Method, apparatus, device, and readable medium for identifying ignition points based on forest environment

Abstract

Embodiments of the present disclosure disclose a method, apparatus, device, and readable medium for identifying ignition points based on a forest environment. A specific implementation of the method includes: obtaining device information of an ignition point identification device corresponding to an alarm message; determining second elevation data corresponding to the alarm message according to device identification area information and first elevation data; determining relative direction information corresponding to the alarm message according to the device identification area information and the second elevation data; generating ignition point coordinate information according to the second elevation data and the relative direction information; obtaining a topographic profile model corresponding to the ignition point identification information; performing correction processing on the ignition point coordinate information according to the topographic profile model to generate corrected ignition point coordinate information; controlling an associated intelligent fire extinguishing device to perform fire extinguishing processing on the area corresponding to the corrected ignition point coordinate information. This implementation avoids incorrect fire extinguishing positions and reduces waste of forest resources.

Description

Technical Field

[0001] Embodiments of the present disclosure relate to the field of computer technology, and particularly to a method, apparatus, device, and readable medium for identifying ignition points based on a forest environment. Background Art

[0002] With the continuous development of image recognition technology, forest fire prevention work mainly uses image recognition technology to replace manual observation and inspection, and helps to improve the monitoring and response efficiency of forest fires through informatization means. Currently, when carrying out forest fire prevention warnings, the commonly used method is: using pre-set recognition devices to continuously obtain high-definition images and video data of the forest, and combining with image recognition technology to locate the fire point position and generate an alarm in the system.

[0003] However, it is found in practice that when using the above method for forest fire prevention warnings, there is often the following technical problem 1: When locating the fire point position through the images obtained by the recognition device, due to the fact that the forest terrain may not be a flat terrain, the determined ignition point position has a deviation, resulting in an incorrect fire extinguishing position and wasting forest resources.

[0004] In the process of adopting technical solutions to solve the above technical problem 1, there is often the following technical problem 2: When recognizing the collected images, environmental factors (such as smoke, dust, sunlight reflection) may be misjudged as a fire, resulting in the sending of false fire reports and wasting fire extinguishing resources. For these problems of the above technical problem 2, the conventional solution is generally: when detecting environmental factors such as smoke, obtain forest images again for recognition. However, the above conventional solution still has the following problems: When recognizing again, it takes time to obtain and recognize the images, and the fire situation may change, resulting in the waste of forest resources.

[0005] The above information disclosed in this background art section is only used to enhance the understanding of the background of the inventive concept, and thus, it may include information that does not form the prior art known to those of ordinary skill in the art in this country. Summary of the Invention

[0006] This content part of the present disclosure is used to briefly introduce concepts, which will be described in detail in the following detailed implementation part. This content part of the present disclosure is not intended to identify the key features or essential features of the claimed technical solution, nor is it intended to limit the scope of the claimed technical solution.

[0007] Some embodiments of the present disclosure propose a method, apparatus, electronic device, and computer-readable medium for identifying ignition points based on a forest environment to solve one or more of the technical problems mentioned in the above background art section.

[0008] In a first aspect, some embodiments of the present disclosure provide a method for identifying a fire ignition point based on a forest environment. The method includes: in response to receiving an alarm message sent by any fire ignition point identification device, obtaining the device information of the fire ignition point identification device corresponding to the alarm message, where the device information includes device identification area information and first elevation data; determining second elevation data corresponding to the alarm message according to the device identification area information and the first elevation data; determining relative direction information corresponding to the alarm message according to the device identification area information and the second elevation data; generating fire ignition point coordinate information according to the second elevation data and the relative direction information; obtaining a topographic profile model corresponding to the fire ignition point identification information; performing correction processing on the fire ignition point coordinate information according to the topographic profile model to generate corrected fire ignition point coordinate information; and controlling an associated intelligent fire extinguishing device to perform fire extinguishing processing on the area corresponding to the corrected fire ignition point coordinate information.

[0009] In a second aspect, some embodiments of the present disclosure provide a device for identifying a fire ignition point based on a forest environment. The device includes: a first acquisition unit configured to obtain the device information of the fire ignition point identification device corresponding to the alarm message in response to receiving an alarm message sent by any fire ignition point identification device, where the device information includes device identification area information and first elevation data; a first determination unit configured to determine second elevation data corresponding to the alarm message according to the device identification area information and the first elevation data; a second determination unit configured to determine relative direction information corresponding to the alarm message according to the device identification area information and the second elevation data; a generation unit configured to generate fire ignition point coordinate information according to the second elevation data and the relative direction information; a second acquisition unit configured to obtain a topographic profile model corresponding to the fire ignition point identification information; a correction unit configured to perform correction processing on the fire ignition point coordinate information according to the topographic profile model to generate corrected fire ignition point coordinate information; and a control unit configured to control an associated intelligent fire extinguishing device to perform fire extinguishing processing on the area corresponding to the corrected fire ignition point coordinate information.

[0010] In a third aspect, some embodiments of the present disclosure provide an electronic device, including: one or more processors; a storage device storing one or more programs thereon, and when the one or more programs are executed by the one or more processors, enabling the one or more processors to implement the method described in any implementation manner of the first aspect above.

[0011] In a fourth aspect, some embodiments of the present disclosure provide a computer-readable medium storing a computer program thereon, where the program, when executed by a processor, implements the method described in any implementation manner of the first aspect above.

