Control method and system for fire-fighting emergency evacuation equipment

Abstract

The invention discloses a control method and system for fire-fighting emergency evacuation equipment, and relates to the technical field of fire-fighting control, and the method comprises the steps: obtaining real-time environment data in a building; importing the real-time environment data into a pre-trained evacuation path risk assessment model, and outputting a risk coefficient of each grid unit in a grid chart corresponding to the building at a future time point; taking the current position of the target person as a starting point, taking the safety area as a terminal point, taking the risk coefficient corresponding to the grid unit as a path weight, planning an evacuation path in a path search mode, and outputting at least one evacuation path; and correspondingly generating a control instruction according to the evacuation path, and dynamically adjusting the image indication content and / or voice broadcast content of the fire-fighting emergency evacuation equipment according to the control instruction. According to the method disclosed by the invention, the safe evacuation path is generated through dynamic risk assessment and intelligent path planning, and the evacuation success rate and safety in an emergency situation are remarkably improved by cooperating with the guiding equipment.

Description

Technical Field

[0001] This invention relates to the field of fire control technology, specifically to a control method and system for fire emergency evacuation equipment. Background Technology

[0002] With the acceleration of urbanization, large and complex buildings are increasing in number. Their complex internal structures and dense populations highlight the limitations of traditional evacuation methods during fires. As the last line of defense for protecting lives, the intelligence and precision of fire emergency evacuation systems directly affect the severity of casualties in disasters.

[0003] Currently, most common fire emergency evacuation systems adopt a static guidance mode with preset logic. Specifically, the system is usually simply linked with the automatic fire alarm system. When the detector triggers the alarm, the system illuminates the nearest evacuation indicator sign, such as an arrow pointing to the nearest safe exit, according to a preset program. The direction of these indicator signs is fixed during installation, and their control logic is relatively simple, mainly based on the principle of nearest exit. They lack the dynamic perception and decision-making ability to monitor the real-time development of the fire, such as the direction of smoke spread and the blockage of passageways.

[0004] However, the shortcomings of existing technologies lie in the fact that their static guidance mode is severely mismatched with the highly uncertain dynamic evolution characteristics of fire scenes. Specifically, the fixed evacuation routes pre-set before a disaster cannot be dynamically adjusted according to real-time changes in environmental factors such as fire spread, smoke diffusion, and passage blockage. As a result, when the fire situation changes abruptly, the indicated directions may lead people to dangerous areas, posing a serious risk of secondary disasters. Summary of the Invention

[0005] In view of the shortcomings of the prior art, the purpose of this invention is to provide a control method and system for fire emergency evacuation equipment, which aims to solve the above-mentioned problems described in the prior art.

[0006] A first aspect of the present invention is to provide a control method for fire emergency evacuation equipment, the method comprising: Acquire real-time environmental data inside the building, including fire source location information, fire source type information, smoke concentration information and temperature information, as well as the status information of each evacuation route; The real-time environmental data is imported into a pre-trained evacuation route risk assessment model, and the risk coefficient of each grid cell in the grid diagram corresponding to the building is output at a future time point. Starting from the current location of the target personnel and ending at the safe zone, and using the risk coefficient corresponding to the grid unit as the path weight, the evacuation route is planned using a path search method, and at least one evacuation route is output. Control commands are generated based on the evacuation routes, and the image indication content and / or voice broadcast content of the fire emergency evacuation equipment are dynamically adjusted based on the control commands.

[0007] According to one aspect of the above technical solution, the step of importing the real-time environmental data into a pre-trained evacuation route risk assessment model and outputting the risk coefficient of each grid cell in the grid diagram corresponding to the building at a future time point includes: Based on the fire source location information, fire source type information, smoke concentration information, and temperature information, the smoke concentration distribution and temperature distribution in various areas of the building at multiple future time points are predicted. According to the preset risk mapping relationship, the predicted smoke concentration value in the smoke concentration distribution and the temperature value in the temperature distribution are mapped to the reference risk value of the corresponding grid cell. The baseline risk value is corrected based on the status information of the evacuation routes; If the evacuation route corresponding to any grid cell is unavailable, the risk coefficient of that grid cell is adjusted to the maximum value.

