then further judging the disaster based on the precipitation. This greatly improves the efficiency and convenience of forestry management, reduces the waste of human resources, and enables continuous real-time monitoring and management of forestry areas.

[0064] In a third aspect, the present application further provides a control device, the device comprising:

[0065] It includes a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed such as the above-mentioned forestry intelligent supervision method based on edge computing.

[0066] In a fourth aspect, the present application also provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed such as the above-mentioned edge computing-based forestry intelligent supervision method.

[0067] In summary, the present application includes at least one of the following beneficial technical effects:

[0068] 1. Early warning of forest disasters is carried out based on temperature and carbon dioxide concentration, and the disaster situation is further judged by precipitation, which greatly improves the efficiency and convenience of forestry management, reduces the waste of human resources, and can continuously monitor and manage forestry areas in real time.

[0069] 2. According to the number of trees corresponding to the current year and the average felling relative value, the estimated number of felled trees this year is calculated and sent to the user end, so as to estimate the number of felled trees based on the changes in forestry in recent years, thereby reducing the situation where excessive felling affects forestry development, so that users can quickly determine the number of trees that can be felled this year.

[0070] 3. When it is detected that the forest density of the logging area is lower than the threshold, the logging area with the largest forest density is re-searched and sent to the user end, thereby reducing the situation where the forest density in some areas is too low, so as to reasonably arrange the logging quantity in each area. BRIEF DESCRIPTION OF THE DRAWINGS

[0071] Figure 1This is a flow chart of a forestry intelligent supervision method based on edge computing in this application.

[0072] Figure 2 This is a structural block diagram of a forestry intelligent supervision device based on edge computing in this application.

[0073] Explanation of reference numerals: 210, monitoring module; 220, analysis module; 230, detection module; 240, precipitation module; 250, output module. DETAILED DESCRIPTION

[0074] The following combination Figure 1 - Figure 2 This application is described in further detail.

[0075] The embodiment of the present application discloses a forestry intelligent supervision method based on edge computing, and the execution subject is a forestry control system, hereinafter referred to as the system. At present, my country's forest resource survey is divided into three categories, among which the forest resource planning and design survey is referred to as the second-class survey. The second-class survey is the basis for the dynamic monitoring of forest resources by local governments. The results of the second-class survey are the basis for updating forest resource archives, formulating forest felling limits, planning and designing forestry projects, and forest resource management. It is one of the most important bases for scientific management of forestry and scientific decision-making of forestry policies. In this application, the monitoring equipment is composed of various sensors, drones and satellites, which can detect factors such as density, area, temperature, carbon dioxide concentration, wind direction and wind force in the forestry. Based on the edge computing platform, the forestry ecological environment data is collected, processed, analyzed and stored in real time through drones, and the forestry disaster situation is quickly responded to, thereby providing real-time and intelligent decision-making support for forestry ecological environment management and forestry fire disaster monitoring and early warning.

[0076] Reference Figure 1 , this application at least includes steps S10 to S50.

[0077] S10, real-time monitoring of forestry conditions is performed according to monitoring equipment to obtain forestry information.

[0078] Among them, forestry information at least includes: temperature and carbon dioxide concentration.

[0079] S20, judging whether a disaster occurs according to a preset information range and forestry information.

[0080] The information range is set according to the local forestry climate and the current time, and the information range is different in different time periods or seasons.

[0081] S30: If the temperature and the carbon dioxide concentration are both greater than the information range, information related to the disaster warning is sent to the administrator terminal.

[0082] S40: If the temperature or the carbon dioxide concentration is greater than the information range, then searching for precipitation records in a preset precipitation database.

[0083] The precipitation database records the precipitation amount and precipitation date in the local forestry area.

[0084] S50: If the precipitation in the preset period is less than the preset threshold, information related to the disaster warning is sent to the administrator terminal.

[0085] In this embodiment, the preset period is 40 days and the threshold is 30 ml.