[0012] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: Through the ignition point recognition method based on the forest environment in some embodiments of the present disclosure, the wrong fire extinguishing position is avoided, thereby reducing the waste of forest resources. Specifically, the reasons for the wrong fire extinguishing position and the waste of forest resources are as follows: When determining the fire point position through the image obtained by the recognition device, due to the fact that the forest terrain may not be a flat terrain, there is a deviation in the determined fire point position, resulting in the wrong fire extinguishing position and the waste of forest resources. Based on this, in some embodiments of the ignition point recognition method based on the forest environment of the present disclosure, first, in response to receiving the alarm information sent by any ignition point recognition device, the device information of the ignition point recognition device corresponding to the above alarm information is obtained. Thus, the information of the device where a fire may occur and an alarm may be issued can be determined. Secondly, according to the above device recognition area information and the above first elevation data, the second elevation data corresponding to the above alarm information is determined. Thus, the altitude of the device where the alarm is issued can be determined. Then, according to the above device recognition area information and the above second elevation data, the relative direction information corresponding to the above alarm information is determined. Thus, the relative direction between the fire point and the recognition device can be determined. After that, according to the above second elevation data and the above relative direction information, the fire point coordinate information is generated. Thus, the horizontal coordinates of the fire point can be determined. Then, a terrain profile model corresponding to the above fire point recognition information is obtained; according to the above terrain profile model, the above fire point coordinate information is corrected to generate corrected fire point coordinate information. Thus, the fire point coordinates can be corrected through the profile model, thereby avoiding the wrong fire extinguishing position and reducing the waste of forest resources. Finally, the associated intelligent fire extinguishing device is controlled to perform fire extinguishing treatment on the area corresponding to the above corrected fire point coordinate information. Thus, the fire extinguishing treatment of the fire point is completed, the wrong fire extinguishing position is avoided, and the waste of forest resources is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] In combination with the accompanying drawings and with reference to the following specific embodiments, the above and other features, advantages and aspects of the various embodiments of the present disclosure will become more obvious. Throughout the accompanying drawings, the same or similar reference numerals represent the same or similar elements. It should be understood that the drawings are schematic and the elements and elements are not necessarily drawn to scale.

[0014] Figure 1 is a flowchart of some embodiments of the ignition point recognition method based on the forest environment according to the present disclosure;

[0015] Figure 2 is a schematic structural diagram of some embodiments of the ignition point recognition device based on the forest environment according to the present disclosure;

[0016] Figure 3 is a schematic structural diagram of an electronic device suitable for implementing some embodiments of the present disclosure. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0017] Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. Although some embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure can be implemented in various forms and should not be construed as limited to the embodiments set forth herein. On the contrary, these embodiments are provided to more thoroughly and completely understand the present disclosure. It should be understood that the drawings and embodiments of the present disclosure are only for exemplary purposes and are not used to limit the protection scope of the present disclosure.

[0018] In addition, it should be noted that for ease of description, only parts related to the relevant invention are shown in the drawings. Without conflict, the embodiments in the present disclosure and the features in the embodiments can be combined with each other.

[0019] It should be noted that the concepts such as "first" and "second" mentioned in the present disclosure are only used to distinguish different devices, modules or units, and are not used to limit the order or mutual dependence relationship of the functions executed by these devices, modules or units.

[0020] It should be noted that the modification of "one" and "plural" mentioned in the present disclosure is illustrative rather than restrictive. Those skilled in the art should understand that unless clearly specified otherwise in the context, it should be understood as "one or more".

[0021] The names of the messages or information exchanged between multiple devices in the embodiments of the present disclosure are only for illustrative purposes and are not used to limit the scope of these messages or information.

[0022] The present disclosure will be described in detail below with reference to the drawings and in combination with embodiments.

[0023] Figure 1 Flow 100 of some embodiments of a fire point identification method based on a forest environment according to the present disclosure is shown. The fire point identification method based on the forest environment includes the following steps:

[0024] Step 101, in response to receiving alarm information sent by any fire point identification device, obtain the device information of the fire point identification device corresponding to the alarm information.

[0025] In some embodiments, the execution entity (such as a server) of the ignition point recognition method based on the forest environment can, in response to receiving the alarm information sent by any ignition point recognition device, obtain the device information of the ignition point recognition device corresponding to the above-mentioned alarm information. Among them, the above-mentioned ignition point recognition device can be an aerial video device. The above-mentioned device information includes device recognition area information and first elevation data. The above-mentioned device recognition area information can represent the range that the above-mentioned ignition point recognition device can recognize. The above-mentioned device recognition area information can be represented by longitude and latitude. The above-mentioned first elevation data can be the height of the position where the above-mentioned ignition point recognition device is installed or located from the ground. The above-mentioned aerial recognition device can observe a range of 360 degrees horizontally and greater than or equal to 90 degrees vertically. The above-mentioned aerial recognition device can also be an ignition point recognition unmanned aerial vehicle. The above-mentioned alarm information can be information used to represent that a fire has been recognized. The above-mentioned device information can be the device configuration information of the above-mentioned ignition point recognition device.

[0026] In practice, the above-mentioned alarm information can be generated through the following steps:

[0027] For each ignition point recognition device among the above-mentioned multiple ignition point recognition devices, perform the following control steps:

[0028] The first control step is to control the above-mentioned ignition point recognition device to collect the area video of the corresponding device recognition area in real time.

[0029] The second control step is to perform video frame extraction processing on the above-mentioned area video to generate an area video frame sequence. Among them, the above-mentioned video frame extraction processing can extract the above-mentioned area video through a key frame extraction algorithm.

