CN115641516B - Unmanned aerial vehicle remote control display method - Google Patents
Unmanned aerial vehicle remote control display method Download PDFInfo
- Publication number
- CN115641516B CN115641516B CN202210176456.8A CN202210176456A CN115641516B CN 115641516 B CN115641516 B CN 115641516B CN 202210176456 A CN202210176456 A CN 202210176456A CN 115641516 B CN115641516 B CN 115641516B
- Authority
- CN
- China
- Prior art keywords
- unmanned aerial
- aerial vehicle
- scene
- weather
- preset
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Abstract
The application relates to a remote control display method of an unmanned aerial vehicle, which belongs to the technical field of unmanned aerial vehicles and comprises the steps of obtaining real-time weather information; acquiring a weather scene of the position of the unmanned aerial vehicle based on the real-time weather information; switching a shooting mode of the unmanned aerial vehicle based on a weather scene; judging whether fire disaster occurs or not based on weather scenes; if yes, acquiring a real-time image shot and transmitted by a camera preset on the unmanned aerial vehicle; and (3) carrying out a preset image processing algorithm on the real-time image to obtain a clear image. The staff of being convenient for discern the conflagration and in time mobilize the fire fighter based on clear image, be favorable to unmanned aerial vehicle when detecting the conflagration simultaneously, satisfy the clear user demand of many weather shooting real-time images.
Description
Technical Field
The application relates to the technical field of unmanned aerial vehicles, in particular to a remote control display method of an unmanned aerial vehicle.
Background
The unmanned plane is an unmanned plane which is operated by using a radio remote control device. The unmanned aerial vehicle can be used for police, urban management, agriculture, geology, weather, electric power, rescue and relief work, video shooting and other scenes.
Existing unmanned aerial vehicles are typically equipped with cameras for taking field pictures. However, when the unmanned aerial vehicle detects a fire scene, due to weather, the real-time image shot by a camera on the unmanned aerial vehicle is easy to blur, so that the real-time image transmitted to a display screen of the remote controller is caused to blur. For example, in foggy days, fog can affect the image quality of a real-time image shot by a camera on the unmanned aerial vehicle, so that the image quality of the real-time image on a display screen of a remote controller is reduced, and the real situation of a fire scene is difficult to reflect; in rainy days, raindrops fall on cameras on the unmanned aerial vehicle can cause the distortion of the shot real-time images, so that the reflection quality of the real-time images on fire scenes is affected.
To sum up, unmanned aerial vehicle is when surveying the conflagration, and the real-time image of camera transmission to remote controller display screen on the unmanned aerial vehicle is easily restricted by the weather, is difficult to satisfy many weather and shoots the clear user demand of real-time image, and the background staff of inconvenience in time early warning according to real-time image.
Disclosure of Invention
In order to facilitate the unmanned aerial vehicle to meet clear use requirements of shooting real-time images in multiple days when detecting fire, and further facilitate background staff to early warn in time according to the real-time images, the application provides a remote control display method of the unmanned aerial vehicle.
The application provides a remote control display method of an unmanned aerial vehicle, which adopts the following technical scheme:
a method for remotely controlling and displaying an unmanned aerial vehicle, comprising:
acquiring real-time weather information;
based on the real-time weather information, obtaining a weather scene of the position of the unmanned aerial vehicle;
switching a shooting mode of the unmanned aerial vehicle based on the weather scene;
judging whether fire disasters occur or not based on the weather scenes;
if yes, acquiring a real-time image shot and transmitted by the unmanned aerial vehicle;
and obtaining a clear image by the real-time image through a preset image processing algorithm.
By adopting the technical scheme, the unmanned aerial vehicle remote controller firstly acquires real-time weather information, is used for acquiring a weather scene of the position of the unmanned aerial vehicle, and switches the shooting mode of the unmanned aerial vehicle based on the weather scene, so that the image quality is convenient to improve; because fire disasters can occur in different weather scenes, the unmanned aerial vehicle remote controller judges whether fire disasters occur or not based on the different weather scenes; if a fire disaster occurs, a preset camera on the unmanned aerial vehicle shoots a real-time image and transmits the real-time image to the unmanned aerial vehicle remote controller, the unmanned aerial vehicle remote controller obtains a clear image through an image processing algorithm, a worker is convenient to distinguish the fire disaster based on the clear image and timely mobilize fire extinguishrs, and meanwhile, when the unmanned aerial vehicle detects the fire disaster, the use requirement that the real-time image is clear is met when multiple weather shooting is carried out.
Optionally, before the step of acquiring the real-time weather information, the method includes:
acquiring a current date;
the current date is brought into a preset season database, and the season corresponding to the current date is obtained;
searching a fire occurrence probability corresponding to a season in a preset season fire database;
judging whether the occurrence probability is higher than a preset first probability threshold value;
if yes, sending reminding information at a preset first time interval;
otherwise, sending the reminding information at a preset second time interval; wherein the second time is greater than the first time.
By adopting the technical scheme, the unmanned aerial vehicle remote controller reminds based on the frequency of fire occurrence in different forests, if the occurrence probability is higher than the first probability threshold value, the unmanned aerial vehicle remote controller indicates that the fire is in a season of high occurrence at the moment, and the unmanned aerial vehicle remote controller sends reminding information at a first time interval at the moment, so that workers can be reminded of monitoring forest fires in time;
if the occurrence probability is lower than the first probability threshold, the unmanned aerial vehicle remote controller sends a reminding message at a second time interval at the moment when the occurrence probability is indicated to be a season with low occurrence probability of the fire disaster, and reminding workers of monitoring forest fire disasters in time is facilitated.
