A fire emergency drill method based on computer technology

Abstract

The invention discloses a fire emergency drill method based on computer technology, and relates to the field of intelligent rescue technology. The invention standardizes and systematizes the fire emergency drill process, defines the tasks, decision nodes and time requirements of each link, avoids human operation errors, improves the coordination of the drill, and makes the task execution smoother. At the same time, an automatic monitoring system is adopted to collect the physical state of firefighters, the use of fire extinguishing equipment and the dynamic development of fire in real time. GPS positioning equipment, biological monitoring equipment and fire sensors continuously track the physical condition of participants and changes in fire conditions, greatly improve the reaction speed and accuracy of the drill, reduce feedback hysteresis, and perform dynamic adjustment through the integration of the automatic monitoring system and the BPMN model. When the fire condition changes significantly, it is immediately fed back to the decision node in the BPMN model, and the emergency strategy is automatically adjusted, thereby enhancing the adaptability of the drill to sudden complex situations and being closer to the dynamic needs in real fires.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent rescue, and particularly to a fire emergency drill method based on computer technology. Background Art

[0002] In fire emergency drills, process control and monitoring are key links to ensure the smooth progress of the drills. However, traditional fire emergency drills mostly rely on preset scripts and manual command, lacking systematic process management and automated monitoring. During the drill process, the connection between each link is not smooth enough, and the execution standards are not unified, making it difficult to accurately simulate the emergency response in case of an emergency. In addition, drill monitoring relies on manual observation and video monitoring, lacking real-time data feedback and automated analysis. The evaluation mostly relies on subjective judgment, unable to quantify the performance of participants, and unable to adapt to sudden changes in the fire situation, making it difficult to truly reflect the dynamic requirements of emergency response.

[0003] In response to the above problems, some existing solutions optimize them. The drill process control is handed over to manual command, and the operation instructions for each link are sequentially issued by the command personnel. The participants execute tasks in sequence, and drill supervisors are arranged to observe and record the performance of the participants on site. After the drill, summary and feedback are carried out based on the monitoring video and manual records. The drill route is based on the preset fire development route, and the participants carry out corresponding evacuation, fire extinguishing, etc. according to the prior plan;

[0004] Although the above solutions can complete the basic drill process, the process control relies on manual command, which is prone to lag and difficult to adapt to the rapidly changing situation in a fire. In addition, the execution time points and order of each link are not precise enough, unable to truly simulate the emergency response situation. Moreover, manual monitoring and recording are subjective, the feedback is not timely, making it difficult to achieve standardized and quantitative evaluation. The drill method has insufficient flexibility and cannot handle sudden situations in complex fire scenes, limiting the test and improvement of the real emergency response capabilities of the participants. Therefore, there is an urgent need for a fire emergency drill method based on computer technology to solve such problems. Summary of the Invention

[0005] In view of the above existing problems, the present invention is proposed.

[0006] The present invention provides a fire emergency drill method based on computer technology to solve the problems that the traditional control process relies on manual command, is prone to lag, difficult to adapt to the rapidly changing situation in a fire, and the execution time points and order of each link are not precise enough, unable to truly simulate the emergency response.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] The present invention provides a fire emergency drill method based on computer technology, which includes,

[0009] Step S1, construct a fire emergency BPMN process model,

[0010] Construct a standardized BPMN model covering fire emergency drills based on the business process modeling BPMN technology. This BPMN model includes multiple task links and decision nodes;

[0011] Step S2, integrate an automated monitoring system,

[0012] Based on the BPMN model constructed in Step S1, integrate the automated monitoring system with the BPMN model. The automated monitoring system is used to track the execution of the drill in real time,

[0013] Step S3, adjust the drill process based on dynamic scenarios,

[0014] According to the real-time execution data feedback by the automated monitoring system, the drill process will be dynamically adjusted according to the changes in the scenario. When the automated monitoring system detects significant changes in the fire situation, the decision nodes in the BPMN model immediately trigger the adjustment of the emergency strategy,

[0015] Step S4, data feedback and drill evaluation,

[0016] During the whole process of the drill, the automated monitoring system continuously collects participant and scenario data, including reaction time, operation of fire extinguishing equipment, and personnel evacuation efficiency, and analyzes the participant and scenario data and feeds it back into the BPMN model to generate an analysis report.

[0017] Furthermore, in Step S1, the tasks of each link include:

[0018] Alarm and preliminary response: including starting the alarm and starting the emergency response team,

[0019] Command and coordination: simulate the decision-making process of the fire commander and allocate emergency resources,

[0020] Personnel evacuation: evacuation process and evacuation route,

[0021] Fire extinguishing and fire control: including using fire extinguishing equipment, evaluating the development of the fire, and deciding on the fire extinguishing strategy,

[0022] Medical rescue: arrange medical first responders to handle the wounded according to the scenario.