[0030] The third control step is to input each area video frame in the above-mentioned area video frame sequence into a pre-trained ignition point recognition model to obtain an ignition point recognition result.

[0031] The fourth control step is to, in response to at least one ignition point recognition result among the obtained ignition point recognition results satisfying a first preset condition, determine the area video frame corresponding to the first ignition point recognition result satisfying the above-mentioned first preset condition as an ignition point image. Among them, the above-mentioned first preset condition can be that the ignition point recognition result indicates that the area video frame shows an open fire.

[0032] The fifth control step is to generate a fire alarm message and combine the above-mentioned fire alarm message and the above-mentioned ignition point image into an alarm message. Among them, the above-mentioned fire alarm message indicates that a fire has occurred.

[0033] Optionally, the above-mentioned ignition point recognition model can be trained through the following steps:

[0034] The first step is to obtain a sample set.

[0035] In some embodiments, the above-mentioned execution entity may obtain a sample set. Among them, the samples in the above-mentioned sample set include sample area video frames and the corresponding sample fire point recognition results of the above-mentioned sample area video frames.

[0036] The second step is to select samples from the above-mentioned sample set.

[0037] In some embodiments, the above-mentioned execution entity may select samples from the above-mentioned sample set. Here, the above-mentioned execution entity may randomly select samples from the above-mentioned sample set.

[0038] The third step is to input the above-mentioned samples into the initial network model to obtain the fire point recognition result corresponding to the above-mentioned samples.

[0039] In some embodiments, the above-mentioned execution entity may input the above-mentioned samples into the initial network model to obtain the fire point recognition result corresponding to the above-mentioned samples. Among them, the above-mentioned initial neural network may be a classification model capable of obtaining a fire point recognition result according to the area video frame.

[0040] The fourth step is to determine the loss value between the above-mentioned fire point recognition result and the sample fire point recognition result included in the above-mentioned sample.

[0041] In some embodiments, the above-mentioned execution entity may determine the loss value between the above-mentioned fire point recognition result and the sample fire point recognition result included in the above-mentioned sample. In practice, the loss value between the above-mentioned fire point recognition result and the sample fire point recognition result included in the above-mentioned sample may be determined based on a preset loss function. For example, the above-mentioned preset loss function may be a cross-entropy loss function.

[0042] The fifth step is to adjust the network parameters of the above-mentioned initial network model in response to the above-mentioned loss value being greater than or equal to a preset threshold.

[0043] In some embodiments, the above-mentioned execution entity may adjust the network parameters of the above-mentioned initial network model in response to the above-mentioned loss value being greater than or equal to a preset threshold. Here, there is no limitation on the setting of the preset threshold. For example, the difference between the loss value and the preset threshold may be calculated to obtain a loss difference. On this basis, methods such as backpropagation and stochastic gradient descent are used to transfer the error value forward from the last layer of the model to adjust the parameters of each layer. Of course, according to needs, the method of network freezing (dropout) may also be adopted to keep the network parameters of some layers unchanged and not adjust them. There is no limitation on this.

[0044] Optionally, in response to the above-mentioned loss value being less than the above-mentioned preset threshold, the above-mentioned initial network model is determined as a fire point recognition model.

[0045] In some embodiments, the above-mentioned execution entity may determine the initial network model as the ignition point recognition model in response to the above-mentioned loss value being less than the above-mentioned preset threshold.

[0046] Step 102: Determine the second elevation data corresponding to the alarm information according to the device identification area information and the first elevation data.

[0047] In some embodiments, the above-mentioned execution entity may determine the second elevation data corresponding to the alarm information according to the above-mentioned device identification area information and the above-mentioned first elevation data.

[0048] In practice, the second elevation data can be determined through the following steps:

[0049] The first step: Perform parsing processing on the above-mentioned device identification area information to generate parsing information. In practice, the above-mentioned parsing processing may be to parse each field name and the corresponding field value included in the above-mentioned device identification area information to generate multiple fields as parsing information.

[0050] The second step: Determine the altitude information corresponding to the above-mentioned ignition point recognition device according to the above-mentioned parsing information. In practice, the altitude corresponding to the longitude and latitude where the above-mentioned ignition point recognition device is located can be determined through the longitude and latitude included in the above-mentioned parsing information.

[0051] The third step: Determine the sum of the above-mentioned altitude information and the above-mentioned first elevation data as the second elevation data.

[0052] Step 103: Determine the relative direction information corresponding to the alarm information according to the device identification area information and the second elevation data.

[0053] In some embodiments, the above-mentioned execution entity may determine the relative direction information corresponding to the alarm information according to the above-mentioned device identification area information and the above-mentioned second elevation data. In practice, first, the included angle between the pitch angle of the ignition point recognition device included in the above-mentioned device identification area information and the horizontal ground can be determined. Second, according to the above-mentioned included angle, the relative direction between the ignition point corresponding to the above-mentioned alarm information and the above-mentioned ignition point recognition device can be determined.

[0054] Step 104: Generate the ignition point coordinate information according to the second elevation data and the relative direction information.

[0055] In some embodiments, the above-mentioned execution entity may generate the ignition point coordinate information according to the above-mentioned second elevation data and the above-mentioned relative direction information.

[0056] In practice, the above-mentioned execution entity may generate the ignition point recognition information through the following steps:

[0057] First step: Determine the pitch angle value corresponding to the ignition point recognition device according to the above device recognition area information. Among them, the above pitch angle value can be the angle between the shooting direction of the ignition point recognition device and the horizontal direction.