[0086] Specifically, the system monitors the forestry area in real time based on the monitoring equipment to obtain forestry information. The system determines whether a disaster has occurred in the forestry area based on the information range and forestry information. If the system detects that both the temperature and the carbon dioxide concentration are greater than the information range, the system sends information related to the disaster warning to the management. If the system detects that one of the temperature or carbon dioxide concentration is greater than the preset information range, the system searches for precipitation records in the precipitation database. If the system detects that the precipitation within the preset period is less than the threshold, the system sends information related to the disaster warning to the administrator terminal, thereby issuing warnings for forestry disasters based on the temperature and carbon dioxide concentrations, and then further judging the disaster based on the precipitation. This greatly improves the efficiency and convenience of forestry management, reduces the waste of human resources, and enables continuous real-time monitoring and management of forestry areas.

[0087] In some embodiments, taking into account the problem of fire situation, in order to quickly understand the fire situation, the corresponding processing steps are as follows: determine the direction of fire spread according to wind direction; calculate the fire area according to temperature changes; control the drone to go to the fire area to find the fire location; search the fire spread level corresponding to the wind speed in the preset fire database; send the fire spread direction, fire location and fire spread level to the administrator terminal.

[0088] Among them, forestry information also includes: wind speed and wind direction. The fire area refers to one or more areas that have been divided in advance. The direction of fire spread is determined by the wind direction, and the fire spread level is determined by the wind force.

[0089] Specifically, the system determines the direction of fire spread based on the wind direction, and estimates the location of the fire area based on the temperature changes of different monitoring devices. That is, based on the location of the monitoring equipment and the detected temperature changes, the direction of the fire and the distance from the monitoring equipment can be obtained. The system then controls the drone to go to the fire area to find the specific location of the fire. The system then searches the fire database for the fire spread level corresponding to the wind speed. The system sends the fire spread level, fire location and fire spread direction to the administrator terminal, so as to quickly determine the fire situation based on the wind speed, wind direction and temperature changes, which makes it easier for firefighters to quickly gain a preliminary understanding of the fire situation, so as to quickly deal with the fire and reduce the harm caused by the fire.

[0090] In some embodiments, considering the problem of guiding trapped persons to quickly escape from fire danger areas, the corresponding processing steps are as follows: retrieve the forestry personnel entry and exit table according to the edge computing platform, and judge whether there are people in distress based on the forestry personnel entry and exit table and the fire location; if it is judged that there are people in distress or a rescue instruction is received, calculate the risk area according to the fire spread direction, the fire location and the fire spread level; control the drone group to conduct a carpet search and take pictures of the risk area at preset intervals to obtain pictures of the risk area; perform real-time character recognition on the risk area pictures according to the edge computing platform, determine and upload the rescue location; according to the fire spread direction and the fire location, dynamically plan the rescue guidance route based on the preset fire route algorithm; control the drone to guide the trapped persons according to the rescue guidance route.

[0091] Specifically, according to the entry and exit table of forestry personnel, it is possible to quickly determine whether there are trapped people. Through the rapid response of the edge computing platform, it is possible to promptly determine the location of trapped people or special objects such as vehicles, and search for rescue personnel in a timely manner. According to factors such as the direction of fire spread, the rescue route is quickly calculated based on the fire route algorithm and real-time dynamic adjustments are made according to the changes in the fire, so that drones can safely guide trapped people and rescue people from fire-prone areas in a timely manner, thereby improving the safety of forestry management.

[0092] In this embodiment, the fire spread speed, fire spread direction, fire intensity, etc. are calculated according to the Phoenix RapidFire fire spread model, and the influence of fire intensity, wind speed and terrain are comprehensively considered to determine the fire influence function. The formula is as follows:

[0093] F(x,y,t)=I(x,y,t)·(1+W v (x,y,t))·W t (x,y,t);

[0094] Among them, fire intensity I(x,y,t): directly reflects the severity of the fire. Wind speed effect Wv(x,y,t): the component of wind speed along the direction of fire spread will increase the fire, so take the cosine value of the angle between wind speed and fire direction, and take its positive value. Terrain effect Wt(x,y,t): the greater the slope, the faster the fire spreads, so an exponential function is used to amplify the effect of the slope.

