Fire-fighting emergency drilling method based on computer technology

Abstract

The invention discloses a fire-fighting emergency drilling method based on a computer technology, relates to the technical field of intelligent rescue, and aims to standardize and systematize a fire-fighting emergency drilling process, define tasks, decision nodes and time requirements of each link, avoid manual operation errors, improve drilling coordination, enable tasks to be executed more smoothly and improve the efficiency of fire-fighting emergency drilling. Meanwhile, an automatic monitoring system is adopted to collect the physical state of firemen, the use condition of fire extinguishing equipment and the dynamic development of a fire in real time, GPS positioning equipment, biological monitoring equipment and a fire sensor continuously track the physical condition and fire behavior change of participants, the response speed and accuracy of drilling are greatly improved, feedback lag is reduced, and the safety of the firemen is improved. Dynamic adjustment is carried out through integration of an automatic monitoring system and the BPMN model, when a fire behavior changes remarkably, the fire behavior is immediately fed back to a decision node in the BPMN model, an emergency strategy is automatically adjusted, the adaptability of drilling to a sudden complex situation is enhanced, and dynamic requirements in a real fire disaster are closer.

Description

Technical Field

[0001] The invention relates to the field of intelligent rescue technology, in particular 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. Traditional fire emergency drills mostly rely on preset scripts and manual command, lacking systematic process management and automated monitoring. During the drills, the links between the various links are not smooth enough, the implementation standards are not unified, and it is difficult to accurately simulate emergency responses in emergency situations. In addition, drill monitoring relies on manual observation and video surveillance, lacks real-time data feedback and automated analysis, and evaluations mostly rely on subjective judgment, which makes it impossible to quantify the performance of participants. It is impossible to adapt to sudden changes in fire situations and it is difficult to truly reflect the dynamic needs of emergency response.

[0003] In response to the above problems, some existing solutions have optimized the drill process control by handing over to manual command. The operation instructions of each link are issued by the commander in sequence, and the participants perform the tasks in order. The drill supervisor is arranged to observe and record the performance of the participants on site. After the drill, a summary and feedback are made based on the surveillance video and manual records. The drill route is based on the preset fire development route, and the participants carry out corresponding evacuation and fire extinguishing according to the pre-planned plan.

[0004] Although the above scheme can complete the basic drill process, the process control relies on manual command, which is prone to lags and difficult to adapt to the rapidly changing situations in fires. The execution time and sequence of each link are not accurate enough to truly simulate emergency response situations. In addition, manual monitoring and recording are subjective, feedback is not timely, and it is difficult to achieve standardization and quantitative evaluation. The drill method is not flexible enough to cope with emergencies in complex fire scenes, which limits the testing and improvement of the participants' real emergency response capabilities. Therefore, a fire emergency drill method based on computer technology is urgently needed 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, is difficult to adapt to the rapidly changing situation in the fire, and the execution time points and sequence of each link are not accurate enough, and cannot truly simulate the emergency response.

[0007] In order 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 comprises:

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

[0010] A standardized BPMN model covering fire emergency drills is constructed based on business process modeling BPMN technology. The BPMN model contains multiple task links and decision nodes.

[0011] Step S2, integrating the automated monitoring system,

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

[0013] Step S3, adjusting the drill process based on the dynamic situation,

[0014] Based on the real-time execution data fed back by the automated monitoring system, the drill process will be dynamically adjusted as the situation changes. When the automated monitoring system detects a significant change in the fire situation, the decision nodes in the BPMN model will immediately trigger the emergency strategy adjustment.

[0015] Step S4: data feedback and exercise evaluation,

[0016] Throughout the drill, the automated monitoring system continuously collected data on participants and scenarios, including reaction time, operation of fire-fighting equipment, and evacuation efficiency. It also analyzed the data and fed 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 initial response: including initiating alarm, activating emergency response team,

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

[0020] Evacuation of personnel: evacuation procedures and evacuation routes,

[0021] Fire extinguishing and fire control: including using fire extinguishing equipment, assessing fire development, and deciding on fire extinguishing strategies.

[0022] Medical rescue: arrange medical first aid personnel to treat the wounded according to the situation.

[0023] Furthermore, in step S1, the fire emergency BPMN process model is constructed as follows:

[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 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,

[0026] To define resource allocation:

[0027] 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,

[0028] Evacuation and evacuation efficiency definition:

[0029] 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.

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

[0031] 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.

[0032] Define the response time for medical rescue:

[0033] 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.

[0034] Furthermore, in step S2, the execution of the drill being tracked and monitored includes:

[0035] Personal equipment monitoring: Firefighters wear GPS positioning devices and biometric monitoring devices to record their location, action path, and physiological data (heart rate, body temperature, respiratory rate, etc.) in real time to assess their physical fitness and response.