[0058] Second step: Determine the above angle range value according to the above pitch angle value. In practice, the sum and difference between the above pitch angle value and a preset angle value can be determined as the maximum and minimum values of the recognition range corresponding to the ignition point recognition device, and the angle range value can be determined according to the above maximum value and the above minimum value.

[0059] Third step: Obtain the ignition point image sent by the above ignition point recognition device. Among them, the above ignition point image can be the image used to represent the ignition point included in the alarm information sent by the ignition point recognition device.

[0060] Fourth step: Determine the horizontal angle value of the ignition point according to the position of the ignition point shown in the above ignition point image in the above ignition point image and the above angle range value. Among them, the above horizontal angle value of the ignition point is the acute angle value between the connection line between the ignition point and the above ignition point recognition device and the horizontal ground.

[0061] Fifth step: Determine the ignition point coordinate information corresponding to the above ignition point according to the above horizontal angle value of the ignition point.

[0062] Step 105: Obtain the terrain profile model corresponding to the ignition point recognition information.

[0063] In some embodiments, the above execution subject can obtain the terrain profile model corresponding to the above ignition point recognition information. Among them, the above terrain profile model can be the profile model of the area corresponding to the above device recognition area information in the pre-generated forest model.

[0064] Step 106: Perform correction processing on the ignition point coordinate information according to the terrain profile model to generate corrected ignition point coordinate information.

[0065] In some embodiments, the above execution subject can perform correction processing on the above ignition point coordinate information according to the above terrain profile model to generate corrected ignition point coordinate information.

[0066] In practice, the corrected ignition point coordinate information can be generated through the following steps:

[0067] In response to the received alarm information being greater than or equal to the preset information quantity, execute the following correction steps:

[0068] First correction step: Determine the ignition point coordinate information corresponding to each alarm information received as the target coordinate information to obtain a set of target coordinate information.

[0069] The second correction step is to determine the coordinate distance between each piece of target coordinate information in the above-mentioned set of target coordinate information and the above-mentioned coordinates of the ignition point. In practice, first, a rectangular coordinate system can be established with the coordinates corresponding to the above-mentioned coordinates of the ignition point as the origin. Second, according to the coordinates of the target coordinate information in the above-mentioned rectangular coordinate system, the distance between the target coordinate information and the above-mentioned coordinates of the ignition point is determined as the coordinate distance.

[0070] The third correction step is to determine the above-mentioned coordinates of the ignition point as the corrected coordinates of the ignition point in response to each determined coordinate distance being less than or equal to a preset coordinate distance. Among them, the above-mentioned preset coordinate distance can be the distance between the preset target coordinate information and the coordinates of the ignition point. For example, the above-mentioned preset coordinate distance can be 100m.

[0071] The fourth correction step is to perform clustering processing on each piece of target coordinate information in the above-mentioned set of target coordinate information in response to there being a coordinate distance greater than the above-mentioned preset coordinate distance among the determined coordinate distances, so as to generate a first coordinate information group and a second coordinate information group. Among them, the above-mentioned clustering processing can be to cluster the regional video frames corresponding to the above-mentioned target coordinate information according to the displayed content. Here, the target coordinate information corresponding to the regional video frame showing an open fire can be determined as the first coordinate information, and the target coordinate information corresponding to the regional video frame showing only smoke can be determined as the second coordinate information.

[0072] Optionally, after the fourth correction step, the following steps are further included:

[0073] The fifth correction step is to perform the following recognition steps for each piece of second coordinate information in the above-mentioned second coordinate information group:

[0074] The first recognition step is to collect the smoke reflectance value of the coordinates represented by the above-mentioned second coordinate information.

[0075] The second recognition step is to obtain a group of normalized smoke recognition ranges, and select the normalized smoke recognition range corresponding to the above-mentioned smoke reflectance value from the above-mentioned group of normalized smoke recognition ranges as the target recognition range.

[0076] The third recognition step is to determine the type of smoke concentration corresponding to the above-mentioned smoke reflectance value according to the above-mentioned target recognition range.

[0077] The fourth recognition step is to input the above-mentioned second coordinate information into a pre-trained smoke background recognition model to obtain a recognition result.

[0078] The fifth recognition step is to generate a predicted fire severity value according to the background type represented by the above-mentioned recognition result and the above-mentioned type of smoke concentration.

[0079] The sixth correction step: According to the generated predicted fire severity values and the above fire origin coordinate system, correct the above fire origin coordinate information to generate corrected fire origin coordinate information.

[0080] The seventh correction step: In response to the coordinate distances corresponding to each of the first coordinate information in the above first coordinate information group being less than or equal to the above preset coordinate distance, determine the above fire origin coordinate information as the corrected fire origin coordinate information.

[0081] The eighth correction step: In response to there being a coordinate distance greater than the above preset coordinate distance among the coordinate distances corresponding to each of the first coordinate information in the above first coordinate information group, establish a fire origin coordinate system based on the first coordinate information group and the above fire origin coordinate information.

[0082] The ninth correction step: According to the above fire origin coordinate system, perform a prediction process on the fire origin to obtain predicted fire origin coordinate information. In practice, the central position of each coordinate corresponding to each of the first coordinate information can be determined as the predicted fire origin coordinate information.

[0083] The tenth correction step: Determine the above predicted fire origin coordinate information as the corrected fire origin coordinate information.

