Method, device and equipment for constructing underground safety route based on digital twinborn model

Abstract

The embodiment of the invention discloses a method, device and equipment for constructing an underground safety route based on a digital twin model. The scheme can comprise the following steps: acquiring three-dimensional scene data of a mine; the three-dimensional scene data at least comprises information of a plurality of roadways; acquiring mine environment data acquired by utilizing a sensor; constructing a digital twin model based on the three-dimensional scene data; judging whether the mine has a safety risk or not based on the mine environment data; if the mine has the safety risk, carrying out risk prediction on the information of the plurality of roadways, and determining the risk value of each roadway; according to the length of the roadway and the speed of the user, the escape duration of the user in each roadway is determined; a congestion factor is determined according to the number of existing users in the roadway and the preset containing number of the roadway; and planning a safe route in the digital twinborn model based on the risk value of each roadway, the user escape duration and the congestion factor.

Description

Technical Field

[0001] The present application relates to the field of digital twin technology, and in particular to a method for constructing an underground safety route based on a digital twin model, a device for constructing an underground safety route based on a digital twin model, and an equipment for constructing an underground safety route based on a digital twin model. Background Art

[0002] During coal mining, there are potential safety risks that could endanger users. To ensure user safety, safe mine routes can be planned, allowing users to escape along safe routes in the event of a threat. Existing technologies often use sensors to obtain environmental parameters, manually planning safe routes based on these parameters, or generating the shortest path based on static tunnel maps. However, these methods fail to consider the actual mine environment, resulting in inaccurate route planning or lengthy planning times, posing significant safety risks to users in the mine.

[0003] Therefore, how to provide a method for quickly and accurately constructing a safe route under a mine is a technical problem that needs to be solved urgently. Summary of the Invention

[0004] The embodiments of this specification provide a method, device, and equipment for constructing a safe underground route based on a digital twin model to solve the problem of inaccurate routes in existing methods for planning safe routes in mines.

[0005] To solve the above technical problems, the embodiments of this specification provide a method for constructing an underground safe route based on a digital twin model, including: Acquire three-dimensional scene data of a mine; the three-dimensional scene data includes at least a plurality of tunnel information; Obtaining mine environment data collected using sensors; Building a digital twin model based on the three-dimensional scene data; determining whether the mine has a safety risk based on the mine environment data; If there is a safety risk in the mine, risk prediction is performed on the information of the plurality of lanes to determine the risk value of each lane; Determine the user's escape time in each lane based on the lane length and user speed; Determine the congestion factor based on the number of existing users in the lane and the lane's preset capacity; Based on the risk value of each lane, the user's escape time and the congestion factor, a safe route is planned in the digital twin model.

[0006] The embodiments of this specification also provide a device for constructing an underground safe route based on a digital twin model, including: A three-dimensional scene acquisition module is used to acquire three-dimensional scene data of a mine; the three-dimensional scene data includes at least a plurality of tunnel information; A mine environment acquisition module is used to obtain mine environment data collected by sensors; A digital twin construction module, configured to construct a digital twin model based on the three-dimensional scene data; A risk judgment module, configured to judge whether the mine has a safety risk based on the mine environment data; a risk value determination module, configured to perform risk prediction on the plurality of lane information and determine the risk value of each lane if there is a safety risk in the mine; The escape time determination module is used to determine the user's escape time in each lane based on the lane length and user speed; A congestion factor determination module, configured to determine a congestion factor based on the number of existing users in the lane and the lane's preset capacity; A safe route planning module is used to plan a safe route in the digital twin model based on the risk value of each lane, the user's escape time and the congestion factor.

[0007] The embodiments of this specification also provide a device for constructing an underground safe route based on a digital twin model, including: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Acquire three-dimensional scene data of a mine; the three-dimensional scene data includes at least a plurality of tunnel information; Obtaining mine environment data collected using sensors; Building a digital twin model based on the three-dimensional scene data; determining whether the mine has a safety risk based on the mine environment data; If there is a safety risk in the mine, risk prediction is performed on the plurality of lane information to determine the risk value of each lane; Determine the user's escape time in each lane based on the lane length and user speed; Determine the congestion factor based on the number of existing users in the lane and the lane's preset capacity; Based on the risk value of each lane, the user's escape time and the congestion factor, a safe route is planned in the digital twin model.

[0008] At least one embodiment of this specification can achieve the following beneficial effects: construct a digital twin model by acquiring three-dimensional scene data containing information about several lanes and hardware equipment; determine whether the mine has a safety risk based on the mine environment data collected by sensors; if the mine has a safety risk, risk prediction can be performed on several lane information to determine the risk value of each lane; determine the user's escape time in each lane based on the lane length and user speed; and determine the congestion factor based on the number of users in the lane and the preset capacity of the lane; plan a safe route in the digital twin model based on the risk value of each lane, the user's escape time, and the congestion factor. Therefore, a digital twin model can be used to plan a safe route in combination with data from multiple dimensions, which can improve the accuracy of safe route planning while also improving the efficiency of planning safe routes and ensuring user safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] To more clearly illustrate the embodiments of this specification or the technical solutions in the prior art, the following briefly introduces the drawings required for the embodiments or the description of the prior art. Obviously, the drawings described below are only some of the embodiments described in this application. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0010] Figure 1 This is a flow chart of a method for constructing an underground safety route based on a digital twin model provided in an embodiment of this specification; Figure 2 This is a schematic diagram of a mine tunnel provided in an embodiment of this specification; Figure 3 This is a schematic diagram of the forces acting on a user moving on a sloped sub-lane provided in an embodiment of this specification; Figure 4 This is a schematic diagram of the structure of a device for constructing an underground safety route based on a digital twin model provided in an embodiment of this specification; Figure 5 This is a structural diagram of a device for building an underground safety route based on a digital twin model provided in an embodiment of this specification. DETAILED DESCRIPTION

[0011] To make the purpose, technical solutions, and advantages of one or more embodiments of this specification more clear, the technical solutions of one or more embodiments of this specification will be clearly and completely described below in conjunction with the specific embodiments of this specification and the corresponding drawings. Obviously, the embodiments described are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of one or more embodiments of this specification.

