Intelligent fire-fighting management method and system based on Internet of Things

Abstract

The invention discloses an intelligent fire-fighting management method and system based on the Internet of Things, and the method comprises the steps: enabling an unmanned plane to fly according to a fire-fighting route given by a satellite communication system, obtaining a fire image, carrying out the real-time monitoring, obtaining the topographic information of a current fire position and the position of a fire region, and predicting the following trend of the fire, according to the method, the terrain information of the current fire position and the fire area position are obtained, the camera is used for capturing the fire scene image, the fire behavior is monitored in real time, automatic identification and positioning of a fire source are achieved, the fire detection accuracy and response speed are improved, and the fire fighting truck is controlled to run to a preset safe fire extinguishing area. Whether the fire trend is controllable or not is judged, the fire fighting truck is controlled to run to the preset safe fire extinguishing area, the safety coefficient of firefighters is improved, the rescue efficiency and the rescue quality are improved, and the method has the advantages of being high in fire behavior prediction capacity and high in safety management degree.

Description

Technical Field

[0001] The present invention relates to the technical field of fire management, and specifically to an intelligent fire management method and system based on the Internet of Things. Background Art

[0002] At present, the domestic fire protection system is developing towards the intelligent direction. The development of domestic intelligent fire protection is rapid, and many enterprises and scientific research institutions are actively investing in research and development. However, there is still a certain gap compared with foreign countries in terms of the depth of data fusion and the degree of system intelligence. With the continuous progress of the Internet of Things and artificial intelligence technologies, the application of multi-source heterogeneous perception data fusion technology in the field of fire protection has become a development trend. By fusing multi-source information such as sensor data and video image data, the accuracy and timeliness of fire detection can be improved, and the deficiencies of single data monitoring can be made up for.

[0003] In the prior art, the intelligent fire management system monitors the fire in real time according to the fire image after a fire occurs, and provides a fire extinguishing plan for the ground fire fighting force. However, when a large fire occurs in some areas, the area of the fire cannot be effectively identified in time; at the same time, in areas with relatively lush vegetation, the area of the fire changes greatly in a short time, especially the smoldering situation of the ground vegetation in the open terrain near the fire is difficult to be monitored, resulting in the intelligent fire management system often lacking the ability to make real-time, accurate and effective judgments and solutions for the secondary change of the fire trend during the fire process, causing casualties to the fire fighting force during the fire extinguishing process. Therefore, it is very necessary to design an intelligent fire management method and system based on the Internet of Things with strong fire trend prediction ability and high safety management level. Summary of the Invention

[0004] The purpose of the present invention is to provide an intelligent fire management method and system based on the Internet of Things to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solutions: An intelligent fire management method and system based on the Internet of Things, including:

[0006] After a fire occurs, the drone flies according to the fire fighting route given by the satellite communication system, acquires the fire image and monitors it in real time, and acquires the terrain information of the current fire location and the location of the fire area;

[0007] Based on the monitoring results, predict the next trend of the fire, and combine the terrain information of the current fire location to analyze the location of the fire area, and judge whether the fire trend is controllable;

[0008] Based on the prediction result of the fire trend, control the fire truck to drive to a preset safe fire extinguishing area.

[0009] According to the above technical solution, the drone flies according to the fire-fighting route given by the satellite communication system, acquires fire images and monitors in real time, and obtains the topographic information of the current fire location and the location of the fire area, including:

[0010] The drone conducts patrol monitoring and takes images, and records the drone shooting position and shooting attitude corresponding to the taken images in real time;

[0011] The drone transmits the images, as well as the position and shooting attitude of the drone, back to the ground station, and the ground station scans the fire images transmitted by the drone;

[0012] The ground station geometrically corrects the fire images using the shooting parameters, and obtains the row and column numbers of potential fire points or burning fire points according to the corrected image coordinate origin and image resolution. The potential fire points include smoldering areas and combustion-supporting areas, and locates the coordinates where the potential fire points or burning fire points are located;

[0013] After positioning and obtaining the topographic information of the current fire location, monitor the spread of the fire in the horizontal direction of the terrain, and calculate the coordinate point on the fire field boundary that is farthest from the fire field center of gravity;

[0014] If there is a burning fire point and the coordinates of the potential fire point are within the coordinate point on the fire field boundary that is farthest from the fire field center of gravity, record the fire image as the location of the fire area.

