Fire extinguishing method and system based on modular unmanned aerial vehicle

Abstract

The invention provides a fire extinguishing method and system based on modular unmanned aerial vehicles, and relates to the technical field of fire fighting, and the method comprises the following steps: collecting on-site multi-dimensional index data through a multi-sensor module loaded by a plurality of unmanned aerial vehicles, and carrying out the recognition and prediction of the multi-dimensional index data, obtaining a corresponding fire area and a fire possible diffusion area; identifying the fire area and the possible fire diffusion area, and determining a corresponding fire point position; acquiring current position data of a plurality of unmanned aerial vehicles, determining corresponding unmanned aerial vehicle fire extinguishing positions based on the position data, the fire point position, the fire area and the possible fire diffusion area, and controlling the plurality of unmanned aerial vehicles to fly to the unmanned aerial vehicle fire extinguishing positions for fire extinguishing treatment; through accurate positioning of the fire point and optimization of the fire extinguishing position of the unmanned aerial vehicle, the unmanned aerial vehicle always carries out operation in the optimal operation position, and the fire extinguishing efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of fire protection technology, and more specifically to a fire extinguishing method and system based on modular unmanned aerial vehicles (UAVs). Background Technology

[0002] Currently, a photovoltaic (PV) power station refers to a power generation system that utilizes solar energy, employs special materials such as crystalline silicon panels, inverters, and other electronic components, and is connected to the power grid to transmit electricity. It is a typical green energy development project. With the increasing scale of PV power stations and the growing demand for deployment in mountainous areas, a growing fire risk has emerged. Furthermore, PV power stations are often located in mountainous regions, and once a fire breaks out and is not extinguished promptly, it can easily ignite a large-scale wildfire, posing a significant challenge to emergency rescue and ecological protection. However, this also presents an opportunity for the application of firefighting drones.

[0003] Although firefighting drones have many advantages such as high mobility and simple maintenance, due to the complex mountainous environment, coupled with shortcomings in fire location identification, adaptability to complex environments, and multi-drone collaborative operation, drones usually operate within a preset threshold range of the fire area, and cannot perform firefighting operations in the optimal location, thus affecting the firefighting efficiency of drones.

[0004] Therefore, how to provide a firefighting method based on modular drones that can solve the above problems is a problem that urgently needs to be solved by those skilled in the art. Summary of the Invention

[0005] In view of this, the present invention provides a fire extinguishing method and system based on modular drones. By accurately locating the fire ignition point and optimizing the drone's fire extinguishing position, the drone can always operate in the optimal working position, thereby improving fire extinguishing efficiency.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: A firefighting method based on modular drones includes the following steps: S1: Collect multi-dimensional indicator data of the scene through multi-sensor modules mounted on multiple drones, and identify and predict the multi-dimensional indicator data to obtain the corresponding fire area and the area where the fire may spread. S2: Identify the fire area and the area where the fire may spread, and determine the corresponding ignition point location; S3: Obtain the current location data of multiple drones, determine the corresponding drone firefighting position based on the location data, the location of the fire ignition point, the fire area, and the area where the fire may spread, and control multiple drones to fly to the drone firefighting position to carry out firefighting.

[0007] Preferred options also include: S4: Update the fire area and the area where the fire may spread in real time during a preset time period, and adjust the corresponding drone firefighting position according to the update results.

[0008] Preferably, S1 includes: S11: Collect multi-dimensional indicator data of the site through multi-sensor modules mounted on multiple drones, wherein the multi-dimensional indicator data includes temperature and humidity data, wind speed data, meteorological data, remote sensing image data and on-site ground data, and preprocess the multi-dimensional indicator data; S12: Construct an identification model by inputting the preprocessed multi-dimensional indicator data into the identification model for processing to obtain the corresponding fire area; S13: Based on the on-site ground data, the remote sensing image data, the meteorological data, and the wind speed data, fire spread prediction is performed to obtain the corresponding potential fire spread area.

[0009] Preferably, the specific implementation process of S2 includes: A target tracking model is constructed and trained. The fire area and the area where the fire may spread are input into the target tracking model for processing to obtain the corresponding ignition point location.

