CN112365673B - Forest fire monitoring system and method - Google Patents
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Abstract
The invention relates to a forest fire monitoring system and method. The system comprises a server, a main unmanned aerial vehicle and an auxiliary unmanned aerial vehicle; the server is used for: acquiring a first image of a forest region calibration area acquired by a main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height; when a fire condition occurs in the calibration area according to the first image, controlling the auxiliary unmanned aerial vehicles to the calibration area, enabling the auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle to form a polygonal array to fly and fly at a second height together, wherein the second height is lower than the first height; acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at a second height respectively, wherein the second images acquired by adjacent unmanned aerial vehicles at least partially coincide; and determining the change trend information of the fire area and the fire center according to all the second images. The technical scheme of the invention can facilitate the timely and reasonable and targeted forest fire extinguishing and disaster relief work so as to reduce the corresponding loss.
Description
Technical Field
The invention relates to the technical field of application of Internet of things, in particular to a forest fire monitoring system and method.
Background
Forests, as a main body of renewable natural resources and terrestrial ecosystems, play an irreplaceable role in human survival and development. In order to protect the forest, on one hand, afforestation needs to be carried out to increase the coverage rate of the forest, and on the other hand, the existing forest needs to be protected by measures such as fire prevention, insect prevention and the like.
Forest fires are large enemies harmful to forests, large pieces of forests can be converted into ash in one fire in the middle of the day, so that serious loss is caused, meanwhile, forest lands lose the coverage of the forests, water and soil loss is easily caused, water, drought, sand and wind disasters are easily caused, and agricultural production is affected. Therefore, fire monitoring of forest areas is required.
If the forest area is large, the existing forest fire monitoring mode is mainly that people patrol on a watchtower, although the fire can be found in most of time, if the conditions of overlarge wind force, too strong smoke and the like occur, the fire information cannot be further accurately obtained in time, and the deployment of effective fire extinguishing and relief work can be delayed.
Disclosure of Invention
Aiming at the defects of the prior art, the invention provides a forest fire monitoring system and a forest fire monitoring method.
In a first aspect, the invention provides a forest fire monitoring system, which comprises a server and a plurality of unmanned aerial vehicles, wherein the unmanned aerial vehicles comprise a main unmanned aerial vehicle and an auxiliary unmanned aerial vehicle;
the server is configured to:
acquiring a first image of a forest region calibration area acquired by a main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height;
when the fire condition of the calibration area is determined according to the first image, controlling a plurality of auxiliary unmanned aerial vehicles to the calibration area, enabling the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle to form a polygonal array to fly and to fly at a second height together, wherein the second height is lower than the first height;
acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at the second height respectively, wherein at least part of the second images acquired by the adjacent unmanned aerial vehicles are overlapped;
and determining the change trend information of the fire area and the fire center according to all the second images.
Further, the server is specifically configured to:
determining a fire area from the first image;
determining a minimum bounding rectangle of the fire zone;
determining vertex coordinates of each vertex of the minimum circumscribed rectangle, and controlling the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle to be located at positions corresponding to the vertex coordinates respectively.
Further, the server is further configured to:
before the auxiliary unmanned aerial vehicles reach the calibration area, controlling the main unmanned aerial vehicle to fly to at least three positions, and respectively obtaining positioning images at each position;
determining a preliminary coordinate of a fire center according to at least three positioning images;
and when the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle form an array to fly, controlling the flying array to take the position corresponding to the preliminary coordinate as the center.
Further, the server is specifically configured to:
according to the acquisition time sequence, splicing all the second images acquired by the main unmanned aerial vehicle and the auxiliary unmanned aerial vehicle corresponding to the calibration time point to obtain a plurality of continuous spliced images;
carrying out visual optimization processing on the spliced image;
and sequentially overlapping a plurality of continuous spliced images subjected to visual optimization treatment with background information to serve as the variation trend information of the ignition area and the fire center.
Further, the server is specifically configured to:
calling a remote sensing image corresponding to the calibration area as the background information, wherein the remote sensing image comprises two-dimensional reference coordinate information;
and superposing the spliced image and the remote sensing image according to the two-dimensional reference coordinate information and the two-dimensional coordinate information of the unmanned aerial vehicle.
Further, the server is specifically configured to:
calling a three-dimensional model corresponding to the calibration area, wherein the three-dimensional model comprises three-dimensional reference coordinate information;
and superposing the spliced image and the three-dimensional model according to the three-dimensional reference coordinate information, the two-dimensional coordinate information of at least three unmanned aerial vehicles and the second height.
Further, the three-dimensional model comprises geographic information and plant type information in the calibration area; the server is further specifically configured to:
predicting the trend of the fire according to the change trend information of the fire area and the fire center and the geographic information;
and generating early warning grades corresponding to all sub-areas in the calibration area according to the fire trend and the plant type information.