[0023] Furthermore, in Step S1, the method of constructing the fire emergency BPMN process model is:

[0024] Define the task links and time nodes, and estimate the time for each link:

[0025] T i =T base +α·Ci +β·D i , where T i represents the total time of task step i, T base represents the base time of the task, i.e., the execution time without any additional conditions. α is the task complexity coefficient, including fire complexity and evacuation route obstacles, C i represents the complexity of task step i, β is the decision-making influence coefficient, D i represents the number of decisions to be made in task step i,

[0026] Define resource allocation:

[0027] where R i represents the effective resource allocation rate of task step i, N i represents the number of firefighters allocated to task step i, K i represents the standard number of personnel required for task step i, P i represents the percentage of available equipment in task step i,

[0028] Define the efficiency of personnel evacuation and withdrawal:

[0029] where T evac represents the total time required for personnel to evacuate from the current location to a safe location, L represents the length of the evacuation route, v represents the average walking speed of personnel, γ is the congestion coefficient, N represents the number of personnel on this route,

[0030] Define the relationship between fire extinguishing equipment and fire control:

[0031] where T fire represents the time required to control the fire using fire extinguishing equipment, E represents the effectiveness of the fire extinguishing equipment, W represents the scale of the fire, F represents the fire spread speed,

[0032] Define the response time of the medical rescue step:

[0033] where T med represents the response time of the medical rescue task, M represents the number of people in need of rescue, A represents the current available medical resources, S represents the average severity of the injuries of the wounded.

[0034] Furthermore, in step S2, the implementation situation of the tracking and monitoring drill includes:

[0035] Personal device monitoring: Firefighters wear GPS positioning devices and biometric monitoring devices to record their locations, movement paths, and physiological data (such as heart rate, body temperature, and respiratory rate) in real time, and to evaluate the physical fitness and response of personnel.

[0036] Internet of Things sensor monitoring: Install sensors and cameras at the drill site to monitor the on-site temperature, smoke concentration, air flow direction, humidity, and the status of fire-fighting equipment (such as the water pressure and flow rate of fire hoses, and the usage of fire extinguishers).

[0037] Fire sensor monitoring: Used to track the spread, location, and scale of the fire in real time, and to feedback the speed and scope of the fire development.

[0038] Furthermore, in step S2, the automated monitoring system is integrated with the BPMN model to track the drill process and evaluate the physical fitness of firefighters and the dynamic changes of the fire. Specifically:

[0039] In fire emergency drills, evaluate the physical fitness status of firefighters based on GPS positioning devices and biometric monitoring devices, and calculate the physical exertion of firefighters:

[0040] Among them, E i represents the physical exertion of the firefighter in task segment i, M represents the weight of the firefighter, H r represents the real-time heart rate of the firefighter in segment i, H max represents the maximum heart rate of the firefighter, T b represents the current body temperature of the firefighter, T norm represents the normal body temperature, d i represents the distance traveled by the firefighter in segment i.

[0041] Use fire sensors to monitor the spread speed, coverage area, and fire source temperature of the fire. The spread speed of the fire is expressed as:

[0042] Among them, V f represents the spread speed of the fire, A t represents the coverage area of the fire at time t, A 0 represents the coverage area at the initial moment of the fire, t represents the time required for the fire to spread from A 0 to A t required.

[0043] Based on the working status of the Internet of Things sensor monitoring equipment, including the water flow rate and water pressure of fire extinguishing, the water flow rate of fire-fighting equipment is:

[0044] Among them, Q eIt represents the water flow rate of the fire extinguishing equipment, P represents the water pressure of the equipment, A represents the effective area of the fire extinguishing nozzle, and R represents the resistance coefficient of the fire extinguishing equipment.

[0045] Based on the sensor data, the BPMN model is adjusted in real time, and the adjustment is triggered when it is detected that the fire spread speed exceeds the expected value:

[0046] Among them, ΔT represents the time interval for urgently adjusting the task process, A t and A 0 represent the change in the fire area, V f represents the fire spread speed, S represents the safe evacuation time, that is, the maximum tolerable time for firefighters and personnel in the dangerous area. When ΔT is less than the preset threshold, the fire development speed is fed back to the BPMN model, and the personnel evacuation route, fire extinguishing plan or resource allocation is adjusted.

[0047] During the monitoring process, the reaction time of firefighters in handling tasks is evaluated simultaneously:

[0048] Among them, T r represents the reaction time of the firefighters, T start represents the basic reaction time at the start of the task, T com represents the communication delay between the time when the firefighters receive the instruction and the time when they execute the instruction, C i represents the complexity of task link i.

[0049] The automated monitoring system is effectively integrated with the BPMN model to achieve tracking and feedback on the physical condition of firefighters, fire spread, the status of fire extinguishing equipment, and the reaction time of personnel. After quantifying the data of each task link, dynamic adjustments are made according to the real-time situation.

[0050] Furthermore, in step S3, the significant change situations include fire spread, obstruction of the personnel evacuation route, or malfunction of the fire extinguishing equipment.

[0051] In step S3, the specific steps for adjusting the emergency strategy include:

[0052] According to the spread situation of the fire, change the personnel evacuation route.

[0053] According to the status of the fire extinguishing equipment and the scale of the fire, switch the fire extinguishing plan.

[0054] According to the personnel location and the change of the fire, reallocate the rescue resources.

