Processing method for autonomous unmanned aerial vehicle fire extinguishing based on ignition point and storage medium

Abstract

The invention discloses an autonomous unmanned aerial vehicle fire extinguishing processing method based on ignition points and a storage medium, and the method comprises the steps: collecting the position information and fire behavior parameters of a plurality of ignition points in real time, the fire behavior parameters comprising flame height, temperature gradient, diffusion velocity and combustible density; calculating a comprehensive danger coefficient according to the fire behavior parameter and the environment parameter of each ignition point; the environment parameters comprise the distance between adjacent buildings, the wind speed and the personnel intensity; all the ignition points are subjected to priority ranking based on the comprehensive danger coefficient, and an initial fire extinguishing sequence is generated; updating and calculating a target fire extinguishing sequence; and controlling the fire extinguishing unmanned aerial vehicle to set and plan an inspection fire extinguishing path from the current position according to the target fire extinguishing sequence. According to the invention, a more robust combat platform and a higher safety guarantee are provided for the field of fire emergency disposal through an intelligent data processing and scheduling mechanism, and development and application of an unmanned aerial vehicle fire extinguishing technology are powerfully promoted.

Description

Technical Field

[0001] The present invention relates to the field of unmanned fire control processing, and particularly to a processing method and a storage medium for autonomous drone fire extinguishing based on the ignition point. Background Art

[0002] The application of drones in fire emergency disposal has become an important development direction in recent years. Traditional fire extinguishing operations mostly rely on manual judgment and fixed dispatching modes. In case of multiple ignition points and complex changes in the on-site environment, it is often difficult to timely and accurately evaluate the fire situation and potential risks, resulting in uneven distribution of fire extinguishing resources and low operation efficiency.

[0003] The existing technologies usually have the following deficiencies: The collection of fire situation information and risk assessment are not comprehensive. Existing systems often only focus on one or a few fire extinguishing parameters, lacking the comprehensive collection of fire situation parameters such as flame height, temperature gradient, diffusion speed, and combustible density. At the same time, environmental factors such as the distance to adjacent buildings, wind speed, and population density are not fully considered, resulting in inaccurate fire situation risk assessment and possible delay of the best fire extinguishing opportunity.

[0004] Lack of dynamic response ability. The situation at the fire scene changes rapidly, and a single and static fire extinguishing sequence plan is difficult to meet the changing requirements of the fire situation. Currently, the dispatching method lacks a real-time monitoring mechanism and fails to perform dynamic sorting for abnormal changes in fire situation parameters, resulting in slow response of fire extinguishing drones to sudden situations at the fire scene and reducing the overall operation efficiency. Summary of the Invention

[0005] The purpose of the present invention is to provide a processing method and a storage medium for autonomous drone fire extinguishing based on the ignition point, which solve the above-mentioned technical problems pointed out in the existing technologies.

[0006] The present invention proposes a processing method for autonomous drone fire extinguishing based on the ignition point. By comprehensively collecting fire situation and environmental data, calculating the comprehensive risk coefficient, and dynamically generating a fire extinguishing priority queue based on the minimum heap data structure, the real-time scheduling and path planning of the fire extinguishing sequence are realized. Further, by dynamically adjusting the weight parameters, real-time monitoring of equipment resources, and introducing a collaborative operation and emergency response module, the entire drone fire extinguishing system has higher sensitivity, self-adaptability, and safety guarantee capabilities.

[0007] The present invention provides a processing method for autonomous drone fire extinguishing based on the ignition point, including the following operating steps:

[0008] S1. Real-time collect the position information and fire situation parameters of multiple ignition points, where the fire situation parameters include flame height, temperature gradient, diffusion speed, and combustible density;

[0009] S2. Calculate the comprehensive risk coefficient based on the fire parameters and environmental parameters of each ignition point; the environmental parameters include the distance to adjacent buildings, wind speed, and population density;

[0010] S3. Prioritize all ignition points based on the comprehensive risk coefficient to generate an initial fire extinguishing order; implement an update calculation for the target fire extinguishing order;

[0011] S4. Control the fire extinguishing drone to set and plan an inspection and fire extinguishing path from the current position according to the target fire extinguishing order;

[0012] The calculation formula for the comprehensive risk coefficient is:

[0013]

[0014] where, R i is the comprehensive risk coefficient of the i-th ignition point, F i is the normalized value of the flame height, T i is the abnormal temperature rise rate, D i is the distance to the nearest building, W i is the real-time wind speed, S i is the change rate of the diffusion area, and α, β, γ, δ are dynamic weight parameters.