[0084] The above first correction step - eighth correction step, as an inventive point of the embodiments of the present disclosure, solves the second technical problem mentioned in the background art, that is, "when recognizing the collected images, environmental factors (such as smoke, dust, sunlight reflection) may be misjudged as a fire, resulting in sending an incorrect fire report and wasting fire extinguishing resources." The reasons for sending an incorrect fire report and wasting fire extinguishing resources are as follows: when recognizing the collected images, environmental factors (such as smoke, dust, sunlight reflection) may be misjudged as a fire, resulting in sending an incorrect fire report and wasting fire extinguishing resources. If the above factors are solved, the effect of avoiding sending an incorrect fire report and reducing the waste of fire extinguishing resources can be achieved. To achieve this effect, the present disclosure first determines the ignition point coordinate information corresponding to each alarm information in the received various alarm information as the target coordinate information, and obtains a set of target coordinate information. Thus, the coordinates of the ignition points recognized by multiple devices can be determined. Second, for each target coordinate information in the above set of target coordinate information, the coordinate distance between the above target coordinate information and the above ignition point coordinate information is determined. Thus, it can be determined whether each detected ignition point is around the ignition point coordinate information. Third, in response to each determined coordinate distance being less than or equal to a preset coordinate distance, the above ignition point coordinate information is determined as the corrected ignition point coordinate information; in response to there being a coordinate distance greater than the above preset coordinate distance among the determined coordinate distances, clustering processing is performed on each target coordinate information in the above set of target coordinate information to generate a first coordinate information group and a second coordinate information group. Thus, the open fire and smoke captured can be distinguished. Fourth, in response to each coordinate distance corresponding to each first coordinate information in the above first coordinate information group being less than or equal to the above preset coordinate distance, the above ignition point coordinate information is determined as the corrected ignition point coordinate information; in response to there being a coordinate distance greater than the above preset coordinate distance among the coordinate distances corresponding to each first coordinate information in the above first coordinate information group, an ignition point coordinate system is established based on the first coordinate information group and the above ignition point coordinate information. Thus, the coordinates of each open fire and the position of the ignition point coordinate in the coordinate system can be determined. Fifth, for each second coordinate information in the above second coordinate information group, the following recognition steps are performed: First, collect the smoke reflectance value of the coordinate represented by the above second coordinate information. Thus, the light reflectance of the smoke at each coordinate can be determined. Second, obtain a set of normalized smoke recognition ranges, and select from the above set of normalized smoke recognition ranges the normalized smoke recognition range corresponding to the above smoke reflectance value as the target recognition range; based on the above target recognition range, determine the type of smoke concentration corresponding to the above smoke reflectance value. Thus, the type of smoke concentration can be determined. Then, input the above second coordinate information into a pre-trained smoke background recognition model to obtain a recognition result; based on the background type represented by the above recognition result and the above type of smoke concentration, generate a predicted fire intensity value.Thus, the fire situation can be predicted to determine the location of the ignition point. Sixth, based on the generated predicted fire severity values and the above-mentioned ignition point coordinate system, the above-mentioned ignition point coordinate information is corrected to generate corrected ignition point coordinate information; in response to the coordinate distances corresponding to each of the first coordinate information in the above-mentioned first coordinate information group being less than or equal to the above-mentioned preset coordinate distance, the above-mentioned ignition point coordinate information is determined as the corrected ignition point coordinate information; in response to there being a coordinate distance greater than the above-mentioned preset coordinate distance among the coordinate distances corresponding to each of the first coordinate information in the above-mentioned first coordinate information group, an ignition point coordinate system is established based on the first coordinate information group and the above-mentioned ignition point coordinate information; based on the above-mentioned ignition point coordinate system, prediction processing is performed on the ignition point to obtain predicted ignition point coordinate information; the above-mentioned predicted ignition point coordinate information is determined as the corrected ignition point coordinate information. Thus, the correction of the ignition point location is completed, avoiding the sending of incorrect fire reports and reducing the waste of fire extinguishing resources.

[0085] Step 107: Control the associated intelligent fire extinguishing equipment to perform fire extinguishing on the area corresponding to the corrected ignition point coordinate information.

[0086] In some embodiments, the above-mentioned execution entity may control the associated intelligent fire extinguishing equipment to perform fire extinguishing on the area corresponding to the above-mentioned corrected ignition point coordinate information. Among them, the above-mentioned associated intelligent fire extinguishing equipment may be a fire extinguishing equipment connected to the above-mentioned execution entity by wire or wirelessly. For example, the above-mentioned intelligent fire extinguishing equipment may be a drone carrying fire extinguishing materials.