Further, the server is further configured to:
determining the fire center coordinates according to the spliced images;
and when the fire center coordinates and the coordinates corresponding to the unmanned aerial vehicles meet preset conditions, adjusting the positions of the plurality of unmanned aerial vehicles.
Further, the server is specifically configured to:
when the first distance is smaller than a second distance, wherein the first distance is the distance between a standard side of a polygon surrounded by the unmanned aerial vehicles and the coordinates of the fire center, and the second distance is 1/8-1/2 of the length of an adjacent side of the standard side; and controlling all the unmanned aerial vehicles to translate towards the direction of the calibration edge, and enabling the position corresponding to the fire center coordinate to be located at the center of a new polygon formed by all the translated unmanned aerial vehicles.
In a second aspect, the invention provides a forest fire monitoring method, which comprises the following steps:
acquiring a first image of a forest region calibration area acquired by a main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height;
when the fire condition of the calibration area is determined according to the first image, controlling a plurality of auxiliary unmanned aerial vehicles to the calibration area, enabling the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle to form a polygonal array to fly and to fly at a second height together, wherein the second height is lower than the first height;
acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at the second height respectively, wherein at least part of the second images acquired by the adjacent unmanned aerial vehicles are overlapped;
and determining the change trend information of the fire area and the fire center according to all the second images.
The forest fire monitoring system and the forest fire monitoring method have the advantages that the primary unmanned aerial vehicle is used for carrying out primary fire monitoring on a forest area with a large range at a high flying height, when the occurrence of fire is preliminarily determined through the acquired image of the primary unmanned aerial vehicle at the moment and the situation indicating that the fire is rapidly spread, such as dense smoke, strong wind and the like is accompanied, the server controls the plurality of secondary unmanned aerial vehicles to fly to the firing area, the secondary unmanned aerial vehicles and the primary unmanned aerial vehicle form a rectangular array together and reduce the flying height, the image acquired by the unmanned aerial vehicles is more accurate at the moment, the plurality of unmanned aerial vehicles can cover the firing area, the images acquired by the spliced unmanned aerial vehicles can ensure the comprehensiveness and accuracy of fire information, so that the firing range, the fire center and the variation trend thereof are accurately mastered, the influence of external environmental factors on fire scene information acquisition, analysis and judgment is reduced, and reasonable and targeted fire extinguishing work is conveniently carried out in time, to reduce the corresponding losses.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, a brief description will be given below to the drawings required for the description of the embodiments or the prior art, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without inventive exercise.
Fig. 1 is a block diagram of a forest fire monitoring system according to an embodiment of the present invention;
fig. 2 is a schematic diagram of an arrangement form of the unmanned aerial vehicles according to the embodiment of the present invention;
fig. 3 is a schematic diagram of an arrangement form of the unmanned aerial vehicles according to the embodiment of the present invention;
fig. 4 is a schematic flow chart of a forest fire monitoring method according to an embodiment of the present invention.
Detailed Description
The principles and features of this invention are described below in conjunction with the following drawings, which are set forth by way of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, the forest fire monitoring system according to the embodiment of the present invention includes a server and a plurality of drones, where the plurality of drones includes a primary drone and a secondary drone.
Specifically, the server can be located forest area monitoring center, and the server and the unmanned aerial vehicle all access to the network layer in order to carry out communication connection. An unmanned aerial vehicle is responsible for monitoring the condition of a fire in the forest in an area, if the forest area is great, can be divided into a plurality of areas with the forest, is responsible for respectively by different unmanned aerial vehicles and monitors. Because unmanned aerial vehicle duration is limited, can send another unmanned aerial vehicle to fly to its region after the unmanned aerial vehicle electric quantity of the previous one drops to a definite value, accomplish the work of handing over. Each unmanned aerial vehicle all disposes camera device to accomplish the image acquisition to the forest zone of monitoring, and each unmanned aerial vehicle is preferably four rotor unmanned aerial vehicles, can accomplish operations such as hover. The unmanned aerial vehicle is provided with a communication device, preferably a 5G communication device, and after the server and the unmanned aerial vehicle are connected to a network layer, high-definition view signals can be transmitted through a 5G network, so that the time delay is low, and first-hand data of a fire scene can be obtained in time.
In addition, the unmanned aerial vehicle can be further provided with a smoke detection device to determine the smoke condition of the fire area, and meanwhile, the unmanned aerial vehicle can be further provided with a wind speed detection device to determine the wind speed condition of the fire area, for example, when the smoke is too large and the wind speed is too large, the flight strategy of the unmanned aerial vehicle is adjusted, and therefore the influence of external environment factors on monitoring information is reduced.
The server is configured to:
and acquiring a first image of the forest region calibration area acquired by the main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height.