[0015] Preferably, prioritize all ignition points based on the comprehensive risk coefficient to generate an initial fire extinguishing order; implement an update calculation for the target fire extinguishing order, which specifically includes the following steps:

[0016] S31. Construct a minimum heap data structure with the comprehensive risk coefficient as the key value; use the minimum heap data structure as the initial fire extinguishing order;

[0017] S32. Monitor the change rate of the comprehensive risk coefficient of each ignition point in real time. When the change rate of the risk coefficient exceeds the preset threshold and triggers the first condition, trigger the readjustment of the heap data structure;

[0018] S33. If a new ignition point is detected or the risk coefficient of an existing ignition point changes suddenly, perform a reconstruction of the heap data structure and output the updated fire extinguishing priority queue;

[0019] Use the updated fire extinguishing priority queue as the target fire extinguishing order.

[0020] Preferably, in step S32, monitor the change rate of the comprehensive risk coefficient of each ignition point in real time. When the change rate of the risk coefficient exceeds the preset threshold and triggers the first condition, trigger the readjustment of the heap data structure, which specifically includes the following steps:

[0021] S321. Periodically calculate the difference in the change of the comprehensive risk coefficient of each ignition point between the current and the previous cycle, and calculate the change rate of the risk coefficient;

[0022] S322. Compare the change rate of the risk coefficient with a preset threshold, and screen out the abnormal change points exceeding the threshold; the first condition is that the proportion of the number of ignition points with abnormal changes to the total number of ignition points exceeds a proportion threshold;

[0023] S323. When the proportion of the number of ignition points with abnormal changes to the total number of ignition points exceeds the proportion threshold, update it to the latest fire extinguishing priority queue.

[0024] Preferably, before the step of calculating the comprehensive risk coefficient according to the fire intensity parameters and environmental parameters of each ignition point, the following steps are further included:

[0025] At intervals of a preset time period, dynamically adjust the weight parameter α.

[0026] Preferably, the step of dynamically adjusting the weight parameter α at intervals of a preset time period specifically includes the following steps:

[0027] S21. Every 5 minutes, count the actual extinguishing time data of the most recent consecutive 3 fire extinguishing cycles; the actual extinguishing time data includes the actual fire extinguishing time t eff ;

[0028] S22. Based on the actual fire extinguishing time t eff and the preset theoretical maximum time t max , use the following formula to calculate the updated value of the weight parameter:

[0029]

[0030] S23. Replace the original dynamic weight parameter α with the updated dynamic weight parameter α′ for subsequent comprehensive risk coefficient calculation.

[0031] Preferably, control the fire extinguishing drone to set and plan the inspection and fire extinguishing path according to the target fire extinguishing order from the current position, and the following steps are further included:

[0032] Perform inspection and fire extinguishing processing in real time according to the target fire extinguishing order, and at the same time, monitor the remaining water resources of the fire extinguishing equipment in real time. If the remaining water resources are lower than the preset threshold, execute the path energy-saving planning mode.

[0033] Preferably, the execution of the path energy-saving planning mode specifically includes the following steps:

[0034] S91. Screen out the ignition points that have not been extinguished in the target fire extinguishing order, and send the numbers of the ignition points that have not been extinguished in the target fire extinguishing order and a request for assisting in fire extinguishing to the central controller;

[0035] S92. The central controller sends control instructions to other drones. After other drones arrive at the current fire extinguishing point, the current drone flies back to the starting point to replenish water resources;

[0036] S93. The central controller generates an assistance report and uploads it to the cloud server for archiving.

[0037] Preferably, the assistance report includes the current UAV number, the remaining water resources of the current UAV, the numbers of the ignition points that have not been extinguished in the target fire extinguishing sequence, and the numbers of other assisting UAVs.

[0038] Preferably, after controlling the fire extinguishing UAV to set and plan the inspection and fire extinguishing path according to the target fire extinguishing sequence from the current position, it further includes executing an emergency response mode when dangerous chemicals are detected, specifically including the following steps:

[0039] S101. Real-time detect the distance between the current ignition point and the surrounding dangerous chemical storage facilities. If the detected distance is less than 10 meters, start the emergency response mode;

[0040] S102. The central controller sends a control instruction for immediate assistance to other UAVs, and controls all UAVs to fly towards the current fire extinguishing point;

[0041] S103. And set the current ignition point as the highest priority in the target fire extinguishing sequence for all UAVs to perform the fire extinguishing task.

[0042] The present invention also provides a storage medium, which includes a stored program. When the program runs, it controls the device where the storage medium is located to execute the above-mentioned processing method for autonomous UAV fire extinguishing based on the ignition point.

