CN114913657A - Control method of forest floating communication relay platform - Google Patents
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- G08B17/005—Fire alarms; Alarms responsive to explosion for forest fires, e.g. detecting fires spread over a large or outdoors area
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- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/12—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions
- G08B17/125—Actuation by presence of radiation or particles, e.g. of infrared radiation or of ions by using a video camera to detect fire or smoke
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Abstract
The invention discloses a control method and a control device for a forest floating communication relay platform, wherein the control method comprises the following steps: receiving video files and image files with different formats and data information of an unmanned aerial vehicle and a command center; performing video image processing based on the data information, the video file and the image file to identify the fire condition; according to the identified fire situation, the fire situation is positioned by combining an electronic map and space measurement so as to determine the fire situation position; and alarming at the front end of the forest floating communication relay platform according to the fire condition and the fire position. The embodiment of the invention overcomes the defects of weak pertinence and scattered functions of the prior art, and forms a special display control method special for forest fire rescue.
Description
Technical Field
The invention relates to the technical field of fire analysis, in particular to a control method of a forest floating communication relay platform.
Background
The method aims at gathering, comprehensive processing and classified transmission of data collected by various sensors of the forest floating communication relay platform, and solves the problem of information management of the forest floating communication relay platform.
The forest floating communication relay platform mainly carries out aerial and ground collected video information, relays ultra-short wave voice information and ad hoc network audio and video information in the aerial, how to process the audio and video information and data information and information distribution are key problems to be solved by a display and control system, and meanwhile, the display and control system automatically generates a fire situation according to the collected information and transmits the fire situation to a designated node according to a command and decision command in a classified mode for commanders to use.
The prior art does not take forest fire fighting use requirements as research targets, so that the functions, the performances and the technical route of the device have universality, namely, the device can only transmit back the photoelectric pod video, the content (especially forest fire) in the video cannot be analyzed, audio and video information cannot be fused with a map, and the device cannot form a comprehensive situation for commanders to use.
Disclosure of Invention
The embodiment of the invention provides a control method and a control device for a forest floating communication relay platform, which are used for solving the defects of weak pertinence and function dispersion in the prior art and forming a special display control method special for forest fire rescue.
The embodiment of the invention provides a control method of a forest floating communication relay platform, which comprises the following steps:
receiving video files and image files with different formats and data information of an unmanned aerial vehicle and a command center;
performing video image processing based on the data information, the video file and the image file to identify the fire condition;
according to the identified fire situation, the fire situation is positioned by combining an electronic map and space measurement so as to determine the fire situation position;
and alarming at the front end of the forest floating communication relay platform according to the fire condition and the fire position.
In some embodiments, video image processing based on the data information, video file, image file to identify a fire condition comprises:
extracting key information in a video file and an image file, and adding context semantic description to a target object based on the key information; and
matching and correcting GPS and video data time based on the data information, and calculating the geographic position of a video frame of a video file by adopting a linear interpolation method;
and building spatial trajectory information based on the geographic location of the video frames.
In some embodiments, performing video image processing based on the data information, video file, image file to identify a fire condition further comprises:
extracting fire characteristics of forest fires from video image data after the video image processing;
and performing flame identification based on the fire characteristics.
In some embodiments, the fire signature comprises: static features including color features and shape and contrast features, and dynamic features including: texture features, frequency features, and motion features;
performing flame identification based on the fire signature includes:
extracting a region with similar color to the flame in the video image data for the color feature, and identifying based on a pre-established flame color model;
judging whether smoke exists or not based on the contrast change of pixels in video image data as shape and contrast characteristics;
calculating flame texture by adopting a background subtraction/foreground accumulation method based on video image data to output each pixel value of a foreground image for texture characteristics, and based on the motion relation between the foreground image and the background image;
based on the frequency characteristic, the state of part of pixel regions is alternately switched in the video image data to judge whether flames exist or not;
for motion characterization, a smoke starting point is determined based on the video image data, and the boundary between the sharp picture and the blurred picture is determined to identify the smoke condition.