[0008] According to one aspect of the above technical solution, the step of mapping the predicted smoke concentration value in the smoke concentration distribution and the temperature value in the temperature distribution to the reference risk value of the corresponding grid cell based on a preset risk mapping relationship includes: Multiple risk level thresholds are set for the smoke concentration values ​​in the smoke concentration distribution and the temperature values ​​in the temperature distribution, respectively; Based on the predicted smoke concentration and temperature values, query their respective risk levels and assign corresponding level scores; Based on preset weights, the level scores of the smoke concentration value and the level scores of the temperature value are weighted and calculated to obtain the baseline risk value of the corresponding grid cell.

[0009] According to one aspect of the above technical solution, the step of weighting the grade score of the smoke concentration value and the grade score of the temperature value based on preset weights to obtain the baseline risk value of the corresponding grid cell includes: Based on the fire source type information, dynamically determine the weighting coefficients corresponding to the smoke concentration value and the temperature value, respectively. The baseline risk value of the corresponding grid cell is obtained by weighting the level score of the smoke concentration value and the level score of the temperature value. The expression for calculating the benchmark risk value is as follows: R =( S × W _ s )+(T × W _ t ); In the formula, R As the benchmark risk value, S The level score is the number of grades for the smoke concentration value. W _ s The weighting coefficient for smoke concentration values. T The temperature value is a grade or fraction. W _ t Let be the weighting coefficient for temperature values, and satisfy . W _ s + W _ t =1.

[0010] According to one aspect of the above technical solution, the steps of generating control commands based on the evacuation routes and dynamically adjusting the image indication content and / or voice broadcast content of the fire emergency evacuation equipment based on the control commands include: Based on the evacuation route, a dynamic guidance identifier bound to the evacuation route is generated, and the dynamic guidance identifier, the route information of the evacuation route, and the overall risk level corresponding to the evacuation route are encapsulated in the control command. According to the control command, the multiple fire emergency evacuation devices on the evacuation route dynamically adjust the image indication content and / or voice broadcast content.

[0011] According to one aspect of the above technical solution, the step of dynamically adjusting the image indication content and / or voice broadcast content of multiple fire emergency evacuation devices on the evacuation path according to the control command includes: Based on the path information of the evacuation route, a registration instruction is sent to all target fire emergency evacuation devices on the path sequence, and the dynamic guidance identifier is bound to the target fire emergency evacuation device; Based on the path length of the evacuation route and the preset evacuation speed, an activation timing command for controlling the differentiated activation of the target fire emergency evacuation equipment is calculated and sent; wherein, the equipment at the starting point of the route is activated immediately and displays a direction containing the dynamic guidance identifier; the subsequent equipment in the route is activated sequentially with a delay according to the activation timing command, forming a progressive dynamic optical flow pointing to the safety exit; The alarm intensity of each target fire emergency evacuation device is adaptively adjusted according to the overall risk level in the control command; wherein the flashing frequency and brightness of the image indication content, as well as the volume and urgency of the voice broadcast content, are positively correlated with the overall risk level.

[0012] According to one aspect of the above technical solution, the step of calculating and sending an activation timing command for controlling the differentiated activation of the target fire emergency evacuation equipment based on the path length of the evacuation route and the preset evacuation speed includes: Based on the path length and preset evacuation speed of the evacuation route, calculate the theoretical activation time of each target fire emergency evacuation device on the evacuation route. The system monitors the personnel passage status of key nodes on the evacuation route in real time, and dynamically delays and corrects the theoretical activation time based on the personnel passage status to generate the final activation timing command.

[0013] A second aspect of the present invention is to provide a control system for a fire emergency evacuation device, applied to the method described in the above-mentioned technical solution, the system comprising: The data acquisition module is used to acquire real-time environmental data inside the building, including fire source location information, fire source type information, smoke concentration information and temperature information, as well as the status information of each evacuation route; The risk assessment module is used to import the real-time environmental data into a pre-trained evacuation route risk assessment model and output the risk coefficient of each grid cell in the grid diagram corresponding to the building at a future time point. The path planning module takes the current location of the target personnel as the starting point, the safe zone as the ending point, and the risk coefficient corresponding to the grid unit as the path weight. It uses a path search method to plan the evacuation path and outputs at least one evacuation path. The instruction execution module is used to generate control instructions corresponding to the evacuation route, and dynamically adjust the image indication content and / or voice broadcast content of the fire emergency evacuation equipment according to the control instructions.