[0087] The above-mentioned various embodiments of the present disclosure have the following beneficial effects: Through the ignition point recognition method based on the forest environment in some embodiments of the present disclosure, the wrong fire extinguishing position is avoided, thereby reducing the waste of forest resources. Specifically, the reasons for the wrong fire extinguishing position and the waste of forest resources are as follows: When the fire point position is located through the image obtained by the recognition device, due to the fact that the forest terrain may not be a horizontal terrain, there is a deviation in the determined fire point position, resulting in a wrong fire extinguishing position and a waste of forest resources. Based on this, in some embodiments of the present disclosure, the ignition point recognition method based on the forest environment, first, in response to receiving the alarm information sent by any ignition point recognition device, obtain the device information of the ignition point recognition device corresponding to the above-mentioned alarm information. Thus, the information of the device where a fire may occur and an alarm can be determined. Secondly, according to the above-mentioned device recognition area information and the above-mentioned first elevation data, determine the second elevation data corresponding to the above-mentioned alarm information. Thus, the altitude of the device where the alarm is issued can be determined. Then, according to the above-mentioned device recognition area information and the above-mentioned second elevation data, determine the relative direction information corresponding to the above-mentioned alarm information. Thus, the relative direction between the fire point and the recognition device can be determined. After that, according to the above-mentioned second elevation data and the above-mentioned relative direction information, generate the fire point coordinate information. Thus, the horizontal coordinates of the fire point can be determined. Then, obtain the terrain profile model corresponding to the above-mentioned fire point recognition information; according to the above-mentioned terrain profile model, perform correction processing on the above-mentioned fire point coordinate information to generate corrected fire point coordinate information. Thus, the fire point coordinates can be corrected through the profile model, thereby avoiding the wrong fire extinguishing position and reducing the waste of forest resources. Finally, control the associated intelligent fire extinguishing device to perform fire extinguishing processing on the area corresponding to the above-mentioned corrected fire point coordinate information. Thus, the fire extinguishing processing of the fire point is completed, the wrong fire extinguishing position is avoided, and the waste of forest resources is reduced.

[0088] Further referring to Figure 2 , as an implementation of the methods shown in the above figures, the present disclosure provides some embodiments of an ignition point recognition device based on the forest environment. These device embodiments correspond to Figure 1 the method embodiments shown, and the ignition point recognition device based on the forest environment can be specifically applied to various electronic devices.

[0089] Such as Figure 2As shown in the figure, the ignition point recognition device 200 based on the forest environment in some embodiments includes: a first acquisition unit 201, a first determination unit 202, a second determination unit 203, a generation unit 204, a second acquisition unit 205, a correction unit 206, and a control unit 207. Among them, the first acquisition unit 201 is configured to, in response to receiving the alarm information sent by any ignition point recognition device, acquire the device information of the ignition point recognition device corresponding to the above alarm information, where the above device information includes device identification area information and first elevation data; the first determination unit 202 is configured to determine the second elevation data corresponding to the above alarm information according to the above device identification area information and the above first elevation data; the second determination unit 203 is configured to determine the relative direction information corresponding to the above alarm information according to the above device identification area information and the above second elevation data; the generation unit 204 is configured to generate ignition point coordinate information according to the above second elevation data and the above relative direction information; the second acquisition unit 205 is configured to acquire the terrain profile model corresponding to the above ignition point recognition information; the correction unit 206 is configured to perform correction processing on the above ignition point coordinate information according to the above terrain profile model to generate corrected ignition point coordinate information; the control unit 207 is configured to control the associated intelligent fire extinguishing device to perform fire extinguishing processing on the area corresponding to the above corrected ignition point coordinate information.

[0090] It can be understood that the various units described in the ignition point recognition device 200 based on the forest environment correspond to the respective steps in the method described in the reference Figure 1 Therefore, the operations, features, and beneficial effects described above for the method also apply to the ignition point recognition device 200 based on the forest environment and the units included therein, and will not be elaborated here.

[0091] Next, refer to Figure 3 , which shows a schematic structural diagram of an electronic device 300 suitable for implementing some embodiments of the present disclosure. The electronic devices in some embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, laptop computers, digital broadcast receivers, PDAs (Personal Digital Assistants), PADs (Tablet Computers), PMPs (Portable Multimedia Players), vehicle terminals (such as vehicle navigation terminals), etc., and fixed terminals such as digital TVs, desktop computers, etc. Figure 3 The electronic device shown is only an example and should not impose any limitations on the functions and usage scopes of the embodiments of the present disclosure.

[0092] As Figure 3As shown, the electronic device 300 may include a processing device 301 (such as a central processing unit, a graphics processing unit, etc.), which may perform various appropriate actions and processes according to a program stored in the read-only memory (ROM) 302 or a program loaded from the storage device 308 into the random access memory (RAM) 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 are also stored. The processing device 301, the ROM 302, and the RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0093] Generally, the following devices may be connected to the I / O interface 305: an input device 306 including, for example, a touch screen, a touchpad, a keyboard, a mouse, a camera, a microphone, an accelerometer, a gyroscope, etc.; an output device 307 including, for example, a liquid crystal display (LCD), a speaker, a vibrator, etc.; a storage device 308 including, for example, a magnetic tape, a hard disk, etc.; and a communication device 309. The communication device 309 may allow the electronic device 300 to communicate with other devices wirelessly or wiredly to exchange data. Although Figure 3 the electronic device 300 with various devices is shown, it should be understood that it is not required to implement or have all the shown devices. Instead, more or fewer devices may be implemented or had. Figure 3 Each block shown in may represent a device or, as needed, multiple devices.

[0094] In particular, according to some embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, some embodiments of the present disclosure include a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program contains program codes for performing the methods shown in the flowcharts. In such some embodiments, the computer program may be downloaded and installed from the network through the communication device 309, or installed from the storage device 308, or installed from the ROM 302. When the computer program is executed by the processing device 301, the above-mentioned functions defined in the methods of some embodiments of the present disclosure are executed.

[0095] It should be noted that the computer-readable media described in some embodiments of the present disclosure may be a computer-readable signal medium, a computer-readable storage medium, or any combination of the two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In some embodiments of the present disclosure, the computer-readable storage medium may be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In some embodiments of the present disclosure, the computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium may also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable signal medium may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (radio frequency), etc., or any suitable combination of the above.