[0036] IoT sensor monitoring: Install sensors and cameras at the drill site to monitor on-site temperature, smoke concentration, airflow direction, humidity, and the status of fire-fighting equipment (water pressure and water flow rate of fire hoses, use of fire extinguishers, etc.).

[0037] 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.

[0038] Furthermore, 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:

[0039] 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:

[0040] 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,

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

[0042] 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,

[0043] 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:

[0044] 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.

[0045] Adjust the BPMN model in real time based on sensor data, triggering adjustments when it detects that the fire is spreading faster than expected:

[0046] 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.

[0047] During the monitoring process, the firefighters’ reaction time in handling the task is also evaluated:

[0048] 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,

[0049] The automated monitoring system is effectively integrated with the BPMN model to track and provide feedback on the physical condition of firefighters, the spread of fire, the status of fire-fighting equipment, and personnel response time. After quantifying the data of each task link, dynamic adjustments can be made based on real-time conditions.

[0050] Furthermore, in step S3, significant changes include fire spreading, blocked evacuation routes, or fire-fighting equipment failure.

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

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

[0053] Switch fire-fighting plans according to the status of fire-fighting equipment and the scale of the fire.

[0054] Reallocate rescue resources based on personnel location and changes in fire severity.

[0055] Furthermore, in step S3, after 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:

[0056] 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:

[0057] 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.

[0058] 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:

[0059] Among them, L new represents the shortest time of the dynamically adjusted evacuation route, di represents the distance from the current node to the next node, and 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,

[0060] 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:

[0061] 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, the fire extinguishing equipment or strategy is switched.

[0062] Furthermore, in step S3, real-time adjustment of resource allocation is performed:

[0063] Reallocate equipment resources in case of fire spread or equipment failure:

[0064] 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.

[0065] 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:

[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 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.

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

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

[0069] Whether the participants' operations in firefighting and evacuation tasks comply with standard procedures,

[0070] Participants' emergency response performance was quantitatively evaluated based on physiological sensor data, reaction speed, and task completion efficiency.

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

[0072] Collect and analyze participants’ reaction times:

[0073] 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, the higher the complexity, the longer the reaction time, 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,

[0074] Evaluate the operational efficiency of your equipment:

[0075] 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 failrepresents the failure time of the equipment under extreme conditions, η represents the operation proficiency coefficient of the equipment, if t op Close to fail , the equipment operating efficiency will drop significantly,

[0076] Calculate the evacuation efficiency:

[0077] 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,

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

[0079] 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 enac For evacuation efficiency,

[0080] The final exercise performance score is formed and fed back into the BPMN model.

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

[0082] The present invention standardizes and systematizes the fire emergency drill process, defines the tasks, decision nodes and time requirements of each link, avoids human operational errors, improves the coordination of the drill, and makes the task execution smoother.

[0083] The present invention adopts an automated monitoring system to collect in real time the physical condition of firefighters, the use of fire-fighting equipment and the dynamic development of the fire. GPS positioning equipment, biological monitoring equipment and fire sensors continuously track the physical condition of participants and changes in fire conditions, greatly improving the reaction speed and accuracy of drills and reducing feedback hysteresis.

[0084] The present invention integrates the automated monitoring system with the BPMN model to perform dynamic adjustments. When the fire situation changes significantly, such as the spread of fire, obstruction of evacuation routes, or equipment failure, feedback is immediately given to the decision nodes in the BPMN model to automatically adjust the emergency strategy, thereby enhancing the adaptability of the drill to sudden and complex situations and being closer to the dynamic needs in real fires.

[0085] The present invention continuously collects reaction time, equipment operating efficiency and evacuation efficiency data through an automated monitoring system, generates a quantitative analysis report, constitutes a comprehensive performance score, and eliminates the subjectivity of the score in the traditional method.

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

[0087] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0088] Figure 1 The present invention is a flowchart of a fire emergency drill method based on computer technology. DETAILED DESCRIPTION

[0089] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0090] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0091] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0092] Example 1, reference Figure 1 This embodiment provides a fire emergency drill method based on computer technology, comprising the following steps:

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

[0094] A standardized BPMN model covering fire emergency drills is constructed based on business process modeling BPMN technology. The BPMN model contains multiple task links and decision nodes.

[0095] The tasks of each link include:

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

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

[0098] Evacuation of personnel: evacuation procedures and evacuation routes,

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

[0100] Medical rescue: arrange medical emergency personnel to treat the wounded according to the situation.

