Fire-fighting dispatching management system

Abstract

The invention discloses a fire-fighting dispatching management system, and the system comprises an environment sensing and monitoring module; the data collection module is responsible for collecting fire scene and external environment data in real time; the fire spreading prediction and evaluation module is responsible for evaluating and predicting the spreading trend of the fire based on the collected data; the intelligent scheduling and decision support module is responsible for dynamically adjusting a resource allocation scheme according to the latest fire spreading trend; the real-time navigation and path planning module is responsible for providing real-time navigation and path planning service for firefighters according to the resource configuration scheme; the intelligent scheduling and decision support module can realize optimal scheduling of firefighters, fire-fighting equipment and other resources according to the real-time changing fire spreading trend and the variability of the external environment. The dynamic adjustment mechanism avoids the limitation that traditional manual scheduling cannot deal with sudden changes, and ensures that resources can be input to the most required places according to the optimal path and the most effective mode.

Description

Technical Field

[0001] The present invention relates to the field of fire fighting technology, and in particular to a fire fighting dispatching and management system. Background Art

[0002] With the acceleration of urbanization, urban population density continues to increase, and building height and complexity are also increasing. This change has led to an upward trend in the frequency and severity of fire accidents, posing a huge challenge to urban firefighting. With the continuous development of information technology, especially the emergence of cutting-edge technologies such as big data, cloud computing and artificial intelligence, it provides strong technical support for the construction of fire dispatch management systems.

[0003] After searching, the invention patent with Chinese patent number CN116543530A discloses a method and system for fire dispatch management and monitoring, which involves the field of data processing technology. The method includes: collecting basic information of the target area, generating a regional replica map, building a dispatch management module including a plan decision submodule and a real-time decision submodule, receiving alarm event information, determining the dispatch decision plan and dispatch execution instructions by the plan decision submodule, sending dispatch execution information to the target terminal based on the dispatch decision plan and the dispatch execution instructions, monitoring and coordinating the dispatch decision plan execution based on the real-time decision submodule, generating adjustment dispatch information, matching the adjustment dispatch information with the target terminal, and performing real-time dispatch management based on the matching results. The present invention solves the technical problems of low fire rescue informationization and low command and dispatch capabilities in the prior art, and achieves the technical effect of improving the fire rescue informationization and command and dispatch capabilities.

[0004] However, in actual use of the above invention, it is difficult to mobilize on-site firefighters in real time according to the real-time changes in the fire scene environment and the risks and trends of fire spread. For example, if the wind is strong, the fire will spread to the downwind direction and may suddenly change the direction of spread, which makes the originally reasonable resource scheduling plan quickly invalid. Therefore, a fire dispatch management system is proposed. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art that it is difficult to mobilize on-site firefighters in real time according to the real-time changes in the fire scene environment and the risks and trends of fire spread, and to propose a fire dispatch management system.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] A fire dispatch management system, comprising:

[0008] Environmental perception and monitoring module: responsible for collecting real-time data on the fire scene and its external environment;

[0009] Fire spread prediction and assessment module: responsible for assessing and predicting the fire spread trend based on the collected data;

[0010] Intelligent scheduling and decision support module: responsible for dynamically adjusting resource allocation plans based on the latest fire spread trends;

[0011] Real-time navigation and path planning module: responsible for providing real-time navigation and path planning services for firefighters according to the resource allocation plan;

[0012] Adaptive warning and feedback module: responsible for adjusting the warning information in real time according to the changes at the fire scene and feeding it back to the system;

[0013] Visual dispatch and command module: responsible for providing an intuitive operation interface for command personnel;