Optionally, the shooting mode includes a fog penetrating mode and a noise reducing mode; the weather scenes comprise a foggy scene, a rainy scene, a cloudy scene and a sunny scene; the step of switching the shooting mode of the unmanned aerial vehicle based on the weather scene comprises the following steps:
if the weather scene is a foggy scene, switching the shooting mode to a fog penetrating mode;
and if the weather scene is a rainy day scene, a sunny day scene or a cloudy day scene, switching the shooting mode to be a noise reduction mode.
By adopting the technical scheme, the unmanned aerial vehicle remote controller switches different shooting modes based on different weather scenes, so that the quality of real-time images shot by the camera is improved conveniently; if the weather is a foggy scene, the shooting mode is switched to a fog penetrating mode, so that the quality of a real-time image is improved; if the weather is a rainy day scene, a sunny day scene or a cloudy day scene, noise points may appear in the real-time image at the moment, the image quality is influenced, and the noise reduction mode is adjusted to be favorable for reducing the noise of the real-time image, so that the image quality is further improved.
Optionally, after the step of switching the shooting mode to the noise reduction mode if the weather scene is a rainy day scene, the step of switching the shooting mode to the noise reduction mode includes:
judging whether rainfall information detected and transmitted by a rainfall sensor preset on a camera of the unmanned aerial vehicle is acquired or not;
if so, a first starting signal is sent to a preset induction windshield wiper on the camera at intervals of preset cleaning time so as to start the induction windshield wiper.
Through adopting above-mentioned technical scheme, rain sensor is used for detecting whether there is the rain this moment, and response windshield wiper is used for clearing up the camera's camera lens in the rainy day, is favorable to preventing that the rainwater from falling on the camera's the lens and causing the influence to real-time image's quality.
Optionally, after the step of switching the shooting mode to the noise reduction mode if the weather scene is a sunny scene, the method includes:
acquiring the brightness of light;
and switching the brightness of the display screen of the remote controller based on the light brightness.
By adopting the technical scheme, if the weather scene is a sunny scene, the unmanned aerial vehicle remote controller automatically switches the brightness of the remote controller display screen based on the solar brightness at the moment, and the eye comfort level of the unmanned aerial vehicle remote controller user is improved.
Optionally, the step of determining whether a fire occurs based on the weather scene includes:
if the weather scene is a foggy weather scene, judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a preset temperature threshold value;
if yes, judging whether the unmanned aerial vehicle detects an infrared signal;
if yes, judging that the fire disaster occurs.
Through adopting above-mentioned technical scheme, when the weather scene is the foggy day scene, unmanned aerial vehicle remote controller detects the infrared signal through the temperature value of detecting and transmitting on the unmanned aerial vehicle and the infrared sensor of predetermineeing on the unmanned aerial vehicle and judges whether to appear the conflagration, judges whether to take place the conflagration and is favorable to improving the accuracy of conflagration judgement through the temperature value and whether detect the infrared signal.
Optionally, the step of determining whether a fire occurs based on the weather scene further includes:
if the weather scene is a rainy scene, a cloudy scene or a sunny scene, acquiring the visibility information monitored by a visibility sensor preset on the unmanned aerial vehicle;
judging whether the visibility information is lower than a preset visibility threshold value or not;
if yes, judging whether the gas concentration detected and transmitted by the unmanned aerial vehicle is greater than the first gas concentration threshold;
if not, judging that the weather scene is a foggy scene; and
executing the step of judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than the temperature threshold value if the weather scene is a foggy weather scene;
if yes, judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a preset temperature threshold value;
if yes, judging whether an infrared sensor preset on the unmanned aerial vehicle detects an infrared signal or not;
if yes, judging that the fire disaster occurs.
By adopting the technical scheme, as the foggy scene can appear in the sunny scene, the cloudy scene and the rainy scene, the priority of the foggy scene is higher than that of the sunny scene, the cloudy scene and the rainy scene;
in sunny scene, cloudy scene and rainy scene, the unmanned aerial vehicle remote controller at first obtains the visibility information of the last preset visibility sensor monitoring of unmanned aerial vehicle, later judges whether be the foggy scene based on the gas concentration that unmanned aerial vehicle detected and transmitted, if be the foggy scene, then unmanned aerial vehicle remote controller continues to carry out next step, if not in the foggy scene, unmanned aerial vehicle remote controller judges whether the forest takes place the conflagration based on temperature value and infrared sensor, further improves the accuracy of conflagration judgement.
Optionally, the shooting mode further comprises a dense smoke shooting mode and a light smoke shooting mode;
after the step of determining that a fire has occurred, comprising:
acquiring the concentration of the gas transmitted by the unmanned aerial vehicle;
judging whether the gas concentration is higher than a preset second gas concentration threshold value or not; wherein the second gas concentration threshold is greater than the first gas concentration threshold;
if yes, switching the shooting mode to be a dense smoke shooting mode;
otherwise, switching the shooting mode to be a light smoke shooting mode.
Through adopting above-mentioned technical scheme, unmanned aerial vehicle remote controller is based on the gas concentration of unmanned aerial vehicle transmission to compare gas concentration with first gas concentration threshold value and second gas concentration threshold value, and then switch the shooting mode of camera on the unmanned aerial vehicle, further improve the quality of real-time image.
Optionally, after the step of switching the shooting mode to the thick smoke shooting mode, the method includes:
transmitting a second starting signal to an infrared imaging sensor preset on the unmanned aerial vehicle so as to start the infrared imaging sensor;
after the step of switching the photographing mode to the light smoke photographing mode, comprising:
acquiring the real-time image transmitted by the unmanned aerial vehicle;
and sharpening the real-time image.