[0015] According to the above technical solution, predict the next trend of the fire based on the monitoring results, combine the topographic information of the current fire location, and analyze the location of the fire area to determine whether the fire trend is controllable, including:

[0016] Obtain specific fire parameters through the cameras set at the lookout monitoring points. The specific fire parameters include wind direction and wind force magnitude information, and combine the terrain of the current fire location and the location of the fire area to predict the next trend of the fire;

[0017] After obtaining the trend of the fire, the system monitors multiple fan-shaped areas in the direction of the fire, and obtains the smoldering areas in each fan-shaped area. The angle of each fan-shaped area θ = θ0%, where θ0 is the preset angle for monitoring the smoldering area, a1 < A < a2, A is an integer, and the number A of fan-shaped areas is determined by the observable angle near the current fire location. a1 is the preset minimum observable angle, and a2 is the preset maximum observable angle. Select the two adjacent fan-shaped areas with the highest density of combustion-supporting areas, obtain the number B of smoldering areas in the fan-shaped area, and calculate the offset angle β between the current predicted direction and the middle dividing line of the two adjacent fan-shaped areas. When Or When the accuracy of predicting the fire trend by the current satellite communication system is 100%; when When it is, it is determined that the fire trend predicted by the current satellite communication system is uncontrollable, and the information that the fire trend is uncontrollable is output. If the system receives the information that the fire trend is uncontrollable, a warning instruction is issued.

[0018] According to the above technical solution, the issuing of the warning instruction further includes:

[0019] Analyze whether the fire is likely to rebound, count the spreading speed of the fire as V0, and combine the terrain and historical information of the current fire location to predict the next spreading speed of the fire;

[0020] When When it is, the spreading speed prediction module predicts that the next spreading speed of the fire will increase, and the specific spreading speed V = λ B V0, where λ is the base coefficient of the power function change of the spreading speed when the fire passes through the smoldering area;

[0021] When And when the angle difference between the current wind direction and the predicted fire trend of the satellite communication system is greater than 90°, it is predicted that the next spreading speed of the fire will weaken. At the same time, obtain the number of smoldering areas C in the area where the fire has spread. If C > δB, it is determined that the fire is likely to rebound, where δ is the coefficient of fire rebound under the current wind direction.

[0022] According to the above technical solution, the obtaining of the smoldering area and the combustion-supporting area includes:

[0023] Locate the characteristics of the combustion-supporting substances through the fire image around the location of the fire area, detect the total area of the combustion-supporting substances. If the total area is greater than the preset minimum safe total area of the combustion-supporting substances, mark this location as the combustion-supporting area;

[0024] Calculate the leaf accumulation amount around the combustion-supporting area, obtain the total leaf accumulation amount per unit area around the combustion-supporting area. When the detected leaf falling amount reaches the rated value X0, it is determined that the current total leaf accumulation amount exceeds the controllable range, and the corresponding area per unit area is superimposed and the corresponding area is set as the smoldering area.

[0025] According to the above technical solution, the controlling the fire truck to drive to the preset safe fire extinguishing area based on the prediction result of the fire trend includes:

[0026] Based on historical data and real-time data, use machine learning algorithms to predict the fire risk;

[0027] Analyze the fire risk according to the real-time data stream processing technology, and dispatch the fire truck to the safe area.

[0028] According to the above technical solution, an intelligent fire management system based on the Internet of Things includes:

[0029] A monitoring module, which is used for after a fire occurs, the drone flies according to the fire-fighting route given by the satellite communication system, obtains fire images and monitors in real time, and obtains the terrain information of the current fire location and the location of the fire area;

[0030] An analysis module, which is used for predicting the next trend of the fire based on the monitoring results, combining with the terrain information of the current fire location, analyzing the location of the fire area, and judging whether the fire trend is controllable;

[0031] A management module, which is used for controlling the fire truck to drive to a preset safe fire-fighting area based on the prediction result of the fire trend.

[0032] According to the above technical solution, the monitoring module includes:

[0033] A positioning module, which is used for the drone to conduct patrol monitoring and take pictures, and record the corresponding drone shooting position and shooting attitude in real time when taking pictures; the drone transmits the image, as well as the position and shooting attitude of the drone, back to the ground station, and the ground station scans the fire image transmitted back by the drone; the ground station uses the shooting parameters to perform geometric correction on the fire image, and according to the corrected image coordinate origin and image resolution, obtains the row and column numbers of potential fire points or burning fire points, where the potential fire points include smoldering areas and combustion-supporting areas, and locates the coordinates where the potential fire points or burning fire points are located;

[0034] A marking module, which is used for after obtaining the terrain information of the current fire location by positioning, monitoring the spread of the fire in the horizontal direction of the terrain, and calculating the coordinate point on the fire field boundary that is farthest from the fire field center of gravity; if there is a burning fire point and the coordinates of the potential fire point are within the coordinate point on the fire field boundary that is farthest from the fire field center of gravity, the fire image is recorded as the location of the fire area.