Specifically, the unmanned aerial vehicle responsible for monitoring and calibrating the forest fire in the area is the main unmanned aerial vehicle in the area, and the unmanned aerial vehicle configuration cost in the whole forest area is saved in order to ensure that the monitoring range is large enough, and the flying height is the first height, for example 500 meters, when the main unmanned aerial vehicle is in a state of performing conventional cruising on the forest area in which the main unmanned aerial vehicle is responsible. Make the image of gathering by main unmanned aerial vehicle this moment be first image, this first height can guarantee that the imaging range of first image is wider, also can guarantee that first image has certain definition.
When the fire condition of the calibration area is determined according to the first image, the auxiliary unmanned aerial vehicles are controlled to reach the calibration area, so that the auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle form a polygonal array to fly and fly at a second height together, wherein the second height is lower than the first height.
Specifically, if the forest zone calibration area takes place the condition of a fire, through the first image of this regional main unmanned aerial vehicle collection, carry out image comparison or infrared information and draw the back, can send out the early warning rapidly and tentatively confirm the central point of a fire position. At this moment, if a large amount of smoke is generated in a short time or the wind is strong, the fire situation cannot be accurately observed by the main unmanned aerial vehicle, the flight stability of the main unmanned aerial vehicle is influenced to influence the quality of the first image and the analysis data based on the first image, the factors may be signs or assistance force for rapidly spreading the fire, if the main unmanned aerial vehicle still only depends on the acquired image at the first height, the fire spreading trend may not be accurately judged, and delay is caused to corresponding fire extinguishing and disaster relief work. Therefore, the server can be used for collecting other unmanned aerial vehicles at the moment, the unmanned aerial vehicles are called as auxiliary unmanned aerial vehicles relative to the main unmanned aerial vehicle, rapidly fly to the forest area calibration area, and jointly form a rectangular array with the main unmanned aerial vehicle for flying, and the rectangular array and the main unmanned aerial vehicle are descended to a second height, such as 100 meters, and image acquisition is continuously carried out. Wherein, supplementary unmanned aerial vehicle can be for the reserve unmanned aerial vehicle that originally is located the surveillance center, also can be for being responsible for the unmanned aerial vehicle of other regional monitoring in forest zone. At this moment, on the one hand, because being closer to the fire point, the collection image is influenced by smog less, and the formation of image picture quality is higher, and on the other hand, unmanned aerial vehicle receives the influence of high air current will be less, all helps providing the collection image of higher quality for the server to confirm the region of catching fire and fire center and its trend of spreading more accurately.
And acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at the second height respectively, wherein at least part of the second images acquired by the adjacent unmanned aerial vehicles are overlapped.
Specifically, after descending to the second height, because single unmanned aerial vehicle's field of view scope reduces, through arranging of many unmanned aerial vehicles, not only can guarantee that the intensity of a fire central zone is located monitoring range all the time, still can guarantee that whole area of catching fire all is in monitoring range. This highly-collected image can be called the second image, and the second image that adjacent unmanned aerial vehicle gathered can have certain coincidence degree between, and in addition, for example in rectangular array, the second image that diagonal unmanned aerial vehicle gathered also can have certain coincidence degree to guarantee that all second images can carry out effective concatenation.
And determining the change trend information of the fire area and the fire center according to all the second images.
Specifically, all the second images are subjected to superposition and de-weighting operations, so that clear and accurate images including a fire center and the whole fire area can be obtained, and the unmanned aerial vehicle can perform continuous image acquisition, so that the change trends of the fire area and the fire center can be effectively judged, and more accurate reference information is provided for fire extinguishing and disaster relief work.
Correspondingly, the server can also be in communication connection with the management terminal of the forestry department in the province and the city where the forest area is located, and when a fire occurs or a certain stage occurs, the corresponding information is reported to the relevant management department.
In the embodiment, the primary fire monitoring is firstly carried out on a forest area with a larger range at a higher flying height through the main unmanned aerial vehicle, when the fire is preliminarily determined to occur through the acquired image of the main unmanned aerial vehicle at the moment and accompanied by the situation such as dense smoke, strong wind and the like indicating that the fire will spread rapidly, the server controls a plurality of auxiliary unmanned aerial vehicles to fly to the fire area, and the auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle jointly form a rectangular array and reduce the flying height, at the moment, the image acquired by the unmanned aerial vehicles is more accurate, and the plurality of unmanned aerial vehicles can cover the fire area, the comprehensiveness and accuracy of the fire information can be ensured by acquiring the images through the spliced unmanned aerial vehicles, so that the ignition range, the fire center and the variation trend thereof can be accurately mastered, the influence of external environmental factors on the fire scene information acquisition, analysis and research and judgment can be reduced, and the reasonable and targeted fire extinguishing work can be conveniently carried out in time, to reduce the corresponding losses.