[0014] A third aspect of the present invention is to provide a readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method described in the above-described technical solution.

[0015] A fourth aspect of the present invention is to provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method described in the above technical solutions.

[0016] Compared with the prior art, the control method for the fire emergency evacuation equipment shown in this embodiment has the following advantages: The method described in this invention acquires real-time environmental data inside a building, including fire source location information, fire source type information, smoke concentration information, temperature information, and status information of each evacuation route. This real-time environmental data is imported into a pre-trained evacuation route risk assessment model, outputting the risk coefficient of each grid cell in the building's corresponding grid diagram at a future time point. Starting from the current location of the target personnel and ending at the safe zone, and using the risk coefficient corresponding to the grid cell as the path weight, a path search method is employed to plan evacuation routes, outputting at least one evacuation route. Control commands are generated based on the evacuation routes, and the image indication content and / or voice broadcast content of the fire emergency evacuation equipment are dynamically adjusted according to the control commands. This method, through dynamic risk assessment and intelligent path planning, generates safe evacuation routes and coordinates with guidance equipment, significantly improving the success rate and safety of evacuation in emergency situations. Attached Figure Description

[0017] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which: Figure 1 A flowchart illustrating the control method for fire emergency evacuation equipment provided in an embodiment of the present invention; Figure 2 The structural block diagram of the control system of the fire emergency evacuation equipment provided in the embodiment of the present invention. Detailed Implementation

[0018] To make the objectives, features, and advantages of the present invention more apparent and understandable, specific embodiments of the present invention will be described in detail below with reference to the accompanying drawings. Several embodiments of the present invention are shown in the drawings. However, the present invention can be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that the disclosure of the present invention will be more thorough and complete.

[0019] It should be noted that when a component is said to be "fixed to" another component, it can be directly on the other component or there may be an intervening component. When a component is said to be "connected to" another component, it can be directly connected to the other component or there may be an intervening component. The terms "vertical," "horizontal," "left," "right," and similar expressions used in this document are for illustrative purposes only.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. The terminology used herein in the description of the invention is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and / or" as used herein includes any and all combinations of one or more of the associated listed items.

[0021] Example 1 Please see Figure 1 The first embodiment of the present invention provides a control method for fire emergency evacuation equipment, the method comprising steps S10-S40: Step S10: Obtain real-time environmental data inside the building, including fire source location information, fire source type information, smoke concentration information and temperature information, as well as the status information of each evacuation route.

[0022] Specifically, in this embodiment, the intelligent control of fire emergency evacuation equipment firstly includes continuously acquiring real-time environmental data inside the building, and then controlling the fire emergency evacuation equipment based on the acquired real-time environmental data. The acquisition of real-time environmental data is specifically achieved through several sensor nodes, i.e., sensor devices, in a pre-built sensor network. These sensor devices include cameras, smoke sensors, temperature sensors, etc. The acquired real-time environmental data includes information on the location of the fire source, the type of fire source, the smoke concentration, the temperature, and the status information of each pre-planned evacuation route in the building, i.e., the occupancy / blockage status information of each evacuation route.

[0023] More specifically, when acquiring real-time environmental data inside a building, the location of the fire source is obtained through a combination of cameras and smoke sensors. The fire source information is obtained through cameras, the smoke concentration information is obtained through smoke sensors, the temperature information is obtained through temperature sensors, and the status information of each evacuation route is obtained through cameras. After acquiring the corresponding data, the data will be standardized and aligned.

[0024] Step S20: Import the real-time environmental data into the pre-trained evacuation route risk assessment model and output the risk coefficient of each grid cell in the grid diagram corresponding to the building at a future time point.

[0025] In this embodiment, the step of importing the real-time environmental data into a pre-trained evacuation route risk assessment model and outputting the risk coefficient of each grid cell in the grid diagram corresponding to the building at a future time point includes: Based on the fire source location information, fire source type information, smoke concentration information, and temperature information, the smoke concentration distribution and temperature distribution in various areas of the building at multiple future time points are predicted. According to the preset risk mapping relationship, the predicted smoke concentration value in the smoke concentration distribution and the temperature value in the temperature distribution are mapped to the reference risk value of the corresponding grid cell. The baseline risk value is corrected based on the status information of the evacuation routes; If the evacuation route corresponding to any grid cell is unavailable, the risk coefficient of that grid cell is adjusted to the maximum value.