[0095] Next, the rescue path is calculated using the path cost formula, which is as follows:

[0096]

[0097] h(n)=distance(n,G);

[0098] f(n)=g(n)+h(n);

[0099] Among them, g(n) is the actual cost, h(n) is the heuristic cost, f(n) is the complete cost, c(i,i+1) is the actual flight cost (such as distance) from node i to node i+1; λ is a weight factor used to adjust the proportion of fire impact in the total cost; F(x i ,y i ,t i ) refers to the fire impact at i in the use index; distance(n,G) is the straight-line distance from node n to the target point G. It should be understood that in the path planning algorithm, cost is an important concept used to measure the "price" or "cost" of going from one point to another. The cost can include many factors, such as distance, time, energy consumption, safety risks, etc. In forest fire rescue missions, the cost includes not only the traditional path length, but also safety factors such as the impact of the fire. In this way, the path with the lowest total cost is calculated to quickly find the optimal safe path.

[0100] At the same time, in a dynamic environment, the path needs to be recalculated based on the latest fire information. Assuming that at time t, the drone needs to move from the current position S to the target position G, and detects a new fire point or a change in the fire intensity, the optimal path is recalculated as follows:

[0101]

[0102] Among them, P(t+1) represents the optimal path at time t+1, p ∝ Represents a candidate path, which is one of all possible paths from the current drone position S to the target position G.

[0103] In some embodiments, taking into account the issue of organizing forestry conditions, in order for users to quickly understand the development of forestry, the corresponding processing steps are as follows: the tree density and forestry area are detected by monitoring equipment according to a preset detection period, and the tree density and forestry area are stored in a preset forestry database; when a forestry report request is received, the forestry report request includes: request year, and the forestry area and tree density corresponding to the requested year are retrieved from the forestry database; the forestry area, tree density and corresponding time are filled into a preset statistical chart according to a preset statistical chart component; and the statistical chart is sent to the user end.

[0104] The detection cycle is generally once every six months, and the requested period is the target period specified by the user, for example, from 2018 to 2022. The forestry database is a database for storing various forestry data, for example, forestry area data and density data. In the embodiment of the present application, the statistical chart component is G2plot.

[0105] Specifically, the system regularly detects the forest density and forest area according to the monitoring cycle, and stores the detected data in the forestry database. When receiving a forestry report request, the system retrieves the forest area and forest density corresponding to the requested year from the forestry database. The system fills the forest area, tree density and corresponding time into the statistical chart according to the statistical chart component, and finally sends the statistical chart to the user end, so that the user can intuitively see the changes in forestry and plan the forestry according to the statistical chart.

[0106] Furthermore, considering the situation of deforestation, in order to reasonably plan the number of deforestation, the corresponding processing steps are as follows: calculate the number of trees according to the forest density and the forestry area; calculate the changing trend in the requested years according to the number of trees; exclude the target year with a decreasing changing trend in the requested years to obtain the increasing years; search the forestry logging information corresponding to the increasing years in the forestry database, and the forestry logging information includes: logging years, logging areas and logging quantities; compare the number of trees corresponding to the logging years with the logging quantity according to the increasing years, and calculate the average logging relative value; calculate the expected logging quantity based on the number of trees corresponding to the current years and the average logging relative value; send the expected logging quantity to the user end.

[0107] Among them, the logging year refers to the year corresponding to forestry logging.

[0108] Specifically, the system calculates the number of trees based on the forestry density and forestry area, and then calculates the changing trend of forestry in the requested years based on the number of trees. The system excludes the years with a decreasing changing trend in the requested years, and the remaining years are increasing years. The system searches the forestry database for forestry logging information corresponding to the increasing years, and then divides the number of felled trees in the same year by the number of trees to calculate the relative value of felling in the same year, and then averages the relative values ​​of felling trees for all increasing years to obtain the average relative value of felling. The system then calculates the expected number of felled trees this year based on the number of trees corresponding to the current year and the average relative value of felling trees, and sends the expected number of felled trees to the user end, so as to estimate the number of felled trees based on the changes in forestry in recent years, thereby reducing the situation where excessive number of felled trees affects forestry development, so that users can quickly determine the number of trees that can be felled this year.

[0109] Furthermore, considering the issue of logging supervision, in order to reduce excessive logging in the same area, the corresponding processing steps are as follows: when a logging application is received, the logging area with the highest tree density is searched in the preset regional database; the logging area is sent to the user end; when it is detected that the tree density in the logging area is lower than the preset threshold, the logging area with the highest tree density is searched again and sent to the user end.