Preferably, the server is specifically configured to, that is, the flying the plurality of secondary drones and the primary drone to form a polygonal array includes:
determining a fire area based on the first image.
In particular, infrared information may be extracted from the first image, from which the approximate extent of the fire zone may be determined, since the flame temperature is higher than the ambient temperature.
Determining a minimum bounding rectangle of the fire zone.
Specifically, as shown in fig. 2, since the ignition area is generally in an irregular pattern, whether a surface fire or a linear fire, by determining the minimum circumscribed rectangle of the ignition area at this time, the minimum circumscribed rectangle can not only cover the ignition area, but also cover the area which is possibly ignited subsequently, thereby being helpful for monitoring the fire behavior variation trend.
Determining vertex coordinates of each vertex of the minimum circumscribed rectangle, and controlling the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle to be located at positions corresponding to the vertex coordinates respectively.
Specifically, since the unmanned aerial vehicle is provided with navigation positioning data, the acquired image of the unmanned aerial vehicle also has corresponding information such as earth coordinates, the vertex coordinates of the minimum circumscribed rectangle can be determined, and the vertex coordinates are two-dimensional coordinates. And then controlling each unmanned aerial vehicle to be located at a second height position corresponding to the vertex coordinate. Because each unmanned aerial vehicle's shooting center is vertex coordinate corresponding position department, the regional sum that catches fire is greater than present in all unmanned aerial vehicle's the formation of image scope, and under unmanned aerial vehicle was in the condition of state of hovering, in the certain time, all areas that catch fire all were located unmanned aerial vehicle formation of image within the scope, help studying the trend of changing in the region of catching fire and fire center like this.
In the preferred embodiment, the detailed information of the fire condition can be accurately obtained, the condition of the whole fire area can be completely collected, and the study and judgment of the change trend of the fire area and the fire center are facilitated.
Preferably, the server is further configured to:
and before the auxiliary unmanned aerial vehicles reach the calibration area, controlling the main unmanned aerial vehicle to fly to at least three positions, and respectively obtaining positioning images at each position.
Specifically, a certain time may be required for other auxiliary unmanned aerial vehicles to fly to the forest region calibration area where the main unmanned aerial vehicle is located, and a certain imaging angle exists for the image shot in the air. In this period, because main unmanned aerial vehicle can hover above the ground fixed point, the server can confirm other positions that can improve the formation of image angle in order to obtain better quality image according to the first image of judging preliminary condition of a fire, makes main unmanned aerial vehicle fly to this other positions and continues to carry out the image shooting.
And determining the initial coordinates of the fire center according to at least three positioning images.
Specifically, after the acquisition images of the main unmanned aerial vehicle at the at least three positions are obtained, because the flight altitude at this stage is the first altitude all the time, the change of the two-dimensional coordinates of the at least three positions where the main unmanned aerial vehicle is located relative to the initial fire center is only realized, and based on the similar positioning principle of the GNSS global navigation satellite system for the ground object, the initial coordinates of the initial fire center can be determined more accurately through the acquisition images of the three positions and the self-contained navigation positioning data of the unmanned aerial vehicle.
And when the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle form an array to fly, controlling the flying array to take the position corresponding to the preliminary coordinate as the center.
Specifically, when many supplementary unmanned aerial vehicles fly to the forest zone calibration area and constitute for example the rectangle array with main unmanned aerial vehicle and fly, can make initial fire center be the rectangle center, follow-up collection image will use the fire center as the center like this, and not only collection image quality is higher, still can effectively cover the area of catching fire.
In this preferred embodiment, utilize and assist the unmanned aerial vehicle to fly to the time of forest zone calibration area, can more accurately confirm the preliminary coordinate of fire center through the collection image of main unmanned aerial vehicle in a plurality of positions, constitute for example the rectangle array at each unmanned aerial vehicle after, regard the rectangle center as the fire center, make like this and gather the image and use the fire center as the center, and can cover the area of catching fire, the quality of gathering the image is higher, can obtain more accurate change trend information at fire center.
Preferably, the server is specifically configured to, that is, the determining of the trend information of the fire area and the fire center from all the second images includes:
and according to the acquisition time sequence, splicing all the second images acquired by the main unmanned aerial vehicle and the auxiliary unmanned aerial vehicle respectively corresponding to the calibration time point to obtain a plurality of continuous spliced images.
Specifically, because the unmanned aerial vehicle can collect continuous images, each image has a corresponding collection time point, and second images collected by each unmanned aerial vehicle at the same time point can be spliced and deduplicated and are called as spliced images of each frame, and a plurality of frames of spliced images form continuous images.
And carrying out visual optimization processing on the spliced image.