In some embodiments, locating the fire based on the identified fire in combination with the electronic map and the spatial measurements to determine the location of the fire comprises:
determining coordinate information of the unmanned aerial vehicle at the time of the timestamp based on the coordinate information of the unmanned aerial vehicle and the timestamp of the fire video segment;
and calculating a conversion matrix among a space coordinate system of the unmanned aerial vehicle, an unmanned aerial vehicle carrier coordinate system and a geocentric coordinate system according to the navigation information and the equipment parameters, and determining coordinate data of the fire in the geocentric coordinate system based on the conversion matrix.
In some embodiments, after the alarm is given at the front end of the forest floating communication relay platform according to the fire situation and the fire position, the method further comprises the following steps of:
according to the fire condition, carrying out comparative analysis or circular analysis on the fire condition and historical fire information to form chart data;
and performing post-fire evaluation based on the chart data.
The embodiment of the invention also provides a control system of the forest floating communication relay platform, which comprises the following steps:
the information aggregation subsystem is configured to receive video files and image files in different formats and data information of the unmanned aerial vehicle and the command center;
the information processing subsystem is configured to perform video image processing on the basis of the data information, the video file and the image file so as to identify the fire situation; and
according to the identified fire situation, carrying out fire location by combining an electronic map and space measurement so as to determine the fire position;
and the information display subsystem is configured to alarm at the front end of the forest floating communication relay platform according to the fire situation and the fire position.
The embodiment of the invention also provides a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and when the computer program is executed by a processor, the steps of the control method for the forest floating communication relay platform are realized.
The embodiment of the invention overcomes the defects of weak pertinence and scattered functions of the prior art, and forms a special display control method special for forest fire rescue.
The foregoing description is only an overview of the technical solutions of the present invention, and the embodiments of the present invention are described below in order to make the technical means of the present invention more clearly understood and to make the above and other objects, features, and advantages of the present invention more clearly understandable.
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Various other advantages and benefits will become apparent to those of ordinary skill in the art upon reading the following detailed description of the preferred embodiments. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a schematic diagram of a basic structure of a forest floating communication relay platform according to an embodiment of the application;
FIG. 2 is a basic flowchart of a control method of a forest floating communication relay platform according to an embodiment of the application;
FIG. 3 is a schematic diagram of a working flow of a forest floating communication relay platform according to an embodiment of the application;
FIG. 4 is a schematic view of a video image processing flow according to an embodiment of the present application;
fig. 5 is a schematic view illustrating a video frame positioning process according to an embodiment of the present application.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
An embodiment of the invention provides a control method of a forest floating communication relay platform, and as shown in fig. 1, the forest floating communication relay platform can comprise an information gathering subsystem, an information processing subsystem and an information display subsystem.
The information aggregation subsystem receives and stores voice, video, images and data sent by the unmanned helicopter subsystem, the photoelectric reconnaissance subsystem, the individual reconnaissance subsystem and the ultrashort wave voice communication subsystem in a wired, mobile 4G, ultrashort wave, ad hoc network, data link and other modes, and can forward the voice and video to the integrated audio and video fusion platform and send live wire information to the command center; and receiving and storing state information of the broadband ad hoc network communication subsystem, the data link subsystem, the photoelectric detection subsystem and the ultrashort wave voice communication subsystem. The information gathering subsystem comprises three functions of information gathering, information storage and information distribution.
The information processing subsystem can extract and arrange the received audio and video information and data information, realize the analysis of fire points and fire wires and realize the calculation of personnel and paths. The information processing subsystem comprises six functions of data fusion, fire point positioning, fire line analysis, personnel search and situation analysis.
The information display subsystem displays the distribution of the fire wire, the fire situation and the fire alarm information through the electronic map, realizes the fusion of audio and video and the geographic information of the electronic map, can play multi-channel videos, realizes audio switching, can upload and issue control instructions to each subsystem, and can display the state information of each subsystem. The information display subsystem comprises eleven functions of GIS geographic information, audio and video management, comprehensive information retrieval, situation display, information data interaction, fire alarm, path planning, individual scout management, subsystem state display, large-screen display and system management.
As shown in fig. 2, the method for controlling a forest floating communication relay platform of the present embodiment includes the following steps:
in step S101, video files and image files in different formats and data information of the drone and the command center are received.
In step S102, video image processing is performed based on the data information, the video file, and the image file to identify a fire situation.
In step S103, according to the identified fire situation, the fire location is determined by combining the electronic map and the spatial measurement.
In step S104, an alarm is given at the front end of the forest floating communication relay platform according to the fire situation and the fire position.
Specifically, as shown in fig. 3, the forest floating communication relay platform receives videos and image files with different formats and data information of an unmanned aerial vehicle and a command center, and performs video image processing through a video image structured processing technology; then, analyzing the video image by means of an artificial intelligence technology of deep learning; recognizing the fire condition, and positioning the fire position by combining an electronic map and a spatial measurement technology; and alarming at the front end of the system.
The embodiment of the invention overcomes the defects of weak pertinence and scattered functions of the prior art, and forms a special display control method special for forest fire rescue.
In some embodiments, video image processing based on the data information, video file, image file to identify a fire condition comprises:
extracting key information in a video file and an image file, and adding context semantic description to a target object based on the key information; and
matching and correcting GPS and video data time based on the data information, and calculating the geographic position of a video frame of a video file by adopting a linear interpolation method;
and building spatial trajectory information based on the geographic location of the video frames.
Specifically, in this embodiment, as shown in fig. 4, in the video image processing, the original video file and the image file are intelligently analyzed, key information is extracted, and possible context semantic descriptions are added. The video picture structuring is to describe specific objects in video files and image files in order to facilitate system analysis, retrieval and query of relevant information in the video pictures. Aiming at the adding and deleting operation of the video frame, the time information needs to be taken into account, the GPS and the video data time are matched and corrected, the geographic position calculation of the video frame is completed by adopting a linear interpolation method, and the video track space information is established. And in combination with other means, the method provides support for applications such as association analysis and deep excavation analysis.
In some embodiments, performing video image processing based on the data information, video file, image file to identify a fire condition further comprises:
and extracting fire characteristics of forest fires from video image data after video image processing, and identifying flames based on the fire characteristics. Specifically, in this example, a fire detection technology based on intelligence and vision is adopted, and various characteristics (such as flame, smoke, and color) of forest fires are extracted from output data after video image processing, so as to analyze and identify the disaster. Flames have distinctive characteristics including color, temperature, shape, and the form of pulsation.
In some embodiments, the fire signature comprises: static features including color features and shape and contrast features, and dynamic features including: texture features, frequency features, and motion features;
performing flame identification based on the fire signature includes:
extracting a region with similar color to the flame in the video image data for the color feature, and identifying based on a pre-established flame color model;
judging whether smoke exists or not based on the contrast change of pixels in video image data for the shape and contrast characteristics;
calculating flame texture by adopting a background subtraction/foreground accumulation method based on video image data to output each pixel value of a foreground image for texture characteristics, and based on the motion relation between the foreground image and the background image;
based on the frequency characteristic, the state of part of pixel regions is alternately switched in the video image data to judge whether flames exist or not;
for motion characterization, a smoke starting point is determined based on the video image data, and the boundary between the sharp picture and the blurred picture is determined to identify the smoke condition.
Specifically, in the present embodiment, the flame is divided into two aspects, namely static characteristics and dynamic characteristics, so as to perform flame identification.
For color features
The color characteristics belong to static characteristics, and in a general fire scene, the colors of the flame pixel points are mainly distributed from orange yellow to white. In order to describe the color distribution of the flame pixels, a statistical model, called a flame color model, is established in this embodiment. Through the flame color model, the region with similar color to the flame in the image can be extracted. The system adopts RGB, HSV and YCrCb color space specifications and uses a machine learning method to establish a flame color model.
For texture features
The texture features may reflect visual features of homogeneity in the image, the slowly or periodically varying surface structure of the flame surface organizing properties. The flame texture has: the local sequences are repeated continuously and are not randomly ordered, and the texture region is characterized by being a uniform and uniform entity. Unlike color features, texture features are represented by the gray scale distribution of a pixel and its surrounding spatial neighborhood.
In the embodiment, a background subtraction method/foreground accumulation method is adopted, and a dynamic background which changes relatively slowly is constructed, so that the interference caused by factors such as illumination change and the like is avoided. The foreground accumulation method continuously accumulates the inter-frame difference of the image, and each pixel value of the output foreground image is in a slowly-reduced state. In the operation process, the pixel value of the moving part (foreground) is continuously increased, the pixel value of the static part (background) is continuously reduced until 0, a threshold value is set, and when the pixel value exceeds the threshold value, the pixel is considered as a moving pixel point, so that a moving area is extracted.
Shape and contrast characteristics
The shape and contrast characteristics belong to static characteristics. The smoke has no obvious distribution in color like a flame, and the color has a direct relation with the concentration of the smoke. Regardless of the shade of the smoke, it can obscure or even completely obscure the following items. In this example, the presence or absence of smoke can be judged by the contrast change of the pixel.
Frequency characteristics
The frequency characteristic belongs to a dynamic characteristic. In this example, the presence of a flame can be further confirmed by capturing the frequency characteristics.
Movement characteristics
The motion pattern of fire smoke is an important dynamic feature. The dynamic characteristics of smoke are important characteristics that distinguish smoke from other things. It has the following characteristics: first, smoke varies in a diffuse manner, and it can be assumed that there are one or several smoke generating points around which smoke diffuses; secondly, similar to flames, there is a certain frequency of changes in the boundaries of smoke. Then, the outline of the smoke is the boundary of the clear picture and the blurred picture; finally, the movement of the smoke is continuous and non-rigid.
In some embodiments, locating the fire based on the identified fire in combination with the electronic map and the spatial measurements to determine the location of the fire comprises:
determining coordinate information of the unmanned aerial vehicle at the time of the timestamp based on the coordinate information of the unmanned aerial vehicle and the timestamp of the fire video segment;
and calculating a conversion matrix among a space coordinate system of the unmanned aerial vehicle, an unmanned aerial vehicle carrier coordinate system and a geocentric coordinate system according to the navigation information and the equipment parameters, and determining coordinate data of the fire in the geocentric coordinate system based on the conversion matrix.
The fire identification and positioning method is characterized in that unmanned aerial vehicle video image data are utilized for fire automatic distinguishing and position positioning based on video image processing and artificial intelligence view analysis, and the fire identification and positioning method mainly comprises two modes of video image frame positioning and fire geographic coordinate positioning.
The view that unmanned aerial vehicle shot has certain shooting angle and shooting distance, and the actual coordinate of condition of a fire needs to carry out the conversion through the unmanned aerial vehicle coordinate and calculates and reachs in this embodiment.
As shown in fig. 5, the fire geographical coordinate positioning inquires the coordinates of the unmanned aerial vehicle at the time of the timestamp according to the fire view timestamp, calculates a transformation matrix among a space coordinate system, an unmanned aerial vehicle carrier coordinate system and a ground-centered coordinate system according to the navigation information and the equipment parameters, and converts to obtain the coordinates of the fire target in the ground-centered coordinate system. In the embodiment, the image matching between the reference image and the real-time image is mainly calculated, and the matching precision and speed are improved as much as possible.
Based on a fire recognition and positioning algorithm model, video data and geographic space data are integrated in a fusion mode, information management and application services combining spatial positions and video images are provided, and functions of automatic fire point recognition and positioning, real-time field situation display, fire command decision support and the like are provided for commanders.
In some embodiments, after the alarm is given at the front end of the forest floating communication relay platform according to the fire situation and the fire position, the method further comprises the following steps of:
according to the fire condition, carrying out comparative analysis or circular analysis on the fire condition and historical fire information to form chart data;
and performing post-fire evaluation based on the chart data.
In a specific embodiment, based on video image data and command operation data, technologies such as data analysis mining and deep learning are comprehensively applied to analyze and apply the data, and through carrying out comparison analysis or ring comparison analysis in various combination forms on fire information which has occurred in the past, the occurrence conditions of fires in different years and months, causes of fires and the like can be analyzed, and the fire causes and the like can be visually presented in various forms such as a pie chart, a histogram and the like, so that the method helps commanders to predict and prevent fires. Meaningful, potential and useful information and knowledge are extracted from video image data resources and extracted, and a more complete, reasonable and accurate analysis and prediction can be made in the future based on comprehensive business application. Aiming at the post-disaster evaluation work, the loss caused by the fire disaster can be evaluated through the system at the first time after the fire disaster is extinguished, and various post-disaster statistical reports are generated. The method solves the correlation between data, can automatically form the fire scene situation, improves the efficiency of fire rescue personnel, and solves the problems that the forest fire fighting can not see and cannot transmit the serious fire.
The embodiment of the invention also provides a control system of the forest floating communication relay platform, which comprises the following steps:
the information aggregation subsystem is configured to receive video files and image files in different formats and data information of the unmanned aerial vehicle and the command center;
the information processing subsystem is configured to perform video image processing on the basis of the data information, the video file and the image file so as to identify the fire situation; and
according to the identified fire situation, carrying out fire location by combining an electronic map and space measurement so as to determine the fire position;
and the information display subsystem is configured to alarm at the front end of the forest floating communication relay platform according to the fire situation and the fire position.
Specifically, the control system of the embodiment receives and assembles voice data, video data, meteorological data, personnel data, equipment data, fire wire data and the like from the photoelectric pod, the command center and the individual soldier scout by means of ultrashort waves, an ad hoc network, a data chain and the like, processes the data through an information fusion technology, forms information such as fire point positioning, fire wire situation, fire scene situation, fire alarm, resource path and the like, and realizes the all-dimensional display of the fire point, the fire wire, the personnel and the environment.
The display control system adopts a C/S architecture, and by using the idea of SOA, business services are disclosed in a loose coupling mode, so that the system is easier to integrate and manage. Through good hierarchical structure, unified interface service can effectively reduce service platform's complexity, include:
original data layer
And audio and video information of different transmission modes and different data formats returned by the photoelectric pod and the individual soldier camera is collected. Meanwhile, the multi-element heterogeneous information such as meteorological data, personnel data, equipment data, fire wire data and the like is accessed from a command center headquarters, and a data resource pool is formed.
Information communication layer
The platform transmits data to the transport vehicle/the measuring and controlling vehicle through means of mobile 4G communication, wired, ultrashort wave, ad hoc network and the like. The display and control seats are respectively arranged in the transport vehicle and the measurement and control vehicle, and the display and control server is arranged in the measurement and control vehicle and is responsible for acquiring the information of the original data layer.
Data fusion layer
The data fusion layer digitizes the information of the original data layer and converts the information into an IP streaming media format. The system guarantees the quality of metadata through modes of consistency check, attribute filling rate and the like; the data integrity, effectiveness, consistency, normalization, openness and shareability management is realized through a series of activities such as unified data standard formulation and release and the like in combination with means such as system constraint, system control and the like; the system is grouped according to an evaluation method, multi-angle quality monitoring is carried out, and a user is assisted to establish a complete quality rule; finally, the system forms data catalogues with different visual angles, better supports the application of various data and realizes the maximum release of data asset value.
Platform service layer
The platform service layer provides functional services of data fusion acquisition, fire real-time early warning, situation fusion display, fire analysis and evaluation, background management and the like of the front-end command aid decision-making system. The fire condition is obtained by automatically/intelligently analyzing videos and images mainly through an artificial intelligence technology.
The system decomposes the video image by adopting a video analysis technology and an automatic video picking technology. The video analysis is a part of artificial intelligence, the video acquisition, preprocessing and processing are realized through sensors such as a camera and the like, then a real image is transmitted to a system, the system adopts multi-layer grading, the resolution of an image background, a slow moving target and a remote target is minimized, and some details are ignored; and carrying out secondary focusing on the foreground characteristic area to obtain more details, and then carrying out fire judgment on the area.
The system uses K-NN, naive Bayes, neural networks as machine learning classifiers to construct a flame color model. In addition, the system also adopts an EM algorithm to train a machine learning clustering algorithm of a Gaussian mixture model to construct a flame color model so as to analyze static characteristics of fire, such as color, shape and the like; the system uses an interframe difference method, a background subtraction method and a foreground accumulation method to analyze dynamic characteristics such as the frequency of fire.
By utilizing an analysis method of dynamic and static combination of color characteristics, motion characteristics, geometric characteristics, texture characteristics and the like, flame and smoke in a video image are automatically analyzed and identified, alarm information is generated, fire detection and alarm are completed in a short time, and the fire alarm time is greatly shortened.
Exposing application layers
The display application layer integrates the unmanned aerial vehicle video and the GIS to realize the display of the unmanned aerial vehicle video in a scene, so that the display of the unmanned aerial vehicle video data is matched with the real geographical position of the unmanned aerial vehicle video data; by positioning the video, a commander can quickly search for a fire point, and quickly interpret video frames by referring to real terrain images or other map data, so that the efficiency of interpreting the video images by the commander is improved. And through the integration of visualization and GIS, the information of images/sounds downloaded by the unmanned aerial vehicle, the fire trend analyzed by the system, the distribution situation of fire fighting resources, the positioning of the fire and the like is displayed on a map, and an auxiliary support means is provided for the command and scheduling of the fire of commanders, the situation analysis and the decision evaluation.
The control system of this application has realized multiple data fusion, can gather the video of photoelectricity nacelle, the audio frequency of ultrashort wave pronunciation, the video of broadband ad hoc network, audio frequency and data, combines data such as current weather, weapon power deployment, forms whole situation through fusing.
And (3) carrying out artificial intelligence view analysis, extracting various characteristics (such as flame, smoke and color) of forest fires, and realizing disaster analysis and identification. The system divides the flame into static characteristics and dynamic characteristics for flame identification
The fire condition is identified and positioned, the fire condition is identified through the photoelectric pod video and the broadband ad hoc network video, fire point positioning is carried out by combining unmanned aerial vehicle information, and the fire condition is fused with GIS information and displayed in a situation form.
The analysis and evaluation can visually present the fire occurrence conditions of different years and months in various forms such as a pie chart, a bar chart and the like, and by extracting meaningful and potentially useful information and knowledge from the video image data resources and refining the information and the knowledge, a more complete, reasonable and accurate analysis and prediction can be made in the future based on comprehensive business application. Aiming at the post-disaster evaluation work, the loss caused by the fire disaster can be evaluated through the system at the first time after the fire disaster is extinguished, and various post-disaster statistical reports are generated.
The embodiment of the invention also provides a computer-readable storage medium, wherein a computer program is stored on the computer-readable storage medium, and when the computer program is executed by a processor, the steps of the control method for the forest floating communication relay platform are realized.
It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention may be embodied in the form of a software product, which is stored in a storage medium (such as ROM/RAM, magnetic disk, optical disk) and includes instructions for enabling a terminal (such as a mobile phone, a computer, a server, or a network device) to execute the method according to the embodiments of the present invention.
While the present invention has been described with reference to the embodiments shown in the drawings, the present invention is not limited to the embodiments, which are illustrative and not restrictive, and it will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (8)
1. A control method for a forest floating communication relay platform is characterized by comprising the following steps:
receiving video files and image files with different formats and data information of an unmanned aerial vehicle and a command center;
performing video image processing based on the data information, the video file and the image file to identify the fire condition;
according to the identified fire situation, the fire situation is positioned by combining an electronic map and space measurement so as to determine the fire situation position;
and alarming at the front end of the forest floating communication relay platform according to the fire condition and the fire position.