[0012] The terms used in one or more embodiments of the present application are for the purpose of describing specific embodiments only and are not intended to limit one or more embodiments of the present application. The singular forms "a", "the" and "the" used in one or more embodiments of the present application and the appended claims are also intended to include plural forms, unless the context clearly indicates otherwise. It should also be understood that the term "and / or" used in one or more embodiments of the present application refers to and includes any or all possible combinations of one or more associated listed items.

[0013] It should be understood that although the terms first, second, etc. may be used to describe various information in one or more embodiments of the present application, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from each other. For example, without departing from the scope of one or more embodiments of the present application, the first may also be referred to as the second, and similarly, the second may also be referred to as the first. Depending on the context, the word "if" as used herein may be interpreted as "at the time of" or "when" or "in response to determining".

[0014] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of the relevant regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0015] The technical solutions provided by the embodiments of this specification are described in detail below with reference to the accompanying drawings.

[0016] Figure 1 This is a flow chart of a method for constructing an underground safety route based on a digital twin model provided in an embodiment of this specification. From a program perspective, the execution entity of the process can be an application server or application client or digital twin platform that carries the program.

[0017] like Figure 1 As shown, the method may include the following steps.

[0018] Step 102: Acquire three-dimensional scene data of the mine.

[0019] The three-dimensional scene data includes at least a number of lane information.

[0020] In the embodiments of this specification, the 3D scene data may be collected using radar, cameras, etc. The 3D scene data may also include information about underground mine buildings, mine shape information, the location and shape of each mine opening, and other information.

[0021] In the embodiments of this specification, the multiple laneway information items may include information such as the laneway's location within the mine, length, width, height, slope, connections between lanes, and intersection coordinates. The 3D scene data may also include hardware device information, including the device model, name, shape, operating status, and location within the mine.

[0022] Step 104: Acquire mine environment data collected by sensors.

[0023] In the embodiments of this specification, mine environment data may include various data such as gas concentration, temperature, humidity, roof displacement rate, and wind speed. Gas concentration may be acquired in real time by a gas concentration sensor deployed in the mine; temperature may be acquired in real time by a temperature sensor; humidity may be acquired in real time by a reading sensor; roof displacement rate may be acquired in real time by a roof displacement detector; and wind speed may be acquired in real time by a ventilation wind pressure sensor.

[0024] Step 106: Construct a digital twin model based on the three-dimensional scene data.

[0025] In the embodiments of this specification, the server can use Building Information Modeling (BIM) to build a high-precision three-dimensional model containing buildings and hardware facilities, and can use Geographic Information System (GIS) to build a mine geospatial model containing data such as the mine's terrain and tunnels. At the same time, the Feature Manipulate Engine (FME) can be used to process the data in the high-precision three-dimensional model and the mine geospatial model, so that the data of the two can be better integrated, and then the Web Graphics Library (WebGL) can be used to render the high-precision three-dimensional model and the mine geospatial model processed by FME to obtain a visual digital twin model consistent with the actual situation of the mine.

[0026] Step 108: Determine whether there is a safety risk in the mine based on the mine environment data.

[0027] As an embodiment, judging whether the mine has a safety risk based on the mine environmental data may specifically include: when the mine environmental data includes the roof movement rate, judging whether the roof movement rate is greater than or equal to the preset rate; and / or, when the mine environmental data includes the gas concentration, judging whether the gas concentration is greater than or equal to the preset concentration; and / or, when the mine environmental data includes the wind speed, judging whether the wind speed is less than or equal to the preset wind speed; thereby, determining whether the mine has a safety risk based on the above judgment results.

[0028] In practical applications, the presence of safety risks in a mine can also be determined based on the hardware equipment information in the digital twin model. Specifically, when the hardware equipment information includes ventilator information, the presence of a ventilator fault can be determined based on the ventilator information. Furthermore, when the hardware equipment information includes high-voltage switchgear information, the presence of a high-voltage switchgear fault can be determined based on the high-voltage switchgear information. Furthermore, when the hardware equipment information includes winch information, the presence of a winch fault can be determined based on the winch information. Thus, the presence of safety risks can be determined from the perspective of the hardware equipment.

[0029] In practical applications, the server can also receive alarm information from users in a mine and determine whether the mine presents a safety risk based on the alarm information. The server can perform simultaneous evaluations of each of the above conditions and determine that the mine presents a safety risk when at least one of the above conditions is met.

[0030] Step 110: If there is a safety risk in the mine, risk prediction is performed on the plurality of tunnel information to determine the risk value of each tunnel.

[0031] In the embodiments of this specification, if at least one of the following information is abnormal: mine environment data, hardware equipment information, and user alarm information, it can be determined that the mine presents a safety risk and that a safe route needs to be constructed using information from each lane. If the mine does not present a safety risk, the aforementioned data is continuously monitored.

[0032] As an implementation method, step 110 may specifically include: determining the risk type based on mine environmental data and a digital twin model; determining a first weight value corresponding to the roof movement rate, a second weight value corresponding to the gas concentration, and a third weight value corresponding to the wind speed based on the risk type; determining the first roof movement rate, the first gas concentration, and the first wind speed of any one of several tunnel information from the mine environmental data; and determining the risk value of any one of the tunnels based on the first weight value, the second weight value, the third weight value, the first roof movement rate, the first gas concentration, and the first wind speed.