Specifically, the visualization optimization processing refers to performing information extraction, addition and other operations on the stitched image, for example, since the ignition area and the fire center may be changed, after information such as the size of the ignition area and the coordinates of the fire center reflected by each frame of the stitched image is obtained according to a corresponding algorithm, a real-time ignition area and the change situation of the ignition area relative to the previous time point, and a real-time fire center coordinate and the change situation of the ignition center relative to the previous time point, for example, the real-time ignition area and the change situation of the ignition center relative to the previous time point move 20 meters to the east-south 30 degrees within 10 s.
And sequentially overlapping a plurality of continuous spliced images subjected to visual optimization treatment with background information to serve as the variation trend information of the ignition area and the fire center.
In particular, the background information may be a two-dimensional or three-dimensional image model of the entire forest area, which is typically fixed. After the dynamically-changed multi-frame spliced images are superposed on the background information, the relative position and the change condition of the fire area relative to the whole forest area can be obtained, and the relative position and the change condition are displayed through a large screen of the monitoring center, so that the method is favorable for more intuitively distinguishing and arranging the allocation mode, the route and the like of fire-fighting equipment.
In addition, the monitoring center is provided with a large screen connected with the server, a corresponding alarm device, an indicating device connected with the server in a remote communication mode and the like. For example, when an area is automatically researched and judged to be possibly ignited in a very short time, the alarm device in the monitoring center sends out a corresponding alarm signal to prompt relevant workers to pay attention to the fire prevention and control work of the area preferentially, and meanwhile, information including the change trend of the fire center, the next possible fire area, the optimal driving route for driving to the area and the like is sent to an indicating device of an on-site disaster relief action department, for example, an intelligent terminal at a fire station close to the fire point to guide the intelligent terminal to perform quick and effective fire extinguishing and relief actions. The server and the indicating device can also communicate based on a 5G network, so that the communication efficiency is improved.
In the preferred embodiment, the spliced images are subjected to visual optimization processing, so that the spliced images have more abundant information which is more favorable for studying and judging the change trend of fire, and after the dynamically-changed multi-frame spliced images are superposed on the background information, the information displayed in a monitoring center can be more intuitive, so that the arrangement of the allocation mode, the route and the like of fire fighting equipment is facilitated, and the efficient fire extinguishing and disaster relief work is carried out.
Preferably, the server is specifically configured to add background information to the consecutive multiple spliced images subjected to the visualization optimization processing in a sequentially stacked manner, and the information of the variation trend of the fire area and the fire center includes:
and calling a remote sensing image corresponding to the calibration area as the background information, wherein the remote sensing image comprises two-dimensional reference coordinate information.
Specifically, the server may be linked with a satellite remote sensing system to acquire a remote sensing image of the forest area through a satellite in advance, the remote sensing image having two-dimensional reference coordinate information whose orientation with respect to the ground actual scene is determined.
And superposing the spliced image and the remote sensing image according to the two-dimensional reference coordinate information and the two-dimensional coordinate information of the unmanned aerial vehicle.
Specifically, because the unmanned aerial vehicle also has two-dimensional coordinate information, the unmanned aerial vehicle can be superposed on the remote sensing image through the coordinate relation, and simultaneously, the processed spliced image and the relevant information reflecting the fire can also be superposed on the remote sensing image, so that the real-time fire situation can be displayed on the basis of the original forest remote sensing image, the real-time fire situation can be displayed in a mode of changing the color of a corresponding area on fire, and meanwhile, the change trend information of the fire center can be dynamically displayed by combining the change information of the fire area and the fire center and the like.
In the embodiment, based on the remote sensing image of the original forest, the dynamic multi-frame splicing images with the change information of the ignition area and the fire center are superposed to be presented together, so that the change trend information of the fire center is more visual, and the high-efficiency and accurate development of fire extinguishing and disaster relief work is facilitated.
Preferably, the server is specifically configured to add background information to the consecutive multiple spliced images subjected to the visualization optimization processing in a sequentially stacked manner, and the information of the variation trend of the fire area and the fire center includes:
and calling a three-dimensional model corresponding to the calibration area, wherein the three-dimensional model comprises three-dimensional reference coordinate information.
Specifically, the three-dimensional model may be constructed in advance based on a GIS geographic information system, and the three-dimensional model has three-dimensional coordinates based on a terrestrial coordinate system, so that it may be combined with actual geographic information of the forest.
And superposing the spliced image and the three-dimensional model according to the three-dimensional reference coordinate information, the two-dimensional coordinate information of at least three unmanned aerial vehicles and the second height.