[0110] In this embodiment, the threshold is set according to factors such as tree types in the local forestry, and the regional database is used to store data such as forest density and regional area of ​​each region that has been divided in advance.

[0111] Specifically, when the system receives a logging application, it searches for the logging area with the highest forest density and sends the logging area to the user end. When the system detects that the forest density in the logging area is lower than the threshold, it searches for the logging area with the highest forest density again and sends it to the user end, thereby reducing the situation where the forest density in some areas is too low, so as to reasonably arrange the logging quantity in each area.

[0112] Furthermore, considering the problem of over-felling, the corresponding processing steps are as follows: the felling application includes the application quantity; the area corresponding to the fellable area is searched in the regional database; the regional density of the fellable area is detected in real time, and the number of felled trees is calculated according to the change of regional density and regional area; until it is detected that the number of felled trees reaches the application quantity, a prompt related to the completion of the felling quantity is sent to the user end.

[0113] In an embodiment of the present application, trees in an area are photographed by using equipment such as drones, and the density of the area is estimated based on the photographs.

[0114] Specifically, the system searches for the area of ​​the fellable area, detects the regional density of the fellable area in real time, and calculates the number of felled trees based on the changes in regional density and regional area. When it is detected that the number of felled trees has reached the applied number, the system sends a prompt to the user terminal regarding the completion of the felling quantity, thereby reducing the situation where the number of felled trees seriously exceeds the standard, so as to protect forestry in accordance with regulations.

[0115] In some embodiments, taking into account the issue of key tree protection, in order to reduce the accidental felling of protected trees, the corresponding processing steps are as follows: searching for protected tree information corresponding to the fellable area in a preset protection database, the protected tree information including: tree coordinates, tree pictures and tree types; marking the location of the tree coordinates on a preset forestry area map; and sending the marked forestry area map, tree pictures and tree types to the user end.

[0116] Among them, the protection database is used to record the information of protected species within the forestry scope.

[0117] Specifically, the system searches for information on protected trees in areas where logging is allowed, and marks them on forest area maps based on the tree coordinates. At the same time, the system sends the marked forest area maps, tree images, and tree species to the user end, thereby reducing the occurrence of accidental felling of protected tree species and facilitating the protection of key trees.

[0118] The implementation principle of an edge computing-based forestry intelligent supervision method in an embodiment of the present application is as follows: the system monitors the forestry area in real time according to the monitoring equipment to obtain forestry information. The system determines whether a disaster occurs in the forestry area according to the information range and the forestry information. If the system detects that both the temperature and the carbon dioxide concentration are greater than the information range, the system sends information related to the disaster warning to the management. If the system detects that one of the temperature or the carbon dioxide concentration is greater than the preset information range, the system searches for precipitation records in the precipitation database. If the system detects that the precipitation within a preset period is less than the threshold, the system sends information related to the disaster warning to the administrator terminal, thereby issuing warnings for forestry disasters based on the temperature and carbon dioxide concentrations, and then further judging the disaster based on the precipitation. This greatly improves the efficiency and convenience of forestry management, reduces the waste of human resources, and enables continuous real-time monitoring and management of forestry areas.

[0119] Figure 1 FIG. 1 is a flow chart of a forestry intelligent supervision method based on edge computing in one embodiment. It should be understood that although Figure 1The steps in the flowchart are shown in sequence as indicated by the arrows, but the steps are not necessarily executed in the order indicated by the arrows; unless otherwise specified in this document, there is no strict order restriction for the execution of the steps, and the steps may be executed in other orders; and Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0120] Based on the same technical concept, Figure 2 The embodiment of the present application also provides a forestry intelligent supervision device based on edge computing, which adopts the following technical solution. The device includes:

[0121] The monitoring module 210 is used to monitor the forestry situation in real time according to the monitoring equipment and obtain forestry information, which includes at least: temperature and carbon dioxide concentration;

[0122] Analysis module 220, used to determine whether a disaster has occurred based on a preset information range and forestry information;

[0123] The detection module 230 is used to send information related to disaster warning to the administrator terminal if the temperature and the carbon dioxide concentration are both greater than the information range;

[0124] A precipitation module 240, for searching for precipitation records in a preset precipitation database if the temperature or carbon dioxide concentration is greater than the information range;

[0125] The output module 250 is used to send information related to disaster warning to the administrator terminal if the precipitation in a preset period is less than a preset threshold.