[0033] In the embodiments of this specification, the weight values corresponding to each data can be determined based on the risk type. For example, if the risk type is an explosion type, the second weight value corresponding to the gas concentration must be greater than the first weight value of the roof movement rate and the third weight value corresponding to the wind speed; if the risk type is a collapse type, the first weight value can be greater than the second weight value and the third weight value; if the risk type is an oxygen deficiency type or the dust concentration is too high, the third weight value can be greater than the first weight value and the second weight value.

[0034] In the embodiment of this specification, it can be based on the formula: , calculate the risk value of any tunnel, where R represents the risk value of any tunnel, V represents the first wind speed, C represents the first gas concentration, and D represents the first roof movement rate. represents the third weight value, represents the second weight value, represents the first weight value, where + + =1.

[0035] In practical applications, risk values can also be calculated based on data such as tunnel support strength and temperature. The risk value is calculated by determining the weight value corresponding to each data point based on the risk type, and these are not listed here one by one.

[0036] In the embodiments of this specification, in order to improve the accuracy of the calculated risk value, the weight value corresponding to each data can be dynamically adjusted. Specifically, the weight value corresponding to each data can be determined based on the duration of the risk occurrence. Taking fire as an example, if the difference between the current time and the time when the fire occurred is less than or equal to the first preset duration, it can be determined that it is in the initial stage of the fire, and the second weight value can be greater than the first weight value and the third weight value; if the difference between the current time and the time when the fire occurred is greater than the first preset duration and less than the second preset duration, it can be determined that it is in the development stage of the fire, and the second weight value can be lowered, and the first weight value and the third weight value can be increased; if the difference between the current time and the time when the fire occurred is greater than or equal to the second preset duration, it can be determined that it is in the attenuation stage of the fire, and the first weight value, the second weight value and the third weight value can be adjusted to the basic weight value. For example, if the time from the occurrence of the fire is less than or equal to 5 minutes, it is determined to be in the initial stage, and it can be determined =0.3, =0.5, =0.2; if the time from fire occurrence to fire loss is greater than 5 minutes and less than 30 minutes, it is determined to be in the development stage, then =0.32, =0.38, =0.3; if the time from the fire to the fire is greater than or equal to 30 minutes, it is determined to be in the development stage, then =0.3, =0.3, =0.4.

[0037] In the embodiments of this specification, the weight of each data can also be dynamically adjusted based on the distance between the roadway and the risk source. Taking fire as an example, the weight value of the gas concentration data can be dynamically adjusted using the distance attenuation model. Specifically, it can be based on the formula: , adjust the weight value corresponding to the gas concentration, Indicates the initial weight value corresponding to the gas concentration; represents the risk intensity; β represents the distance attenuation coefficient, which can be determined based on expert experience; d represents the distance from the source of the risk.

[0038] In actual applications, the weight values of various data can also be dynamically adjusted in combination with the operating status of the hardware equipment. For example, if the ventilation system is normal, the risk value can be calculated according to the original weight. If the ventilation system is abnormal, the third weight corresponding to the wind speed and the second weight corresponding to the gas concentration can be increased. The weight values can also be determined based on the location of the risk source. For example, if the risk occurs in the air intake tunnel, the second weight and the third weight are greater than the first weight, and the second weight and the third weight can be equal. If the risk occurs in the return air tunnel, the second weight can be higher than the first weight and the third weight, and the first weight is less than the third weight, and so on. I will not list them one by one here.

[0039] In practical applications, the weight values can be adjusted based on one or more of the above methods, and the adjusted weight values can be normalized to improve the accuracy of the risk value calculation results. The risk value can also be adjusted based on the structural safety of the roadway and the emergency facilities in the roadway. For example, if the support strength of the roadway is low, a first preset risk value can be added to the weighted sum to obtain the corresponding risk value of the roadway. If the roadway contains a refuge chamber, a second preset risk value can be subtracted from the weighted sum to obtain the corresponding risk value of the roadway. And so on, which are not listed here one by one.

[0040] In practical applications, to improve the efficiency of planning safe routes, a pre-trained risk prediction model can be used to predict the risk value corresponding to each lane. The risk prediction model can be trained based on historical data.

[0041] As an embodiment, the risk value of any tunnel is determined based on the first weight value, the second weight value, the third weight value, the first roof movement rate, the first gas concentration and the first wind speed. Specifically, it can include: normalizing the first roof movement rate to obtain the second roof movement rate; normalizing the first gas concentration to obtain the second gas concentration; normalizing the first wind speed to obtain the second wind speed; and determining the risk value of any tunnel based on the first weight value, the second weight value, the third weight value, the second roof movement rate, the second gas concentration and the second wind speed.

[0042] In the embodiments of this specification, the server can normalize the data using one of the methods such as linear normalization, Z-Score standardization, mean normalization, nonlinear normalization, and neural network-specific normalization, so that each data has a unified standard, thereby improving the accuracy of the risk value calculation results.

[0043] In practical applications, the server can use the formula: , normalize the wind speed, where V represents the first wind speed obtained based on the sensor, and the unit can be m / s; The first wind speed threshold and the second wind speed threshold can be determined based on expert experience. For example, the first wind speed threshold can be 1m / s, 1.5m / s, etc., and the second wind speed threshold can be 0.25m / s, 0.5m / s, etc. The formula can be used: , normalize the gas concentration, where C represents the first gas concentration and the unit can be %; Indicates the second gas concentration. The formula can be used: , normalize the top plate moving rate, where D represents the first top plate moving rate, and the unit can be mm / h; Indicates the moving speed of the second top plate.

[0044] Step 112: Determine the user's escape time in each lane based on the lane length and the user's speed.