By adopting the technical scheme, when the shooting mode is the dense smoke shooting mode, the unmanned aerial vehicle remote controller sends a starting signal to start the infrared imaging sensor on the unmanned aerial vehicle, the infrared sensor is used for detecting life bodies in fire, and if the life bodies exist in the fire, workers can rescue in time;
when the shooting mode is a light smoke shooting mode, the unmanned aerial vehicle remote controller performs sharpening processing on the real-time image, and therefore image quality of the real-time image is improved.
Optionally, after the step of obtaining the clear image by passing the real-time image through a preset image processing algorithm, the method includes:
acquiring a flame image contour of the clear image shot by the unmanned aerial vehicle at a preset height based on a preset flame image processing algorithm;
acquiring area information of the flame image outline;
judging whether the area information is larger than a preset first area threshold value or not;
if yes, a primary alarm is sent out;
otherwise, judging whether the area information is larger than a preset second area threshold value or not;
if yes, a secondary alarm is sent out;
otherwise, a three-level alarm is issued.
By adopting the technical scheme, the flame image outline is obtained through the flame image processing algorithm, an alarm is sent out based on the powder image outline, the primary alarm indicates that the fire is large at the moment, and fire extinguishing staff needs to consider the safety problem of the fire to the fire extinguishing staff at the moment and take corresponding measures; the secondary alarm shows that the fire coverage area is smaller at the moment, and fire extinguishing actions are needed to be performed in time at the moment when the fire spreads in a fireproof situation; the three-level alarm shows that the fire is small at the moment and is in an initial fire state, and the moment is the best fire extinguishing moment at the moment so as to remind workers of timely fire extinguishing.
In summary, the application has at least one of the following beneficial technical effects:
1. the unmanned aerial vehicle remote controller switches the shooting mode of the unmanned aerial vehicle based on weather scenes, so that the image quality is improved conveniently; the unmanned aerial vehicle remote controller obtains clear images through an image processing algorithm with the real-time images that acquire, and the staff of being convenient for distinguishes the conflagration and in time mobilizes the fire fighter based on clear images, is favorable to unmanned aerial vehicle when detecting the conflagration simultaneously, satisfies the clear user demand of many weather shooting real-time images.
2. In sunny scene, cloudy scene and rainy scene, unmanned aerial vehicle remote controller judges whether be the foggy scene based on visibility information and gas concentration, if be the foggy scene, unmanned aerial vehicle remote controller judges whether to appear the conflagration through temperature value and whether detect infrared signal, if not in the foggy scene, unmanned aerial vehicle remote controller judges whether to take place the conflagration based on temperature value and infrared sensor, is favorable to improving the accuracy of conflagration judgement.
3. When the shooting mode is a dense smoke shooting mode, the infrared imaging sensor is started and used for detecting life bodies in a fire disaster, so that workers can rescue in time; when the shooting mode is a light smoke shooting mode, the unmanned aerial vehicle remote controller performs sharpening processing on the real-time image, and therefore image quality of the real-time image is improved.
Drawings
Fig. 1 is an overall flowchart of a remote control display method of a unmanned aerial vehicle according to an embodiment of the present application.
Fig. 2 is a flowchart of determining whether a fire disaster occurs based on a weather scene in the unmanned aerial vehicle remote control display method according to the embodiment of the application.
Fig. 3 is a flowchart of a remote control display method of an unmanned aerial vehicle after a step of determining that a fire occurs in an embodiment of the present application.
Detailed Description
The embodiment of the application discloses a remote control display method for an unmanned aerial vehicle.
Referring to fig. 1, a remote control display method of an unmanned aerial vehicle includes:
s100, acquiring the current date.
In this embodiment, the unmanned aerial vehicle remote controller communicates with the unmanned aerial vehicle through the wireless module, and the unmanned aerial vehicle remote controller uses the Android system, and the Android obtains current system date, i.e. unmanned aerial vehicle remote controller obtains current date.
S200, the current date is brought into a preset season database, and a season corresponding to the current date is obtained.
The season database is preset and can be set according to seasons of different areas. For example, setting 3 months to 6 months as spring; setting the summer period from 6 months to 9 months; setting 9 months to 12 months as autumn; setting 1 month to 3 months as winter.
S300, searching the occurrence probability of the fire corresponding to the seasons in a preset seasonal fire database.
The seasonal fire database is also preset, and specifically, the seasonal fire database performs summary analysis according to the frequency of four seasons fire in the last ten years of forests, and obtains the frequency of fire occurrence corresponding to each season by taking an average value, and generally, the frequency of fire occurrence in each season is different according to different areas of the forest fire. In general, forest fires are liable to occur in summer and autumn, and the frequency of monitoring forest fires is required to be enhanced.
S400, judging whether the occurrence probability is higher than a preset first probability threshold.
S500, if yes, sending reminding information at preset first time intervals.
If the occurrence probability is higher than a preset first probability threshold, the season in which the current date is located is indicated to be a forest fire high-incidence period, and at the moment, the supervision of the forest is required to be enhanced, so that the forest fire is prevented in time. The unmanned aerial vehicle remote controller sends a reminding message to a remote controller display screen at a preset first time interval so as to remind workers to monitor and control forests. For example, if the probability of fire occurrence on the current date is 20%, the first time is 4 days, the first probability threshold is 15%, and the 20% >15% is set, so that the unmanned aerial vehicle remote controller sends the reminding message 4 days apart and displays the reminding message on the display screen.
S600, otherwise, sending reminding information at intervals of a preset second time; wherein the second time is greater than the first time.