[0043] Compared with the prior art, the embodiments of the present invention have at least the following technical advantages:

[0044] Analyzing the above-mentioned processing method and storage medium for autonomous UAV fire extinguishing based on the ignition point provided by the present invention, in specific applications, S1. Real-time collect the position information and fire parameters of multiple ignition points, and the fire parameters include flame height, temperature gradient, diffusion speed, and combustible density; S2. Calculate the comprehensive hazard coefficient according to the fire parameters and environmental parameters of each ignition point; the environmental parameters include the distance to adjacent buildings, wind speed, and population density; S3. Based on the comprehensive hazard coefficient, prioritize all ignition points to generate an initial fire extinguishing sequence; implement and update the calculation of the target fire extinguishing sequence; S4. Control the fire extinguishing UAV to set and plan the inspection and fire extinguishing path according to the target fire extinguishing sequence from the current position.

[0045] The present invention proposes a processing method for autonomous UAV fire extinguishing based on ignition points. By comprehensively collecting fire and environmental data, calculating a comprehensive risk coefficient, and dynamically generating a fire extinguishing priority queue based on the minimum heap data structure, real-time scheduling of the fire extinguishing sequence and path planning are achieved. Further, by dynamically adjusting weight parameters, real-time monitoring of device resources, and introducing a collaborative operation and emergency response module, the entire UAV fire extinguishing system is equipped with higher sensitivity, self-adaptability, and safety guarantee capabilities. The present invention not only makes up for the deficiencies of traditional fire extinguishing methods in aspects such as information collection, risk assessment, dynamic sorting, and resource collaboration, but also provides a brand-new technical solution for the efficient fire extinguishing of UAV clusters in complex and dynamic fire field environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0047] Figure 1 Schematic diagram of the overall operation steps of a processing method for autonomous UAV fire extinguishing based on ignition points provided by an embodiment of the present invention;

[0048] Figure 2 Schematic diagram of a specific operation process in a processing method for autonomous UAV fire extinguishing based on ignition points provided by an embodiment of the present invention;

[0049] Figure 3 Schematic diagram of another specific operation process in a processing method for autonomous UAV fire extinguishing based on ignition points provided by an embodiment of the present invention;

[0050] Figure 4 Schematic diagram of yet another specific operation process in a processing method for autonomous UAV fire extinguishing based on ignition points provided by an embodiment of the present invention;

[0051] Figure 5 Schematic diagram of still another specific operation process in a processing method for autonomous UAV fire extinguishing based on ignition points provided by an embodiment of the present invention;

[0052] Figure 6 Schematic diagram of the storage medium corresponding to a processing method for autonomous UAV fire extinguishing based on ignition points provided by an embodiment of the present invention.

[0053] Reference numerals: memory 1130; communication interface 1120; processor 1110. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0054] The technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work belong to the scope of protection of the present invention.

[0055] The present invention will be further described in detail below through specific embodiments in conjunction with the accompanying drawings.

[0056] Embodiment 1

[0057] As Figure 1 shown, the present invention also proposes a processing method for autonomous UAV fire extinguishing based on the ignition point, including the following operating steps:

[0058] S1. Real-time collect the location information and fire parameters of multiple ignition points, where the fire parameters include flame height, temperature gradient, diffusion speed, and combustible density;

[0059] S2. Calculate the comprehensive risk coefficient according to the fire parameters and environmental parameters of each ignition point; the environmental parameters include the distance to adjacent buildings, wind speed, and population density;

[0060] S3. Based on the comprehensive risk coefficient, prioritize all ignition points to generate an initial fire extinguishing order; implement and update the calculation of the target fire extinguishing order;

[0061] S4. Control the fire extinguishing UAV to set and plan the inspection and fire extinguishing path from the current position according to the target fire extinguishing order;

[0062] The calculation formula for the comprehensive risk coefficient is:

[0063]

[0064] where R i is the comprehensive risk coefficient of the i-th ignition point, F i is the standardized value of the flame height, T i is the abnormal temperature rise rate, D i is the distance to the nearest building, W i is the real-time wind speed, S i is the change rate of the diffusion area, and α, β, γ, δ are dynamic weight parameters.

[0065] In specific applications, S1. Real-time collect the location information and fire parameters of multiple ignition points, where the fire parameters include flame height, temperature gradient, diffusion speed, and combustible density; S2. Calculate the comprehensive hazard coefficient based on the fire parameters and environmental parameters of each ignition point; the environmental parameters include the distance to adjacent buildings, wind speed, and population density; S3. Based on the comprehensive hazard coefficient, prioritize all ignition points to generate an initial fire extinguishing order; implement and update the calculation of the target fire extinguishing order; S4. Control the fire extinguishing drone to set and plan a patrol and fire extinguishing path from the current position according to the target fire extinguishing order.