[0126] In some embodiments, the forestry information also includes: wind speed and direction;

[0127] The detection module 230 is also used to determine the direction of fire spread based on the wind direction;

[0128] Calculate the fire area based on the temperature changes;

[0129] Control the drone to go to the fire area to find the fire location;

[0130] Searching for the fire spread level corresponding to the wind speed in a preset fire database;

[0131] The fire spreading direction, fire location and fire spreading level are sent to the administrator terminal.

[0132] In some embodiments, the detection module 230 is further used to detect the tree density and forest area through monitoring equipment according to a preset detection cycle, and store the tree density and forest area in a preset forestry database;

[0133] When a forestry report request is received, the forestry report request includes: a requested year, and a forestry area and a forest density corresponding to the requested year retrieved from the forestry database;

[0134] Fill the forest area, forest density and corresponding time into the preset statistical chart according to the preset statistical chart component;

[0135] Send the statistical chart to the user end.

[0136] In some embodiments, the detection module 230 is further used to calculate the number of trees according to the tree density and the forest area;

[0137] Calculate the trend of the number of trees in the requested years;

[0138] Exclude the target years with decreasing trend from the requested years to obtain the increasing years;

[0139] Searching the forestry logging information corresponding to the increase years in the forestry database, the forestry logging information includes: logging years, logging areas and logging quantities;

[0140] According to the increase years, the number of trees corresponding to the felling years is compared with the number of felled trees, and the average relative value of felling trees is calculated;

[0141] Calculate the expected logging quantity based on the number of trees corresponding to the current year and the average logging relative value;

[0142] The estimated logging quantity is sent to the user end.

[0143] In some embodiments, the detection module 230 is further configured to search for a logging area with the highest tree density in a preset area database upon receiving a logging application;

[0144] Send the logging area to the user end;

[0145] When it is detected that the tree density in the fellable area is lower than a preset threshold, the fellable area with the largest tree density is searched again and sent to the user end.

[0146] In some embodiments, the logging application includes the application quantity; the detection module 230 is further used to search the area corresponding to the logging area in the area database;

[0147] Real-time detection of regional density of logging areas, and calculation of the number of logged trees based on changes in regional density and regional area;

[0148] When it is detected that the number of trees cut down has reached the number requested, a prompt related to the completion of the number of trees cut down is sent to the user terminal.

[0149] In some embodiments, the detection module 230 is further used to search for protected tree information corresponding to the fellable area in a preset protection database, where the protected tree information includes: tree coordinates, tree pictures, and tree types;

[0150] Mark the location of tree coordinates on the preset forestry area map;

[0151] The marked forestry area map, tree pictures and tree types are sent to the user end.

[0152] The embodiment of the present application also discloses a control device.

[0153] Specifically, the control device includes a memory and a processor, and the memory stores a computer program that can be loaded by the processor and execute the above-mentioned edge computing-based forestry intelligent supervision method.

[0154] The embodiment of the present application also discloses a computer-readable storage medium.

[0155] Specifically, the computer-readable storage medium stores a computer program that can be loaded by a processor and executed such as the above-mentioned forestry intelligent supervision method based on edge computing. The computer-readable storage medium includes, for example: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, and other media that can store program codes.

[0156] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A forestry intelligent supervision method based on edge computing, characterized in that: The method comprises: Monitor forestry conditions in real time using monitoring equipment to obtain forestry information, the forestry information at least including: temperature and carbon dioxide concentration; Determine whether a disaster has occurred based on a preset information range and the forestry information; If the temperature and the carbon dioxide concentration are both greater than the information range, information related to disaster area warning is sent to the administrator terminal; If the temperature or the carbon dioxide concentration is greater than the information range, searching for precipitation records in a preset precipitation database; If the precipitation is less than the preset threshold within the preset period, information related to the disaster warning is sent to the administrator terminal.

2. The method according to claim 1, characterized in that The forestry information also includes: wind speed and direction; After determining whether a disaster has occurred according to the preset information range and the forestry information, the method further includes: Determine the direction of fire spread according to the wind direction; Calculating the fire area according to the temperature variation; Control the drone to go to the fire area to find the fire location; Searching a preset fire database for a fire spread grade corresponding to the wind speed; The fire spread direction, the fire location and the fire spread level are sent to an administrator terminal.