If the occurrence probability is lower than the first probability threshold, the occurrence probability of forest fires is indicated to be difficult to occur or smaller, and the monitoring frequency of forest fires can be reduced. For example, if the second time is 10 days and the occurrence probability is 5%, the unmanned aerial vehicle remote controller transmits the reminding information and displays the reminding information on the display screen at intervals of 10 days at this time because the occurrence probability is 5% < 15%.
S700, acquiring real-time weather information.
In this embodiment, the Android system obtains weather services provided by the national weather service, that is, real-time weather information, through webservice.
S800, obtaining a weather scene of the position of the unmanned aerial vehicle based on real-time weather information.
The unmanned aerial vehicle remote controller can obtain weather scenes of the positions where the unmanned aerial vehicle is located through real-time weather information, and the weather scenes comprise a sunny scene, a cloudy scene, a rainy scene and a foggy scene.
S900, switching a shooting mode of the unmanned aerial vehicle based on the weather scene.
Because the rays of different weather scenes are different, different weather scenes need to correspond to different shooting modes so as to improve the image quality.
Specifically, the shooting mode includes a fog penetrating mode and a noise reducing mode; the weather scenes comprise a foggy scene, a cloudy scene, a rainy scene and a sunny scene;
the step of switching the shooting mode of the unmanned aerial vehicle based on the weather scene comprises the following steps:
s910, if the weather scene is a foggy scene, switching the shooting mode to a fog penetrating mode.
In this embodiment, the fog-penetrating mode is to change the quality of optical imaging by using digital fog penetration, so as to achieve the fog penetration effect. The digital fog penetration adopts an algorithm fog penetration technology, namely, the concentration of the fog is judged according to the formation model of the physical fog and the grey degree of the local area, so that a clear haze-free image is restored.
S920, if the weather scene is a rainy scene, a sunny scene or a cloudy scene, switching the shooting mode to a noise reduction mode.
If the weather scene is a rainy scene, a sunny scene or a cloudy scene, the unmanned aerial vehicle remote controller switches the shooting mode of the camera on the unmanned aerial vehicle to a noise reduction mode, and the noise reduction mode refers to the noise reduction function of the unmanned aerial vehicle camera.
If the weather scene is a rainy day scene, the step of switching the shooting mode to the noise reduction mode comprises the following steps:
s921, judging whether rainfall information detected and transmitted by a rainfall sensor preset on a camera of the unmanned aerial vehicle is acquired or not.
The rainfall sensor is used for detecting rainfall information, and the unmanned aerial vehicle remote controller judges whether a rainy scene rains or not through whether the rainfall sensor detects the rainfall information.
And S922, if so, sending a first starting signal to a preset induction windshield wiper on the camera at intervals of preset cleaning time so as to start the induction windshield wiper.
Because raindrops can cause the quality of real-time image that the camera on the unmanned aerial vehicle took to drop on the lens when raining, so when unmanned aerial vehicle remote controller judges that unmanned aerial vehicle's position is raining, send the start signal promptly to the response windshield wiper to start the clean camera lens of response windshield wiper.
If the unmanned aerial vehicle remote controller does not acquire the rainfall information, the unmanned aerial vehicle remote controller does not act.
After the step of switching the shooting mode to the noise reduction mode if the weather scene is a sunny scene, the method comprises the following steps:
s923, light brightness is obtained.
S924, switching the brightness of the display screen of the remote controller based on the light brightness.
In this embodiment, the light brightness is obtained through a light sensor preset on the unmanned aerial vehicle. If the weather scene is a sunny scene, the brightness of the display screen of the remote controller is automatically switched by the unmanned aerial vehicle remote controller based on the light brightness, and the eye comfort level of a user of the unmanned aerial vehicle remote controller is improved. The brightness of the remote controller display screen is switched based on the brightness of the light, so that the description thereof is omitted.
Referring to fig. 1, S1000 determines whether a fire occurs based on a weather scene.
Different weather scenes all have the risk of forest fire, and unmanned aerial vehicle remote controller judges whether to appear the conflagration based on weather scene.
Specifically, based on weather scenes, the step of judging whether a fire disaster occurs includes:
s1001, if the weather scene is a foggy weather scene, judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a preset temperature threshold.
When weather scene is the foggy scene, if the conflagration takes place, if be the thick fog, the conflagration is difficult for in time being found, and unmanned aerial vehicle judges whether to take place the conflagration through the temperature value that temperature sensor that presets on the unmanned aerial vehicle detected and infrared sensor whether detected infrared signal this moment.
If the temperature value detected by the temperature sensor is greater than the temperature threshold value, the possibility of fire occurrence is indicated. For example, the temperature threshold is set to 80 degrees celsius, and if the temperature value detected by the temperature sensor is 90 degrees celsius, the unmanned aerial vehicle remote controller executes the next step at this time.
And if the temperature value is smaller than the temperature threshold value, the unmanned aerial vehicle remote controller executes the step of acquiring the real-time image shot and transmitted by the camera preset on the unmanned aerial vehicle.
S1002, if yes, judging whether the unmanned aerial vehicle detects an infrared signal.
If the forest fires, a large amount of gases such as carbon monoxide (CO), hydrogen sulfide (H2S), nitrogen dioxide (NO 2), hydrogen Cyanide (HCN) and the like are generated in the fire process, the gas concentration is higher, if the gas concentration is greater than a first gas concentration threshold value, the fact that the forest has a hidden danger of fire occurrence at the moment is indicated, and at the moment, the unmanned aerial vehicle remote controller further judges whether the forest has fire through whether an infrared signal is detected or not. Specifically, the infrared signal is detected through an infrared sensor preset by the unmanned aerial vehicle. The infrared sensor detects fire phenomena by detecting specific infrared spectrums released by carbon monoxide generated during the initial combustion of plants and carbon dioxide generated by open flame.