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

[0102] Define the 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 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,

[0104] To define resource allocation:

[0105] 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,

[0106] 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 travel speed of personnel, γ represents the congestion coefficient, and N represents the number of personnel on the route.

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

[0109] 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.

[0110] Define the response time for medical rescue:

[0111] 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, S represents the average severity of the wounded,

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

[0113] Step S2, integrating the automated monitoring system,

[0114] Based on the BPMN model constructed in step S1, the automated monitoring system is integrated 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 to be tracked and monitored includes:

[0116] Personal equipment monitoring: Firefighters wear GPS positioning devices and biometric monitoring devices to record their location, action path, and physiological data (heart rate, body temperature, respiratory rate, etc.) in real time to assess their physical fitness and response.

[0117] IoT sensor monitoring: Install sensors and cameras at the drill site to monitor on-site temperature, smoke concentration, airflow direction, humidity, and the status of fire-fighting equipment (water pressure and water flow rate of fire hoses, use of fire extinguishers, etc.).

[0118] 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.

[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 the firefighters and the dynamic changes of the fire. Specifically:

[0120] 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:

[0121] 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,

[0122] Fire sensors are used to monitor the fire spread speed, coverage area and fire source temperature. The fire spread speed is expressed as:

[0123] 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,

[0124] 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:

[0125] 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.

[0126] Adjust the BPMN model in real time based on sensor data, triggering adjustments when it detects that the fire is spreading faster than expected:

[0127] 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.

[0128] During the monitoring process, the firefighters’ reaction time in handling the task is also evaluated:

[0129] 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,

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

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

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

[0133] Based on the real-time execution data fed back by the automated monitoring system, the drill process will be dynamically adjusted as the situation changes. When the automated monitoring system detects a significant change in the fire situation, the decision nodes in the BPMN model will immediately trigger the emergency strategy adjustment.

[0134] In step S3, significant changes include fire spreading, blocked evacuation routes, or fire-fighting equipment failure.

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

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

[0137] Switch fire-fighting plans according to the status of fire-fighting equipment and the scale of the fire.

[0138] Rescue resources are reallocated according to personnel locations and changes in fire conditions.

[0139] 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:

[0140] 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:

[0141] 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.

[0142] 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:

[0143] 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,

[0144] 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:

[0145] 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, the fire extinguishing equipment or strategy is switched.

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

[0147] Reallocate equipment resources in case of fire spread or equipment failure:

[0148] 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.

[0149] 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:

[0150] 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 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.

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

[0152] Step S4: data feedback and exercise evaluation,

[0153] During the entire process of the drill, the automated monitoring system continuously collects data on participants and scenarios, including reaction time, operation of fire-fighting equipment, and evacuation efficiency. It also analyzes the data on participants and scenarios and feeds it back into the BPMN model to generate an analysis report.

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

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

[0156] Whether the participants' operations in firefighting and evacuation tasks comply with standard procedures,

[0157] Based on physiological sensor data, reaction speed and task completion efficiency, the emergency response performance of participants was quantitatively evaluated.

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

[0159] Collect and analyze participants’ reaction times:

[0160] 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, the higher the complexity, the longer the reaction time, S prepresents 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,

[0161] Evaluate the operational efficiency of your equipment:

[0162] 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, if t op Close to fail , the equipment operating efficiency will drop significantly,

[0163] Calculate the evacuation efficiency:

[0164] 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,

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

[0166] 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 enac For evacuation efficiency,

[0167] Form the final exercise performance score and feed it back into the BPMN model;

[0168] Specifically, the automated monitoring system continuously collects data on participants’ reaction time, equipment operation conditions, and personnel evacuation efficiency to form a comprehensive evaluation function, and ultimately generates a quantitative analysis report. This eliminates the drawbacks of traditional drills that rely on subjective judgment, provides detailed performance feedback for each participant, and generates 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 rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in 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; 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, 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. 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 S1, the fire emergency BPMN process model is constructed as follows: 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.

4. A fire emergency drill method based on computer technology according to claim 3, characterized in that: 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.

5. A fire emergency drill method based on computer technology according to claim 4, characterized in that: 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.

6. A fire emergency drill method based on computer technology according to claim 5, characterized in that: 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 location and changes in fire severity.

7. A fire emergency drill method based on computer technology according to claim 6, characterized in that: 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, the fire extinguishing equipment or strategy is switched.

8. A fire emergency drill method based on computer technology according to claim 7, characterized in that: 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 Ri 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 origial 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.

9. A fire emergency drill method based on computer technology according to claim 8, 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.

10. A fire emergency drill method based on computer technology according to claim 9, 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 dela y 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.

Images