3. The method according to claim 2, characterized in that After sending the fire spreading direction, the fire location and the fire spreading level to the administrator terminal, the method further includes: Retrieving the forestry personnel entry and exit table according to the edge computing platform, and judging whether there are people in distress according to the forestry personnel entry and exit table and the fire location; If it is determined that there are people in distress or a rescue order is received, the risk area is calculated according to the fire spread direction, the fire location and the fire spread level; Control the drone group to conduct a carpet search of the risk area and take photos at preset intervals to obtain pictures of the risk area; Performing real-time person recognition on the risk area image according to the edge computing platform, determining and uploading the rescue location; According to the fire spreading direction and the fire location, dynamically planning a rescue guidance route based on a preset fire route algorithm; The drone is controlled to guide the trapped persons along the rescue guidance route.

4. The method according to claim 1, characterized in that The method further comprises: Detecting the tree density and the forest area through monitoring equipment according to a preset detection cycle, and storing the tree density and the forest area in a preset forestry database; When a forestry report request is received, the forestry report request includes: a requested year, and retrieving the forestry area and the forest density corresponding to the requested year in the forestry database; Filling the forest area, the tree density and the corresponding time into a preset statistical chart according to a preset statistical chart component; The statistical graph is sent to a user terminal.

5. The method according to claim 4, characterized in that Before filling the forest area, the forest density and the corresponding time into the preset statistical chart according to the preset statistical chart component, the method further includes: Calculate the number of trees based on the tree density and the forest area; Calculate the trend of changes in the requested years based on the number of trees; Excluding the target years with a decreasing trend from the requested years, to obtain the increasing years; Searching the forestry database for forestry logging information corresponding to the increase years, wherein the forestry logging information includes: logging years, logging areas, and logging quantities; According to the said increase years, the number of trees corresponding to the said felling years is compared with the said felling number to calculate the average felling relative value; Calculate the estimated felling quantity based on the number of trees corresponding to the current year and the average felling relative value; The estimated felling quantity is sent to the user terminal.

6. The method according to claim 5, characterized in that The method further comprises: When receiving a logging application, search the preset regional database for the logging area with the highest tree density; Sending the logging area to a user terminal; When it is detected that the tree density in the fellable area is lower than a preset threshold, a fellable area with the largest tree density is searched again and sent to the user end.

7. The method according to claim 6, characterized in that The logging application includes the application amount; When it is detected that the tree density in the fellable area is lower than a preset threshold, the fellable area with the largest tree density is searched again and sent to the user end, the method further includes: Searching the area database for the area corresponding to the logging area; Real-time detection of the regional density of the fellable area, and calculation of the number of felled trees according to the change of the regional density and the area of ​​the area; When it is detected that the number of trees cut down reaches the number of trees applied for, a prompt related to the completion of the number of trees cut down is sent to the user terminal.

8. The method according to claim 6, characterized in that The method further comprises: Searching for protected tree information corresponding to the fellable area in a preset protection database, wherein the protected tree information includes: tree coordinates, tree pictures, and tree types; Marking the locations of the tree coordinates on a preset forestry area map; The marked forestry area map, the tree pictures and the tree types are sent to the user end.

9. A forestry intelligent monitoring device based on edge computing, characterized in that: The device comprises: A monitoring module (210) is used to monitor forestry conditions in real time according to monitoring equipment to obtain forestry information, wherein the forestry information at least includes: temperature and carbon dioxide concentration; An analysis module (220) is used to determine whether a disaster has occurred based on a preset information range and the forestry information; A detection module (230) is used to send information related to disaster warning to an administrator terminal if both the temperature and the carbon dioxide concentration are greater than the information range; A precipitation module (240), configured to search for precipitation records in a preset precipitation database if the temperature or the carbon dioxide concentration is greater than the information range; The output module (250) is used to send information related to disaster warning to the administrator terminal if the precipitation in a preset period is less than a preset threshold.

10. A control device, characterized in that: The device comprises: The method comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute the method according to any one of claims 1 to 8.

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