The unmanned aerial vehicle remote controller further judges whether fire occurs or not through whether the infrared sensor detects the infrared signal.
If the temperature value is less than or equal to the preset temperature threshold value, the unmanned aerial vehicle remote controller does not act.
And S1003, if yes, judging that a fire disaster occurs.
If the temperature value detected by the temperature sensor on the unmanned aerial vehicle is greater than the temperature threshold value, and the infrared sensor detects an infrared signal, the unmanned aerial vehicle remote controller judges that a forest fire occurs.
If the infrared signal is not detected, the unmanned aerial vehicle remote controller does not act.
Referring to fig. 2, the step of judging whether a fire occurs based on the weather scene further includes:
s1010, if the weather scene is a rainy scene, a cloudy scene or a sunny scene, acquiring the visibility information monitored by a preset visibility sensor on the unmanned aerial vehicle.
Because the rainy day scene, the cloudy day scene and the sunny day scene can all appear in the foggy day scene, the visibility at this moment is judged through the visibility information that the visibility sensor monitored to the unmanned aerial vehicle remote controller.
S1020, judging whether the visibility information is lower than a preset visibility threshold value.
And S1030, if so, judging whether the gas concentration detected and transmitted by the unmanned aerial vehicle is greater than a first gas concentration threshold.
In this embodiment, the gas concentration is detected by a smoke sensor preset on the unmanned aerial vehicle.
There are two cases of low visibility. The first case is that the visibility caused by the thick fog is low, and the second case is that the visibility caused by the smoke generated by the fire is low. At the moment, the unmanned aerial vehicle remote controller judges whether the scene is a foggy day or not through the gas concentration detected and transmitted by the unmanned aerial vehicle and the first gas concentration threshold value.
If the visibility information is higher than the visibility threshold, the unmanned remote controller performs step S1050.
S1040, if not, judging that the weather scene is a foggy scene; and
and executing the step of judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a temperature threshold value if the weather scene is a foggy weather scene.
For example, if the first gas concentration threshold is set to 18mg/m 3 If the gas concentration detected by a smoke sensor preset on the unmanned aerial vehicle is 8mg/m 3 And if so, indicating that the visibility is low and the gas concentration is low, the unmanned aerial vehicle remote controller judges that the weather scene is a foggy scene at the moment, and executing step S1001.
It should be noted that, the priority of the foggy scene is highest, that is, when the unmanned aerial vehicle remote controller determines that the current weather scene has the foggy scene, the fire disaster determination step of the foggy scene is performed, that is, the step S1001 is performed.
S1050, if so, judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a preset temperature threshold.
If the visibility is low and the gas concentration is greater than the first gas concentration threshold, it indicates that a forest fire may exist at the moment. For example, if the gas concentration detected by the unmanned aerial vehicle is 20mg/m 3 At this point the drone remote continues to execute the next step.
And if the gas concentration is smaller than the first gas concentration threshold value, the unmanned aerial vehicle remote controller does not act.
S1060, if yes, judging whether an infrared sensor preset on the unmanned aerial vehicle detects an infrared signal.
And if the temperature value is smaller than the temperature threshold value, the unmanned aerial vehicle remote controller does not act.
And S1070, if yes, judging that the fire disaster occurs.
If the visibility is low, the gas concentration is larger than a first gas concentration threshold value, and the infrared sensor detects an infrared signal, and at the moment, the unmanned aerial vehicle remote controller judges that a forest fire disaster occurs.
If the infrared signal is not detected, the unmanned aerial vehicle remote controller does not act.
Referring to fig. 3, the photographing modes further include a strong smoke photographing mode and a weak smoke photographing mode;
after the step of determining the occurrence of the fire, comprising:
s1071, acquiring the concentration of the gas transmitted by the unmanned aerial vehicle.
S1072, judging whether the gas concentration is higher than a preset second gas concentration threshold value; wherein the second gas concentration threshold is greater than the first gas concentration threshold.
After the step of judging the fire disaster, the unmanned aerial vehicle remote controller obtains the gas concentration detected by the smoke sensor on the unmanned aerial vehicle and compares the gas concentration with a second gas concentration threshold value so as to switch different shooting modes.
And S1073, if yes, switching the shooting mode to a dense smoke shooting mode.
If the gas concentration value is larger than the second gas concentration threshold value, the shooting mode is switched to be a thick smoke shooting mode, and specifically, the thick smoke shooting mode is to increase the secondary exposure of a camera on the unmanned aerial vehicle and reduce the aperture.
Specifically, after the step of switching the photographing mode to the thick smoke photographing mode, it includes:
and S1073a, sending a second starting signal to an infrared imaging sensor preset on the unmanned aerial vehicle so as to start the infrared imaging sensor.
The infrared imaging sensor is used for detecting whether a life body exists in a fire disaster, and if the life body exists, workers can rescue in time. Unmanned aerial vehicle in this embodiment takes locate function, and unmanned aerial vehicle fixes a position through GPS outdoors.
Referring to fig. 3, if the gas concentration is less than the second gas concentration threshold, S1074, the shooting mode is switched to the light smoke shooting mode.
If the gas concentration is smaller than the second gas concentration threshold, the unmanned aerial vehicle remote controller switches the shooting mode of the camera of the unmanned aerial vehicle to a light smoke shooting mode, and the light smoke shooting mode is that the first-level exposure of the camera is increased.