[0026] In addition, the step of mapping the predicted smoke concentration values ​​in the smoke concentration distribution and the temperature values ​​in the temperature distribution to the baseline risk values ​​of the corresponding grid cells according to the preset risk mapping relationship includes: Multiple risk level thresholds are set for the smoke concentration values ​​in the smoke concentration distribution and the temperature values ​​in the temperature distribution, respectively; Based on the predicted smoke concentration and temperature values, query their respective risk levels and assign corresponding level scores; Based on preset weights, the level scores of the smoke concentration value and the level scores of the temperature value are weighted and calculated to obtain the baseline risk value of the corresponding grid cell.

[0027] In addition, the step of weighting the level scores of the smoke concentration value and the temperature value based on preset weights to obtain the baseline risk value of the corresponding grid cell includes: Based on the fire source type information, dynamically determine the weighting coefficients corresponding to the smoke concentration value and the temperature value, respectively. The baseline risk value of the corresponding grid cell is obtained by weighting the level score of the smoke concentration value and the level score of the temperature value. The expression for calculating the benchmark risk value is as follows: R =( S × W _ s )+( T × W _ t ); In the formula, R As the benchmark risk value, S The level score is the number of grades for the smoke concentration value. W _ s The weighting coefficient for smoke concentration values. T The temperature value is a grade or fraction. W _ t Let be the weighting coefficient for temperature values, and satisfy . W _ s + W _ t =1.

[0028] Specifically, in this embodiment, the process of importing real-time environmental data into a pre-trained evacuation route risk assessment model and outputting the risk coefficient of each grid cell in the building's corresponding grid diagram at future time points is achieved through a pre-set smoke flow and heat conduction model. It should be noted that this smoke flow and heat conduction model can be a simplified physical model based on computational fluid dynamics principles, or a machine learning model trained with a large amount of fire scenario data, such as a time-series predictive neural network. By acquiring real-time environmental data within the building, and based on the current fire source location, type, initial smoke concentration, and temperature, the diffusion and distribution of smoke and temperature within the building space at specific future time points, such as 30 seconds and 60 seconds, are dynamically predicted. By gridding the building's internal space, the predicted output results are the smoke concentration and temperature values ​​for each grid cell at different future time points. This gridding process discretizes the continuous physical space into a computer-processable data structure, laying a solid foundation for subsequent risk quantification.

[0029] The purpose of quantifying the baseline risk value based on risk mapping is to convert physical parameters into a unified risk metric, i.e., to determine the risk level of the data format. In specific implementation, a set of risk level thresholds needs to be set for smoke concentration and temperature, for example, dividing them into four levels: "Safe," "Caution," "Danger," and "Extremely Dangerous," and setting corresponding concentration and temperature threshold ranges. These thresholds are determined based on human tolerance characteristics, fire protection standards, and massive amounts of historical disaster data. Then, the predicted physical quantity value of each grid cell is compared with the preset threshold range to determine its risk level and assign a quantified score, thereby converting continuous physical quantities into discrete risk scores. Considering that smoke concentration and temperature contribute differently to the threat to life in different fires, this embodiment will also dynamically determine weighting coefficients based on the type of fire source and use a weighted calculation formula to generate a baseline risk value for each grid cell, aiming to comprehensively reflect the static risk level caused by environmental factors at that location.

[0030] The final risk coefficient correction step, which incorporates the status of evacuation routes, allows risk assessments to better reflect actual evacuation conditions. After obtaining a baseline risk value, the status information of evacuation routes associated with each grid unit is queried, such as the status of safety exit door magnets, camera-detected blockages, or the status of fireproof roller shutters. For example, if an evacuation route corresponding to a grid unit is determined to be unusable, regardless of the level of environmental risk, the final risk coefficient of that grid unit is adjusted to a preset maximum value. This fundamentally ensures that route planning will not guide personnel to unusable evacuation routes, greatly improving the safety and reliability of the evacuation plan. Conversely, if the evacuation route is unobstructed, the final risk coefficient equals the baseline risk value.

[0031] In this embodiment, real-time environmental parameters are obtained to make conditional judgments and output risk coefficients. Each grid cell in the building grid diagram is given a final risk coefficient that can reflect both the real-time environmental hazards and the availability of the passage, providing accurate data basis for the subsequent generation of the optimal evacuation route.