[0045] As an embodiment, the method for obtaining the user speed in step 112 may specifically include: obtaining the user speed of each user during the escape drill; or, using a sensor to obtain the user speed of each user in real time; or, determining the average speed of the user based on the displacement of the user within a preset time period and a preset duration; or, obtaining the correspondence between age and preset user speed, and determining the user speed based on the user's age and the correspondence.

[0046] In the embodiments of this specification, the sensor for obtaining the user's speed may be a sensor contained in a terminal worn by the user, or a sensor installed in a mine for measuring speed, displacement, or position. In determining the user's speed based on age, the user's physical condition may also be considered, and so on. These are not listed here.

[0047] In the existing technology, the escape time is mostly calculated based on the average speed of an adult moving on a flat surface. However, some tunnels in mines have slopes and are at an angle to the horizontal plane. When users move in the sloped tunnels, their speed may slow down. If the escape time is still calculated based on the average speed of an adult moving on a flat surface, the calculation result may be inaccurate. If an inaccurate escape time is used to plan a safe route, it is easy to endanger the lives of users in the mine.

[0048] In order to solve the problem of inaccurate calculation of escape time in the prior art, as an implementation method, any lane contains multiple sub-lanes. For step 112, it can specifically include: determining the angle between each sub-lane and the horizontal line; determining the target speed based on the angle and the user speed; determining the escape time corresponding to each sub-lane based on the length of each sub-lane and the target speed; and determining the escape time of any lane based on the escape time of each sub-lane.

[0049] In order to clearly illustrate the existence of slopes in underground mines, Figure 2 This is a schematic diagram of a mine tunnel provided in the embodiment of this specification. Figure 2 As shown, section a and section b can be two sub-tunnels belonging to the same tunnel under the mine, section c and the dotted extension line on the left side of section c can be the ground plane on the mine; the section a sub-tunnel can be the ground parallel to the section c ground plane, and the speed v1 of the user moving on the horizontal plane can be used to calculate the escape time in this section; there is an angle between the section b sub-tunnel and the section c ground plane, and the angle between the section b sub-tunnel and the section c ground plane can be determined. Based on the angle, the speed v2 of the user moving in the section b sub-tunnel is determined, and the calculated v2 can be used to determine the escape time required for the user to escape from the section b sub-tunnel, and then the sum of the escape time corresponding to the section a sub-tunnel and the escape time corresponding to the section b sub-tunnel can be used to determine the escape time required for the user to successfully escape from the starting position of the section a sub-tunnel to the ground plane.

[0050] In the embodiments of this specification, the angle can be determined from a digital twin model, and the angle is less than or equal to ninety degrees. The target speed is determined based on the angle and the user's speed. Specifically, the user's weight can be obtained, and the ground material of the sub-lane can be obtained from the digital twin model; the friction coefficient can be determined based on the ground material of the sub-lane; a first friction force of the user on a horizontal surface can be determined based on the user's weight and the friction coefficient; a second friction force of the user on the sub-lane can be determined based on the angle and the user's weight; a first work value generated by the user moving a preset length can be determined based on the first friction force; a second work value generated by the user moving a preset length can be determined based on the second friction force, the angle, and the user's weight; the ratio of the second work value to the first work value is used as an adjustment coefficient; the product of the adjustment coefficient and the user's speed can be used as the target speed, thereby obtaining the target speed corresponding to each sub-lane. Furthermore, the sub-escape time corresponding to each sub-lane can be determined based on the target speed and sub-lane length of each sub-lane; and the sub-escape time of each sub-lane in any lane is summed to obtain the escape time of any lane.

[0051] In order to more clearly illustrate the process of calculating the adjustment coefficient based on the work generated by the user's movement. Figure 3The present invention provides a schematic diagram of the force applied to a user moving on a sloped sub-lane. Figure 3 As shown in the figure, the solid line released by the user is a sub-lane with a slope; the dotted line is a horizontal line; o can represent the angle between the sub-lane and the horizontal line; G can represent the gravity calculated based on the weight of the user; f can represent the second friction force generated by the user when moving on the sub-lane. Since the second friction force and the component of gravity on the slope have the same value, the value corresponding to the second friction force can be determined based on the formula: f=G*sino; h can represent the height distance between the sub-lane and the horizontal plane, which can be specifically calculated based on the length of the sub-lane, which can be L, h=L*sino; thus, the second work value can be calculated based on the formula: W2=f*L+G*h; the first friction force of the user on the horizontal plane can also be determined based on gravity, n=G*γ, where n represents the first friction force and γ represents the friction coefficient determined based on the lane material; the first work value is determined based on the formula: W1=n*L; the adjustment coefficient is calculated based on the formula: τ=W2 / W1, so that the target speed can be determined by multiplying the adjustment coefficient and the user speed. The adjustment coefficient can also be a range value determined based on the result calculated based on the first power value and the second power value. For example, if the adjustment coefficient is 0.8 based on the formula, the value range of the adjustment coefficient can be determined to be [0.78, 0.82]. A random value can be taken from this range to determine the target speed.

[0052] In actual applications, the longer the escape time is, the worse the user's physical strength will be, and the speed may also decrease. In order to determine the accuracy of the escape time, the target speed can also be determined based on the user's escape time. Specifically, it can be based on the formula: , calculate the target speed corresponding to each sub-lane, where v represents the target speed; Indicates user speed; represents the adjustment coefficient; t represents the user's escape time; thus, the target speed corresponding to each sub-lane can be obtained. The sub-escape time is calculated based on the target speed and the length of each sub-lane, and then the sub-escape time is summed to obtain the escape time of any lane.

[0053] Step 114: Determine a congestion factor based on the number of existing users in the lane and the preset capacity of the lane.