[0055] Furthermore, in step S3, after the automated monitoring system feeds back the real-time data, the BPMN model is dynamically adjusted according to the significant changes in the fire situation, and the adjustment method is:

[0056] When the automated monitoring system detects the spread of fire, calculate the rate of fire spread and determine whether the current fire situation exceeds the preset threshold. The rate of fire spread is:

[0057] where v f represents the rate of fire spread, that is, the rate of change of the fire coverage area with time. dA represents the increment of the fire coverage area, and dt represents the time increment. If v f exceeds the set threshold, trigger the corresponding emergency strategy adjustment.

[0058] If the fire spread blocks the original evacuation route of the personnel, adjust the evacuation path, adopt the dynamic path planning formula based on the Dijkstra algorithm, and adjust the new evacuation route in combination with the rate of fire spread:

[0059] where L new represents the shortest time of the dynamically adjusted evacuation route, di represents the distance from the current node to the next node, v i represents the moving speed of the personnel on this section of the road, λ represents the weight coefficient affecting the fire spread, represents the total spread impact of the fire changing with time t.

[0060] When the fire situation develops beyond expectations, adjust the fire extinguishing strategy: monitor the effectiveness of the fire extinguishing equipment and determine whether to switch the fire extinguishing strategy:

[0061] where T extinguish represents the time required for fire extinguishing, W f represents the current heat energy or the size of the fire, E current represents the current effectiveness of the fire extinguishing equipment, δ represents the attenuation rate of the fire extinguishing equipment effectiveness, t represents the continuous use time of the fire extinguishing equipment. When T extinguish exceeds the preset threshold, switch the fire extinguishing equipment or strategy.

[0062] Furthermore, in step S3, perform real-time resource allocation adjustment:

[0063] When the fire spreads or equipment fails, reallocate equipment resources:

[0064] where R i represents the resource satisfaction rate in task link i, N available represents the current available resource quantity, and the drill personnel are also regarded as the resource quantity. N required represents the standard resource quantity required in task link i, η represents the emergency impact coefficient of fire spread, v f represents the rate of fire spread, V maxrepresents the preset maximum fire spread rate. When R i is less than 1, it indicates that the current resources are insufficient and immediate adjustment is required.

[0065] During the entire drill process, the comprehensive risk assessment function is calculated in real time to determine whether to immediately trigger the adjustment of the emergency strategy:

[0066] Among them, F risk represents the comprehensive risk assessment function. The higher the value, the greater the risk. α represents the weight coefficient of the fire spread rate, β represents the weight coefficient of the impact of evacuation route adjustment, γ represents the weight coefficient of the deviation of the fire extinguishing time, θ represents the weight coefficient of insufficient resource allocation, and L original represents the length of the original evacuation route. When F risk exceeds the preset threshold, the decision node in the BPMN model automatically triggers the adjustment of the emergency strategy, changing the evacuation route, fire extinguishing strategy, or resource allocation.

[0067] Furthermore, in step S4, the content of the analysis report includes:

[0068] The execution time point and completion degree of each task link,

[0069] Whether the operations of the participants in the fire extinguishing and evacuation tasks conform to the standard procedures,

[0070] Quantitatively evaluate the emergency performance of the participants based on physiological sensing data, reaction speed, and task completion efficiency.

[0071] Furthermore, in step S4, the data feedback and drill evaluation method is as follows:

[0072] Collect and analyze the reaction time of the participants:

[0073] Among them, T r represents the actual reaction time of the participants, T base represents the basic reaction time, κ represents the weight factor of task complexity, C represents the complexity level of the task. The higher the complexity, the longer the reaction time, and S p represents the preset experience level of the participants, H r represents the current heart rate, H max represents the maximum heart rate of the participants, and T delay represents the additional reaction delay under high-intensity tasks.

[0074] Evaluate the operation efficiency of the equipment:

[0075] Among them, E op represents the operation efficiency of the fire extinguishing equipment, P used represents the power actually used by the equipment, Pmax Represents the maximum power of the device, t op Represents the actual operation time of the device, t fail Represents the failure time of the device under extreme conditions. η represents the operation proficiency coefficient of the device. If t op is close to t fail , the operation efficiency of the device will decrease significantly.

[0076] Calculate the personnel evacuation efficiency:

[0077] Among them, E evac Represents the personnel evacuation efficiency, L opt Represents the length of the optimal evacuation route, L actual Represents the actual evacuation route length, v avg Represents the average walking speed of the participants, v max Represents the maximum moving speed under normal conditions, N crowd Represents the number of people encountering congestion during the evacuation, N cap Represents the maximum capacity of the evacuation route.

[0078] Based on the reaction time, fire extinguishing equipment operation, and evacuation efficiency data, conduct weighted comprehensive feedback on the overall drill performance:

[0079] Among them, P total Represents the comprehensive performance score of the drill. α represents the weight factor of the reaction time, T r is the actual reaction time, T target is the target reaction time. β represents the weight factor of the fire extinguishing equipment operation, E op is the operation efficiency of the fire extinguishing equipment. γ represents the weight factor of the evacuation efficiency, E enac is the evacuation efficiency.

[0080] Form the final drill performance score and feedback it to the BPMN model.

[0081] The beneficial effects of the present invention are:

[0082] In the present invention, the fire emergency drill process is standardized and systematized, the tasks, decision nodes, and time requirements of each link are defined, human operation errors are avoided, the coordination of the drill is improved, and the task execution is smoother.

[0083] In the present invention, an automated monitoring system is adopted to collect the physical fitness status of firefighters, the usage of fire extinguishing equipment, and the dynamic development of fires in real time. GPS positioning equipment, biological monitoring equipment, and fire sensors continuously track the physical condition of participants and the changes in the fire situation, greatly improving the reaction speed and accuracy of the drill and reducing the feedback latency.

[0084] In the present invention, through the integration of an automated monitoring system and a BPMN model for dynamic adjustment, when significant changes occur in a fire situation, such as the spread of the fire, obstruction of the evacuation route, or equipment failure, it is immediately fed back to the decision-making nodes in the BPMN model, automatically adjusting the emergency strategy, enhancing the adaptability of the drill to sudden and complex situations, and being closer to the dynamic requirements in a real fire.

[0085] In the present invention, the automated monitoring system continuously collects data on response time, equipment operation efficiency, and evacuation efficiency, generates a quantitative analysis report, and constitutes a comprehensive performance score, eliminating the subjectivity of scoring in traditional methods.

[0086] In the present invention, the real-time monitoring system dynamically monitors the equipment status, the scale of the fire, and the physical condition of firefighters, and automatically adjusts the resource allocation based on real-time data, avoiding the lag of manual deployment. BRIEF DESCRIPTION OF THE DRAWINGS

[0087] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0088] Figure 1 It is a schematic flowchart of a fire emergency drill method based on computer technology of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0089] In order to make the above objects, features, and advantages of the present invention more obvious and understandable, the following will make a detailed description of the specific embodiments of the present invention in conjunction with the drawings of the specification.

[0090] In the following description, many specific details are set forth in order to fully understand the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0091] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation manner of the present invention. The phrase "in one embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that is mutually exclusive with other embodiments.

[0092] Embodiment 1, referring to Figure 1 , this embodiment provides a fire emergency drill method based on computer technology, including the following steps:

[0093] Step S1, construct a fire emergency BPMN process model.

[0094] Based on the Business Process Modeling BPMN technology, construct a standardized BPMN model covering fire emergency drills. This BPMN model contains multiple task links and decision nodes.

[0095] The tasks for each link include:

[0096] Alarm and initial response: including initiating the alarm and activating the emergency response team.

[0097] Command and coordination: simulate the decision-making process of the fire commander and allocate emergency resources.

[0098] Personnel evacuation: evacuation process and evacuation routes.

[0099] Fire extinguishing and fire control: including using fire extinguishing equipment, assessing the development of the fire, and deciding on fire extinguishing strategies.

[0100] Medical rescue: arrange medical first responders to handle the wounded according to the situation.

[0101] In step S1, the method of constructing the fire emergency BPMN process model is as follows:

[0102] Define task links and time nodes, and estimate the time for each link:

[0103] T i =T base +α·C i +β·D i where T i represents the total time of task link i, T base represents the basic time of this task, that is, the execution time without any additional conditions. α is the task complexity coefficient, including fire complexity and evacuation route obstacles. C i represents the complexity of task link i. β is the decision impact coefficient, and D i represents the number of decisions to be made in task link i.

[0104] Conduct resource allocation definition:

[0105] where R i represents the effective resource allocation rate of task link i, N i represents the number of firefighters assigned to task link i, K i represents the standard number of personnel required for task link i, and P i represents the percentage of available equipment in task link i.

[0106] Conduct personnel evacuation and evacuation efficiency definition:

[0107] Among them, T evac represents the total time required for personnel to evacuate from the current location to a safe location, L represents the length of the evacuation route, v represents the average walking speed of personnel, γ is the congestion coefficient, and N represents the number of personnel on this route.

[0108] Define the relationship between fire extinguishing equipment and fire control:

[0109] Among them, T fire represents the time required to control the fire using fire extinguishing equipment, E represents the effectiveness of the fire extinguishing equipment, W represents the scale of the fire, and F represents the fire spreading speed.

[0110] Define the response time of the medical rescue link:

[0111] Among them, T med represents the response time of the medical rescue task, M represents the number of people in need of rescue, A represents the current available medical resources, and S represents the average severity of the injuries of the wounded.

[0112] Specifically, the BPMN technology is used to standardize the task links in the fire emergency drill, including alarm and preliminary response, personnel evacuation, fire extinguishing, and medical rescue, define the execution time, resource requirements, and decision-making nodes of each link, provide a structured basis, and effectively reduce the lag of manual command.

[0113] Step S2, integrate the automated monitoring system.

[0114] Based on the BPMN model constructed in Step S1, integrate the automated monitoring system with the BPMN model. The automated monitoring system is used to track the execution of the drill in real time.

[0115] In Step S2, the execution of the drill tracked and monitored includes:

[0116] Personal equipment monitoring: Firefighters wear GPS positioning equipment and biological monitoring equipment to record their locations, movement paths, and physiological data (heart rate, body temperature, respiratory rate, etc.) in real time, and evaluate the physical fitness and response of personnel.

[0117] Internet of Things sensor monitoring: Install sensors and cameras in the drill site to monitor the on-site temperature, smoke concentration, air flow direction, humidity, and the status of fire extinguishing equipment (water pressure and water flow rate of fire hoses, usage of fire extinguishers, etc.).

[0118] Fire sensor monitoring: Used to track the spread, location, and scale of the fire in real time, and feedback the speed and scope of the fire development.

[0119] In step S2, the automated monitoring system is integrated with the BPMN model to track the drill process and evaluate the physical condition of firefighters and the dynamic changes of the fire. Specifically:

[0120] In the fire emergency drill, the physical condition of firefighters is evaluated based on GPS positioning devices and biological monitoring devices, and the physical exertion of firefighters is calculated:

[0121] Among them, E i represents the physical exertion of firefighters in task link i, M represents the weight of firefighters, and H r represents the real-time heart rate of firefighters in link i, and H max represents the maximum heart rate of firefighters, T b represents the current body temperature of firefighters, and T norm represents the normal body temperature, and d i represents the distance traveled by firefighters in link i,

[0122] The spread speed, coverage area, and fire source temperature of the fire are monitored using fire sensors. The fire spread speed is expressed as:

[0123] Among them, V f represents the fire spread speed, A t represents the fire coverage area at time t, and A 0 represents the initial fire coverage area, and t represents the time required for the fire to spread from A 0 to A t

[0124] Based on the working status of the Internet of Things sensor monitoring equipment, including the fire extinguishing water flow rate and water pressure, the water flow rate of the fire extinguishing equipment is:

[0125] Among them, Q e represents the water flow rate of the fire extinguishing equipment, P represents the water pressure of the equipment, A represents the effective area of the fire extinguishing nozzle, and R represents the resistance coefficient of the fire extinguishing equipment,

[0126] Based on the sensor data, the BPMN model is adjusted in real time, and the adjustment is triggered when it is detected that the fire spread speed exceeds the expected value:

[0127] Among them, ΔT represents the time interval for urgently adjusting the task process, and A t and A 0 represent the change in the fire area, and V f ​ΔT represents the fire spread speed, and S represents the safe evacuation time, that is, the maximum tolerable time for firefighters and personnel in the dangerous area. When ΔT is less than the preset threshold, the fire development speed is fed back to the BPMN model, and the personnel evacuation route, fire extinguishing plan, or resource allocation is adjusted.

[0128] During the monitoring process, the response time of firefighters in handling tasks is also evaluated:

[0129] Among them, T r represents the response time of firefighters, T start represents the basic response time at the start of the task, T com represents the communication delay between when the firefighter receives the instruction and executes the instruction, C i represents the complexity of task link i,

[0130] The automated monitoring system is effectively integrated with the BPMN model to achieve tracking and feedback on the physical condition of firefighters, fire spread, the status of fire extinguishing equipment, and the response time of personnel. After quantifying the data of each task link, dynamic adjustments are made according to the real-time situation.

[0131] Specifically, an automated monitoring system is introduced. Through GPS positioning devices, biological monitoring devices, Internet of Things sensors, and fire sensors, the physical condition of participants, the status of equipment, and the dynamic changes of the fire are monitored in real time, and various types of data are quantified to facilitate the rapid identification of problems.

[0132] Step S3, adjusting the drill process based on the dynamic situation,

[0133] According to the real-time execution situation data fed back by the automated monitoring system, the drill process will be dynamically adjusted according to the changes in the situation. When the automated monitoring system detects significant changes in the fire situation, the decision-making nodes in the BPMN model immediately trigger the adjustment of emergency strategies.

[0134] In step S3, the significant change situations include fire spread, blocked personnel evacuation routes, or malfunction of fire extinguishing equipment.

[0135] In step S3, the specific steps for adjusting the emergency strategy include:

[0136] According to the spread of the fire situation, change the personnel evacuation route,

[0137] According to the status of the fire extinguishing equipment and the scale of the fire, switch the fire extinguishing plan,

[0138] According to the personnel location and the change of the fire situation, reallocate rescue resources,

[0139] In step S3, after the automated monitoring system feeds back the real-time data, the BPMN model is dynamically adjusted according to the significant changes in the fire situation. The adjustment method is:

[0140] When the automated monitoring system detects the spread of fire, calculate the spread rate of the fire and determine whether the current fire situation exceeds the preset threshold. The fire spread rate is:

[0141] where v f represents the spread rate of the fire, that is, the change rate of the fire coverage area with time. dA represents the increment of the fire coverage area, and dt represents the time increment. If v f exceeds the set threshold, trigger the corresponding emergency strategy adjustment.

[0142] If the fire spread blocks the original evacuation route of the personnel, adjust the evacuation path. Adopt the dynamic path planning formula based on the Dijkstra algorithm and adjust the new evacuation route in combination with the fire spread rate:

[0143] where L new represents the shortest time of the dynamically adjusted evacuation route, d i represents the distance from the current node to the next node, v i represents the moving speed of the personnel on this section of the road, and λ represents the weight coefficient affecting the fire spread. represents the total spread impact of the fire changing with time t.

[0144] Adjust the fire extinguishing strategy when the fire situation develops beyond expectations: Monitor the effectiveness of the fire extinguishing equipment and determine whether to switch the fire extinguishing strategy:

[0145] where T extinguish represents the time required for fire extinguishing, W f represents the current thermal energy or fire size of the fire, E current represents the current effectiveness of the fire extinguishing equipment, δ represents the attenuation rate of the fire extinguishing equipment effectiveness, and t represents the continuous use time of the fire extinguishing equipment. When T extinguish exceeds the preset threshold, switch the fire extinguishing equipment or strategy.