[0066] The present invention proposes a processing method for autonomous drone fire extinguishing based on ignition points. By comprehensively collecting fire and environmental data, calculating the comprehensive hazard coefficient, and dynamically generating a fire extinguishing priority queue based on the minimum heap data structure, it realizes the real-time scheduling of the fire extinguishing order and path planning.

[0067] In the specific implementation process, the system first calculates the comprehensive hazard coefficient of each fire point using a preset model based on the collected fire and environmental data. To apply the calculation results to task scheduling, the system further constructs a dynamic fire extinguishing priority queue using the minimum heap data structure. As an efficient data structure, the minimum heap can quickly sort the hazard levels of fire points under the condition of continuously changing fire situations. When the system detects a sudden increase in the risk coefficient of a certain fire scene or the emergence of a new fire point, it will trigger the reconstruction of the minimum heap, quickly reflecting the latest safety information in the priority queue. In this way, the drone can always execute the fire extinguishing task according to the latest fire severity.

[0068] To improve the intelligent level of the system, the present invention introduces a mechanism for dynamically adjusting weight parameters. Within a preset time period (for example, every 5 minutes), the system will count the actual fire extinguishing time in the past three fire extinguishing cycles and compare this data with the preset theoretical maximum time. Then, it calculates the updated value of the dynamic weight parameter using a formula. The updated parameter will replace the original setting, making the calculation of the hazard coefficient closer to the actual on-site situation.

[0069] Thus, the comprehensively hazard coefficient that has been continuously adaptively adjusted can not only reflect the instantaneous changes in the fire scene risk but also provide more accurate guidance for the drone task planning, improving the system's response speed and fire extinguishing efficiency in complex environments.

[0070] In addition, to ensure long-term continuous operation, the system is also designed with a function to monitor the remaining amount of fire extinguishing equipment (water resources) in real time. During the fire extinguishing mission, the drone continuously detects the status of the water resources it carries. When the water resources are lower than the preset threshold, the system automatically switches to the path energy-saving planning mode and sends an assistance request to the central controller in a timely manner. After receiving the request, the central controller coordinates and schedules other drones to ensure the continuous progress of the fire extinguishing mission at the fire scene while allowing the drone with insufficient current water resources to fly back to the starting point or base for replenishment. During the entire collaborative operation process, the system not only transmits the numbers, remaining water volumes, and current task status of each drone but also generates a detailed assistance report to be uploaded to the cloud server to provide data support for the overall combat effectiveness and subsequent improvement of the emergency plan.

[0071] In the special case where dangerous goods are stored near the fire scene, the system is further designed with an emergency response module. This module realizes the real-time detection of the distance between the fire point and the hazardous chemical facilities. When the distance is lower than the safety threshold (e.g., 10 meters), the system immediately triggers an emergency response, sets the current fire point as the highest-priority target, and sends a collaborative operation instruction to all drones in the cluster, requiring them to quickly gather at this fire point for joint fire extinguishing. This measure can not only prevent the spread of the fire and avoid secondary accidents caused by hazardous chemicals but also ensure the most effective control of the real-time risk at the fire scene, fundamentally enhancing the on-site safety guarantee ability.

[0072] Generally speaking, the drone fire extinguishing system of the present invention realizes the high sensitivity, self-adaptability, and collaboration of drones in fire extinguishing tasks by organically integrating fire and environmental data, constructing a real-time updated fire extinguishing priority queue using the minimum heap data structure, combined with dynamic weight parameter adjustment, real-time resource monitoring, and an emergency response module. The system can not only effectively judge the multi-point, scattered, and dynamically changing fire scene environment but also flexibly optimize the operation path and resource scheduling according to the actual situation on-site. This solution effectively makes up for the deficiencies of traditional fire extinguishing methods in information collection, risk assessment, dynamic sorting, and resource collaboration, providing a new technical support and solution for the precise and efficient fire extinguishing operation of drone clusters in complex fire scene environments. Through the intelligent data processing and scheduling mechanism, the present invention provides a more robust combat platform and higher safety guarantee for the field of fire emergency disposal, strongly promoting the development and application of drone fire extinguishing technology.