[0054] In the embodiments of this specification, the preset lane capacity can be determined based on the lane width, length, and height. The preset lane capacity can also be determined based on the lane length, width, and height in combination with the lane oxygen content. Specifically, the mine environment data includes at least the lane oxygen content. A user's oxygen demand is obtained, and the preset lane capacity is determined based on the user's oxygen demand and the lane oxygen content.

[0055] In the embodiment of this specification, it is possible to first determine whether the height and width of the tunnel meet the preset conditions. The preset conditions may be whether the height of the tunnel is greater than or equal to the preset height, and whether the width of the tunnel is greater than or equal to the preset width. The preset height and preset width may be determined based on expert experience; if the preset conditions are not met, it is determined to be a high-risk tunnel and passage is prohibited; if the preset conditions are met, it can be determined whether the oxygen concentration in the tunnel meets the respiratory protection standards specified by the U.S. Occupational Safety and Health Administration; if not, the tunnel is determined to be an extremely high-risk area and users are prohibited from passing through; if it meets, it can be determined whether the ventilation system is normal. If the ventilation system is normal, it can be determined that the oxygen supply in the tunnel is normal; the air intake rate can be determined based on the parameters of the ventilation system, and the unit can be L / min. The preset capacity is determined based on the air intake volume per unit time, the oxygen concentration of the input gas, the minimum oxygen concentration, and the oxygen consumption rate of each person, where the oxygen consumption rate can also be L / min. The oxygen concentration of the input gas and the minimum oxygen concentration can be determined based on the proportion of oxygen in the gas components, and the minimum oxygen concentration can be determined based on the respiratory protection standard. The input oxygen concentration can be determined based on the parameters of the ventilation system. If the ventilation system inputs fresh air, the input oxygen concentration can be 20.9%; if the input is pure oxygen, the input oxygen concentration can be 99%. The oxygen consumption rate of each person can be determined based on the user's status. For example, in the escape state, the user's oxygen consumption rate is greater than the user's oxygen consumption rate in the static state.

[0056] In the embodiments of this specification, the preset capacity is determined based on the intake rate, the oxygen concentration of the input gas, the minimum oxygen concentration, and the oxygen consumption rate of each person. Specifically, the concentration difference between the oxygen concentration of the input gas and the minimum oxygen concentration can be determined, and the product of the concentration difference and the intake rate can be determined; the product is divided by the oxygen consumption rate to obtain the preset capacity.

[0057] In addition, if there is a refuge chamber in the tunnel, it is possible to determine how many users' oxygen needs can be met by the oxygen content in the refuge chamber within a preset time, and the determined number of users can be used as the preset capacity of the tunnel. Specifically, if the oxygen in the refuge chamber cannot be ventilated, the total oxygen content that the refuge chamber can provide to meet the needs of users can be determined based on the spatial volume of the refuge chamber, the oxygen concentration in the refuge chamber, the minimum oxygen concentration, and the oxygen density in the refuge chamber; the oxygen consumption rate of the user in a resting state can be determined; the maximum time required for rescue can be determined; based on the oxygen exchange rate and the maximum time, the amount of oxygen that a user needs to consume while waiting for rescue can be determined; and the preset capacity can be determined by dividing the total oxygen content by the amount of oxygen that a user needs to consume while waiting for rescue.

[0058] Through the above implementation, the maximum number of users that the tunnel can accommodate can be determined from the perspective of oxygen content, avoiding insufficient oxygen supply and endangering the lives of users, greatly ensuring the safety of users in the mine and the feasibility and accuracy of the planned safe route.

[0059] If the number of users in a lane exceeds the preset capacity, the lane can be identified as a risky lane and other lanes can be planned for the users; alternatively, a new safe route can be planned based on other lanes connected to the lane to divert the users in the lane, thereby avoiding insufficient oxygen content for users to breathe, causing breathing difficulties or even suffocation.

[0060] In actual applications, the preset capacity determined based on the oxygen amount can also be used as the first preset capacity; the preset activity area of users in the alley can be determined based on expert experience; the second preset capacity can be determined based on the width of the alley, the length of the alley and the preset activity area; the smaller value of the first preset capacity and the second preset capacity can be used as the preset capacity of the alley; this can avoid the situation where there are sufficient oxygen but the space is small, and there are too many users causing congestion, and they cannot evacuate safely according to the scheduled time, resulting in casualties or trampling.

[0061] In the embodiments of this specification, the congestion factor may indicate the congestion of the current lane. It is understood that a larger congestion factor indicates a more congested lane. The congestion factor may be obtained by dividing the number of existing users by the preset lane capacity.

[0062] Step 116: Plan a safe route in the digital twin model based on the risk value of each lane, the user's escape time, and the congestion factor.

[0063] As an implementation method, step 116 may specifically include: determining the safety value of each lane based on the risk value, the user's escape time, and the congestion factor; marking the lanes in the digital twin model whose safety value is less than or equal to the first preset threshold as a first color area; marking the lanes in the digital twin model whose safety value is greater than or equal to the second preset threshold as a second color area; marking the lanes in the digital twin model whose safety value is greater than the first preset threshold and less than the second preset threshold as a third color area; and planning the safe route based on the lanes corresponding to the second color area and the third color area.

[0064] In the embodiment of this specification, the congestion factor and the escape time can be used to determine the target escape time. Specifically, the target escape time can be determined based on the formula: m =T a* (1 + 0.3p), calculate the target escape time, where T m Indicates the target's escape time; T a Indicates the escape time; p indicates the congestion factor, which can be based on p=n / n max Determined, n represents the number of existing users in the lane, n max Represents the preset capacity of the alley. The target escape time and risk value are normalized to determine a duration weight corresponding to the target escape time and a risk weight corresponding to the risk value. A weighted sum is determined based on the normalized target escape time, the normalized risk value, the duration weight, and the risk weight. The safety value is obtained by subtracting the weighted sum from one. The safety value can also be obtained by subtracting the weighted sum of the congestion factor, escape time, and risk value from one.