[0146] In step S3, perform real-time adjustment of resource allocation:

[0147] When the fire spreads or equipment fails, reallocate equipment resources:

[0148] where R i represents the resource satisfaction rate in task link i, N available represents the current available resource quantity, and the drill personnel are also regarded as the resource quantity. N required represents the standard resource quantity required in task link i, η represents the emergency impact coefficient of the fire spread, v fIndicates the fire spread rate, V max Indicates the preset maximum fire spread rate. When R i Is less than 1, it indicates that the current resources are insufficient and immediate adjustment is required.

[0149] During the entire drill process, the comprehensive risk assessment function is calculated in real time to determine whether to immediately trigger the adjustment of the emergency strategy:

[0150] Among them, F risk Indicates the comprehensive risk assessment function. The higher the value, the greater the risk. α represents the weight coefficient of the fire spread rate, β represents the weight coefficient of the impact of evacuation route adjustment, γ represents the weight coefficient of the deviation of the fire extinguishing time, θ represents the weight coefficient of insufficient resource allocation, and L original Indicates the length of the original evacuation route. When F risk Exceeds the preset threshold, the decision node in the BPMN model automatically triggers the adjustment of the emergency strategy, changing the evacuation route, fire extinguishing strategy or resource allocation.

[0151] Specifically, when the monitoring system detects that the fire spread exceeds the preset value, the evacuation route is blocked or there is equipment failure, the decision node in the BPMN model will automatically trigger the adjustment of the emergency strategy. The adjustment includes not only task switching, but also the re-planning of the evacuation route, the switching of fire extinguishing equipment and the re-allocation of resources, dynamically optimizing the evacuation route and fire extinguishing strategy.

[0152] Step S4, data feedback and drill evaluation,

[0153] During the entire process of the drill, the automated monitoring system continuously collects participant and scenario data, including reaction time, the operation of fire extinguishing equipment, and the evacuation efficiency of personnel, analyzes the participant and scenario data, and feeds it back into the BPMN model to generate an analysis report.

[0154] In step S4, the content of the analysis report includes:

[0155] The execution time point and completion degree of each task link,

[0156] Whether the operations of the participants in the fire extinguishing and evacuation tasks comply with the standard procedures,

[0157] Quantitatively evaluate the emergency performance of the participants based on physiological sensing data, reaction speed and task completion efficiency.

[0158] In step S4, the data feedback and drill evaluation method is:

[0159] Collect and analyze the reaction time of the participants:

[0160] Among them, T rRepresents the actual reaction time of the participant, T base Represents the base reaction time, κ represents the weight factor of task complexity, C represents the complexity level of the task, the higher the complexity, the longer the reaction time, S p Represents the preset experience level of the participant, H r Represents the current heart rate, H max Represents the maximum heart rate of the participant, T delay Represents the additional reaction delay under high-intensity tasks

[0161] Evaluate the operation efficiency of the equipment:

[0162] Among them, E op Represents the operation efficiency of the fire extinguishing equipment, P used Represents the power actually used by the equipment, P max Represents the maximum power of the equipment, t op Represents the actual time of equipment operation, t fail Represents the failure time of the equipment under extreme conditions, η represents the operation proficiency coefficient of the equipment, if t op Is close to t fail , the operation efficiency of the equipment will decrease significantly

[0163] Calculate the personnel evacuation efficiency:

[0164] Among them, E evac Represents the personnel evacuation efficiency, L opt Represents the length of the optimal evacuation route, L actual Represents the actual evacuation route length, v avg Represents the average walking speed of the participant, v max Represents the maximum moving speed under normal conditions, N crowd Represents the number of people encountering congestion during the evacuation, N cap Represents the maximum capacity of the evacuation route

[0165] Based on the reaction time, fire extinguishing equipment operation and evacuation efficiency data, conduct weighted comprehensive feedback on the overall exercise performance:

[0166] Among them, P total Represents the comprehensive performance score of the exercise, α represents the weight factor of reaction time, T r Is the actual reaction time, T target Is the target reaction time, β represents the weight factor of fire extinguishing equipment operation, E op Is the operation efficiency of the fire extinguishing equipment, γ represents the weight factor of evacuation efficiency, E enac Is the evacuation efficiency

[0167] Form the final drill performance score and feedback it into the BPMN model;

[0168] Specifically, the automated monitoring system continuously collects data on participants' reaction times, equipment operation conditions, and personnel evacuation efficiency, forms a comprehensive evaluation function, and finally generates a quantitative analysis report, eliminating the drawbacks of relying on subjective judgment in traditional drills, providing detailed performance feedback for each participant, and generating a comprehensive performance score for the drill.

[0169] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered within the scope of the claims of the present invention.