[0073] As Figure 2 shown, based on the comprehensive danger coefficient, all fire points are sorted by priority to generate the initial fire extinguishing order; the target fire extinguishing order is updated and calculated, specifically including the following operation steps:

[0074] S31. Construct a minimum heap data structure with the comprehensive danger coefficient as the key value; use the minimum heap data structure as the initial fire extinguishing order;

[0075] S32. Monitor the change rate of the comprehensive risk coefficient of each ignition point in real time. When the change rate of the risk coefficient exceeds the preset threshold and triggers the first condition, trigger the readjustment of the heap data structure;

[0076] S33. If a new ignition point is detected or the risk coefficient of an existing ignition point mutates, then perform the reconstruction of the heap data structure and output the updated fire extinguishing priority queue;

[0077] Use the updated fire extinguishing priority queue as the target fire extinguishing order.

[0078] In the above technical solution, a priority queue of the comprehensive risk coefficient is constructed using a minimum heap data structure, which can quickly sort the risk levels of all ignition points. By monitoring and judging the changes in fire situation parameters in real time (such as the appearance of a new ignition point or the mutation of an existing ignition point), the reconstruction of the data structure is triggered in a timely manner, so that the fire extinguishing order is dynamically updated, ensuring that the UAV fire extinguishing task can be flexibly adjusted according to the on-site situation.

[0079] As Figure 3 shown, in step S32, monitoring the change rate of the comprehensive risk coefficient of each ignition point in real time. When the change rate of the risk coefficient exceeds the preset threshold and triggers the first condition, trigger the readjustment of the heap data structure, which specifically includes the following steps:

[0080] S321. Periodically calculate the difference in the change of the comprehensive risk coefficient of each ignition point between the current and the previous period, and calculate the change rate of the risk coefficient;

[0081] S322. Compare the change rate of the risk coefficient with the preset threshold to screen out the abnormal change points that exceed the threshold; the first condition is that the proportion of the number of ignition points with abnormal changes to the total number of ignition points exceeds the proportion threshold;

[0082] S323. When the proportion of the number of ignition points with abnormal changes to the total number of ignition points exceeds the proportion threshold, update it to the latest fire extinguishing priority queue.

[0083] In the above technical solution, introducing the periodic calculation of the change rate of the comprehensive risk coefficient of each ignition point, and setting the preset threshold and the abnormal proportion condition, triggering re-sorting when the abnormal change points reach a certain proportion. It effectively improves the sensitivity and response speed of the system to fire situation changes, and ensures the real-time and accuracy of the adjustment of the fire extinguishing priority.

[0084] Preferably, before the step of calculating the comprehensive risk coefficient according to the fire situation parameters and environmental parameters of each ignition point, the following steps are further included:

[0085] At intervals of a preset time period, dynamically adjust the weight parameter α.

[0086] Preferably, the specific method for dynamically adjusting the weight parameter α at intervals of a preset time period is as follows:

[0087] S21. Statistically collect the actual fire extinguishing time data for the most recent consecutive 3 fire extinguishing cycles every 5 minutes; the actual fire extinguishing time data includes the actual fire extinguishing time t eff ;

[0088] S22. Based on the actual fire extinguishing time t eff and the preset theoretical maximum time t max , use the following formula to calculate the updated value of the weight parameter:

[0089]

[0090] S23. Replace the original dynamic weight parameter α with the updated dynamic weight parameter α′ for subsequent calculation of the comprehensive hazard coefficient.

[0091] Before calculating the comprehensive hazard coefficient, adjust the dynamic weight parameter according to the preset time period so that the weight values of each parameter can adapt to the actual situation of the on-site fire and environment. By statistically collecting the actual fire extinguishing time data for the most recent consecutive 3 fire extinguishing cycles and comparing it with the preset theoretical maximum time, the updated value of the weight parameter is obtained using the formula, thereby achieving dynamic replacement. This enables the calculation of the comprehensive hazard coefficient to continuously adapt to the time fluctuations that occur in actual fire extinguishing operations, ensuring that the sorting decision is more in line with the on-site operation performance.

[0092] Preferably, control the fire extinguishing drone to set and plan the patrol and fire extinguishing path according to the target fire extinguishing order from the current position, and it also includes the following steps:

[0093] Continuously perform the patrol and fire extinguishing process according to the target fire extinguishing order in real time, and simultaneously monitor the remaining water resources of the fire extinguishing equipment in real time. If the remaining water resources are lower than the preset threshold, execute the path energy-saving planning mode.

[0094] It should be noted that when implementing the above steps in this embodiment, in addition to planning the path according to the target fire extinguishing order, the remaining amount of the drone fire extinguishing equipment (water resources) is also monitored in real time; when the water resources are lower than the preset threshold, it is automatically switched to the path energy-saving planning mode. This effectively avoids interrupting the task due to insufficient water resources, extends the continuous operation time of the drone, and ensures that key fire situations are given priority for disposal.