[0014] The environmental perception and monitoring module is responsible for real-time perception of the fire scene and the external environment, obtaining various environmental parameters, especially focusing on dynamic environmental factors such as wind speed, wind direction, temperature, humidity, etc., especially when the wind is strong, the direction of fire spread will be significantly affected by wind speed. The environmental perception and monitoring module captures the trend of wind direction changes and fire spread in real time, and feeds back this information to other modules in time for adjustment. The environmental perception and monitoring module transmits the acquired environmental data to the fire spread prediction and evaluation module and the visual scheduling and command module. The fire spread prediction and evaluation module is responsible for real-time processing of environmental data, combining with fire spread models, such as fire simulation algorithms, to predict the trend and risk of fire spread, especially the dynamic impact of factors such as wind force and temperature on fire spread. When the wind speed changes greatly, the module can quickly update the fire spread prediction results and timely evaluate the changing direction of fire spread. The fire spread prediction and evaluation module transmits the prediction results to the intelligent scheduling and decision support module and the visual scheduling and command module. The intelligent scheduling and decision support module is responsible for dynamically adjusting the resource allocation plan based on the fire spread evaluation results and resource conditions (firefighters, equipment, vehicles, etc.), especially when the wind speed changes greatly. When the wind is strong or the direction of fire spread changes suddenly, the intelligent scheduling and decision support module should reconfigure resources according to the new fire assessment results to ensure that firefighting forces and equipment can reach the key areas of the fire scene efficiently and timely. The intelligent scheduling and decision support module transmits the resource allocation plan to the real-time navigation and path planning module and the visual scheduling and command module. The real-time navigation and path planning module is responsible for dynamically adjusting the travel path of firefighting resources according to the resource allocation plan provided by the intelligent scheduling and decision support module in the case of strong wind or other sudden environmental changes (such as changes in the direction of fire spread, road blocking, obstacles, etc.), ensuring that resources can reach the target area efficiently and safely in the changing fire scene environment. The real-time navigation and path planning module transmits the generated travel route to the visual scheduling and command module. The visual scheduling and command module is responsible for integrating the data from each module and displaying it to the commander through an intuitive interface to help the commander monitor the situation at the fire scene in real time and adjust the decision and command strategy. The adaptive early warning and feedback module is responsible for generating early warning information and feeding it back to the system according to the real-time changes at the fire scene, helping to further optimize the decision-making process and emergency response.

[0015] The above technical solution further includes:

[0016] Preferably, the environmental perception and monitoring module includes a multi-parameter environmental sensor unit, a video monitoring and image processing unit, a drone monitoring unit and a data acquisition and communication unit. The multi-parameter environmental sensor unit is responsible for real-time monitoring of environmental changes at the fire scene through various sensors, acquiring various physical and chemical parameters, and providing comprehensive environmental data. The video monitoring and image processing unit is responsible for providing visual data of the fire scene, and analyzing the on-site situation in conjunction with image recognition technology to assist in real-time monitoring and evaluation of fire development trends. The drone monitoring unit is responsible for providing an aerial perspective and quickly acquiring real-time data on the scene and surrounding environment, which is particularly suitable for areas where the fire scene cannot be directly contacted or are dangerous. The data acquisition and communication unit is responsible for collecting and transmitting data acquired by various sensors, monitoring equipment, and drones to ensure efficient and timely transmission of data to the fire spread prediction and evaluation module and the adaptive early warning and feedback module.

[0017] Preferably, the fire spread prediction and assessment module includes a data receiving unit, a data fusion and processing unit, a fire spread prediction unit, a risk assessment and analysis unit and a prediction result transmission unit. The data receiving unit is responsible for receiving data transmitted from the environment perception and monitoring module. The data fusion and processing unit is responsible for fusing and processing the data received by the data receiving unit, eliminating noise, ensuring the accuracy and integrity of the data, and providing high-quality input for fire spread prediction. The fire spread prediction unit is responsible for calculating the fire spread speed, direction, range and other information in real time based on environmental data and fire spread models, and generating short-term and medium-term fire spread predictions. The risk assessment and analysis unit is responsible for performing risk assessment on the fire spread prediction results, analyzing the potential threat of fire spread to the surrounding environment, personnel and buildings, and evaluating the difficulty of fire extinguishing and possible consequences. The prediction result transmission unit is responsible for transmitting the fire spread prediction results and risk assessment information to the intelligent scheduling and decision support module and the visual scheduling and command module in real time, so as to facilitate the formulation of the best rescue strategy and resource allocation plan.