[0065] In the embodiments of this specification, the first color area may represent a high-risk area and may be represented by red; the second color area may represent a medium-risk area and may be represented by yellow; and the third color area may represent a low-risk area and may be represented by green. In actual applications, other colors may also be used for representation, which is not specifically limited here.

[0066] In practice, if the congestion factor is greater than or equal to a preset value, at least two safe routes can be planned based on the current lane. A risk level can also be determined. If the risk level exceeds the preset level, planning can be performed based on the lanes corresponding to the second and third color areas. If the risk level does not exceed the preset level, planning can be performed based on the lane corresponding to the third color area. This allows lanes that can be used for safe route planning to be quickly identified by the marked color areas, improving the accuracy and efficiency of safe route planning.

[0067] In actual applications, the user's location can also be detected, and the tunnel the user is in can be determined based on the user's location. The safe route can be planned using the tunnel where the user is as the starting point of the safe route. In this way, multiple safe routes can be accurately planned, providing at least one safe route for each user in the mine to ensure user safety.

[0068] In practical applications, the escape risk can also be determined based on the risk value, the user's escape time, and the congestion factor. Specifically, the first escape risk of each first lane connected to the risk source can be calculated; based on each first escape risk, at least one first target lane suitable for escape can be selected; and each second lane connected to the first target lane can be determined; the second escape risk corresponding to the second lane is calculated; based on each second escape risk, at least one second target lane suitable for escape can be selected, and so on, until the safe route planning is completed.

[0069] In actual applications, the server can also use the improved A* algorithm to process the risk value, user escape time and congestion factor, and plan at least one safe route from multiple alleys.

[0070] As an implementation manner, the method described in the embodiments of this specification may further include: sending the safe route to a user terminal; or broadcasting voice information according to the safe route.

[0071] In the embodiments of this specification, each user can carry a terminal capable of receiving messages from the server, which can include a wearable terminal such as AR glasses or a mobile phone terminal. The server can send the portion of the digital twin model that displays a safe route to the user terminal, so that the user terminal can escape based on the actual safe route. Alternatively, the server can use various voice broadcast devices to broadcast the safe route planned in the digital twin model to guide the user to escape.

[0072] In the embodiments of this specification, accidents can occur at any time in a mine. To improve user safety and the accuracy of the planned safe route, a safe route can be planned according to a preset period. Alternatively, when a new risk is detected, the safe route can be replanned. Alternatively, upon receiving a request from a user to replan a safe route, the safe route can be replanned according to the above method.

[0073] In actual applications, if a user fails to follow a safe escape route, the system can monitor their behavior and plan a new route based on that behavior. For example, if a user has a leg injury and is unable to move, and a second user is helping the first user escape, but the second user is moving too slowly and cannot follow the planned safe escape route, the system can replan a safe route for the first and second users based on oxygen concentration, oxygen exchange rate, and user movement speed, allowing them to escape successfully or wait for rescue.

[0074] It should be understood that the order of some steps in the methods described in one or more embodiments of this specification can be interchanged according to actual needs, or some steps can be omitted or deleted.

[0075] Figure 1The method constructs a digital twin model by acquiring three-dimensional scene data containing information about several lanes and hardware devices. It then determines whether the mine presents a safety risk based on mine environmental data collected by sensors. If a safety risk is present, it then performs a risk prediction on the lanes to determine the risk value for each lane. It then determines the user's escape time in each lane based on lane length and user speed. It also determines the congestion factor based on the number of users in the lane and the lane's preset capacity. Based on the risk value, user escape time, and congestion factor for each lane, a safe route is planned within the digital twin model. This allows the digital twin model to be combined with multiple dimensions to plan safe routes, improving both the accuracy and efficiency of safe route planning and ensuring user safety.

[0076] Based on the same idea, the embodiments of this specification also provide a device corresponding to the above method. Figure 4 This is a schematic diagram of a device for constructing an underground safety route based on a digital twin model provided in an embodiment of this specification. Figure 4 As shown, the device may include: The three-dimensional scene acquisition module 402 is used to acquire three-dimensional scene data of the mine; the three-dimensional scene data includes at least a plurality of tunnel information; A mine environment acquisition module 404 is used to acquire mine environment data collected by sensors; A digital twin construction module 406 is configured to construct a digital twin model based on the three-dimensional scene data; A risk judgment module 408 is configured to judge whether the mine has a safety risk based on the mine environment data; A risk value determination module 410 is configured to perform risk prediction on the plurality of lane information and determine a risk value for each lane if there is a safety risk in the mine; The escape time determination module 412 is used to determine the escape time of the user in each lane according to the lane length and the user's speed; A congestion factor determination module 414 is configured to determine a congestion factor based on the number of existing users in the lane and the lane's preset capacity; The safe route planning module 416 is used to plan a safe route in the digital twin model based on the risk value of each lane, the user's escape time and the congestion factor.

[0077] based on Figure 4 The present specification also provides some specific implementation plans of the method, which are described below.

[0078] Optionally, the risk assessment module may be used to: When the mine environment data includes a roof movement rate, determining whether the roof movement rate is greater than or equal to a preset rate; and / or, when the mine environment data includes gas concentration, determining whether the gas concentration is greater than or equal to a preset concentration; And / or, when the mine environment data includes wind speed, determining whether the wind speed is less than or equal to a preset wind speed.

[0079] Optionally, the mine environment data includes at least roof movement rate, gas concentration, and wind speed; and the risk value determination module may be specifically configured to: Determining a risk type based on the mine environment data and the digital twin model; Determining, based on the risk type, a first weight value corresponding to the roof movement rate, a second weight value corresponding to the gas concentration, and a third weight value corresponding to the wind speed; Determining a first roof movement rate, a first gas concentration, and a first wind speed of any one of the plurality of tunnel information from the mine environment data; The risk value of any one of the tunnels is determined based on the first weight value, the second weight value, the third weight value, the first roof movement rate, the first gas concentration, and the first wind speed.