[0096] In some embodiments, the client and the server can communicate using any currently known or future-developed network protocol such as HTTP (HyperText Transfer Protocol), and can be interconnected with digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include local area networks ("LAN"), wide area networks ("WAN"), the Internet (e.g., the Internet), and end-to-end networks (e.g., ad hoc end-to-end networks), as well as any currently known or future-developed network.

[0097] The above computer-readable medium may be included in the above electronic device; or it may exist separately and not be assembled into the electronic device. The above computer-readable medium carries one or more programs. When the above one or more programs are executed by the electronic device, the electronic device is caused to: in response to receiving an alarm message sent by any ignition point identification device, obtain the device information of the ignition point identification device corresponding to the alarm message, where the above device information includes device identification area information and first elevation data. Determine the second elevation data corresponding to the alarm message according to the above device identification area information and the above first elevation data. Determine the relative direction information corresponding to the alarm message according to the above device identification area information and the above second elevation data. Generate ignition point coordinate information according to the above second elevation data and the above relative direction information. Obtain the terrain profile model corresponding to the above ignition point identification information. Perform correction processing on the above ignition point coordinate information according to the above terrain profile model to generate corrected ignition point coordinate information. Control the associated intelligent fire extinguishing device to perform fire extinguishing processing on the area corresponding to the above corrected ignition point coordinate information.

[0098] Computer program code for performing the operations of some embodiments of the present disclosure may be written in one or more programming languages or combinations thereof. The above programming languages include object-oriented programming languages - such as Java, Smalltalk, C++; and also include conventional procedural programming languages - such as the "C" language or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network - including a local area network (LAN) or a wide area network (WAN) - or may be connected to an external computer (for example, by using an Internet service provider to connect through the Internet).

[0099] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architectures, functions, and operations of systems, methods, and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagram may represent a module, a segment of a program, or a part of code that contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than that marked in the accompanying drawings. For example, two consecutive blocks shown may actually be executed substantially in parallel, and they may sometimes be executed in the reverse order, depending on the functions involved. It should also be noted that each block in the block diagram and / or flowchart, as well as combinations of blocks in the block diagram and / or flowchart, can be implemented by a dedicated hardware-based system that performs the specified functions or operations, or can be implemented by a combination of dedicated hardware and computer instructions.

[0100] The units described in some embodiments of the present disclosure can be implemented in software or in hardware. The described units can also be provided in a processor. For example, it can be described as: a processor includes a first acquisition unit, a first determination unit, a second determination unit, a generation unit, a second acquisition unit, a correction unit, and a control unit. Among them, the names of these units do not constitute a limitation on the unit itself in some cases. For example, the control unit can also be described as "a unit that controls the associated intelligent fire extinguishing device to perform fire extinguishing treatment on the area corresponding to the corrected ignition point coordinate information".

[0101] The functions described above can be performed at least in part by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that can be used include: Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), Systems on Chip (SOCs), Complex Programmable Logic Devices (CPLDs), and so on.

[0102] The above description is only some preferred embodiments of the present disclosure and an explanation of the technical principles applied. Those skilled in the art should understand that the scope of the invention involved in the embodiments of the present disclosure is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the above inventive concept. For example, technical solutions formed by mutually replacing the above features with technical features (but not limited to) having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method for identifying ignition points based on a forest environment, which is applied to an ignition point identification system, wherein, The ignition point recognition system includes multiple ignition point recognition devices, and the method includes: In response to receiving the alarm information sent by any one of the ignition point recognition devices, obtain the device information of the ignition point recognition device corresponding to the alarm information, where the device information includes device recognition area information and first elevation data, the device recognition area information is used to characterize the range that the ignition point recognition device can recognize, represented by longitude and latitude, and the first elevation data is the height of the position where the ignition point recognition device is installed or located from the ground; According to the device recognition area information and the first elevation data, determine the second elevation data corresponding to the alarm information, where the second elevation data is the altitude of the ignition point recognition device; Among them, the determining the second elevation data corresponding to the alarm information according to the device recognition area information and the first elevation data includes: Perform parsing processing on the device recognition area information to generate parsing information; According to the parsing information, determine the altitude information corresponding to the ignition point recognition device; Determine the sum of the altitude information and the first elevation data as the second elevation data; According to the device recognition area information and the second elevation data, determine the relative direction information corresponding to the alarm information; Generate ignition point coordinate information according to the second elevation data and the relative direction information; Among them, the generating ignition point coordinate information according to the second elevation data and the relative direction information includes: According to the device recognition area information, determine the pitch angle value corresponding to the ignition point recognition device; According to the pitch angle value, determine the angle range value; Obtain the ignition point image sent by the ignition point recognition device; According to the position of the ignition point shown in the ignition point image and the angle range value, determine the ignition point horizontal angle value, where the ignition point horizontal angle value is the acute angle between the line connecting the ignition point and the ignition point recognition device and the horizontal ground; According to the ignition point horizontal angle value, determine the ignition point coordinate information corresponding to the ignition point; Obtain the terrain profile model corresponding to the ignition point recognition information; According to the terrain profile model, perform correction processing on the ignition point coordinate information to generate corrected ignition point coordinate information; Control the associated intelligent fire extinguishing device to perform fire extinguishing on the area corresponding to the corrected ignition point coordinate information.