[0032] Step S30: Starting from the current location of the target personnel and ending at the safe zone, and using the risk coefficient corresponding to the grid unit as the path weight, the evacuation route is planned using a path search method, and at least one evacuation route is output.

[0033] In this embodiment, the steps of planning evacuation routes and outputting at least one evacuation route, using the target personnel's current location as the starting point, the safe zone as the ending point, and the risk coefficient corresponding to the grid cell as the path weight, and employing a path search method, include: Starting from the target personnel's current location and ending at the safe zone, the path weight is determined by the risk coefficient corresponding to the grid cell. The cost function is constructed by combining the physical length of the path and the real-time risk coefficient of the grid cells it passes through. The path with the minimum comprehensive cost is then searched and determined as the main evacuation path. Set the risk coefficient of the grid cells involved in the key sections of the main evacuation route to the maximum value, and search again to determine at least one alternative evacuation route that differs from the main evacuation route.

[0034] In the step of searching and determining the path with the minimum comprehensive cost as the main evacuation path, the cost function F(n) is expressed as: F(n)=G(n)+H(n)+λ*ΣR(m). In the formula, G(n) is the actual path length cost from the starting point to the current node n, H(n) is the estimated length cost from node n to the end point, ΣR(m) is the sum of the risk coefficients of all grids m along the path from the starting point to node n, and λ is the risk penalty factor.

[0035] Specifically, this embodiment constructs a multi-objective cost function and searches for the main evacuation route based on it. Its core lies in unifying the two objectives of shortest path and lowest risk within a quantifiable framework. The cost function F(n) = G(n) + H(n) + λ*ΣR(m) is an innovative improvement on the classic A* algorithm. The G(n) + H(n) term inherits the traditional algorithm's pursuit of path length, ensuring efficient spatial search. The newly added λ*ΣR(m) term introduces a quantitative assessment of safety, accumulating the sum of risk coefficients of all grids traversed along the entire path from the starting point to the current node n. The risk penalty factor λ is a key configurable parameter whose value directly determines the algorithm's tendency to balance path length and safety risk. When λ is large, high-risk paths are avoided first, even if a longer route needs to be chosen; conversely, the shortest path is preferred. Furthermore, the value of the risk penalty factor λ can be dynamically adjusted based on factors such as real-time fire conditions and building functions, thereby achieving adaptive intelligent decision-making. During the path search process, starting from the starting point, the cost function of adjacent grids is continuously evaluated, and the node with the lowest cost is expanded first until the destination is found. Finally, the path with the lowest overall cost, which is also the shortest path and the lowest risk, is determined as the main evacuation path.

[0036] After determining the primary evacuation route through comprehensive cost assessment, this embodiment will further search for and determine at least one backup evacuation route, aiming to provide an effective safety backup for the primary evacuation route and significantly improve robustness in the face of emergencies such as sudden failure of the primary route.

[0037] Specifically, the risk coefficient of the grid cells involved in the key sections of the main evacuation route is temporarily set to the maximum value. This is an equivalent simulation of the scenario where the grid cells involved in the key sections, i.e. the corresponding key passages, become impassable due to the intensification of the fire or obstruction by obstacles. By marking the grid cells involved as extremely dangerous or dangerous, this embodiment will use the same path search algorithm again to perform calculations in the updated risk field. This time, the search will be forced to completely bypass the marked grid cells, thereby searching and determining at least one new path that is significantly different from the main evacuation route, i.e., an alternative evacuation route.

[0038] Step S40: Generate control instructions according to the evacuation route, and dynamically adjust the image indication content and / or voice broadcast content of the fire emergency evacuation equipment according to the control instructions.

[0039] Specifically, in this embodiment, the planned digital path is transformed into precise guidance instructions that can be executed on-site. After the device receives the above instructions, the emergency lighting fixtures form a coherent visual guidance by projecting arrow directions and light flow effects, while the emergency broadcast can also play voice content that matches the risk level of the path, thereby realizing dynamic evacuation guidance that is coordinated by images and voice and adapts to the risk level.