[0035] According to the above technical solution, the analysis module includes:

[0036] A prediction module is used to obtain specific fire parameters through a camera set at a lookout monitoring point. The specific fire parameters include wind direction and wind force information, and combined with the terrain of the current fire location and the location of the fire area, predict the next direction of the fire; after obtaining the direction of the fire, the system monitors multiple fan-shaped areas in the direction of the fire, and obtains the smoldering area in each fan-shaped area, wherein the angle of each fan-shaped area is θ=θ0%, wherein θ0 is the preset angle for monitoring the smoldering area, a1<A<a2, A is an integer, and the number of fan-shaped areas A is determined by the observable angle near the current fire location, a1 is the preset minimum observable angle, and a2 is the preset maximum observable angle, and the two adjacent fan-shaped areas with the largest density of combustion-supporting areas are selected, and the number of smoldering areas in the fan-shaped area is obtained as B, and the offset angle between the current predicted direction and the intermediate interval line between the two adjacent fan-shaped areas is calculated as β. When or When , the accuracy of the fire direction predicted by the current satellite communication system is judged to be 100%; when When the fire direction predicted by the current satellite communication system is uncontrollable, it is determined that the fire direction is uncontrollable, and the information that the fire direction is uncontrollable is output. If the system receives the information that the fire direction is uncontrollable, an early warning instruction is issued;

[0037] The fire analysis module is used to calculate the speed of fire spread as V0, and combine the terrain and historical information of the current fire location to predict the next speed of fire spread; When the fire spread rate prediction module predicts that the fire will spread faster, the specific spread rate V = λ B V0, where λ is the base coefficient of the power function change of the fire spread speed when it passes through the smoldering area; When the angle difference between the current wind direction and the direction of the fire predicted by the satellite communication system is greater than 90°, it is predicted that the subsequent spread of the fire will slow down, and the number of smoldering areas in the area where the fire has spread is obtained as C. If C>δB, it is judged that the fire may rebound, where δ is the coefficient of fire rebound under the current wind force reverse.

[0038] According to the above technical solution, the management module includes:

[0039] A safety area locking module, the safety area locking module is used to locate the characteristics of the combustion-supporting materials around the fire area through the fire image, detect the total area of ​​the combustion-supporting materials, and mark the position as the combustion-supporting area if the total area is greater than a preset minimum safe total area of ​​the combustion-supporting materials;

[0040] Calculate the amount of leaf accumulation around the combustion-assisting area to obtain the total amount of leaves accumulated per unit area around the combustion-assisting area. When it is detected that the amount of fallen leaves reaches the rated value X0, determine that the current total amount of leaves exceeds the controllable range, superimpose the corresponding area per unit area and set the corresponding area as the smoldering area;

[0041] A scheduling module, which is used to predict the fire risk by using machine learning algorithms based on historical data and real-time data; analyze the fire risk according to real-time data stream processing technology, and dispatch the fire truck to a safe area.

[0042] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In the present invention, by obtaining the terrain information of the current fire location and the fire area location, capturing the fire scene images by using a camera, and through image processing and analysis algorithms, the fire situation is monitored in real time. In the intelligent fire protection system, combined with artificial intelligence algorithms, automatic identification and positioning of the fire source are realized, the accuracy and response speed of fire detection are improved, it is judged whether the fire trend is controllable, and the fire truck is controlled to drive to a preset safe fire extinguishing area, which improves the safety factor of firefighters, and improves the rescue efficiency and rescue quality. Description of the Drawings

[0043] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0044] Figure 1 is a flowchart of a method for intelligent fire protection management based on the Internet of Things provided by an embodiment of the present invention. Detailed Embodiments

[0045] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0046] Please refer to Figure 1 , which is a flowchart of a method for intelligent fire protection management based on the Internet of Things provided by an embodiment of the present invention. As Figure 1 can be seen, the method for intelligent fire protection management based on the Internet of Things includes:

[0047] Step S1: After a fire occurs, the drone flies according to the fire protection route given by the satellite communication system, obtains fire images and monitors in real time, and obtains the terrain information of the current fire location and the fire area location;

[0048] Step S2: Predict the next trend of the fire based on the monitoring results, analyze the location of the fire area in combination with the terrain information at the current fire location, and determine whether the fire trend is controllable;

[0049] Step S3: Control the fire truck to drive to a preset safe fire extinguishing area based on the predicted result of the fire trend.

[0050] In an embodiment of the present invention, by obtaining the terrain information at the current fire location and the location of the fire area, using a camera to capture the fire scene image, through image processing and analysis algorithms, the fire situation is monitored in real time. In the intelligent fire protection system, combined with artificial intelligence algorithms, automatic identification and positioning of the fire source are realized, the accuracy and response speed of fire detection are improved, whether the fire trend is controllable is judged, and the fire truck is controlled to drive to a preset safe fire extinguishing area, which improves the safety factor of firefighters, the rescue efficiency and the rescue quality.

[0051] In some preferred embodiments, the drone flies according to the fire fighting route given by the satellite communication system, obtains the fire image and monitors it in real time, and obtains the terrain information at the current fire location and the location of the fire area, including:

[0052] Step S11: The drone conducts circuit monitoring and takes images, and records the corresponding drone shooting position and shooting attitude in real time when taking the images, and draws a three-dimensional map of the interior of the building in intelligent fire protection;

[0053] Step S12: The drone transmits the image, as well as the position and shooting attitude of the drone, back to the ground station, and the ground station scans the fire image transmitted by the drone; uses a camera to capture the fire scene image, through image processing and analysis algorithms, monitors the fire situation in real time. In the intelligent fire protection system, combined with artificial intelligence algorithms, automatic identification and positioning of the fire source are realized, and the accuracy and response speed of fire detection are improved;

[0054] Step S13: The ground station geometrically corrects the fire image using the shooting parameters, and obtains the row and column numbers of potential fire points or burning fire points according to the corrected image coordinate origin and image resolution. The potential fire points include smoldering areas and combustion-supporting areas, and locates the coordinates where the potential fire points or burning fire points are located. The potential fire points include smoldering areas and combustion-supporting areas;

[0055] Step S14: After positioning and obtaining the terrain information at the current fire location, monitor the spread of the fire in the horizontal direction of the terrain, and calculate the coordinate point on the fire scene boundary that is farthest from the fire scene centroid. The fire scene includes the area location coordinates of the burning fire points;

[0056] Step S15: If there is a burning ignition point and the coordinates of the potential ignition point are within the coordinates of the point on the fire ground boundary that is farthest from the fire ground center of gravity, record the fire image as the location of the fire area.

[0057] Through this technical solution, environmental data of the fire area in real time is provided, the current fire and the fire range before the fire truck extinguishes the fire in the future are framed, which provides a strong basis for the subsequent analysis of the smoldering area and the combustion-supporting area. At the same time, it helps firefighters quickly understand the internal combustion situation and its structure of the fire ground to formulate rescue plans; it is also used to detect the diffusion of smoke and flames.

[0058] Intelligent fire hydrant monitoring is used to monitor the status of fire hydrants within the location of the fire area in real time, including water pressure, valve switch, etc. When the fire hydrant is abnormal, an alarm is sent to the fire department to ensure that the fire hydrant can be used normally in case of emergency.

[0059] In some preferred embodiments, predicting the next trend of the fire based on the monitoring results, combining the terrain information of the current fire location, analyzing the location of the fire area location, and judging whether the fire trend is controllable, including:

[0060] Step S21: After the fire occurs, the satellite communication system obtains specific fire parameters through the camera set at the lookout monitoring point. The drone accurately flies according to the fire fighting route given by the satellite communication system, and at the same time obtains information on the wind direction and wind force magnitude. Combining the terrain of the current fire location and the location of the fire area location, predict the next trend of the fire;

[0061] Step S22: After obtaining the trend of the fire, the system monitors multiple fan-shaped areas in the direction of the fire, and obtains the smoldering areas in each fan-shaped area, where the angle θ of each fan-shaped area = θ0%, θ0 is the preset angle for smoldering area monitoring, the number A of fan-shaped areas is determined by the observable angle near the current fire location, A is an integer, a1 is the preset minimum observable angle, and a2 is the preset maximum observable angle. In a preferred embodiment, the angle θ of each fan-shaped area = 15%, 8 < A < 12. Select the two adjacent fan-shaped areas with the highest density of combustion-supporting areas, obtain the number B of smoldering areas in the fan-shaped area, and calculate the offset angle β between the current predicted direction and the intermediate line of the two adjacent fan-shaped areas. When or When, it is determined that the accuracy of the fire trend predicted by the current satellite communication system is 100%; when When, it is determined that the fire trend predicted by the current satellite communication system is uncontrollable, and the information that the fire trend is uncontrollable is output;

[0062] Step S23: If the system receives the information that the fire trend is uncontrollable, issue a warning instruction and analyze whether the fire is likely to rebound.

[0063] Due to the limited real-time fire pictures provided by drones and the cameras at the lookout monitoring points, the general fire command center needs to use the satellite communication system to command the fire scene.

[0064] After a fire occurs, the hot air generated by the combustibles rises, and the cold and hot air convection easily "disturbs" the wind direction. Coupled with the complex terrain changes, the fire trend is very likely to mutate.

[0065] When happens, the offset angle between the combustion-supporting area and the wind direction predicted by the system is small, the actual offset angle generated by the fire during subsequent combustion is small, and the accuracy of the fire trend predicted by the satellite communication system is high; when happens, the offset angle between the combustion-supporting area and the wind direction predicted by the system is large, and the fire is basically not affected by the combustion-supporting area during subsequent combustion, and the accuracy of the fire trend predicted by the satellite communication system is high; when happens, the fire will be partially affected by the combustion-supporting area during subsequent combustion, which may cause a partial deviation from the fire trend predicted by the satellite communication system, and the accuracy of the fire trend predicted by the satellite communication system is relatively low.

[0066] Perform a secondary prediction on the direction of fire spread, considering the influence of the smoldering area on the lateral change trend of fire spread, which improves the accuracy of satellite communication quality assessment and also improves the safety factor of firefighters.

[0067] In some preferred embodiments, the issuing of the warning instruction further includes:

[0068] Step S231: Analyze whether the fire is likely to rebound, count the fire spread speed as V0, and combine the terrain and historical information at the current fire location to predict the next fire spread speed;

[0069] Step S232: When happens, the spread speed prediction module predicts that the next fire spread speed will increase, and the specific spread speed V = λ B V0, where λ is the base coefficient of the power function change of the spread speed when the fire passes through the smoldering area;

[0070] Step S233: When and the angle difference between the current wind direction and the fire trend predicted by the satellite communication system is greater than 90°, predict that the next fire spread speed will weaken, and at the same time obtain the number of smoldering areas C in the area where the fire has spread. If C > δB, judge that the fire is likely to rebound, where δ is the coefficient of fire rebound under the current wind direction.

[0071] When the angular difference between the predicted fire direction of the satellite communication system and the secondary prediction result of the fire spread direction prediction module is lower than At this time, the fire spread speed will change exponentially due to the smoldering areas in the passed areas, and the change in the spread speed is specifically determined by the number of smoldering areas in the area.

[0072] Sometimes firefighters extinguish the fire behind the fire front, and there is also a huge risk of the fire rebounding. Through the fire prediction method, the safety factor of firefighters is greatly improved.

[0073] The satellite communication quality assessment system performs a secondary prediction on the fire spread speed through the spread speed prediction module, considering the influence of smoldering areas on the longitudinal change trend in special fire spread situations, and further improving the accuracy of satellite communication quality assessment.

[0074] In some preferred embodiments, the obtaining of the smoldering area and the combustion-supporting area includes:

[0075] Step S221: Locate the characteristics of the combustion-supporting substances around the fire area position through the fire image, detect the total area of the combustion-supporting substances, and if the total area is greater than the preset minimum safe total area of the combustion-supporting substances, mark the position as the combustion-supporting area;

[0076] Step S222: Calculate the amount of leaf accumulation around the combustion-supporting area, obtain the total amount of leaves accumulated per unit area around the combustion-supporting area. When it is detected that the amount of leaf fall reaches the rated value X0, it is determined that the current total amount of leaves exceeds the controllable range, and the corresponding area per unit area is superimposed and the corresponding area is set as the smoldering area.

[0077] The combustibles of the ground vegetation undergo oxidative decomposition after long-term accumulation, namely the smoldering phenomenon, generating a large amount of volatile combustible gases. At the same time, after being mixed with the rotten solid combustibles, an explosive combustion phenomenon occurs under the action of a sudden strong wind, and an explosive growth combustion occurs due to the instability of the air flow.

[0078] In the preferred embodiment, at the fire scene, by identifying the fire image, locate the target positions where additional smoldering areas may appear: some item characteristics show burn-through situations, forming a burn-through hole. The burn-through area extends into the thickness of the item, and there is an obvious carbonized area around it. The upper surface of the carbonized area often has a surface inclined towards the burn-through hole. The certain items are within the already burning fire point, which is distinguished from the location of the smoldering area in step S222. Since the secondary combustion caused by the item combustion may have more serious impacts, it is necessary to locate this smoldering area and increase the safety distance of the firefighters;

[0079] The smoldering area includes an ashing area and a carbonization area. The thickness of the carbonization area is relatively large compared to that of flaming combustion, with an approximately circular mark. The oxygen concentration and the thickness of the char layer affect the propagation speed of smoldering. The greater the oxygen concentration, the greater the smoldering speed; the thicker the char layer, the slower the smoldering speed.

[0080] In some preferred embodiments, controlling the fire truck to drive to a preset safe fire extinguishing area based on the prediction result of the fire trend includes:

[0081] Step S31: Based on historical data and real-time data, use machine learning algorithms to predict fire risks, issue early warning information in advance, and provide support for fire fighting decisions;

[0082] Step S32: Analyze fire risks according to real-time data stream processing technology, dispatch the fire truck to a safe area, and improve rescue efficiency.

[0083] Based on the same concept as the above embodiments, an embodiment of the present invention further provides an Internet of Things-based intelligent fire management system, including:

[0084] A monitoring module, which is used after a fire occurs. The drone flies according to the fire fighting route given by the satellite communication system, acquires fire images and monitors in real time, and acquires the terrain information of the current fire location and the location of the fire area;

[0085] An analysis module, which is used to predict the next trend of the fire based on the monitoring results, combine the terrain information of the current fire location, analyze the location of the fire area, and judge whether the fire trend is controllable;

[0086] A management module, which is used to control the fire truck to drive to a preset safe fire extinguishing area based on the prediction result of the fire trend.

[0087] In this embodiment, the monitoring module includes:

[0088] A positioning module, which is used for the drone to conduct patrol monitoring and take pictures, and record the corresponding drone shooting position and shooting attitude in real time when taking pictures; the drone transmits the image, as well as the position and shooting attitude of the drone, back to the ground station, and the ground station scans the fire images transmitted by the drone; the ground station uses the shooting parameters to perform geometric correction on the fire images, and according to the corrected image coordinate origin and image resolution, obtains the row and column numbers of potential fire points or burning fire points. The potential fire points include a smoldering area and a combustion-supporting area, and locates the coordinates where the potential fire points or burning fire points are located;

[0089] A marking module is used to locate and obtain the terrain information of the current fire location, monitor the spread of the fire in the horizontal direction of the terrain, and calculate the coordinate point on the fire boundary that is farthest from the center of gravity of the fire scene; if there is a burned fire point and the coordinates of the potential fire point are within the coordinate point on the fire boundary that is farthest from the center of gravity of the fire scene, the fire image is recorded as the fire area location.

[0090] In this embodiment, the analysis module includes:

[0091] A prediction module is used for after a fire occurs. The satellite communication system obtains specific fire parameters through a camera set at a lookout monitoring point. The drone flies accurately according to the firefighting route given by the satellite communication system, and obtains wind direction and wind force information at the same time. Combined with the terrain of the current fire location and the location of the fire area, the next direction of the fire is predicted; after obtaining the direction of the fire, the system monitors multiple fan-shaped areas in the direction of the fire, and obtains the smoldering area in each fan-shaped area, wherein the angle of each fan-shaped area θ=θ0%, wherein θ0 is the preset angle for monitoring the smoldering area, a1<A<a2, A is an integer, and the number of fan-shaped areas A is determined by the observable angle near the current fire location, a1 is the preset minimum observable angle, and a2 is the preset maximum observable angle, and the two adjacent fan-shaped areas with the largest density of combustion-supporting areas are selected, and the number of smoldering areas in the fan-shaped area is obtained as B, and the offset angle between the current prediction direction and the intermediate interval line between the two adjacent fan-shaped areas is calculated as β. When or When , the accuracy of the fire direction predicted by the current satellite communication system is judged to be 100%; when When the fire direction predicted by the current satellite communication system is uncontrollable, it is judged that the fire direction is uncontrollable, and the information of the uncontrollable fire direction is output; if the system receives the information that the fire direction is uncontrollable, it issues a warning instruction and analyzes whether the fire may rebound;

[0092] The fire analysis module is used for the UAV to accurately fly the fire route given by the satellite communication system, and at the same time calculate the speed of fire spread as V0, and combine the terrain and historical information of the current fire location to predict the next spread speed of the fire; When the fire spreads faster, the fire spread prediction module predicts that the fire will spread faster, and the specific spread speed V = λ B V0, where λ is the base coefficient of the power function change of the fire spread speed when it passes through the smoldering area; When the angle difference between the current wind direction and the fire direction predicted by the satellite communication system is greater than 90°, the fire is predicted to spread at a slower rate. At the same time, the number of smoldering areas in the area where the fire has spread is obtained as C. If C>δB, it is judged that the fire may rebound, where δ is the coefficient of fire rebound under the current wind force reverse

[0093] In this embodiment, the management module includes:

[0094] A safety area locking module, the safety area locking module is used to locate the characteristics of the combustion-supporting materials around the fire area through the fire image, detect the total area of ​​the combustion-supporting materials, and mark the position as the combustion-supporting area if the total area is greater than a preset minimum safe total area of ​​the combustion-supporting materials;

[0095] The accumulation amount of leaves around the combustion-supporting area is calculated to obtain the total accumulation amount of leaves per unit area around the combustion-supporting area. When it is detected that the amount of fallen leaves reaches the rated value X0, it is determined that the current total accumulation amount of leaves exceeds the controllable range, and the corresponding area of ​​the unit area is superimposed and set as the smoldering area.

[0096] The dispatching module is used to predict the fire risk based on historical data and real-time data using a machine learning algorithm; analyze the fire risk according to real-time data stream processing technology, and dispatch the fire truck to a safe area.