2. The method according to claim 1, wherein The performing correction processing on the ignition point coordinate information according to the terrain profile model to generate corrected ignition point coordinate information includes: In response to the received alarm information being greater than or equal to the preset information quantity, perform the following correction steps: Determine the ignition point coordinate information corresponding to each alarm information in the received alarm information as the target coordinate information to obtain a set of target coordinate information; For each target coordinate information in the set of target coordinate information, determine the coordinate distance between the target coordinate information and the ignition point coordinate information; In response to determining that each of the identified coordinate distances is less than or equal to a preset coordinate distance, determine the fire point coordinate information as the corrected fire point coordinate information; In response to determining that there is a coordinate distance greater than the preset coordinate distance among the identified coordinate distances, perform clustering processing on each target coordinate information in the target coordinate information set to generate a first coordinate information group and a second coordinate information group, where the first coordinate information in the first coordinate information group is the target coordinate information corresponding to the region video frame with visible open flames, and the second coordinate information in the second coordinate information group is the target coordinate information corresponding to the region video frame with only visible smoke; For each second coordinate information in the second coordinate information group, perform the following identification steps: Collect the smoke reflectance value of the coordinate represented by the second coordinate information; Obtain a normalized smoke recognition range group, and select, from the normalized smoke recognition range group, the normalized smoke recognition range corresponding to the smoke reflectance value as the target recognition range; Determine the smoke concentration type corresponding to the smoke reflectance value according to the target recognition range; Input the second coordinate information into a pre-trained smoke background recognition model to obtain an identification result; Generate a predicted fire severity value according to the background type represented by the identification result and the smoke concentration type; Perform correction processing on the fire point coordinate information according to the generated predicted fire severity values and the fire point coordinate system to generate corrected fire point coordinate information; In response to determining that each coordinate distance corresponding to the first coordinate information in the first coordinate information group is less than or equal to the preset coordinate distance, determine the fire point coordinate information as the corrected fire point coordinate information; In response to determining that there is a coordinate distance greater than the preset coordinate distance among the coordinate distances corresponding to the first coordinate information in the first coordinate information group, establish a fire point coordinate system according to the first coordinate information group and the fire point coordinate information; Perform prediction processing on the fire point according to the fire point coordinate system to obtain predicted fire point coordinate information; Determine the predicted fire point coordinate information as the corrected fire point coordinate information.

3. The method according to claim 1, wherein, The warning information is generated through the following steps: For each fire point identification device among the multiple fire point identification devices, perform the following control steps: Control the fire point identification device to collect the regional video of the corresponding device identification area in real time; Perform video frame extraction processing on the regional video to generate a regional video frame sequence; For each regional video frame in the regional video frame sequence, input the regional video frame into a pre-trained fire point identification model to obtain a fire point identification result; In response to determining that there is at least one fire point identification result that satisfies a first preset condition among the obtained fire point identification results, determine the first fire point identification result that satisfies the first preset condition as the fire point image; Generate a fire warning information, and combine the fire warning information and the fire point image into warning information.

4. The method according to claim 3, wherein The fire point identification model is trained through the following steps: Obtain a sample set, where the samples in the sample set include sample area video frames and corresponding sample fire point recognition results for the sample area video frames; Select a sample from the sample set; Input the sample into an initial network model to obtain a fire point recognition result corresponding to the sample; Determine a loss value between the fire point recognition result corresponding to the sample and the sample fire point recognition result included in the sample; In response to the loss value being greater than or equal to a preset threshold, adjust the network parameters of the initial network model.

5. The method according to claim 4, wherein, The method further includes: In response to the loss value being less than the preset threshold, determine the initial network model as a fire point recognition model.

6. A fire point recognition device based on a forest environment, including: A first acquisition unit, configured to obtain device information of the fire point recognition device corresponding to the alarm information in response to receiving alarm information sent by any fire point recognition device, where the device information includes device identification area information and first elevation data, the device identification area information is used to characterize the range that the fire point recognition device can recognize, represented by longitude and latitude, and the first elevation data is the height of the position where the fire point recognition device is installed or located from the ground; A first determination unit, configured to determine second elevation data corresponding to the alarm information according to the device identification area information and the first elevation data, where the second elevation data is the altitude of the fire point recognition device; The first determination unit is further configured to: Perform parsing processing on the device identification area information to generate parsing information; Determine altitude information corresponding to the fire point recognition device according to the parsing information; Determine the sum of the altitude information and the first elevation data as the second elevation data; A second determination unit, configured to determine relative direction information corresponding to the alarm information according to the device identification area information and the second elevation data; A generation unit, configured to generate fire point coordinate information according to the second elevation data and the relative direction information; the generation unit is further configured to: Determine a pitch angle value corresponding to the fire point recognition device according to the device identification area information; Determine the angle range value according to the pitch angle value; Obtain a fire point image sent by the fire point recognition device; Determine a fire point horizontal angle value according to the position of the fire point shown in the fire point image and the angle range value in the fire point image, where the fire point horizontal angle value is the acute angle between the line connecting the fire point and the fire point recognition device and the horizontal ground; Determine the fire point coordinate information corresponding to the fire point according to the fire point horizontal angle value; A second acquisition unit, configured to obtain a terrain profile model corresponding to the fire point recognition information; A correction unit, configured to perform correction processing on the fire point coordinate information according to the terrain profile model to generate corrected fire point coordinate information; A control unit configured to control an associated intelligent fire extinguishing device to perform fire extinguishing on the area corresponding to the corrected coordinates of the ignition point.

7. An electronic device, comprising: One or more processors; A storage device having stored thereon one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the method according to any one of claims 1 to 5.

8. A computer-readable medium having a computer program stored thereon, wherein, When the program is executed by the processor, the method according to any one of claims 1 to 5 is implemented.

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