Claims

1. A fire emergency drill method based on computer technology, characterized in that: include, Step S1, constructing a fire emergency BPMN process model, and constructing a standardized BPMN model covering fire emergency drills based on the business process modeling BPMN technology, wherein the BPMN model includes multiple task links and decision nodes; The way to build the fire emergency BPMN process model is: Define the task links and time nodes, and estimate the time for each link: T i =T base +α·C i +β·D i , where T i represents the total time of task link i, T base represents the basic time of the task, that is, the execution time without any additional conditions, α is the task complexity coefficient, including the complexity of the fire and obstacles on the evacuation route, C i represents the complexity of task link i, β is the decision-making influence coefficient, and D i represents the number of decisions that need to be made in task step i, To define resource allocation: Among them, R i represents the effective resource allocation rate of task link i, N i represents the number of firefighters assigned to task link i, K i represents the standard number of personnel required for task link i, P i represents the percentage of available equipment in task link i, Evacuation and evacuation efficiency definition: Among them, T evac represents the total time required for personnel to evacuate from the current location to a safe location, L represents the length of the evacuation route, v represents the average travel speed of personnel, γ represents the congestion coefficient, and N represents the number of personnel on the route. Define the relationship between fire extinguishing equipment and fire control: Among them, T fire It indicates the time required to control the fire using fire-fighting equipment, E indicates the effectiveness of the fire-fighting equipment, W indicates the scale of the fire, and F indicates the speed of fire spread. Define the response time for medical rescue: Among them, T med represents the response time of the medical rescue mission, M represents the number of people who need to be rescued, A represents the number of medical resources currently available, and S represents the average severity of the injuries of the wounded; Step S2, integrating the automated monitoring system, based on the BPMN model constructed in step S1, integrating the automated monitoring system with the BPMN model, the automated monitoring system is used to track the execution of the drill in real time, In step S2, the execution of the drill to be tracked and monitored includes: Personal equipment monitoring: Firefighters wear GPS positioning devices and biometric monitoring devices to record their location, movement path and physiological data in real time, and assess their physical fitness and response status. IoT sensor monitoring: Install sensors and cameras at the exercise site to monitor on-site temperature, smoke concentration, airflow direction, humidity, and the status of fire-fighting equipment. Fire sensor monitoring: used to track the spread, location and scale of fire in real time, and provide feedback on the speed and scope of fire development; In step S2, the automated monitoring system is integrated with the BPMN model to track the drill process and evaluate the physical condition of the firefighters and the dynamic changes of the fire. Specifically: In fire emergency drills, the physical condition of firefighters is assessed based on GPS positioning equipment and biological monitoring equipment, and the physical exertion of firefighters is calculated: Among them, E i represents the physical energy consumption of the firefighter in task link i, M represents the weight of the firefighter, H r represents the real-time heart rate of the firefighter in link i, H max represents the maximum heart rate of the firefighter, T b Represents the current body temperature of the firefighter, T norm Indicates normal body temperature, d i represents the distance traveled by the firefighter in link i, Fire sensors are used to monitor the fire spread speed, coverage area and fire source temperature. The fire spread speed is expressed as: Among them, V f Indicates the speed of fire spread, A t represents the coverage area of ​​the fire at time t, A0 represents the coverage area at the initial moment of the fire, and t represents the spread of the fire from A0 to A t The time required, Based on the IoT sensor monitoring equipment's working status, including fire extinguishing water flow rate and water pressure, the water flow rate of the fire extinguishing equipment is: Among them, Q e It represents the water flow rate of the fire extinguishing equipment, P represents the water pressure of the equipment, A represents the effective area of ​​the fire extinguishing nozzle, and R represents the resistance coefficient of the fire extinguishing equipment. Adjust the BPMN model in real time based on sensor data, triggering adjustments when it detects that the fire is spreading faster than expected: Among them, ΔT represents the time interval that requires urgent adjustment of the task flow, A t and A0 represent the change of fire area, V f It represents the speed of fire spread, S represents the safe evacuation time, that is, the maximum time that firefighters and personnel can bear in the danger zone. When ΔT is less than the preset threshold, the fire development speed is fed back to the BPMN model, and the evacuation route, fire extinguishing plan or resource deployment are adjusted. During the monitoring process, the firefighters’ reaction time in handling the task is also evaluated: Among them, T r represents the firefighters’ response time, T start represents the basic reaction time at the beginning of the task, T com represents the communication delay between the firefighter receiving the command and executing the command, C i represents the complexity of task link i; Step S3, adjust the drill process based on dynamic scenarios. According to the real-time execution data fed back by the automated monitoring system, the drill process will be dynamically adjusted as the scenario changes. When the automated monitoring system detects a significant change in the fire situation, the decision node in the BPMN model immediately triggers the emergency strategy adjustment. In step S3, significant changes include fire spreading, blocked evacuation routes, or fire-fighting equipment failure. In step S3, the specific steps of adjusting the emergency strategy include: According to the spread of the fire, change the evacuation route. Switch fire-fighting plans according to the status of fire-fighting equipment and the scale of the fire. Reallocate rescue resources based on personnel locations and changes in fire conditions; In step S3, when the automated monitoring system feeds back real-time data, the BPMN model is dynamically adjusted according to significant changes in the fire situation. The adjustment method is: When the automatic monitoring system detects the spread of fire, it calculates the spread rate of the fire to determine whether the current fire situation exceeds the preset threshold. The fire spread rate is: Among them, v f It represents the spread rate of fire, that is, the rate of change of fire coverage area over time, dA represents the increment of fire coverage area, dt represents the time increment, if v f If the set threshold is exceeded, the corresponding emergency strategy adjustment will be triggered. If the spread of fire hinders the original evacuation route of personnel, the evacuation route is adjusted, and the dynamic path planning formula based on the Dijkstra algorithm is used to adjust the new evacuation route in combination with the fire spread rate: Among them, L new represents the shortest time of the dynamically adjusted evacuation route, d i Indicates the distance from the current node to the next node, v i represents the moving speed of personnel on the road section, λ represents the weight coefficient affecting the spread of fire, represents the total spread effect of fire over time t, Adjust the fire-fighting strategy when the fire develops beyond expectations: Monitor the effectiveness of the fire-fighting equipment to determine whether to switch the fire-fighting strategy: Among them, T extinguish Indicates the time required to extinguish the fire, W f Indicates the current heat energy or fire size of the fire, E current represents the current effectiveness of the fire extinguishing equipment, δ represents the attenuation rate of the effectiveness of the fire extinguishing equipment, and t represents the continuous use time of the fire extinguishing equipment. extinguish When the preset threshold is exceeded, switch the fire-fighting equipment or strategy; In step S3, real-time adjustment of resource allocation is performed: Reallocate equipment resources in case of fire spread or equipment failure: Among them, R i represents the resource satisfaction rate in task link i, N available Indicates the number of currently available resources. The drill personnel are also considered as the number of resources. N required represents the number of standard resources required for task link i, η represents the emergency impact coefficient of fire spread, v f Indicates the fire spread rate, V max Indicates the preset maximum fire spread rate. When R i When it is lower than 1, it means that the current resources are insufficient and need to be adjusted immediately. During the entire exercise, the comprehensive risk assessment function is calculated in real time to determine whether emergency strategy adjustments need to be triggered immediately: Among them, F risk represents the comprehensive risk assessment function, α represents the weight coefficient of the fire spread rate, β represents the weight coefficient of the evacuation route adjustment, γ represents the weight coefficient of the fire extinguishing time deviation, θ represents the weight coefficient of insufficient resource allocation, and L original Indicates the length of the original evacuation route. risk When the preset threshold is exceeded, the decision nodes in the BPMN model automatically trigger emergency strategy adjustments, changing evacuation routes, fire-fighting strategies or resource deployment; Step S4, data feedback and drill evaluation. During the entire process of the drill, the automated monitoring system continuously collects participant and scenario data, including reaction time, operation of fire-fighting equipment, and personnel evacuation efficiency, analyzes the participant and scenario data, and feeds them back to the BPMN model to generate an analysis report.

2. A fire emergency drill method based on computer technology according to claim 1, characterized in that: In step S1, the tasks of each link include: Alarm and initial response: including initiating alarm, activating emergency response team, Command and coordination: simulate the decision-making process of fire commanders and allocate emergency resources. Evacuation of personnel: evacuation procedures and evacuation routes, Fire extinguishing and fire control: including using fire extinguishing equipment, assessing fire development, and deciding on fire extinguishing strategies. Medical rescue: arrange medical first aid personnel to treat the wounded according to the situation.

3. A fire emergency drill method based on computer technology according to claim 2, characterized in that: In step S4, the analysis report includes: The execution time and completion degree of each task link, Whether the participants' operations in firefighting and evacuation tasks comply with standard procedures, Participants' emergency response performance was quantitatively evaluated based on physiological sensor data, reaction speed, and task completion efficiency.

4. A fire emergency drill method based on computer technology according to claim 3, characterized in that: In step S4, the data feedback and exercise evaluation method is: Collect and analyze participants’ reaction times: Among them, T r represents the actual reaction time of the participant, T base represents the basic reaction time, κ represents the weight factor of task complexity, C represents the complexity level of the task, S p represents the pre-set experience level of the participants, H r Indicates the current heart rate, H max represents the participant's maximum heart rate, T delay represents the additional reaction delay under high-intensity tasks, Evaluate the operational efficiency of your equipment: Among them, E op Indicates the operating efficiency of the fire extinguishing equipment, P used Indicates the actual power used by the device, P max Indicates the maximum power of the device, t op Indicates the actual time of device operation, t fail represents the failure time of the equipment under extreme conditions, η represents the operation proficiency coefficient of the equipment, Calculate the efficiency of personnel evacuation: Among them, E evac represents the evacuation efficiency, L opt represents the length of the optimal evacuation route, L actual represents the actual evacuation route length, v avg represents the average travel speed of the participants, v max Indicates the maximum moving speed under normal circumstances, N crowd Indicates the number of people who encountered congestion during the evacuation process, N cap represents the maximum capacity of the evacuation route, Based on the reaction time, fire extinguishing equipment operation and evacuation efficiency data, weighted comprehensive feedback is provided on the overall exercise performance: Among them, P total represents the overall performance score of the exercise, α represents the weighting factor of the reaction time, T r is the actual reaction time, T target is the target reaction time, β represents the weight factor of fire extinguishing equipment operation, E op is the operating efficiency of the fire extinguishing equipment, γ represents the weight factor of the evacuation efficiency, E evac For evacuation efficiency, The final exercise performance score is formed and fed back into the BPMN model.

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