[0040] Compared with the prior art, the control method for the fire emergency evacuation equipment shown in this embodiment has the following advantages: The method described in this invention acquires real-time environmental data inside a building, including fire source location information, fire source type information, smoke concentration information, temperature information, and status information of each evacuation route. This real-time environmental data is imported into a pre-trained evacuation route risk assessment model, outputting the risk coefficient of each grid cell in the building's corresponding grid diagram at a future time point. Starting from the current location of the target personnel and ending at the safe zone, and using the risk coefficient corresponding to the grid cell as the path weight, a path search method is employed to plan evacuation routes, outputting at least one evacuation route. Control commands are generated based on the evacuation routes, and the image indication content and / or voice broadcast content of the fire emergency evacuation equipment are dynamically adjusted according to the control commands. This method, through dynamic risk assessment and intelligent path planning, generates safe evacuation routes and coordinates with guidance equipment, significantly improving the success rate and safety of evacuation in emergency situations.

[0041] Example 2 The second embodiment of the present invention also provides a control method for fire emergency evacuation equipment. The method shown in this embodiment is basically similar to the method shown in the first embodiment, except that: In this embodiment, the steps of generating control commands based on the evacuation routes and dynamically adjusting the image indication content and / or voice broadcast content of the fire emergency evacuation equipment based on the control commands include: Based on the evacuation route, a dynamic guidance identifier bound to the evacuation route is generated, and the dynamic guidance identifier, the route information of the evacuation route, and the overall risk level corresponding to the evacuation route are encapsulated in the control command. According to the control command, the multiple fire emergency evacuation devices on the evacuation route dynamically adjust the image indication content and / or voice broadcast content.

[0042] The step of dynamically adjusting the image indication content and / or voice broadcast content of multiple fire emergency evacuation devices along the evacuation route according to the control command includes: Based on the path information of the evacuation route, a registration instruction is sent to all target fire emergency evacuation devices on the path sequence, and the dynamic guidance identifier is bound to the target fire emergency evacuation device; Based on the path length of the evacuation route and the preset evacuation speed, an activation timing command for controlling the differentiated activation of the target fire emergency evacuation equipment is calculated and sent; wherein, the equipment at the starting point of the route is activated immediately and displays a direction containing the dynamic guidance identifier; the subsequent equipment in the route is activated sequentially with a delay according to the activation timing command, forming a progressive dynamic optical flow pointing to the safety exit; The alarm intensity of each target fire emergency evacuation device is adaptively adjusted according to the overall risk level in the control command; wherein the flashing frequency and brightness of the image indication content, as well as the volume and urgency of the voice broadcast content, are positively correlated with the overall risk level.

[0043] The step of calculating and sending activation timing instructions for controlling the differentiated activation of the target fire emergency evacuation equipment based on the path length of the evacuation route and the preset evacuation speed includes: Based on the path length and preset evacuation speed of the evacuation route, calculate the theoretical activation time of each target fire emergency evacuation device on the evacuation route. The system monitors the personnel passage status of key nodes on the evacuation route in real time, and dynamically delays and corrects the theoretical activation time based on the personnel passage status to generate the final activation timing command.

[0044] Specifically, in this embodiment, at the device control level, precise networking and centralized management of all devices along the evacuation path are achieved through device registration and identifier binding. This includes proactively sending registration commands to target devices in the sequence based on planned path information and binding each command to a unique dynamic guidance identifier. This not only ensures that control commands are accurately delivered to the target device cluster, avoiding misguidance, but also constructs a virtual logical group based on the path. When it is necessary to update or revoke the guidance scheme, only the device group associated with the identifier needs to be operated on, effectively improving management efficiency and data consistency.

[0045] Secondly, regarding the guidance mode, this embodiment utilizes a time-series activation mechanism to create a progressive dynamic optical flow guidance. Specifically, based on the path length and a preset safe evacuation speed, the theoretical activation time of each device node is calculated. The starting device is activated immediately, and subsequent devices are activated sequentially according to the calculated delay, thus forming a forward-flowing light band on the ground or wall. This optical flow effect aligns with the expected movement of people, naturally and intuitively guiding the evacuation direction. Especially in low-visibility, dense smoke environments, this continuous dynamic visual effect offers stronger guidance and greater tolerance than a single static arrow marker.

[0046] Most importantly, this embodiment does not mechanically execute a preset timing sequence, but monitors the actual passage status of people at key nodes in real time. When the passage rate is detected to be lower than expected, such as when congestion occurs, the activation delay parameter of subsequent devices is dynamically increased to slow down the movement speed of the optical flow. This effectively prevents secondary disasters such as stampedes caused by the continuous accumulation of people at congestion points during the evacuation process, significantly improving the safety of the evacuation process.