After the step of switching the photographing mode to the light smoke photographing mode, comprising:
and S1074a, acquiring a real-time image transmitted by the unmanned aerial vehicle.
And S1074b, sharpening the real-time image.
The sharpening process is used for compensating the outline of the image, enhancing the edge and the gray jump part of the image, and making the image clear.
Referring to fig. 1, in S1100, if a fire occurs, a real-time image captured and transmitted by a camera preset on the unmanned aerial vehicle is acquired.
S1200, the real-time image is subjected to a preset image processing algorithm to obtain a clear image.
In this embodiment, the image processing algorithm adopts a bilateral filtering algorithm, which is used for performing noise reduction processing on the real-time image, so that the image is clearer, after the image processing algorithm, the unmanned aerial vehicle remote controller obtains a clear image, and the clear image is displayed on the display screen.
Specifically, after the step of obtaining a clear image by passing the real-time image through a preset image processing algorithm, the method comprises the following steps:
s1210, acquiring a flame image contour of a clear image based on a preset flame image processing algorithm.
The flame image processing algorithm comprises three steps of image preprocessing, noise removal and flame identification, and the flame outline in the clear image is obtained after the flame image processing algorithm. Since the image preprocessing, noise removal and flame recognition are widely used, they will not be described in detail herein.
S1220, acquiring area information of the outline of the flame image.
Because the flame image in the clear image consists of a plurality of coordinate points, the area information of the outline of the flame image can be obtained by calculating the number of the coordinate points, namely, the sum of the pixel points in the outline of the flame image is obtained.
S1230, judging whether the area information is larger than a preset first area threshold.
And S1240, if yes, sending out a primary alarm.
If the area information of the flame image outline is larger than the first area threshold value, the situation that the fire is larger at the moment is indicated, the unmanned aerial vehicle remote controller sends out a primary alarm, and at the moment, fire extinguishing staff needs to consider the safety problem of the fire to the fire extinguishing staff and take corresponding measures.
S1250, if not, judging whether the area information is larger than a preset second area threshold value.
S1260, if yes, sending out a secondary alarm.
If the area information is larger than the second area threshold and smaller than the first area threshold, the area information indicates that the fire coverage area is smaller at the moment, and fire extinguishing actions are needed to be timely performed at the moment when the fire situation spreads.
S1270, otherwise, a three-level alarm is issued.
If the area information is smaller than the second area threshold value, the fire is smaller at the moment, the fire is in an initial state, the best fire extinguishing opportunity is achieved at the moment, and the unmanned aerial vehicle remote controller sends out three-level alarms for reminding workers of timely extinguishing the fire.
The implementation principle of the unmanned aerial vehicle remote control display method provided by the embodiment of the application is as follows: the unmanned aerial vehicle remote controller firstly obtains real-time weather and obtains a weather scene based on the real-time weather. The weather scenes comprise a rainy day scene, a cloudy day scene, a sunny day scene and a foggy day scene, and the priority of the foggy day scene is highest. The unmanned aerial vehicle remote controller judges whether a fire disaster occurs based on different weather scenes, if the fire disaster occurs, a preset camera on the unmanned aerial vehicle shoots a real-time image, the real-time image is transmitted to the unmanned aerial vehicle remote controller, the unmanned aerial vehicle remote controller obtains a clear image after the real-time image passes through an image processing algorithm, and therefore the unmanned aerial vehicle can meet the clear use requirement of shooting the real-time image in multiple weather when detecting the fire disaster.
The above embodiments are not intended to limit the scope of the present application, so: all equivalent changes in structure, shape and principle of the application should be covered in the scope of protection of the application.
Claims (8)
1. The unmanned aerial vehicle remote control display method is characterized by comprising the following steps of:
acquiring real-time weather information;
based on the real-time weather information, obtaining a weather scene of the position of the unmanned aerial vehicle;
switching a shooting mode of the unmanned aerial vehicle based on the weather scene;
judging whether fire disasters occur or not based on the weather scenes;
if yes, acquiring a real-time image shot and transmitted by the unmanned aerial vehicle;
the real-time image is subjected to a preset image processing algorithm to obtain a clear image;
the shooting mode comprises a fog penetrating mode and a noise reducing mode; the weather scenes comprise a foggy scene, a rainy scene, a cloudy scene and a sunny scene;
the step of switching the shooting mode of the unmanned aerial vehicle based on the weather scene comprises the following steps:
if the weather scene is a foggy scene, switching the shooting mode to a fog penetrating mode;
if the weather scene is a rainy scene, a sunny scene or a cloudy scene, switching the shooting mode to a noise reduction mode;
wherein, based on the weather scene, the step of judging whether fire disaster occurs comprises:
if the weather scene is a foggy weather scene, judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a preset temperature threshold value;
if yes, judging whether the unmanned aerial vehicle detects an infrared signal;
if yes, judging that the fire disaster occurs.
2. The unmanned aerial vehicle remote control display method of claim 1, wherein prior to the step of obtaining real-time weather information, comprising:
acquiring a current date;
the current date is brought into a preset season database, and the season corresponding to the current date is obtained;
searching a fire occurrence probability corresponding to a season in a preset season fire database;
judging whether the occurrence probability is higher than a preset first probability threshold value;
if yes, sending reminding information at a preset first time interval;
otherwise, sending the reminding information at a preset second time interval; wherein the second time is greater than the first time.