[0080] Optionally, the risk value determination module may be specifically configured to: Normalizing the first top plate movement rate to obtain a second top plate movement rate; normalizing the first gas concentration to obtain a second gas concentration; Normalizing the first wind speed to obtain a second wind speed; The risk value of any one of the tunnels is determined based on the first weight value, the second weight value, the third weight value, the second roof movement rate, the second gas concentration, and the second wind speed.

[0081] Optionally, any lane among the plurality of lanes includes multiple sub-lanes; and the escape time determination module may be specifically configured to: Determine the angle between each sub-lane and the horizontal line; determining a target speed based on the angle and the user speed; Determining the escape time corresponding to each sub-lane based on the length of each sub-lane and the target speed; The escape time of any lane is determined based on the escape time of each sub-lane.

[0082] Optionally, the safe route planning module may be used to: Determining a safety value of each lane based on the risk value, the user's escape time, and the congestion factor; Marking the lanes in the digital twin model where the safety value is less than or equal to a first preset threshold as a first color area; Marking lanes in the digital twin model whose safety values are greater than or equal to a second preset threshold into a second color area; Marking the lanes in the digital twin model where the safety value is greater than the first preset threshold and less than the second preset threshold as a third color area; The safe route is planned based on lanes corresponding to the second color area and the third color area.

[0083] Optionally, the device may also be used to: send the safe route to a user terminal; or broadcast voice information according to the safe route.

[0084] Optionally, the device may also be used to plan the safe route according to a preset cycle.

[0085] Based on the same idea, the embodiments of this specification also provide devices corresponding to the above methods.

[0086] Figure 5 This is a schematic diagram of a device for constructing an underground safety route based on a digital twin model provided in an embodiment of this specification. Figure 5 As shown, the device 500 may include: at least one processor 510; and, A memory 530 in communication with the at least one processor; wherein, The memory 530 stores instructions 520 executable by the at least one processor 510. The instructions are executed by the at least one processor 510 to enable the at least one processor 510 to: Acquire three-dimensional scene data of a mine; the three-dimensional scene data includes at least a plurality of tunnel information; Obtaining mine environment data collected using sensors; Building a digital twin model based on the three-dimensional scene data; determining whether the mine has a safety risk based on the mine environment data; If there is a safety risk in the mine, risk prediction is performed on the information of the plurality of lanes to determine the risk value of each lane; Determine the user's escape time in each lane based on the lane length and user speed; Determine the congestion factor based on the number of existing users in the lane and the lane's preset capacity; Based on the risk value of each lane, the user's escape time and the congestion factor, a safe route is planned in the digital twin model.

[0087] The various embodiments in this specification are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. Figure 5 As for the device shown, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0088] In the 1990s, technological improvements could be clearly distinguished as either hardware improvements (for example, improvements to circuit structures like diodes, transistors, and switches) or software improvements (improvements to process flows). However, with the advancement of technology, many process flow improvements can now be considered direct improvements to hardware circuit structures. Designers almost always create the corresponding hardware circuit structure by programming the improved process flow into the hardware circuit. Therefore, it cannot be said that a process flow improvement cannot be implemented using physical hardware modules. For example, a programmable logic device (PLD), such as a field programmable gate array (FPGA), is an integrated circuit whose logical function is determined by user programming. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to hire a chip manufacturer to design and manufacture a dedicated integrated circuit chip. Moreover, nowadays, instead of manually fabricating integrated circuit chips, this programming is mostly performed using software called a "logic compiler." This is similar to the software compilers used during program development. Before compilation, the original code must be written in a specific programming language, called a Hardware Description Language (HDL). There are many types of HDL, including ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, and RHDL (Ruby Hardware Description Language). Currently, the most commonly used are VHDL (Very-High-Speed Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art will also understand that simply by programming a method flow in one of these hardware description languages and then programming it into an integrated circuit, a hardware circuit that implements the logic method flow can be easily obtained.

[0089] The controller can be implemented in any suitable manner. For example, the controller can take the form of a microprocessor or processor and a computer-readable medium storing computer-readable program code (e.g., software or firmware) executable by the (micro)processor, logic gates, switches, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller. Examples of controllers include, but are not limited to, the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320. The memory controller can also be implemented as part of the memory control logic. Those skilled in the art will also appreciate that, in addition to implementing the controller purely in computer-readable program code, the controller can also be implemented in the form of logic gates, switches, an application-specific integrated circuit, a programmable logic controller, an embedded microcontroller, etc. by logically programming the method steps. Therefore, such a controller can be considered a hardware component, and the means for implementing the various functions included therein can also be considered as structures within the hardware component. Alternatively, the means for implementing the various functions can be considered both a software module implementing the method and a structure within the hardware component.

[0090] The systems, devices, modules, or units described in the above embodiments may be implemented by computer chips or entities, or by products having certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smartphone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0091] For the convenience of description, the above devices are described as being divided into various units according to their functions. Of course, when implementing this application, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0092] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0093] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0094] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0095] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0096] In a typical configuration, a computing device includes one or more processors (CPUs), input / output interfaces, network interfaces, and memory.

[0097] Memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. Memory is an example of a computer-readable medium.

[0098] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can be implemented using any method or technology for information storage. Information can be computer-readable instructions, data structures, program modules, or other data. Examples of computer storage media include, but are not limited to, phase-change RAM (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, compact disc read-only memory (CD-ROM), digital versatile disc (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices, or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer-readable media does not include transitory computer-readable media such as modulated data signals and carrier waves.