Specifically, the two-dimensional coordinates of the unmanned aerial vehicle, that is, the vertex coordinates of the polygon are also based on the terrestrial coordinate system, and the relative relationship between the plurality of unmanned aerial vehicles can be used for correcting the relationship with the three-dimensional model. In addition, the unmanned aerial vehicle flies at the second height at the moment, and can be converted into the relative height in the three-dimensional model, so that the three-dimensional unmanned aerial vehicle model can be added on the three-dimensional model, the fire situation can be displayed on the basis of the original three-dimensional forest model, for example, the fire situation can be displayed by changing the color of the model elements, and meanwhile, the change trend information of the fire center can be dynamically displayed by combining the change information of the fire area, the fire center and the like.
In the preferred embodiment, based on a three-dimensional model such as a GIS model, a dynamic multi-frame splicing image with the change information of the ignition area and the fire center is presented together with the three-dimensional model in a three-dimensional element form, so that the change trend information of the fire center is more visual, and the fire extinguishing and relieving work can be efficiently and accurately carried out.
Preferably, the three-dimensional model comprises geographic information and plant type information within the calibration area; the server is further specifically configured to:
and predicting the trend of the fire according to the change trend information of the fire area and the fire center and the geographic information.
In particular, in a three-dimensional model, such as a GIS model, a forest may be divided into different sub-regions in advance. For forest regions, due to the fact that various plants are often planted, the regions where different plants are gathered can be regarded as a type of sub-regions, plant type information of the sub-regions can be preset, the plant type information comprises plant varieties, fire resistance degree of the varieties and other information, for example, if herbaceous plants with low water content are mainly arranged in a certain sub-region, the fire resistance degree of the herbaceous plants is low, and the advancing speed of fire in the region can be determined to be about 20 meters per minute according to past data experience. It should be noted that the plant type information may be updated according to seasonal changes, for example, winter grassland is more prone to rapid fire than summer grassland. In addition, as geographical factors such as rivers, water channels, basins and the like exist in the forest region, the factors can also be embodied in geographical information. For example, if the current spreading trend of the fire center determined by the images acquired by the unmanned aerial vehicle is in the south-bound direction, but a river exists in the south-bound direction and the southwest direction of the area, and a basin is arranged in the southeast direction, the vegetation density is higher, the possibility that the fire center is transferred to the southeast direction can be predicted, and fire prevention and extinguishing measures in the area can be distributed in advance.
And generating early warning grades corresponding to all sub-areas in the calibration area according to the fire trend and the plant type information.
Specifically, for example, if the fire center 10s moves 20 meters inward to the east-south 30 degrees, and the geographic information in the GIS model indicates that the area is a grassland area with a 45-degree direction of 1 kilometer, a river with an average width of 10 meters exists in the southwest direction of the area, the river opposite to the bank is a bush with a medium fire resistance, and a tree with a strongest fire resistance is located in the righteast direction of the area with a 2 kilometer, the early warning level of the area at the 1 kilometer position in the southeast 45 degrees direction of the east-south direction is the highest, the area can be marked as flickering purple in the GIS model, the area with a 2 kilometers in the righteast direction is the lowest, the area can be marked as flickering yellow in the GIS model, and other temporarily unharmed areas can remain unchanged. However, in the process of fire change, if the early warning levels in different areas change, the early warning levels can still be displayed in the GIS model in time.
Meanwhile, because the GIS model can also preset road network information, if a fire-fighting vehicle is adopted for fire extinguishment, an optimal running route can be generated, and on the premise that different types of fire-fighting vehicles can reach an ignition area in time, the safety degree of the running route is ensured as much as possible, for example, the area which cannot be safely passed due to large fire is avoided.
In the preferred embodiment, the three-dimensional model of GIS model and the image that gathers through unmanned aerial vehicle for example are combined, not only can carry out visual observation to current forest condition of a fire, still can predict the trend of the fire behavior according to information such as geography, vegetation of forest to confirm the risk of catching fire in different regions, thereby can arrange the accuse in advance to relevant region, help avoiding the fire behavior to enlarge and put out the forest fire in advance, further reduce the loss that the forest fire brought.
Preferably, the server is further configured to:
and determining the fire center coordinates according to the spliced image.
Specifically, in order to obtain a clearer and more accurate image, the unmanned aerial vehicle is mainly in a hovering state, although the spliced images of multiple unmanned aerial vehicles can cover a fire area and a part of peripheral areas, if the fire spreads quickly, the range of the current spliced image may not be enough to continuously cover a subsequent fire area. In order to accurately acquire the live-action image of the subsequent ignition area with fast fire spread, firstly, the fire center coordinates in the spliced image acquired when each unmanned aerial vehicle flies in a polygonal array are determined. The fire center can be the highest temperature point, namely the strongest infrared information, or can be determined in other ways.
And when the fire center coordinates and the coordinates corresponding to the unmanned aerial vehicles meet preset conditions, adjusting the positions of the plurality of unmanned aerial vehicles.