[0095] As Figure 4 shown, the implementation of the path energy-saving planning mode specifically includes the following steps:

[0096] S91. Screen the ignition points that have not been extinguished in the target fire extinguishing order, and send the numbers of the ignition points that have not been extinguished in the target fire extinguishing order and a request for assisting in fire extinguishing to the central controller;

[0097] S92. The central controller sends control instructions to other UAVs. After other UAVs arrive at the current fire extinguishing point, the current UAV flies back to the starting point to replenish water resources.

[0098] S93. The central controller generates an assistance report and uploads it to the cloud server for archiving.

[0099] Preferably, the assistance report includes the current UAV number, the remaining water resources of the current UAV, the numbers of the ignition points that have not been extinguished in the target fire extinguishing sequence, and the numbers of other UAVs that provide assistance.

[0100] When water resources are scarce, by sending an assistance request and information on the target fire extinguishing ignition points to the central controller, and then the central controller coordinates other UAVs to rush to the fire extinguishing site, realizing the collaborative operation between UAVs.

[0101] This task collaboration mechanism can ensure the continuity of the fire extinguishing task, and at the same time enable the current UAV to return in time to replenish water resources, thereby globally optimizing the fire extinguishing intensity. The assistance report details the current UAV number, the remaining water resources, the numbers of the ignition points that have not been extinguished, and the numbers of other UAVs that provide assistance.

[0102] As Figure 5 shown, after the fire extinguishing UAV sets and plans the patrol and fire extinguishing path according to the target fire extinguishing sequence from the current position, it also includes executing an emergency response mode when dangerous chemicals are detected, specifically including the following steps:

[0103] S101. Continuously detect the distance between the current ignition point and the surrounding dangerous chemical storage facilities. If the detected distance is less than 10 meters, start the emergency response mode.

[0104] S102. The central controller sends control instructions for immediate assistance to other UAVs, controlling all UAVs to fly towards the current fire extinguishing point.

[0105] S103. And set the current ignition point as the highest priority in the target fire extinguishing sequence for all UAVs to perform the fire extinguishing task.

[0106] A processing method for autonomous UAV fire extinguishing based on the ignition point proposed in the embodiment of the present invention automatically triggers the emergency response mode when the distance is less than 10 meters by continuously detecting the distance between the ignition point and the surrounding dangerous chemical storage facilities. The central controller quickly issues collaborative instructions to other UAVs and raises this ignition point to the highest priority target, thereby realizing risk control and safety prevention during the fire handling process with the risk of dangerous chemicals.

[0107] Embodiment Two

[0108] Embodiment 2 of the present invention also provides a storage medium (or computer storage medium). The storage medium includes a stored program. When the program runs, it controls the device where the storage medium is located to execute the processing method of autonomous drone fire extinguishing based on the ignition point in Embodiment 1 above.

[0109] As Figure 6 shown, it is a schematic structural framework diagram of the computer storage medium provided by Embodiment 2 of the present invention, which includes:

[0110] A memory 1130 for storing computer programs;

[0111] A communication interface 1120 for connecting the memory 1130 to the processor 1110;

[0112] A processor 1110 for executing computer programs to implement the processing method of autonomous drone fire extinguishing based on the ignition point involved in any of the above-mentioned embodiments in combination.

[0113] In summary, the processing method of autonomous drone fire extinguishing based on the ignition point proposed in the embodiments of the present invention is essentially a drone fire extinguishing system based on the comprehensive collection of fire and environmental data, the dynamic calculation of the danger coefficient, and the generation of a fire extinguishing priority queue.

[0114] This system uses a variety of sensors to collect fire parameters such as flame height, temperature gradient, fire spread speed, and combustible density in real time, and at the same time obtains environmental factors such as the distance to adjacent buildings, real-time wind speed, and personnel density. After standardizing and preprocessing the data, it is input into the background processing platform, and the comprehensive danger coefficient of each ignition point is calculated through certain mathematical formulas, providing a scientific basis for subsequent fire extinguishing scheduling. The entire system makes full use of the technology of combining real-time data monitoring and dynamic calculation, overcomes the limitations of traditional fire extinguishing methods that only rely on single parameters or static judgments, and realizes a full-range and multi-dimensional risk assessment of the on-site fire situation.