[0099] It should also be noted that the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, method, commodity, or apparatus that includes a series of elements includes not only those elements but also other elements not explicitly listed, or includes elements inherent to such process, method, commodity, or apparatus. In the absence of further limitations, an element defined by the phrase "comprises a ..." does not exclude the presence of other identical elements in the process, method, commodity, or apparatus that includes the element.

[0100] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] The present application may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present application may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communications network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0102] The foregoing is merely an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application should all be included within the scope of the claims of the present application.

Claims

1. A method for constructing an underground safety route based on a digital twin model, characterized in that: include: Obtain three-dimensional scene data of the mine; The three-dimensional scene data includes at least a number of lane information; Obtaining mine environment data collected using sensors; Building a digital twin model based on the three-dimensional scene data; determining whether the mine has a safety risk based on the mine environment data; If there is a safety risk in the mine, risk prediction is performed on the plurality of lane information to determine the risk value of each lane; Determine the user's escape time in each lane based on the lane length and user speed; Determine the congestion factor based on the number of existing users in the lane and the lane's preset capacity; Based on the risk value of each lane, the user's escape time and the congestion factor, a safe route is planned in the digital twin model.

2. The method according to claim 1, characterized in that The determining whether the mine has a safety risk based on the mine environment data specifically includes: When the mine environment data includes a roof movement rate, determining whether the roof movement rate is greater than or equal to a preset rate; and / or, when the mine environment data includes gas concentration, determining whether the gas concentration is greater than or equal to a preset concentration; And / or, when the mine environment data includes wind speed, determining whether the wind speed is less than or equal to a preset wind speed.

3. The method according to claim 1, characterized in that The mine environment data includes at least roof movement rate, gas concentration, and wind speed; risk prediction is performed on the plurality of laneway information to determine the risk value of each laneway, specifically including: Determining a risk type based on the mine environment data and the digital twin model; Determining, based on the risk type, a first weight value corresponding to the roof movement rate, a second weight value corresponding to the gas concentration, and a third weight value corresponding to the wind speed; Determining a first roof movement rate, a first gas concentration, and a first wind speed of any one of the plurality of tunnel information from the mine environment data; The risk value of any one of the tunnels is determined based on the first weight value, the second weight value, the third weight value, the first roof movement rate, the first gas concentration, and the first wind speed.

4. The method according to claim 3, characterized in that The determining the risk value of any roadway based on the first weight value, the second weight value, the third weight value, the first roof movement rate, the first gas concentration, and the first wind speed specifically includes: Normalizing the first top plate movement rate to obtain a second top plate movement rate; normalizing the first gas concentration to obtain a second gas concentration; Normalizing the first wind speed to obtain a second wind speed; The risk value of any one of the tunnels is determined based on the first weight value, the second weight value, the third weight value, the second roof movement rate, the second gas concentration, and the second wind speed.

5. The method according to claim 1, wherein Any lane among the plurality of lanes includes a plurality of sub-lanes; and determining the escape time of the user in each lane based on the lane length, lane slope, and user speed, specifically includes: Determine the angle between each sub-lane and the horizontal line; determining a target speed based on the angle and the user speed; Determining the escape time corresponding to each sub-lane based on the length of each sub-lane and the target speed; The escape time of any lane is determined based on the escape time of each sub-lane.

6. The method according to claim 1, characterized in that Planning a safe route in the digital twin model based on the risk value of each lane, the user's escape time, and the congestion factor specifically includes: Determining a safety value of each lane based on the risk value, the user's escape time, and the congestion factor; Marking the lanes in the digital twin model where the safety value is less than or equal to a first preset threshold as a first color area; Marking lanes in the digital twin model whose safety values are greater than or equal to a second preset threshold into a second color area; Marking the lanes in the digital twin model where the safety value is greater than the first preset threshold and less than the second preset threshold as a third color area; The safe route is planned based on lanes corresponding to the second color area and the third color area.

7. The method according to claim 1, characterized in that The method further comprises: sending the safe route to a user terminal; Alternatively, a voice message is played along the described safe route.

8. The method according to claim 1, characterized in that The method further comprises: Plan the safe route according to the preset cycle.

9. A device for constructing an underground safety route based on a digital twin model, characterized in that: include: A three-dimensional scene acquisition module is used to obtain three-dimensional scene data of the mine; The three-dimensional scene data includes at least a number of lane information; A mine environment acquisition module is used to obtain mine environment data collected by sensors; A digital twin construction module, configured to construct a digital twin model based on the three-dimensional scene data; A risk judgment module, configured to judge whether the mine has a safety risk based on the mine environment data; a risk value determination module, configured to perform risk prediction on the plurality of lane information and determine the risk value of each lane if there is a safety risk in the mine; The escape time determination module is used to determine the user's escape time in each lane based on the lane length and user speed; A congestion factor determination module, configured to determine a congestion factor based on the number of existing users in the lane and the lane's preset capacity; A safe route planning module is used to plan a safe route in the digital twin model based on the risk value of each lane, the user's escape time and the congestion factor.

10. A device for constructing an underground safety route based on a digital twin model, characterized in that: include: at least one processor; as well as, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: Acquire three-dimensional scene data of a mine; the three-dimensional scene data includes at least a plurality of tunnel information; Obtaining mine environment data collected using sensors; Building a digital twin model based on the three-dimensional scene data; determining whether the mine has a safety risk based on the mine environment data; If there is a safety risk in the mine, risk prediction is performed on the plurality of lane information to determine the risk value of each lane; Determine the user's escape time in each lane based on the lane length and user speed; Determine the congestion factor based on the number of existing users in the lane and the lane's preset capacity; Based on the risk value of each lane, the user's escape time and the congestion factor, a safe route is planned in the digital twin model.

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