[0018] Preferably, the fire spread model in the fire spread prediction unit uses CFD simulation to dynamically simulate the fire spread process, and the specific steps include:

[0019] Establish a physical model: According to the actual situation of the fire scene, establish a physical model that includes the building structure, combustible material distribution, and fire source location information;

[0020] Set boundary conditions: according to environmental data, set the boundary conditions of the simulation, such as wind speed, wind direction, temperature, etc.;

[0021] Choose a solver: Choose a suitable CFD solver, such as a finite volume method or finite difference method based solver;

[0022] Set equation: Set the continuity equation that describes the conservation of mass. The specific formula is:

[0023]

[0024] Where ρ is the density of the fluid, v is the velocity of the fluid, is the gradient operator,

[0025] Set up the momentum equation that describes the conservation of momentum. The specific formula is:

[0026]

[0027] Among them, p is the pressure of the fluid, u is the viscosity of the fluid, and f is the external force term.

[0028] Set up the energy equation that describes energy conservation, and its specific formula is:

[0029]

[0030] Where e is the energy in the unit volume, q is the heat flux, It is the heat released by the fire;

[0031] Conduct simulation: Run the solver to simulate the fire spread process;

[0032] Result analysis: Based on the simulation results, calculate the speed, direction, and range of fire spread.

[0033] Preferably, the specific steps of performing risk assessment in the risk assessment and analysis unit include:

[0034] Data integration: Obtain environmental data and fire spread prediction results, and integrate the geographical, meteorological, building structure and personnel distribution information of the fire scene;

[0035] Threat identification: Analyze the potential threat of fire spread to the surrounding environment, such as forests, residential areas, industrial areas, etc., assess the potential harm of fire to personnel, including the difficulty of evacuation, the impact of smoke and high temperature, and assess the potential damage of fire to buildings, including structural stability, distribution of combustibles, etc.;

[0036] Risk quantification: Use mathematical models and algorithms to quantify the risk of fire spread, including the prediction of fire spread speed, scope, intensity, and the potential impact of these parameters on the environment and personnel safety;

[0037] Firefighting difficulty assessment: Assess the difficulty and possible obstacles of firefighting operations by considering factors such as the accessibility of firefighting equipment, water supply, and the capabilities of firefighters;

[0038] Consequence analysis: Analyze the direct and indirect consequences that a fire may cause, such as casualties, property losses, environmental impacts, etc., and consider the duration of the fire and the possibility of controlling the fire;

[0039] Risk level classification: Based on the results of consequence analysis, the risk of fire spread is divided into different levels, such as low, medium, high, and very high, to help firefighters quickly understand the risk situation and make corresponding decisions.

[0040] Preferably, the specific steps of the intelligent scheduling and decision support module generating a resource allocation plan include:

[0041] Demand analysis: Determine the type and quantity of firefighting resources required, including firefighters, firefighting equipment, firefighting vehicles, etc., based on the fire spread assessment results and fire risk level;

[0042] Prioritization: Prioritize the required firefighting resources according to the urgency and risk level of the fire scene;

[0043] Optimal resource allocation: According to the fire spread trend and resource demand assessment, formulate the optimal resource allocation plan to maximize rescue efficiency, shorten response time, ensure personnel safety, and ensure effective use of resources. Assume there are n target areas and the resource demand of each area is d i , the cost of each resource is C i , the maximum available amount of resources is B i , the resource allocation decision is x i , then the optimization objective can be expressed as:

[0044]

[0045] Constraints include: The resource requirements of each region must meet:

[0046]

[0047] The maximum available amount of each resource cannot exceed the current amount of resources that can be allocated:

[0048]

[0049] The resource allocation for each region cannot be negative:

[0050]

[0051] And use simulation software to verify the generated resource allocation plan to ensure its feasibility and effectiveness;

[0052] Plan output and adjustment: The generated resource allocation plan is output to the fire commander in a graphical and visual way, including detailed information on resource allocation, rescue routes, time nodes, etc. According to the feedback from the fire commander and changes in actual conditions, the resource allocation plan is adjusted and optimized as necessary.