[0097] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0098] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A smart fire management method based on the Internet of Things, characterized by: include: After a fire occurs, the drone flies according to the firefighting route given by the satellite communication system, obtains fire images and monitors them in real time, and obtains the terrain information of the current fire location and the location of the fire area; Predict the direction of the fire based on the monitoring results, analyze the location of the fire area based on the terrain information of the current fire location, and determine whether the direction of the fire is controllable; Based on the prediction result of the fire direction, the fire truck is controlled to drive to a preset safe fire extinguishing area.

2. According to the method of intelligent fire protection management based on the Internet of Things according to claim 1, it is characterized in that: The drone flies according to the firefighting route given by the satellite communication system, obtains fire images and monitors them in real time, and obtains the terrain information of the current fire location and the location of the fire area, including: The drone conducts patrol monitoring and takes pictures, and records the shooting position and shooting posture of the drone corresponding to the shooting of the pictures in real time; The drone transmits the image as well as the drone's position and shooting posture back to the ground station, and the ground station scans the fire image transmitted back by the drone; The ground station uses the shooting parameters to perform geometric correction on the fire image, and obtains the row and column numbers of the potential fire point or the burned fire point according to the corrected image coordinate origin and image resolution. The potential fire point includes a smoldering area and a combustion-supporting area, and locates the coordinates of the potential fire point or the burned fire point; After locating and acquiring the terrain information of the current fire location, the fire spread is monitored in the horizontal direction of the terrain, and the coordinate point on the fire boundary farthest from the center of gravity of the fire is calculated; If there is a burned fire point and the coordinates of the potential fire point are within the coordinate point farthest from the center of gravity of the fire scene on the fire scene boundary, the fire image is recorded as the fire area position.

3. According to the method of intelligent fire management based on the Internet of Things in claim 1, it is characterized by: The method of predicting the next direction of the fire based on the monitoring results and analyzing the location of the fire area in combination with the terrain information of the current fire location to determine whether the direction of the fire is controllable includes: The specific fire parameters including wind direction and wind force are obtained through the cameras installed at the observation and monitoring points. The next direction of the fire is predicted by combining the terrain of the current fire location and the location of the fire area. After obtaining the direction of the fire, the system monitors multiple sector areas in the direction of the fire, and obtains the smoldering area in each sector area, where the angle of each sector area is θ=θ0%, where θ0 is the preset angle for monitoring the smoldering area, a1<A<a2, A is an integer, and the number of sector areas A is determined by the observable angle near the current fire position, a1 is the preset minimum observable angle, and a2 is the preset maximum observable angle. The two adjacent sector areas with the largest density of combustion-supporting areas are selected, and the number of smoldering areas in the sector area is obtained as B, and the offset angle between the current predicted direction and the interval line between the two adjacent sector areas is calculated as β. When or When , the accuracy of the fire direction predicted by the current satellite communication system is judged to be 100%; when When the fire direction predicted by the current satellite communication system is uncontrollable, it is determined that the fire direction is uncontrollable, and information indicating that the fire direction is uncontrollable is output; If the system receives information that the fire is developing uncontrollably, it will issue a warning command.

4. According to the method of intelligent fire protection management based on the Internet of Things in claim 3, it is characterized by: The issuing of the warning instruction also includes: Analyze whether the fire is likely to rebound, calculate the fire spread speed V0, and combine the terrain and historical information of the current fire location to predict the next fire spread speed; when When the fire spreads faster, the fire spread prediction module predicts that the fire will spread faster, and the specific spread speed V = λ B V0, where λ is the base coefficient of the power function change of the fire spread speed when it passes through the smoldering area; when When the angle difference between the current wind direction and the direction of the fire predicted by the satellite communication system is greater than 90°, it is predicted that the subsequent spread of the fire will slow down, and the number of smoldering areas in the area where the fire has spread is obtained as C. If C>δB, it is judged that the fire may rebound, where δ is the coefficient of fire rebound under the current wind force reverse.

5. According to the method of intelligent fire management based on the Internet of Things in claim 3, it is characterized by: The obtaining of the smoldering area and the combustion-supporting area comprises: Locating the features of the combustion-supporting materials around the fire area through the fire image, detecting the total area of ​​the combustion-supporting materials, and marking the location as a combustion-supporting area if the total area is greater than a preset minimum safe total area of ​​the combustion-supporting materials; The accumulation amount of leaves around the combustion-supporting area is calculated to obtain the total accumulation amount of leaves per unit area around the combustion-supporting area. When it is detected that the amount of fallen leaves reaches the rated value X0, it is determined that the current total accumulation amount of leaves exceeds the controllable range, and the corresponding area of ​​the unit area is superimposed and set as the smoldering area.

6. The method for intelligent fire protection management based on the Internet of Things according to claim 5 is characterized in that: The method of controlling the fire truck to drive to a preset safe fire extinguishing area based on the prediction result of the fire direction includes: Use machine learning algorithms to predict fire risks based on historical and real-time data; The fire risk is analyzed according to the real-time data stream processing technology, and the fire truck is dispatched to a safe area.