[0047] Example 3 Please see Figure 2 A third embodiment of the present invention provides a control system for a fire emergency evacuation device, applied to the method described in any of the above embodiments, the system comprising: The data acquisition module 10 is used to acquire real-time environmental data inside the building, including fire source location information, fire source type information, smoke concentration information and temperature information, as well as the status information of each evacuation route. Risk assessment module 20 is used to import the real-time environmental data into a pre-trained evacuation route risk assessment model and output the risk coefficient of each grid cell in the grid diagram corresponding to the building at a future time point. The path planning module 30 takes the current location of the target personnel as the starting point, the safe area as the ending point, and the risk coefficient corresponding to the grid unit as the path weight. It uses a path search method to plan the evacuation path and outputs at least one evacuation path. The instruction execution module 40 is used to generate control instructions according to the evacuation route, and dynamically adjust the image indication content and / or voice broadcast content of the fire emergency evacuation equipment according to the control instructions.

[0048] Compared with existing technologies, the control system of the fire emergency evacuation equipment shown in this embodiment has the following advantages: The system described in this invention acquires real-time environmental data inside a building, including fire source location information, fire source type information, smoke concentration information, temperature information, and status information of each evacuation route. This real-time environmental data is imported into a pre-trained evacuation route risk assessment model, which outputs the risk coefficient of each grid cell in the building's corresponding grid diagram at a future time point. Starting from the current location of the target personnel and ending at the safe zone, and using the risk coefficient corresponding to the grid cell as the path weight, the system plans evacuation routes using a path search method, outputting at least one evacuation route. Control commands are generated based on the evacuation routes, and the image indication content and / or voice broadcast content of the fire emergency evacuation equipment are dynamically adjusted according to the control commands. Through dynamic risk assessment and intelligent path planning, the system generates safe evacuation routes and coordinates with guidance equipment, significantly improving the success rate and safety of evacuation in emergency situations.

[0049] Example 4 A fourth embodiment of the present invention provides a readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the steps of the method described in any of the above embodiments.

[0050] Example 5 A fifth embodiment of the present invention provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the method described in any of the above embodiments.

[0051] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0052] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these all fall within the protection scope of the present invention. Therefore, the protection scope of this patent should be determined by the appended claims.

Claims

1. A control method for fire emergency evacuation equipment, characterized in that, The method includes: Acquire real-time environmental data inside the building, including fire source location information, fire source type information, smoke concentration information and temperature information, as well as the status information of each evacuation route; The real-time environmental data is imported into a pre-trained evacuation route risk assessment model, and the risk coefficient of each grid cell in the grid diagram corresponding to the building is output at a future time point. Starting from the current location of the target personnel and ending at the safe zone, and using the risk coefficient corresponding to the grid unit as the path weight, the evacuation route is planned using a path search method, and at least one evacuation route is output. Control commands are generated based on the evacuation routes, and the image indication content and / or voice broadcast content of the fire emergency evacuation equipment are dynamically adjusted based on the control commands.

2. The control method for fire emergency evacuation equipment according to claim 1, characterized in that, The steps of importing the real-time environmental data into a pre-trained evacuation route risk assessment model and outputting the risk coefficient of each grid cell in the grid map corresponding to the building at a future time point include: Based on the fire source location information, fire source type information, smoke concentration information, and temperature information, the smoke concentration distribution and temperature distribution in various areas of the building at multiple future time points are predicted. According to the preset risk mapping relationship, the predicted smoke concentration value in the smoke concentration distribution and the temperature value in the temperature distribution are mapped to the reference risk value of the corresponding grid cell. The baseline risk value is corrected based on the status information of the evacuation routes; If the evacuation route corresponding to any grid cell is unavailable, the risk coefficient of that grid cell is adjusted to the maximum value.

3. The control method for fire emergency evacuation equipment according to claim 2, characterized in that, The step of mapping the predicted smoke concentration values ​​in the smoke concentration distribution and the temperature values ​​in the temperature distribution to the baseline risk values ​​of the corresponding grid cells according to the preset risk mapping relationship includes: Multiple risk level thresholds are set for the smoke concentration values ​​in the smoke concentration distribution and the temperature values ​​in the temperature distribution, respectively; Based on the predicted smoke concentration and temperature values, query their respective risk levels and assign corresponding level scores; Based on preset weights, the level scores of the smoke concentration value and the level scores of the temperature value are weighted and calculated to obtain the baseline risk value of the corresponding grid cell.