[0053] Preferably, the specific steps of calculating the best route by the real-time navigation and path planning module are:

[0054] Input parameters: input the current coordinates of the firefighters or equipment, the target location generated by the intelligent dispatch and decision support module, environmental information (affected area of ​​fire spread, obstacles, road network, buildings, passable area, etc.), data on the change of the fire affected area over time, the prediction results based on the fire spread, and the dynamically detected obstacle locations and road traffic status;

[0055] Path planning algorithm: According to the complexity and real-time requirements of the fire scene, select A * The algorithm calculates the initial path from the starting point to the end point;

[0056] Dynamically adjust the path: According to the changes in the fire scene environment (such as the spread of fire, the appearance of obstacles, etc.), dynamically adjust the path. After calculating multiple feasible paths, select the optimal path based on path length, time cost, and risk cost factors;

[0057] Result output and decision feedback: The generated optimal route is transmitted to the visual scheduling and command module through the real-time navigation and path planning module, and the path is dynamically updated according to changes in fire spread and obstacle information, and the latest path planning results are transmitted to firefighters or equipment.

[0058] Preferably, the visual scheduling and command module uses a desktop application to visualize the data in the system to the command personnel through maps, charts, and dashboards, and uses VR / AR technology to allow commanders to view the fire scene in real time through an immersive view to enhance on-site decision-making capabilities. The environmental perception data, prediction results, and resource scheduling information are transmitted to the visual interface in real time through the MQTT protocol to ensure the timeliness of the information.

[0059] The present invention has the following beneficial effects:

[0060] 1. In the present invention, the intelligent scheduling and decision support module can realize the optimal scheduling of firefighters, firefighting equipment and other resources by following the real-time changing fire spreading trend and the variability of the external environment. This dynamic adjustment mechanism avoids the limitation of traditional manual scheduling that cannot cope with sudden changes, and ensures that resources can be invested in the most needed places in the best path and the most effective way.

[0061] 2. In the present invention, the environment perception and monitoring module can collect real-time data of the fire scene and its external environment, such as wind speed, temperature, humidity, fire size, etc., to ensure comprehensive perception of the fire scene. Through these data, the system can quickly identify the potential risk of fire spread. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 This is a system architecture diagram of a fire dispatch management system proposed by the present invention. DETAILED DESCRIPTION

[0063] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0064] like Figure 1 As shown, a fire dispatch management system comprises:

[0065] Environmental perception and monitoring module: responsible for collecting real-time data on the fire scene and its external environment;

[0066] Fire spread prediction and assessment module: responsible for assessing and predicting the fire spread trend based on the collected data;

[0067] Intelligent scheduling and decision support module: responsible for dynamically adjusting resource allocation plans based on the latest fire spread trends;

[0068] Real-time navigation and path planning module: responsible for providing real-time navigation and path planning services for firefighters according to the resource allocation plan;

[0069] Adaptive warning and feedback module: responsible for adjusting the warning information in real time according to the changes at the fire scene and feeding it back to the system;

[0070] Visual dispatch and command module: responsible for providing an intuitive operation interface for command personnel;

[0071] The environmental perception and monitoring module is responsible for real-time perception of the fire scene and the external environment, and obtaining various environmental parameters. The environmental perception and monitoring module transmits the obtained environmental data to the fire spread prediction and evaluation module and the visual scheduling and command module. The fire spread prediction and evaluation module is responsible for real-time processing of environmental data, and combines the fire spread model to predict the trend and risk of fire spread. The fire spread prediction and evaluation module transmits the prediction results to the intelligent scheduling and decision support module and the visual scheduling and command module. The intelligent scheduling and decision support module is responsible for dynamically adjusting the resource allocation plan based on the fire spread evaluation results and resource situation factors. The intelligent scheduling and decision support module transmits the resource allocation plan to the real-time navigation and path planning module and the visual scheduling and command module. The real-time navigation and path planning module is responsible for real-time calculation of the optimal route of firefighters and equipment according to the resource allocation plan provided by the intelligent scheduling and decision support module. The real-time navigation and path planning module transmits the generated route to the visual scheduling and command module. The visual scheduling and command module is responsible for integrating the data from each module and displaying it to the commander through an intuitive interface. The adaptive warning and feedback module is responsible for generating warning information and feeding it back to the system according to the real-time changes of the fire scene, so as to further optimize the decision-making process and emergency response.

[0072] In the embodiment of the present invention, the adaptive early warning and feedback module uses a data-based early warning system to predict possible future fire changes based on sensor data and fire spread models, and promptly transmits early warning information to on-site firefighters and the command center through text messages, phone calls, APP notifications, alarms, and other methods. The threshold is usually dynamically adjusted based on historical fire data and regional characteristics. If the fire spread rate reaches or exceeds a certain threshold, or the fire risk assessment value of certain areas exceeds the preset safety threshold, the system will issue an early warning. Assume that v t is the current fire spreading speed, the condition for determining whether to issue an early warning can be expressed by the following formula: Alert = if V t >v1 or R t >R1, where v1 and R1 are the preset fire spread rate threshold and risk threshold.

[0073] In one embodiment, the environmental perception and monitoring module includes a multi-parameter environmental sensor unit, a video monitoring and image processing unit, a drone monitoring unit, and a data acquisition and communication unit. The multi-parameter environmental sensor unit is responsible for real-time monitoring of environmental changes at the fire scene through various sensors and obtaining various physical and chemical parameters. The video monitoring and image processing unit is responsible for providing visual data of the fire scene and analyzing the on-site situation in conjunction with image recognition technology. The drone monitoring unit is responsible for providing an aerial perspective and quickly obtaining real-time data on the scene and the surrounding environment. The data acquisition and communication unit is responsible for collecting and transmitting data obtained by various sensors, monitoring equipment, and drones.

[0074] In the embodiment of the present invention, the video monitoring unit captures the image of the fire scene in real time, and the image processing technology extracts important information such as the location of the fire source, the size of the fire, and the trend of the fire spread by analyzing the video stream. Assuming that the brightness of the fire source L in the video image is related to the intensity of the fire I, it can be described by the following relationship I = α·L, where α is a proportional coefficient used to adjust the estimation of the fire intensity according to the image brightness. The spread speed of the fire source v t Estimate the fire source displacement in consecutive frame images Where Δx is the displacement of the fire source between two consecutive frames in the image, and Δt is the time interval.

[0075] In one embodiment, the fire spread prediction and assessment module includes a data receiving unit, a data fusion and processing unit, a fire spread prediction unit, a risk assessment and analysis unit, and a prediction result transmission unit. The data receiving unit is responsible for receiving data transmitted from the environmental perception and monitoring module, the data fusion and processing unit is responsible for fusing and processing the data received by the data receiving unit, the fire spread prediction unit is responsible for generating short-term and medium-term fire spread predictions based on environmental data and fire spread models, the risk assessment and analysis unit is responsible for performing risk assessment on the fire spread prediction results, and the prediction result transmission unit is responsible for transmitting the fire spread prediction results and risk assessment information to the intelligent scheduling and decision support module and the visual scheduling and command module in real time.

[0076] In one embodiment, the fire spread model in the fire spread prediction unit uses CFD simulation to dynamically simulate the fire spread process, and the specific steps include:

[0077] Establish a physical model: According to the actual situation of the fire scene, establish a physical model that includes the building structure, combustible material distribution, and fire source location information;

[0078] Set boundary conditions: Set the boundary conditions of the simulation according to the environmental data;

[0079] Choose a solver: Choose a suitable CFD solver;

[0080] Set equation: Set the continuity equation that describes the conservation of mass. The specific formula is:

[0081]

[0082] Where ρ is the density of the fluid, v is the velocity of the fluid, is the gradient operator,

[0083] Set up the momentum equation that describes the conservation of momentum. The specific formula is:

[0084]

[0085] Among them, p is the pressure of the fluid, u is the viscosity of the fluid, and f is the external force term.

[0086] Set up the energy equation that describes energy conservation, and its specific formula is:

[0087]

[0088] Where e is the energy in the unit volume, q is the heat flux, It is the heat released by the fire;

[0089] Conduct simulation: Run the solver to simulate the fire spread process;

[0090] Result analysis: Based on the simulation results, calculate the speed, direction, and range of fire spread.

[0091] In one embodiment, the specific steps of performing risk assessment in the risk assessment and analysis unit include:

[0092] Data integration: Obtain environmental data and fire spread prediction results, and integrate the geographical, meteorological, building structure and personnel distribution information of the fire scene;

[0093] Threat identification: Analyze the potential threat of fire spread to the surrounding environment, assess the potential harm of fire to personnel, and assess the potential damage of fire to buildings;

[0094] Risk quantification: Use mathematical models and algorithms to quantify the risk of fire spread;

[0095] Firefighting difficulty assessment: assess the difficulty and possible obstacles of firefighting operations;

[0096] Consequence analysis: Analyze the direct and indirect consequences of a fire, taking into account the duration of the fire and the possibility of controlling the fire;

[0097] Risk level classification: The risk of fire spread is divided into different levels based on the results of consequence analysis.

[0098] In the embodiment of the present invention, risk quantification is to convert the risk of fire spread into a measurable indicator, usually using a probability and consequence model. The basic formula for risk quantification is R = P × C, where R is the overall risk of fire, P is the probability of fire spread, and C is the possible consequences of fire. The probability P of fire spread can be calculated by the following formula: Among them, λ is the average number of fires per unit time, and k is the number of fires that occurred in a specific time period.

[0099] In one embodiment, the specific steps of the intelligent scheduling and decision support module generating a resource allocation plan include:

[0100] Demand analysis: Determine the type and quantity of firefighting resources required based on the fire spread assessment results and fire risk level;

[0101] Prioritization: Prioritize the required firefighting resources according to the urgency and risk level of the fire scene;

[0102] Optimal resource allocation: According to the fire spread trend and resource demand assessment, the optimal resource allocation plan is formulated. Assuming there are n target areas, the resource demand of each area is d i , the cost of each resource is C i , the maximum available amount of resources is B i , the resource allocation decision is x i , then the optimization objective can be expressed as:

[0103]

[0104] Constraints include: The resource requirements of each region must meet:

[0105]

[0106] The maximum available amount of each resource cannot exceed the current amount of resources that can be allocated:

[0107]

[0108] The resource allocation for each region cannot be negative:

[0109]

[0110] And use simulation software to verify the generated resource allocation plan;

[0111] Plan output and adjustment: The generated resource allocation plan is output to the fire commander in a graphical and visual way, and the resource allocation plan is adjusted and optimized as necessary according to the feedback from the fire commander and the changes in the actual situation.

[0112] In one embodiment, the specific steps of the real-time navigation and path planning module to calculate the best route are:

[0113] Input parameters: input the current coordinates of firefighters or equipment, the target location generated by the intelligent dispatch and decision support module, environmental information, data on the fire impact area changing over time, and the location of dynamically detected obstacles and road traffic status;

[0114] Path planning algorithm: According to the complexity and real-time requirements of the fire scene, select A * The algorithm calculates the initial path from the starting point to the end point;

[0115] Dynamically adjust the path: According to the changes in the fire scene environment, the path is dynamically adjusted. After calculating multiple feasible paths, the optimal path is selected based on path length, time cost, and risk cost factors;

[0116] Result output and decision feedback: The generated optimal route is transmitted to the visual scheduling and command module through the real-time navigation and path planning module, and the path is dynamically updated according to changes in fire spread and obstacle information, and the latest path planning results are transmitted to firefighters or equipment.

[0117] In the embodiment of the present invention, A * The algorithm is a path planning algorithm based on heuristic search, which combines the actual path cost and the heuristic estimated target distance to optimize the path. * The goal of the algorithm is to minimize the path cost. The specific formula is: f(x) = g(x) + h(x), where f(x) is the estimated total cost from the starting point to the target point, g(x) is the actual cost from the starting point to the current point, and h(x) is the estimated cost from the current point to the target point. h(x) can be combined with the fire spread prediction results to dynamically adjust the impact area of ​​the target point. Assuming the fire spread speed is v t After time t, the area affected by the fire is: R(t) = R0 + v t t,

[0118] Among them, R0 is the radius of the initial fire spread area, and t is the time.

[0119] In one embodiment, the visual scheduling and command module uses a desktop application to visualize the data in the system to the commander through maps, charts, and dashboards. It uses VR / AR technology to allow commanders to view the fire scene in real time through an immersive view, and transmits environmental perception data, prediction results, and resource scheduling information to the visualization interface in real time through the MQTT protocol.

[0120] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A fire dispatch management system, characterized in that: include: Environmental perception and monitoring module: responsible for collecting real-time data on the fire scene and its external environment; Fire spread prediction and assessment module: responsible for assessing and predicting the fire spread trend based on the collected data; Intelligent scheduling and decision support module: responsible for dynamically adjusting resource allocation plans based on the latest fire spread trends; Real-time navigation and path planning module: responsible for providing real-time navigation and path planning services for firefighters according to the resource allocation plan; Adaptive warning and feedback module: responsible for adjusting the warning information in real time according to the changes at the fire scene and feeding it back to the system; Visual dispatch and command module: responsible for providing an intuitive operation interface for command personnel; The environmental perception and monitoring module is responsible for real-time perception of the fire scene and the external environment, and obtaining various environmental parameters. The environmental perception and monitoring module transmits the obtained environmental data to the fire spread prediction and evaluation module and the visual scheduling and command module. The fire spread prediction and evaluation module is responsible for real-time processing of environmental data, and combines the fire spread model to predict the trend and risk of fire spread. The fire spread prediction and evaluation module transmits the prediction results to the intelligent scheduling and decision support module and the visual scheduling and command module. The intelligent scheduling and decision support module is responsible for dynamically adjusting the resource allocation plan based on the fire spread evaluation results and resource situation factors. The decision support module transmits the resource allocation plan to the real-time navigation and path planning module and the visual scheduling and command module. The real-time navigation and path planning module is responsible for calculating the optimal route for firefighters and equipment in real time according to the resource allocation plan provided by the intelligent scheduling and decision support module. The real-time navigation and path planning module transmits the generated route to the visual scheduling and command module. The visual scheduling and command module is responsible for integrating the data from each module and displaying it to the command personnel through an intuitive interface. The adaptive early warning and feedback module is responsible for generating early warning information and feeding it back to the system according to the real-time changes at the fire scene, so as to further optimize the decision-making process and emergency response.

2. A fire dispatch management system according to claim 1, characterized in that: The environmental perception and monitoring module includes a multi-parameter environmental sensor unit, a video monitoring and image processing unit, a drone monitoring unit, and a data acquisition and communication unit. The multi-parameter environmental sensor unit is responsible for real-time monitoring of environmental changes at the fire scene through various sensors and obtaining various physical and chemical parameters. The video monitoring and image processing unit is responsible for providing visual data of the fire scene and analyzing the on-site situation in conjunction with image recognition technology. The drone monitoring unit is responsible for providing an aerial perspective and quickly obtaining real-time data on the scene and the surrounding environment. The data acquisition and communication unit is responsible for collecting and transmitting data obtained by various sensors, monitoring equipment, and drones.

3. A fire dispatch management system according to claim 1, characterized in that: The fire spread prediction and assessment module includes a data receiving unit, a data fusion and processing unit, a fire spread prediction unit, a risk assessment and analysis unit, and a prediction result transmission unit. The data receiving unit is responsible for receiving data transmitted from the environment perception and monitoring module, the data fusion and processing unit is responsible for fusing and processing the data received by the data receiving unit, the fire spread prediction unit is responsible for generating short-term and medium-term fire spread predictions based on environmental data and fire spread models, the risk assessment and analysis unit is responsible for performing risk assessment on fire spread prediction results, and the prediction result transmission unit is responsible for transmitting the fire spread prediction results and risk assessment information to the intelligent scheduling and decision support module and the visual scheduling and command module in real time.

4. A fire dispatch management system according to claim 3, characterized in that: The fire spread model in the fire spread prediction unit uses CFD simulation to dynamically simulate the fire spread process, and its specific steps include: Establish a physical model: According to the actual situation of the fire scene, establish a physical model that includes the building structure, combustible material distribution, and fire source location information; Set boundary conditions: Set the boundary conditions of the simulation according to the environmental data; Choose a solver: Choose a suitable CFD solver; Set equation: Set the continuity equation that describes the conservation of mass. The specific formula is: Where ρ is the density of the fluid, v is the velocity of the fluid, is the gradient operator, Set up the momentum equation that describes the conservation of momentum. The specific formula is: Among them, p is the pressure of the fluid, u is the viscosity of the fluid, and f is the external force term. Set up the energy equation that describes energy conservation, and its specific formula is: Where e is the energy in the unit volume, q is the heat flux, It is the heat released by the fire; Conduct simulation: Run the solver to simulate the fire spread process; Result analysis: Based on the simulation results, calculate the speed, direction, and range of fire spread.

5. A fire dispatch management system according to claim 3, characterized in that: The specific steps of risk assessment in the risk assessment and analysis unit include: Data integration: Obtain environmental data and fire spread prediction results, and integrate the geographical, meteorological, building structure and personnel distribution information of the fire scene; Threat identification: Analyze the potential threat of fire spread to the surrounding environment, assess the potential harm of fire to personnel, and assess the potential damage of fire to buildings; Risk quantification: Use mathematical models and algorithms to quantify the risk of fire spread; Firefighting difficulty assessment: assess the difficulty and possible obstacles of firefighting operations; Consequence analysis: Analyze the direct and indirect consequences of a fire, taking into account the duration of the fire and the possibility of controlling the fire; Risk level classification: The risk of fire spread is divided into different levels based on the results of consequence analysis.

6. A fire dispatch management system according to claim 1, characterized in that: The specific steps of the intelligent scheduling and decision support module generating a resource allocation plan include: Demand analysis: Determine the type and quantity of firefighting resources required based on the fire spread assessment results and fire risk level; Prioritization: Prioritize the required firefighting resources according to the urgency and risk level of the fire scene; Optimal resource allocation: According to the fire spread trend and resource demand assessment, the optimal resource allocation plan is formulated. Assuming there are n target areas, the resource demand of each area is d i , the cost of each resource is C i , the maximum available amount of resources is B i , the resource allocation decision is x i , then the optimization objective can be expressed as: Constraints include: The resource requirements of each region must meet: The maximum available amount of each resource cannot exceed the current amount of resources that can be allocated: The resource allocation for each region cannot be negative: And use simulation software to verify the generated resource allocation plan; Plan output and adjustment: The generated resource allocation plan is output to the fire commander in a graphical and visual way, and the resource allocation plan is adjusted and optimized as necessary according to the feedback from the fire commander and the changes in the actual situation.

7. A fire dispatch management system according to claim 1, characterized in that: The specific steps of the real-time navigation and path planning module to calculate the best route are: Input parameters: input the current coordinates of firefighters or equipment, the target location generated by the intelligent dispatch and decision support module, environmental information, data on the fire impact area changing over time, and the location of dynamically detected obstacles and road traffic status; Path planning algorithm: According to the complexity and real-time requirements of the fire scene, select A * The algorithm calculates the initial path from the starting point to the end point; Dynamically adjust the path: According to the changes in the fire scene environment, the path is dynamically adjusted. After calculating multiple feasible paths, the optimal path is selected based on path length, time cost, and risk cost factors; Result output and decision feedback: The generated optimal route is transmitted to the visual scheduling and command module through the real-time navigation and path planning module, and the path is dynamically updated according to changes in fire spread and obstacle information, and the latest path planning results are transmitted to firefighters or equipment.

8. A fire dispatch management system according to claim 1, characterized in that: The visual scheduling and command module uses desktop applications to visualize the data in the system to commanders through maps, charts, and dashboards. It uses VR / AR technology to allow commanders to view the fire scene in real time through an immersive view, and transmits environmental perception data, prediction results, and resource scheduling information to the visualization interface in real time through the MQTT protocol.

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