7. An intelligent fire management system based on the Internet of Things, characterized by: include: A monitoring module, which is used when a fire occurs. The UAV flies according to the firefighting route given by the satellite communication system, obtains fire images and monitors them in real time, and obtains the terrain information of the current fire location and the location of the fire area; An analysis module, which is used to predict the next direction of the fire based on the monitoring results, analyze the location of the fire area in combination with the terrain information of the current fire location, and determine whether the direction of the fire is controllable; A management module is used to control the fire truck to travel to a preset safe fire extinguishing area based on the prediction result of the fire direction.

8. The intelligent fire management system based on the Internet of Things according to claim 7 is characterized in that: The monitoring module comprises: A positioning module, the positioning module is used for the drone to conduct patrol monitoring and take images, and to record in real time the drone's shooting position and shooting posture corresponding to the time of taking the image; the drone transmits the image and the drone's position and shooting posture back to the ground station, and the ground station scans the fire image sent back by the drone; the ground station uses the shooting parameters to perform geometric correction on the fire image, and obtains the row and column numbers of the potential fire point or the burned fire point according to the corrected image coordinate origin and image resolution, the potential fire point includes a smoldering area and a combustion-supporting area, and locates the coordinates of the potential fire point or the burned fire point; a marking module, the marking module is used to locate and obtain the terrain information of the current fire position, monitor the spread of the fire in the horizontal direction of the terrain, and calculate the coordinate point on the fire boundary that is farthest from the center of gravity of the fire; if there is a burned fire point and the coordinates of the potential fire point are within the coordinate point on the fire boundary that is farthest from the center of gravity of the fire, the fire image is recorded as the fire area position.

9. The intelligent fire management system based on the Internet of Things according to claim 8 is characterized by: The analysis module comprises: A prediction module is used to obtain specific fire parameters through a camera set at a lookout monitoring point. The specific fire parameters include wind direction and wind force information, and combined with the terrain of the current fire location and the location of the fire area, predict the next direction of the fire; after obtaining the direction of the fire, the system monitors multiple fan-shaped areas in the direction of the fire, and obtains the smoldering area in each fan-shaped area, wherein the angle of each fan-shaped area is θ=θ0%, wherein θ0 is the preset angle for monitoring the smoldering area, a1<A<a2, A is an integer, and the number of fan-shaped areas A is determined by the observable angle near the current fire location, a1 is the preset minimum observable angle, and a2 is the preset maximum observable angle, and the two adjacent fan-shaped areas with the largest density of combustion-supporting areas are selected, and the number of smoldering areas in the fan-shaped area is obtained as B, and the offset angle between the current predicted direction and the intermediate interval line between the two adjacent fan-shaped areas is calculated as β. When or When , the accuracy of the fire direction predicted by the current satellite communication system is judged to be 100%; when When the fire direction predicted by the current satellite communication system is uncontrollable, it is judged that the fire direction is uncontrollable, and the information of the uncontrollable fire direction is output; if the system receives the information that the fire direction is uncontrollable, an early warning instruction is issued; The fire analysis module is used to calculate the speed of fire spread as V0, and combine the terrain and historical information of the current fire location to predict the next speed of fire spread; When the fire spreads faster, the fire spread prediction module predicts that the fire will spread faster, and the specific spread speed V = λ B V0, where λ is the base coefficient of the power function change of the fire spread speed when it passes through the smoldering area; When the angle difference between the current wind direction and the direction of the fire predicted by the satellite communication system is greater than 90°, it is predicted that the subsequent spread of the fire will slow down, and the number of smoldering areas in the area where the fire has spread is obtained as C. If C>δB, it is judged that the fire may rebound, where δ is the coefficient of fire rebound under the current wind force reverse.

10. The intelligent fire management system based on the Internet of Things according to claim 9 is characterized in that: The management module comprises: A safety area locking module, the safety area locking module is used to locate the characteristics of the combustion-supporting materials around the fire area through the fire image, detect the total area of ​​the combustion-supporting materials, and mark the position as the combustion-supporting area if the total area is greater than a preset minimum safe total area of ​​the combustion-supporting materials; The accumulation amount of leaves around the combustion-supporting area is calculated to obtain the total accumulation amount of leaves per unit area around the combustion-supporting area. When it is detected that the amount of fallen leaves reaches the rated value X0, it is determined that the current total accumulation amount of leaves exceeds the controllable range, and the corresponding area of ​​the unit area is superimposed and set as a smoldering area. The dispatching module is used to predict the fire risk based on historical data and real-time data using a machine learning algorithm; analyze the fire risk according to real-time data stream processing technology, and dispatch the fire truck to a safe area.

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