4. The control method for fire emergency evacuation equipment according to claim 3, characterized in that, The step of calculating the baseline risk value of the corresponding grid cell by weighting the level score of the smoke concentration value and the level score of the temperature value based on preset weights includes: Based on the fire source type information, dynamically determine the weighting coefficients corresponding to the smoke concentration value and the temperature value, respectively. The baseline risk value of the corresponding grid cell is obtained by weighting the level score of the smoke concentration value and the level score of the temperature value. The expression for calculating the benchmark risk value is as follows: R =( S × W _ s )+( T × W _ t ); In the formula, R As the benchmark risk value, S The level score is the number of grades for the smoke concentration value. W _ s The weighting coefficient for smoke concentration values. T The grade fraction of the temperature value. W _ t Let be the weighting coefficient for temperature values, and satisfy . W _ s + W _ t =1.

5. The control method for fire emergency evacuation equipment according to any one of claims 1-4, characterized in that, The steps of generating control commands based on the evacuation routes and dynamically adjusting the image indication content and / or voice broadcast content of the fire emergency evacuation equipment based on the control commands include: Based on the evacuation route, a dynamic guidance identifier bound to the evacuation route is generated, and the dynamic guidance identifier, the route information of the evacuation route, and the overall risk level corresponding to the evacuation route are encapsulated in the control command. According to the control command, the multiple fire emergency evacuation devices on the evacuation route dynamically adjust the image indication content and / or voice broadcast content.

6. The control method for fire emergency evacuation equipment according to claim 5, characterized in that, The step of dynamically adjusting the image indication content and / or voice broadcast content of multiple fire emergency evacuation devices on the evacuation route according to the control command includes: Based on the path information of the evacuation route, a registration instruction is sent to all target fire emergency evacuation devices on the path sequence, and the dynamic guidance identifier is bound to the target fire emergency evacuation device; Based on the path length of the evacuation route and the preset evacuation speed, an activation timing command for controlling the differentiated activation of the target fire emergency evacuation equipment is calculated and sent; wherein, the equipment at the starting point of the route is activated immediately and displays a direction containing the dynamic guidance identifier; the subsequent equipment in the route is activated sequentially with a delay according to the activation timing command, forming a progressive dynamic optical flow pointing to the safety exit; The alarm intensity of each target fire emergency evacuation device is adaptively adjusted according to the overall risk level in the control command; wherein the flashing frequency and brightness of the image indication content, as well as the volume and urgency of the voice broadcast content, are positively correlated with the overall risk level.

7. The control method for fire emergency evacuation equipment according to claim 6, characterized in that, The steps of calculating and sending activation timing commands for controlling the differentiated activation of the target fire emergency evacuation equipment based on the path length of the evacuation route and the preset evacuation speed include: Based on the path length and preset evacuation speed of the evacuation route, calculate the theoretical activation time of each target fire emergency evacuation device on the evacuation route. The system monitors the personnel passage status of key nodes on the evacuation route in real time, and dynamically delays and corrects the theoretical activation time based on the personnel passage status to generate the final activation timing command.

8. A control system for a fire emergency evacuation device, characterized in that, The system, applicable to the method of any one of claims 1-7, comprises: The data acquisition module is used to acquire real-time environmental data inside the building, including fire source location information, fire source type information, smoke concentration information and temperature information, as well as the status information of each evacuation route; The risk assessment module is used to import the real-time environmental data into a pre-trained evacuation route risk assessment model and output the risk coefficient of each grid cell in the grid diagram corresponding to the building at a future time point. The path planning module takes the current location of the target personnel as the starting point, the safe zone as the ending point, and the risk coefficient corresponding to the grid unit as the path weight. It uses a path search method to plan the evacuation path and outputs at least one evacuation path. The instruction execution module is used to generate control instructions corresponding to the evacuation route, and dynamically adjust the image indication content and / or voice broadcast content of the fire emergency evacuation equipment according to the control instructions.

9. A readable storage medium having computer instructions stored thereon, characterized in that, When executed by the processor, this instruction implements the steps of the method as described in any one of claims 1-7.

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the method as described in any one of claims 1-7.

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