Specifically, as the fire spreads, the fire center changes, since when the area of fire is large, an effective image of the whole fire area may not be accurately monitored, and the change of the fire center may reflect the change trend of the fire to a great extent, for example, the area most likely to be ignited in the next stage, on the basis of which the fire-fighting arrangement for the area is performed in advance. If the images collected by the unmanned aerial vehicles at the current positions are about to meet the requirement of continuous monitoring of the fire center, the positions of the unmanned aerial vehicles can be adjusted to meet the requirement of observation continuity and effectiveness.
In this preferred embodiment, to the condition that the fire center changes along with the fire spreads and takes place fast, can guarantee to gather the image and splice the image and can effectively track the fire center through the position of adjustment unmanned aerial vehicle to sustainably provide the trend of change information at effectual fire center, help developing of whole fire prevention work of putting out a fire.
Preferably, the server is specifically configured to, that is, the adjusting the positions of the plurality of drones includes:
when the first distance is smaller than a second distance, wherein the first distance is the distance between a standard side of a polygon surrounded by the unmanned aerial vehicles and the coordinates of the fire center, and the second distance is 1/8-1/2 of the length of an adjacent side of the standard side; and controlling all the unmanned aerial vehicles to translate towards the direction of the calibration edge, and enabling the position corresponding to the fire center coordinate to be located at the center of a new polygon formed by all the translated unmanned aerial vehicles.
Specifically, as shown in fig. 2 and 3, if four drones are arranged in a rectangular shape, each at A, B, C, D, the preliminary fire center is approximately at O, but as the fire spreads and changes, the fire center moves continuously toward C. With this fire center at O ', all drones can be moved downward in the figure when the distance between O' H is less than the distance between CDs, e.g., 1/4. Similarly, when O' is less than 1/4 for the inter-BC distance from CD, all drones may be moved to the right in the figure. The movements in different directions may be performed simultaneously or separately. After the movement, the four unmanned aerial vehicles are respectively positioned at A ', B ', C ' and D ', and the center of the new rectangle is O '. In this way, the acquired images of the rearranged multiple unmanned aerial vehicles and the spliced images thereof can re-cover the fire center and leave enough margin for the potential advancing direction area. It should be noted that, as the change trend of the fire area and the fire center may be influenced by the change of the geographic information and the real-time weather condition, the change trend of the fire area and the fire center does not always face to one direction, but no matter how the change of the fire area and the fire center, the fire center can be ensured to be located in the imaging range of the unmanned aerial vehicle by the above-mentioned manner of adjusting the position of the unmanned aerial vehicle.
In this preferred embodiment, through the adjustment of unmanned aerial vehicle relative position, can guarantee that constantly changing catch fire region and fire center are located unmanned aerial vehicle's formation of image within range all the time, can provide the change trend information of catching fire region and fire center more accurately, help the arrangement of the work of putting out a fire and rescuing.
As shown in fig. 4, a forest fire monitoring method according to an embodiment of the present invention is based on the system, and includes the following steps:
the method comprises the steps of obtaining a first image of a forest zone calibration area collected by a main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height.
When the fire condition of the calibration area is determined according to the first image, the auxiliary unmanned aerial vehicles are controlled to reach the calibration area, so that the auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle form a polygonal array to fly and fly at a second height together, wherein the second height is lower than the first height.
And acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at the second height respectively, wherein at least part of the second images acquired by the adjacent unmanned aerial vehicles are overlapped.
And determining the change trend information of the fire area and the fire center according to all the second images.
The reader should understand that in the description of this specification, reference to the description of the terms "one embodiment," "some embodiments," "an example," "a specific example" or "some examples," etc., means that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction.
Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention, and that variations, modifications, substitutions and alterations can be made to the above embodiments by those of ordinary skill in the art within the scope of the present invention.
Claims (9)
1. A forest fire monitoring system is characterized by comprising a server and a plurality of unmanned aerial vehicles, wherein the unmanned aerial vehicles comprise a main unmanned aerial vehicle and an auxiliary unmanned aerial vehicle;
the server is configured to:
acquiring a first image of a forest region calibration area acquired by the main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height;
when the fire condition of the calibration area is determined according to the first image, controlling a plurality of auxiliary unmanned aerial vehicles to the calibration area, enabling the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle to form a polygonal array to fly and to fly at a second height together, wherein the second height is lower than the first height; before the auxiliary unmanned aerial vehicles reach the calibration area, controlling the main unmanned aerial vehicle to fly to at least three positions, and respectively obtaining positioning images at each position; determining a preliminary coordinate of a fire center according to at least three positioning images; when the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle form an array to fly, controlling a flying array to take the position corresponding to the preliminary coordinate as a center;
acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at the second height respectively, wherein at least part of the second images acquired by the adjacent unmanned aerial vehicles are overlapped;
and determining the change trend information of the fire area and the fire center according to all the second images.
2. The forest fire monitoring system of claim 1, wherein the server is specifically configured to:
determining a fire area from the first image;
determining a minimum bounding rectangle of the fire zone;
determining vertex coordinates of each vertex of the minimum circumscribed rectangle, and controlling the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle to be located at positions corresponding to the vertex coordinates respectively.
3. The forest fire monitoring system of claim 1 or 2, wherein the server is specifically configured to:
according to the acquisition time sequence, splicing all the second images acquired by the main unmanned aerial vehicle and the auxiliary unmanned aerial vehicle corresponding to the calibration time point to obtain a plurality of continuous spliced images;
carrying out visual optimization processing on the spliced image;
and sequentially overlapping a plurality of continuous spliced images subjected to visual optimization treatment with background information to serve as the variation trend information of the ignition area and the fire center.
4. The forest fire monitoring system of claim 3, wherein the server is specifically configured to:
calling a remote sensing image corresponding to the calibration area as the background information, wherein the remote sensing image comprises two-dimensional reference coordinate information;
and superposing the spliced image and the remote sensing image according to the two-dimensional reference coordinate information and the two-dimensional coordinate information of the unmanned aerial vehicle.
5. The forest fire monitoring system of claim 3, wherein the server is specifically configured to:
calling a three-dimensional model corresponding to the calibration area, wherein the three-dimensional model comprises three-dimensional reference coordinate information;
and superposing the spliced image and the three-dimensional model according to the three-dimensional reference coordinate information, the two-dimensional coordinate information of at least three unmanned aerial vehicles and the second height.
6. The forest fire monitoring system of claim 5, wherein the three-dimensional model includes geographic information and plant type information within the calibration area; the server is further specifically configured to:
predicting the trend of the fire according to the change trend information of the fire area and the fire center and the geographic information;
and generating early warning grades corresponding to all sub-areas in the calibration area according to the fire trend and the plant type information.
7. The forest fire monitoring system of claim 3, wherein the server is further configured to:
determining the fire center coordinates according to the spliced images;
when the fire center coordinates and the coordinates corresponding to the unmanned aerial vehicles meet preset conditions, the positions of the unmanned aerial vehicles are adjusted.
8. The forest fire monitoring system of claim 7, wherein the server is specifically configured to:
when the first distance is smaller than a second distance, wherein the first distance is the distance between a standard side of a polygon surrounded by the unmanned aerial vehicles and the coordinates of the fire center, and the second distance is 1/8-1/2 of the length of an adjacent side of the standard side; and controlling all the unmanned aerial vehicles to translate towards the direction of the calibration edge, and enabling the position corresponding to the fire center coordinate to be located at the center of a new polygon formed by all the translated unmanned aerial vehicles.
9. A forest fire monitoring method is characterized by comprising the following steps:
acquiring a first image of a forest region calibration area acquired by a main unmanned aerial vehicle, wherein the main unmanned aerial vehicle flies at a first height;
when the fire condition of the calibration area is determined according to the first image, controlling a plurality of auxiliary unmanned aerial vehicles to the calibration area, enabling the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle to form a polygonal array to fly and fly at a second height together, wherein the second height is lower than the first height; before the auxiliary unmanned aerial vehicles reach the calibration area, controlling the main unmanned aerial vehicle to fly to at least three positions, and respectively obtaining positioning images at each position; determining a preliminary coordinate of a fire center according to at least three positioning images; when the plurality of auxiliary unmanned aerial vehicles and the main unmanned aerial vehicle form an array to fly, controlling a flying array to take the position corresponding to the preliminary coordinate as a center;
acquiring a plurality of continuous second images acquired by the main unmanned aerial vehicle and each auxiliary unmanned aerial vehicle at the second height respectively, wherein at least part of the second images acquired by the adjacent unmanned aerial vehicles are overlapped;
and determining the change trend information of the fire area and the fire center according to all the second images.
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| CN113110579B (en) * | 2021-04-16 | 2021-12-14 | 深圳市艾赛克科技有限公司 | Unmanned aerial vehicle inspection method and device based on thermal radiation, unmanned aerial vehicle and storage medium |
| CN113947863A (en) * | 2021-10-13 | 2022-01-18 | 上海翼枭航空科技有限公司 | Remote control method and system for unmanned aerial vehicle |
| CN115689076B (en) * | 2022-08-23 | 2023-06-16 | 北京化工大学 | Forest fire rescue vehicle path optimization method loaded with fire extinguishing bomb |
| CN115779300A (en) * | 2022-11-30 | 2023-03-14 | 亿航智能设备（广州）有限公司 | Unmanned aerial vehicle fire extinguishing method, readable storage medium and electronic equipment |
| CN117036444A (en) * | 2023-10-08 | 2023-11-10 | 深圳市其域创新科技有限公司 | Three-dimensional model output method, device, equipment and computer readable storage medium |
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