[0115] In the specific implementation process, the system first calculates the comprehensive danger coefficient of each fire point based on the collected fire and environmental data using a preset model. To apply the calculation results to task scheduling, the system further constructs a dynamic fire extinguishing priority queue using the minimum heap data structure. As an efficient data structure, the minimum heap can quickly sort the danger levels of fire points in the case of changing fire situations. When the system detects a sudden increase in the risk coefficient of a certain fire scene or the appearance of a new fire point, it will trigger the reconstruction of the minimum heap, quickly reflecting the latest safety information in the priority queue. In this way, the drone can always execute the fire extinguishing task according to the latest fire severity.

[0116] To improve the intelligence level of the system, the present invention introduces a mechanism for dynamically adjusting weight parameters. Within a preset time period (for example, every 5 minutes), the system will count the actual fire extinguishing time in the recent three fire extinguishing cycles, compare this data with the preset theoretical maximum time, and calculate the updated value of the dynamic weight parameter using a formula. The updated parameter will replace the original setting, making the calculation of the danger coefficient closer to the actual situation on-site.

[0117] Thus, the comprehensive danger coefficient that has been continuously adaptively adjusted can not only reflect the instantaneous changes in the fire risk, but also provide more accurate guidance for the UAV mission planning, improving the system's response speed and fire extinguishing efficiency in complex environments.

[0118] In addition, to ensure long-term continuous operation, the system also designs a function for real-time monitoring of the remaining amount of fire extinguishing equipment (water resources). During the fire extinguishing mission, the UAV will continuously detect the status of the water resources it carries. When the water resources are below the preset threshold, the system automatically switches to the path energy-saving planning mode and sends an assistance request to the central controller in a timely manner. After receiving the request, the central controller will coordinate and dispatch other UAVs to ensure the continuous progress of the fire extinguishing mission at the fire site while allowing the UAV with insufficient current water resources to fly back to the starting point or base for replenishment. During the entire collaborative operation process, the system not only transmits the numbers, remaining water volumes, and current task status of each UAV, but also generates a detailed assistance report to be uploaded to the cloud server to provide data support for the overall combat effectiveness and subsequent improvement of the emergency plan.

[0119] In the special case where there are dangerous goods stored near the fire site, the system further designs an emergency response module. This module realizes the real-time detection of the distance between the fire point and the dangerous chemical facilities. When the distance is below the safety threshold (for example, 10 meters), the system will immediately trigger an emergency response, set the current fire point as the highest priority target, and send a collaborative operation instruction to all UAVs in the cluster, requiring them to quickly gather at this fire point for joint fire extinguishing. This measure can not only prevent the spread of the fire and avoid secondary accidents caused by dangerous chemicals, but also ensure the most effective control of the real-time risk at the fire site, fundamentally improving the on-site safety guarantee ability.

[0120] Generally speaking, the drone fire extinguishing system of the present invention realizes high sensitivity, self - adaptability and coordination of drones in fire - fighting tasks by organically integrating fire and environmental data, using the minimum heap data structure to construct a real - time updated fire - fighting priority queue, combined with dynamic weight parameter adjustment and real - time resource monitoring and emergency response modules. The system can not only effectively judge the multi - point, scattered and dynamically changing fire field environment, but also flexibly optimize the operation path and resource scheduling according to the actual situation on site. This solution effectively makes up for the deficiencies of traditional fire - fighting methods in information collection, risk assessment, dynamic sorting and resource coordination, and provides a new technical support and solution for the precise and efficient fire - fighting operations of drone swarms in complex fire field environments. Through the intelligent data processing and scheduling mechanism, the present invention provides a more robust operation platform and higher safety guarantee for the field of fire emergency disposal, and strongly promotes the development and application of drone fire - fighting technology.

[0121] Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present invention, not to limit them; those of ordinary skill in the art can modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements on some or all of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A processing method for autonomous UAV fire extinguishing based on the ignition point, characterized in that It includes the following steps: Collect the location information and fire parameters of multiple ignition points in real time. The fire parameters include flame height, temperature gradient, diffusion speed, and combustible density; Calculate the comprehensive risk coefficient based on the fire parameters and environmental parameters of each ignition point. The environmental parameters include the distance to adjacent buildings, wind speed, and population density; Rank all ignition points based on the comprehensive risk coefficient to generate an initial fire extinguishing order; Implement and update the calculation of the target fire extinguishing order; Control the fire extinguishing drone to set and plan an inspection and fire extinguishing path from the current position according to the target fire extinguishing order; The calculation formula for the comprehensive risk coefficient is: Among them, R i is the comprehensive risk coefficient of the i-th ignition point, F i is the normalized value of the flame height, T i is the abnormal temperature rise rate, D i is the distance to the nearest building, W i is the real-time wind speed, S i is the change rate of the diffusion area, and α, β, γ, δ are dynamic weight parameters.

2. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 1, wherein Rank all ignition points based on the comprehensive risk coefficient to generate an initial fire extinguishing order; Implement and update the calculation of the target fire extinguishing order, which specifically includes the following steps: Construct a minimum heap data structure with the comprehensive risk coefficient as the key value; Use the minimum heap data structure as the initial fire extinguishing order; Real-time monitor the change rate of the comprehensive risk coefficient of each ignition point. When the change rate of the risk coefficient exceeds the preset threshold and triggers the first condition, trigger the readjustment of the heap data structure; If a new ignition point is detected or the risk coefficient of an existing ignition point undergoes a mutation, perform the reconstruction of the heap data structure and output the updated fire extinguishing priority queue; Use the updated fire extinguishing priority queue as the target fire extinguishing order.

3. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 2, wherein, In step S32, when real-time monitoring the change rate of the comprehensive risk coefficient of each ignition point, when the change rate of the risk coefficient exceeds the preset threshold and triggers the first condition, triggering the readjustment of the heap data structure specifically includes the following steps: Periodically calculate the difference in the change of the comprehensive risk coefficient of each ignition point between the current and the previous cycle, and calculate the change rate of the risk coefficient; Compare the change rate of the risk coefficient with the preset threshold to screen out the abnormal change points that exceed the threshold. The first condition is that the proportion of the number of abnormally changing ignition points to the total number of ignition points exceeds the proportion threshold; When the proportion of the number of abnormally changing ignition points to the total number of ignition points exceeds the proportion threshold, update to the latest fire extinguishing priority queue.

4. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 3, wherein, Before the step of calculating the comprehensive risk coefficient based on the fire parameters and environmental parameters of each ignition point, it also includes the following steps: Dynamically adjust the weight parameter α at preset time intervals.

5. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 4, characterized in that, The step of dynamically adjusting the weight parameter α at preset time intervals specifically includes the following steps: Statistically analyze the actual fire fighting time data for the most recent three consecutive fire extinguishing cycles every 5 minutes; the actual fire fighting time data includes the actual fire extinguishing time t eff ; Based on the actual fire extinguishing time t eff and the preset theoretical maximum time t max , the updated value of the weight parameter is calculated using the following formula: Replace the original dynamic weight parameter α with the updated dynamic weight parameter α′ for subsequent comprehensive risk coefficient calculation.

6. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 1, characterized in that, Controlling the fire extinguishing drone to set and plan an inspection and fire extinguishing path from the current position according to the target fire extinguishing order also includes the following steps: Perform inspection and fire extinguishing processing in real time according to the target fire extinguishing order, and at the same time, real-time monitor the remaining water resources of the fire extinguishing equipment. If the remaining water resources are lower than the preset threshold, execute the path energy-saving planning mode.

7. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 6, characterized in that, The execution of the path energy-saving planning mode specifically includes the following steps: Screen out the ignition points that have not been extinguished in the target fire extinguishing order, and send the numbers of the ignition points that have not been extinguished in the target fire extinguishing order and a request for assisting in fire extinguishing to the central controller; The central controller sends control instructions to other drones. After other drones arrive at the current fire extinguishing point, the current drone flies back to the starting point to replenish water resources; The central controller generates an assistance report and uploads it to the cloud server for archiving.

8. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 7, characterized in that, The assistance report includes the current UAV number, the remaining water resources of the current UAV, the numbers of the ignition points that have not been extinguished in the target fire extinguishing sequence, and the numbers of other UAVs providing assistance.

9. The processing method for autonomous UAV fire extinguishing based on the ignition point according to claim 1, characterized in that, After controlling the fire extinguishing UAV to set and plan the inspection and fire extinguishing path according to the target fire extinguishing sequence from the current position, it further includes executing an emergency response mode when hazardous chemicals are detected, specifically including the following steps: Real-time detect the distance between the current ignition point and the surrounding hazardous chemical storage facilities. If the detected distance is less than 10 meters, then activate the emergency response mode; The central controller sends a control instruction for immediate assistance to other UAVs, controlling all UAVs to fly towards the current fire extinguishing point; And set the current ignition point as the highest priority in the target fire extinguishing sequence for all UAVs to perform the fire extinguishing task.

10. A storage medium, characterized in that, The storage medium includes a stored program, wherein when the program runs, it controls the device where the storage medium is located to execute the processing method for autonomous UAV fire extinguishing based on the ignition point according to any one of claims 1-9 above.

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