[0010] Preferably, S3 includes: S31: Establish a corresponding field coordinate system based on the field ground data, and transform the location of the ignition point to the field coordinate system to obtain the corresponding actual coordinates of the ignition point; S32: Establish a UAV coordinate system based on the location data, establish a transformation relationship between the UAV coordinate system and the field coordinate system, and obtain the actual coordinates of the UAV corresponding to the UAV based on the transformation relationship; S33: Construct a location decision model to determine the corresponding drone firefighting location coordinates based on the actual coordinates of the drone, the actual coordinates of the fire ignition point, the fire area, and the area where the fire may spread. S34: Control the drone to move to the drone's firefighting location coordinates to complete the firefighting operation.

[0011] The present invention also provides a fire extinguishing system based on a modular unmanned aerial vehicle (UAV), comprising: The acquisition module is used to collect multi-dimensional indicator data of the scene through multiple sensor modules mounted on multiple drones, and to identify and predict the multi-dimensional indicator data to obtain the corresponding fire area and the area where the fire may spread. The identification module is used to identify the fire area and the area where the fire may spread, and to determine the location of the corresponding ignition point. The control module is used to acquire the current location data of multiple drones, determine the corresponding drone firefighting position based on the location data, the location of the fire ignition point, the fire area and the area where the fire may spread, and control multiple drones to fly to the drone firefighting position to carry out firefighting. The update module is used to update the fire area and the area where the fire may spread in real time during a preset period, and adjust the corresponding drone firefighting position according to the update results.

[0012] As can be seen from the above technical solution, compared with the prior art, the present invention discloses a fire extinguishing method and system based on modular unmanned aerial vehicles (UAVs), which has the following beneficial effects: 1. This invention uses a multi-sensor module mounted on a drone to simultaneously collect multiple types of data, comprehensively capture key information such as the fire environment, fire status, and terrain conditions, quickly locate the fire area through an identification model, combine meteorological and wind speed data to predict the fire spread trend, and then use a target tracking model to accurately locate the ignition point, thereby improving the identification accuracy of the fire area, ignition point, and spread range. 2. This invention establishes a transformation relationship between the on-site coordinate system and the UAV coordinate system, unifying the fire ignition point location and the UAV location to the same spatial dimension, thereby achieving accurate calculation of the fire extinguishing location coordinates and avoiding misalignment of UAV operations due to spatial positioning deviations.

[0013] 3. Based on the location data of multiple drones, this invention allocates fire extinguishing locations by combining the fire area and the spread range. It can simultaneously carry out operations on multiple ignition points, the core area of ​​the fire, and the spread warning area, thereby improving operational efficiency and adapting to the rapid control needs of complex fire sites such as mountainous areas. 4. This invention updates the fire area and spread range in real time by preset time periods and adjusts the fire-fighting position of the drone simultaneously. This solves the problem that traditional one-time fire-fighting decisions cannot cope with the spread of fire and the transfer of fire points. It achieves dynamic adaptation, avoids fire-fighting failure due to changes in fire intensity, and shortens the fire control time. Attached Figure Description

[0014] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0015] Figure 1 A flowchart illustrating the overall process of a firefighting method based on a modular unmanned aerial vehicle (UAV) provided by this invention. Figure 2 The present invention provides a structural principle block diagram of a fire extinguishing system based on a modular unmanned aerial vehicle. Detailed Implementation

[0016] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] See Figure 1 As shown in the figure, an embodiment of the present invention discloses a fire extinguishing method based on a modular unmanned aerial vehicle (UAV), comprising the following steps: S1: Collect multi-dimensional indicator data of the scene through multi-sensor modules mounted on multiple drones, and identify and predict the multi-dimensional indicator data to obtain the corresponding fire area and the area where the fire may spread. S2: Identify the fire area and the area where the fire may spread, and determine the corresponding ignition point location; S3: Obtain the current location data of multiple drones, determine the corresponding drone firefighting position based on the location data, the location of the fire ignition point, the fire area, and the area where the fire may spread, and control multiple drones to fly to the drone firefighting position to carry out firefighting.

[0018] In one specific embodiment, S1 includes: S11: Collect multi-dimensional indicator data of the site through multi-sensor modules mounted on multiple drones. The multi-dimensional indicator data includes temperature and humidity data, wind speed data, meteorological data, remote sensing image data and on-site ground data. The multi-dimensional indicator data is preprocessed. The on-site ground data can also be combined with big data or Beidou positioning, including corresponding on-site location data, terrain data and other parameters. S12: Construct an identification model. Input the preprocessed multi-dimensional indicator data into the identification model for processing to obtain the corresponding fire area. The identification model can be a combination of a CNN model and a YOLOv5 model. The CNN model is used to extract the feature data corresponding to the multi-dimensional indicator data, and the YOLOv5 model is used to identify the feature data to obtain the corresponding fire area. S13: Based on the on-site ground data, the remote sensing image data, the meteorological data, and the wind speed data, fire spread prediction is performed to obtain the corresponding possible fire spread area. The prediction process can be achieved by constructing a relevant prediction model (such as a transformer model).

[0019] In a specific embodiment, the specific implementation process of S2 includes: A target tracking model is constructed and trained. The fire area and the area where the fire may spread are input into the target tracking model for processing to obtain the corresponding ignition point location. The target tracking model can be a lightweight single-target tracking model, DeepSORT.

[0020] In one specific embodiment, S3 includes: S31: Establish a corresponding field coordinate system based on the field ground data, and transform the location of the ignition point to the field coordinate system to obtain the corresponding actual coordinates of the ignition point; S32: Establish a UAV coordinate system based on the location data, establish a transformation relationship between the UAV coordinate system and the field coordinate system, and obtain the actual coordinates of the UAV corresponding to the UAV based on the transformation relationship; S33: Construct a location decision model. Input the actual coordinates of the UAV, the actual coordinates of the ignition point, the fire area, and the area where the fire may spread into the location decision model for processing to obtain the corresponding UAV firefighting location coordinates. The location decision model can be a composite model that combines random forest and decision tree. S34: Control the drone to move to the drone's firefighting location coordinates to complete the firefighting operation.

[0021] Specifically, the implementation process of S33 may also include the following steps: The location decision model also outputs the corresponding drone distance threshold. It calculates the corresponding distance by combining the drone's firefighting location coordinates and the actual coordinates of the fire point. If the distance does not meet the drone distance threshold requirement, the drone's firefighting location coordinates are adjusted to meet the threshold requirement to ensure the safe use of the drone.

[0022] In one specific embodiment, it also includes: S4: Update the fire area and the area where the fire may spread in real time during a preset time period, and adjust the corresponding drone firefighting position according to the update results.

[0023] Specifically, the implementation process of S4 may include: The remote sensing image data and environmental data of the site were re-acquired by drones and pre-processed. The remote sensing image data is identified to determine whether there is a fire point. If there is no fire point, the update ends. If there is a fire point, the pre-processed remote sensing image data and environmental data are input into the identification model for processing to obtain new fire area identification results. The new fire area identification result is compared with the original fire area. If it is greater than or equal to the original fire area, staff are remotely notified to dispatch additional fire-fighting drones or ground fire-fighting equipment for auxiliary handling. If it is less than the original fire area identification result, the new fire area identification result is further compared with the area where the fire may spread. If the fire spread area is smaller than the original potential fire spread area, a new ignition point coordinate is determined based on the new fire area identification result. The new ignition point coordinate and the new fire area identification result are then input into the location decision model for processing to obtain the new drone firefighting location coordinates. If the fire spread area is greater than or equal to the original potential fire spread area, the potential fire spread area is re-predicted based on the pre-processed remote sensing image data and environmental data. The new ignition point coordinate, the new potential fire spread area, the new fire area identification result, and the actual drone coordinates are then input into the location decision model for processing to obtain the corresponding drone firefighting location coordinates, thus achieving the purpose of updating.

[0024] See Figure 2 As shown, this embodiment of the invention also provides a system utilizing the fire extinguishing method based on a modular unmanned aerial vehicle (UAV) described in any of the above embodiments, comprising: The acquisition module is used to collect multi-dimensional indicator data of the scene through multiple sensor modules mounted on multiple drones, and to identify and predict the multi-dimensional indicator data to obtain the corresponding fire area and the area where the fire may spread. The identification module is used to identify the fire area and the area where the fire may spread, and to determine the location of the corresponding ignition point. The control module is used to acquire the current location data of multiple drones, determine the corresponding drone firefighting position based on the location data, the location of the fire ignition point, the fire area and the area where the fire may spread, and control multiple drones to fly to the drone firefighting position to carry out firefighting. The update module is used to update the fire area and the area where the fire may spread in real time during a preset period, and adjust the corresponding drone firefighting position according to the update results.

[0025] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since they correspond to the methods disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to the method section.

[0026] The above description of the disclosed embodiments enables those skilled in the art to make or use the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A firefighting method based on modular unmanned aerial vehicles (UAVs), characterized in that, Includes the following steps: S1: Collect multi-dimensional indicator data of the scene through multi-sensor modules mounted on multiple drones, and identify and predict the multi-dimensional indicator data to obtain the corresponding fire area and the area where the fire may spread. S2: Identify the fire area and the area where the fire may spread, and determine the corresponding ignition point location; S3: Obtain the current location data of multiple drones, determine the corresponding drone firefighting position based on the location data, the location of the fire ignition point, the fire area, and the area where the fire may spread, and control multiple drones to fly to the drone firefighting position to carry out firefighting.

2. The fire extinguishing method based on a modular unmanned aerial vehicle (UAV) according to claim 1, characterized in that, Also includes: S4: Update the fire area and the area where the fire may spread in real time during a preset time period, and adjust the corresponding drone firefighting position according to the update results.

3. A firefighting method based on a modular unmanned aerial vehicle (UAV) according to claim 1, characterized in that, S1 includes: S11: Collect multi-dimensional indicator data of the site through multi-sensor modules mounted on multiple drones, wherein the multi-dimensional indicator data includes temperature and humidity data, wind speed data, meteorological data, remote sensing image data and on-site ground data, and preprocess the multi-dimensional indicator data; S12: Construct an identification model by inputting the preprocessed multi-dimensional indicator data into the identification model for processing to obtain the corresponding fire area; S13: Based on the on-site ground data, the remote sensing image data, the meteorological data, and the wind speed data, fire spread prediction is performed to obtain the corresponding potential fire spread area.

4. A firefighting method based on a modular unmanned aerial vehicle (UAV) according to claim 3, characterized in that, The specific implementation process of S2 includes: A target tracking model is constructed and trained. The fire area and the area where the fire may spread are input into the target tracking model for processing to obtain the corresponding ignition point location.

5. A firefighting method based on a modular unmanned aerial vehicle (UAV) according to claim 4, characterized in that, S3 includes: S31: Establish a corresponding field coordinate system based on the field ground data, and transform the location of the ignition point to the field coordinate system to obtain the corresponding actual coordinates of the ignition point; S32: Establish a UAV coordinate system based on the location data, establish a transformation relationship between the UAV coordinate system and the field coordinate system, and obtain the actual coordinates of the UAV corresponding to the UAV based on the transformation relationship; S33: Construct a location decision model to determine the corresponding drone firefighting location coordinates based on the actual coordinates of the drone, the actual coordinates of the fire ignition point, the fire area, and the area where the fire may spread. S34: Control the drone to move to the drone's firefighting location coordinates to complete the firefighting operation.

6. A system utilizing the firefighting method based on a modular unmanned aerial vehicle as described in any one of claims 1-5, characterized in that, include: The acquisition module is used to collect multi-dimensional indicator data of the scene through multiple sensor modules mounted on multiple drones, and to identify and predict the multi-dimensional indicator data to obtain the corresponding fire area and the area where the fire may spread. The identification module is used to identify the fire area and the area where the fire may spread, and to determine the location of the corresponding ignition point. The control module is used to acquire the current location data of multiple drones, determine the corresponding drone firefighting position based on the location data, the location of the fire ignition point, the fire area and the area where the fire may spread, and control multiple drones to fly to the drone firefighting position to carry out firefighting. The update module is used to update the fire area and the area where the fire may spread in real time during a preset period, and adjust the corresponding drone firefighting position according to the update results.

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