3. The method for remotely controlling and displaying a unmanned aerial vehicle according to claim 1, wherein after the step of switching the shooting mode to the noise reduction mode if the weather scene is a rainy scene, the method comprises:
judging whether rainfall information detected and transmitted by a rainfall sensor preset on a camera of the unmanned aerial vehicle is acquired or not;
if so, a first starting signal is sent to a preset induction windshield wiper on the camera at intervals of preset cleaning time so as to start the induction windshield wiper.
4. The method for remotely controlling and displaying a unmanned aerial vehicle according to claim 1, wherein after the step of switching the shooting mode to the noise reduction mode if the weather scene is a sunny scene, the method comprises:
acquiring the brightness of light;
and switching the brightness of the display screen of the remote controller based on the light brightness.
5. The method of claim 1, wherein,
the step of judging whether fire disaster occurs based on the weather scene further comprises:
if the weather scene is a rainy scene, a cloudy scene or a sunny scene, acquiring the visibility information monitored by a visibility sensor preset on the unmanned aerial vehicle;
judging whether the visibility information is lower than a preset visibility threshold value or not;
if yes, judging whether the gas concentration detected and transmitted by the unmanned aerial vehicle is greater than a first gas concentration threshold value;
if not, judging that the weather scene is a foggy scene; and
executing the step of judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than the temperature threshold value if the weather scene is a foggy weather scene;
if yes, judging whether the temperature value detected and transmitted by the unmanned aerial vehicle is greater than a preset temperature threshold value;
if yes, judging whether an infrared sensor preset on the unmanned aerial vehicle detects an infrared signal or not;
if yes, judging that the fire disaster occurs.
6. The unmanned aerial vehicle remote control display method of claim 5, wherein the shooting mode further comprises a dense smoke shooting mode and a light smoke shooting mode;
after the step of determining that a fire has occurred, comprising:
acquiring the concentration of the gas transmitted by the unmanned aerial vehicle;
judging whether the gas concentration is higher than a preset second gas concentration threshold value or not; wherein the second gas concentration threshold is greater than the first gas concentration threshold;
if yes, switching the shooting mode to be a dense smoke shooting mode;
otherwise, switching the shooting mode to be a light smoke shooting mode.
7. The method of claim 6, wherein,
after the step of switching the photographing mode to the thick smoke photographing mode, comprising:
transmitting a second starting signal to an infrared imaging sensor preset on the unmanned aerial vehicle so as to start the infrared imaging sensor;
after the step of switching the photographing mode to the light smoke photographing mode, comprising:
acquiring the real-time image transmitted by the unmanned aerial vehicle;
and sharpening the real-time image.
8. The unmanned aerial vehicle remote control display method according to claim 1, wherein after the step of obtaining a clear image by subjecting the real-time image to a preset image processing algorithm, the method comprises:
acquiring a flame image contour of the clear image shot by the unmanned aerial vehicle at a preset height based on a preset flame image processing algorithm;
acquiring area information of the flame image outline;
judging whether the area information is larger than a preset first area threshold value or not;
if yes, a primary alarm is sent out;
otherwise, judging whether the area information is larger than a preset second area threshold value or not;
if yes, a secondary alarm is sent out;
otherwise, a three-level alarm is issued.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210176456.8A CN115641516B (en) | 2022-02-24 | 2022-02-24 | Unmanned aerial vehicle remote control display method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210176456.8A CN115641516B (en) | 2022-02-24 | 2022-02-24 | Unmanned aerial vehicle remote control display method |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115641516A CN115641516A (en) | 2023-01-24 |
| CN115641516B true CN115641516B (en) | 2023-09-22 |
Family
ID=84940024
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210176456.8A Active CN115641516B (en) | 2022-02-24 | 2022-02-24 | Unmanned aerial vehicle remote control display method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115641516B (en) |
Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100480887B1 (en) * | 2004-06-29 | 2005-04-06 | 주식회사 창성에이스산업 | Fire extinguishing system for forecasting and diagnosing fire using digital real time |
| KR20080065833A (en) * | 2007-01-10 | 2008-07-15 | 한국서부발전 주식회사 | Fire alarm method and system |
| KR100981428B1 (en) * | 2010-03-18 | 2010-09-10 | (합)동양아이텍 | Forest fire monitoring system and method |
| KR20120125716A (en) * | 2011-05-09 | 2012-11-19 | 이순영 | Fire imaging detection system and method |
| CN103607528A (en) * | 2013-11-11 | 2014-02-26 | 成都市晶林电子技术有限公司 | Active infrared camera |
| CN104299351A (en) * | 2014-10-22 | 2015-01-21 | 常州大学 | Intelligent early warning and fire extinguishing robot |
| CN106971485A (en) * | 2017-03-30 | 2017-07-21 | 浙江大学 | Realtime graphic based on FPGA monitors multi-functional fire wireless alarm system and method |
| CN107438995A (en) * | 2016-09-30 | 2017-12-05 | 深圳市大疆创新科技有限公司 | For the method, apparatus and equipment of the shooting strategy for determining capture apparatus |