2. The method for controlling the forest floating communication relay platform according to claim 1, wherein performing video image processing based on the data information, the video file and the image file to identify the fire condition comprises:
extracting key information in a video file and an image file, and adding context semantic description to a target object based on the key information; and
matching and correcting GPS and video data time based on the data information, and calculating the geographic position of a video frame of a video file by adopting a linear interpolation method;
and building spatial trajectory information based on the geographic location of the video frames.
3. The method for controlling the forest floating communication relay platform according to claim 1, wherein performing video image processing based on the data information, the video file and the image file to identify a fire condition further comprises:
extracting fire characteristics of forest fires from video image data after the video image processing;
and performing flame identification based on the fire characteristics.
4. A control method for a forest floating communication relay platform according to claim 3, wherein the fire characteristics comprise: static features including color features and shape and contrast features, and dynamic features including: texture features, frequency features, and motion features;
performing flame identification based on the fire signature includes:
extracting a region with similar color to the flame in the video image data for the color feature, and identifying based on a pre-established flame color model;
judging whether smoke exists or not based on the contrast change of pixels in video image data as shape and contrast characteristics;
calculating flame texture by adopting a background subtraction/foreground accumulation method based on video image data to output each pixel value of a foreground image for texture characteristics, and based on the motion relation between the foreground image and the background image;
based on the frequency characteristic, the state of part of pixel regions is alternately switched in the video image data to judge whether flames exist or not;
for motion characterization, a smoke starting point is determined based on the video image data, and the boundary between the sharp picture and the blurred picture is determined to identify the smoke condition.
5. The method for controlling the forest floating communication relay platform according to claim 4, wherein the step of carrying out fire location by combining an electronic map and space measurement according to the identified fire situation to determine the fire position comprises the following steps:
determining coordinate information of the unmanned aerial vehicle at the time of the timestamp based on the coordinate information of the unmanned aerial vehicle and the timestamp of the fire video segment;
and calculating a conversion matrix among a space coordinate system of the unmanned aerial vehicle, an unmanned aerial vehicle carrier coordinate system and a geocentric coordinate system according to the navigation information and the equipment parameters, and determining coordinate data of the fire in the geocentric coordinate system based on the conversion matrix.
6. The method for controlling the forest floating communication relay platform according to the claim 1, wherein after the forest floating communication relay platform gives an alarm according to the fire situation and the fire position, the method further comprises the following steps of analyzing and evaluating the fire situation:
according to the fire condition, carrying out comparative analysis or circular analysis on the fire condition and historical fire information to form chart data;
and performing post-fire evaluation based on the chart data.
7. The utility model provides a forest floats sky communication relay platform's control system which characterized in that includes:
the information aggregation subsystem is configured to receive video files and image files in different formats and data information of the unmanned aerial vehicle and the command center;
the information processing subsystem is configured to perform video image processing on the basis of the data information, the video file and the image file so as to identify the fire situation; and
according to the identified fire situation, the fire situation is positioned by combining an electronic map and space measurement so as to determine the fire situation position;
and the information display subsystem is configured to alarm at the front end of the forest floating communication relay platform according to the fire situation and the fire position.
8. A computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium, which computer program, when being executed by a processor, carries out the steps of the method for controlling a forest floating communication relay platform according to any one of claims 1 to 6.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115376269A (en) * | 2022-10-21 | 2022-11-22 | 南京信大卫星应用研究院有限公司 | Fire monitoring system based on unmanned aerial vehicle |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115376269A (en) * | 2022-10-21 | 2022-11-22 | 南京信大卫星应用研究院有限公司 | Fire monitoring system based on unmanned aerial vehicle |
| CN115376269B (en) * | 2022-10-21 | 2022-12-30 | 南京信大卫星应用研究院有限公司 | Fire monitoring system based on unmanned aerial vehicle |
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