| CN108416963A (en) * | 2018-05-04 | 2018-08-17 | 湖北民族学院 | Forest Fire Alarm method and system based on deep learning |
| CN108520615A (en) * | 2018-04-20 | 2018-09-11 | 芜湖岭上信息科技有限公司 | A kind of fire identification system and method based on image |
| CN112509270A (en) * | 2020-11-19 | 2021-03-16 | 北京城市轨道交通咨询有限公司 | Fire monitoring linkage method, device and system for train compartment |
| CN112802287A (en) * | 2020-12-16 | 2021-05-14 | 广东电网有限责任公司电力科学研究院 | Power transmission line forest fire monitoring, early warning and positioning system and method thereof |
| CN113283324A (en) * | 2021-05-14 | 2021-08-20 | 成都鸿钰网络科技有限公司 | Forest fire prevention early warning method and system based on dynamic image |
| CN113341568A (en) * | 2021-06-04 | 2021-09-03 | 深圳市前海合航科技有限公司 | Intelligent wearable and air purification combined device |
-
2022
- 2022-02-24 CN CN202210176456.8A patent/CN115641516B/en active Active
Patent Citations (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| KR100480887B1 (en) * | 2004-06-29 | 2005-04-06 | 주식회사 창성에이스산업 | Fire extinguishing system for forecasting and diagnosing fire using digital real time |
| KR20080065833A (en) * | 2007-01-10 | 2008-07-15 | 한국서부발전 주식회사 | Fire alarm method and system |
| KR100981428B1 (en) * | 2010-03-18 | 2010-09-10 | (합)동양아이텍 | Forest fire monitoring system and method |
| KR20120125716A (en) * | 2011-05-09 | 2012-11-19 | 이순영 | Fire imaging detection system and method |
| CN103607528A (en) * | 2013-11-11 | 2014-02-26 | 成都市晶林电子技术有限公司 | Active infrared camera |
| CN104299351A (en) * | 2014-10-22 | 2015-01-21 | 常州大学 | Intelligent early warning and fire extinguishing robot |
| CN107438995A (en) * | 2016-09-30 | 2017-12-05 | 深圳市大疆创新科技有限公司 | For the method, apparatus and equipment of the shooting strategy for determining capture apparatus |
| CN106971485A (en) * | 2017-03-30 | 2017-07-21 | 浙江大学 | Realtime graphic based on FPGA monitors multi-functional fire wireless alarm system and method |
| CN108520615A (en) * | 2018-04-20 | 2018-09-11 | 芜湖岭上信息科技有限公司 | A kind of fire identification system and method based on image |
| CN108416963A (en) * | 2018-05-04 | 2018-08-17 | 湖北民族学院 | Forest Fire Alarm method and system based on deep learning |
| CN112509270A (en) * | 2020-11-19 | 2021-03-16 | 北京城市轨道交通咨询有限公司 | Fire monitoring linkage method, device and system for train compartment |
| CN112802287A (en) * | 2020-12-16 | 2021-05-14 | 广东电网有限责任公司电力科学研究院 | Power transmission line forest fire monitoring, early warning and positioning system and method thereof |
| CN113283324A (en) * | 2021-05-14 | 2021-08-20 | 成都鸿钰网络科技有限公司 | Forest fire prevention early warning method and system based on dynamic image |
| CN113341568A (en) * | 2021-06-04 | 2021-09-03 | 深圳市前海合航科技有限公司 | Intelligent wearable and air purification combined device |
Non-Patent Citations (5)
| Title |
|---|
| Thermal Infrared Sensing for Near Real-Time Data-Driven Fire Detection and Monitoring Systems;Maria João Sousa et al.;Sensors (Basel);全文 * |
| 关于无人机在森林防火中应用的探讨;周建;闫铁铮;森林防火(03);全文 * |
| 基于双光谱图像处理的林火监控应用研究;刘兆春等;滁州学院学报;第22卷(第5期);全文 * |
| 小型无人机林火监测与图像处理技术;郭伟;昂海松;张思玉;森林防火(04);全文 * |
| 新型森林火情预警监控系统设计探析;杨燕丽;范超;李颖;张威;张烈;韩仁江;科技创业月刊(08);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115641516A (en) | 2023-01-24 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US7786877B2 (en) | Multi-wavelength video image fire detecting system | |
| US9390604B2 (en) | Fire detection system | |
| CN101334924B (en) | Fire hazard probe system and its fire hazard detection method | |
| CN201936415U (en) | Automatic forest fire identification and alarm system | |
| CN105788028A (en) | Automobile data recorder with fatigue driving pre-warning function | |
| CN107437318B (en) | Visible light intelligent recognition algorithm | |
| CN111310556A (en) | Drowning prevention safety supervision system based on primary and middle school student area and monitoring method thereof | |
| CN114821406A (en) | Method and system for judging electric power operation field violation behaviors | |
| CN115376269B (en) | Fire monitoring system based on unmanned aerial vehicle | |
| CN114241589B (en) | Bus driver violation behavior determination method and device based on vehicle-mounted video | |
| Ollero et al. | Techniques for reducing false alarms in infrared forest-fire automatic detection systems | |
| CN111091110A (en) | Wearing identification method of reflective vest based on artificial intelligence | |
| CN104634784A (en) | Atmospheric visibility monitoring method and device | |
| CN115512510B (en) | Intelligent fire disaster treatment system and method for charging pile | |
| CN114566056A (en) | Highway tunnel driving safety risk identification, prevention and control method and system | |
| CN114971409A (en) | Smart city fire monitoring and early warning method and system based on Internet of things | |
| CN111429681A (en) | Comprehensive perimeter security system with infrared thermal image verification and method | |
| CN115641516B (en) | Unmanned aerial vehicle remote control display method | |
| CN116434533A (en) | AI wisdom highway tunnel synthesizes monitoring platform based on 5G | |
| US8346703B2 (en) | Systems and methods for analyzing communication options | |
| CN116189372A (en) | Forest fire prevention multilayer early warning and monitoring system and method applying big data technology | |
| CN115457331A (en) | Intelligent inspection method and system for construction site | |
| CN113870513A (en) | Smoke and fire identification and early warning method based on GIS | |
| CN112637418A (en) | Danger reminding method and device | |
| CN116486313B (en) | Video analysis system and method suitable for scenes |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |