Vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system and method

Abstract

This invention discloses a vehicle-mounted integrated method and system for monitoring camping fire safety and providing early warning of fire risks, belonging to the field of vehicle-mounted safety monitoring technology. The system includes a multi-source sensing module, a fire source identification module, a risk assessment module, a dynamic safety module, and a fire-out monitoring module. It calculates flame confidence by simultaneously acquiring visible light and thermal imaging data through multispectral sensors, achieving accurate fire source identification. Combining real-time wind speed, vegetation dryness, flammable material distance, and flammability coefficient, a risk index model is constructed to assess fire risk. The minimum safe distance and ring-shaped warning zone are calculated and graphically displayed based on fire source size, wind speed, and dryness. After fire extinguishing, the ember temperature is continuously monitored, and a temperature-time dual-threshold judgment method is used to warn of smoldering and reignition. This invention overcomes the passivity of traditional monitoring, the rigidity of static alarms, and the blind spots in ember monitoring, achieving proactive, dynamic, and closed-loop safety protection throughout the entire lifecycle of camping fire use.

Description

Technical Field

[0001] This invention relates to the field of vehicle-mounted safety monitoring technology, and in particular to a vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system and method. Background Technology

[0002] With the increasing popularity of outdoor activities such as camping and off-roading, RVs and off-road vehicles have become the preferred mode of transportation for these activities. In such scenarios, open flames such as campfires and barbecues are frequently used, and their openness and unpredictability pose significant fire safety hazards. Firstly, current technology only triggers alarms when a fire has already started or is large enough to provide early warning before it spreads. Furthermore, it is susceptible to interference from heat sources such as sunlight and vehicle headlights, leading to misidentification of non-fire sources as fires. Secondly, some existing safety systems or guidelines only provide a fixed safe distance warning. However, weather conditions (such as wind speed) and geographical environment (such as vegetation dryness) at campsites are dynamic. While a vehicle may be at a safe distance in light winds, it can become extremely dangerous in strong winds. Therefore, this rigid, static alarm model that does not consider dynamic environmental factors cannot provide truly effective safety assurance. Finally, most existing monitoring systems assume the risk is eliminated and stop working once the open flame is extinguished. However, one of the main causes of campfires is the reignition of smoldering embers due to factors such as wind, which often result in "ember blind spots." This makes it impossible to continuously and effectively monitor and warn of the smoldering state after the fire is extinguished, leaving a huge safety hazard.

[0003] Therefore, there is still an urgent need for an intelligent safety monitoring solution that can achieve proactive early warning, dynamic assessment, and cover the entire life cycle of fire use, in order to improve the safety of vehicles using fire while camping in the wild. Summary of the Invention

[0004] To address the aforementioned issues, this invention proposes a vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system and method.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system includes:

[0007] Multi-source sensing module: used to acquire and time-synchronize multi-source data related to fire risk monitoring, and output standardized multi-source data, including: visible light image data, thermal imaging data, wind speed data, vegetation dryness data, flammability coefficient and flammable distance data;

[0008] Fire source identification module: Based on the visible light image data and thermal imaging data, the flame confidence level is calculated through multispectral collaborative calculation. When it is a real flame, the size level of the fire source and the distance of the fire source from the vehicle are obtained based on the visible light data.

[0009] Risk assessment module: Based on the fire source size level, distance of fire source from vehicle, wind speed data, vegetation dryness data, flammability coefficient, and distance of flammable material data, a risk index is obtained according to the risk formula;

[0010] Dynamic safety module: includes a safety distance calculation unit and a graphical interface generation unit;

[0011] The safe distance calculation unit calculates the minimum safe distance based on the fire source size level, wind speed data, and vegetation dryness data using a formula; the image interface generation unit is used for real-time visual fire source risk monitoring, including a ring-shaped warning zone, a wind rose diagram, and warning text.

[0012] Flameout monitoring module: Used to monitor the ember area and trigger different safety responses based on changes in the state of the ember area.

[0013] As a preferred embodiment of the present invention, the multi-source sensing module includes:

[0014] Multispectral sensor: includes a visible light imaging unit for capturing ambient light reflected by the scene and generating visible light image data; a thermal imaging unit for detecting mid- and far-infrared radiation emitted by the object itself and generating thermal imaging data; and analysis of the target vegetation area based on the visible light imaging unit, as well as obtaining vegetation dryness data by querying a dryness lookup table.

[0015] Wind speed sensor: Located on the roof, trunk door or roof rack, used to collect wind speed data and output it through the controller area network bus;

[0016] 3D vision sensor: Used to acquire the distance to flammable materials and ignition sources; based on a color image stream, it identifies flammable materials and ignition sources in the field of view through a built-in visual recognition algorithm, and acquires the corresponding 3D spatial coordinates. The distance data of flammable materials is then obtained according to a formula.

[0017]

[0018] In the formula, This is distance data for flammable materials. For fire source coordinate, For fire source coordinate, For fire source coordinate, Flammable coordinate, Flammable coordinate, Flammable coordinate.

[0019] As a preferred embodiment of the present invention, the flammable material coefficient is obtained based on the flammable material according to a preset flammable material coefficient lookup table.

[0020] As a preferred embodiment of the present invention, the fire source identification module includes:

[0021] Based on the visible light image data and thermal imaging data, regions that suddenly appear or continuously move in the image are analyzed, and regions matching the flame color are selected according to a preset flame color threshold. Candidate fire source regions are then obtained based on the temperature of these regions. The flame color threshold includes: in the red-green-blue color space, the red component value is greater than 200, the green component value is less than 150, and the blue component value is less than 100. A flame confidence level is then obtained based on the candidate fire source regions. The expression is:

[0022]

[0023] In the formula, A_flicker is the number of flickering pixels in the candidate region, A_region is the total number of pixels in the candidate region, ΔT_max is the maximum temperature difference between the highest temperature in the candidate region and the ambient temperature, and the coefficients 0.6 and 0.4 represent the weights of flickering characteristics and temperature characteristics, respectively.

[0024] When the flame confidence level exceeds a preset value, the candidate fire source area is considered a real flame. Based on the visible light data, the flame size level L is obtained through a flame size level lookup table, and the distance D from the fire source to the vehicle is calculated according to the monocular vision ranging principle. The expression is:

[0025]

[0026] In the formula, f is the camera focal length, W_actual is the actual physical size of the reference object, and W_pixels is the pixel size of the fire source in the image.

[0027] As a preferred embodiment of the present invention, the risk formula is:

[0028]

[0029] In the formula, As a risk index, For fire source size rating, For wind speed data, This is data on vegetation aridity. The distance between the fire source and the vehicle. For flammability coefficient, This is distance data for flammable materials.

[0030] As a preferred embodiment of the present invention, the minimum safety distance calculation formula in the dynamic safety module is as follows:

[0031]

[0032] In the formula, 4 represents the minimum safe distance, and 4 is the safety factor. For fire source size rating, For wind speed data, This is data on vegetation aridity.

[0033] The image interface generation unit includes:

[0034] The ring-shaped warning zone is divided into three color rings: red, yellow, and green, each corresponding to a different level of fire risk, and is installed on the vehicle's infotainment screen.

[0035] The wind rose diagram displays the current wind direction, wind speed, and location of flammable materials in real time.

[0036] The prompt text displays the current minimum safe distance in real time.

[0037] As a preferred embodiment of the present invention, the flameout monitoring module includes:

[0038] When the "Confirm Engine Shutdown" button is pressed, monitoring of the ember area will begin according to the preset time.

[0039] Based on the multispectral sensor, when the temperature of the ember area is greater than 80 degrees, a voice prompt will be output indicating that the temperature is too high; if the temperature is less than 80 degrees, silence will be maintained and monitoring will continue.

[0040] When the temperature rise rate in the ember area exceeds the preset value and flame or smoke characteristics are captured simultaneously, a high-frequency audible and visual alarm is activated and the recording function is automatically started.

[0041] When the highest temperature in the ember area is below 50 degrees Celsius and this condition persists for 5 minutes, the push notification indicates that the area is in a safe state.

[0042] As a preferred embodiment of the present invention, it also includes an emergency linkage module: if the risk index is greater than 0.5 and the wind speed data is greater than 10 meters per second, then the audible and visual alarm is activated, video recording is started, and an alarm signal is sent.

[0043] As a preferred embodiment of the present invention, the vegetation aridity data includes:

[0044] The visible light unit analyzes the visible light imaging data of the target vegetation area, sets the yellow and brown ranges in the hue-saturation-brightness color space as the withered yellow state, counts the number of all pixels belonging to the withered yellow state, and obtains the real-time percentage of withered yellow state pixels by calculating the ratio of the number of withered yellow state pixels to the total number of pixels in the vegetation area. The percentage of withered yellow state pixels is then input into a preset dryness lookup table to obtain vegetation dryness data.

[0045] Vehicle-mounted integrated fire safety monitoring and fire risk early warning methods for camping include:

[0046] Acquire and synchronize multi-source data related to fire risk monitoring in real time, and output standardized multi-source data, including: visible light image data, thermal imaging data, wind speed data, vegetation dryness data, flammability coefficient data, and flammable material distance data;

[0047] Based on the visible light image data and thermal imaging data, the flame confidence level is calculated through multispectral collaborative calculation. When it is a real flame, the size level of the fire source and the distance of the fire source from the vehicle are obtained based on the visible light data.

[0048] Based on the fire source size level, fire source distance from vehicle, wind speed data, vegetation dryness data, flammability coefficient, and flammability distance data, a risk index is obtained according to the risk formula.

[0049] Based on the fire source size rating, wind speed data, and vegetation dryness data, the minimum safe distance is obtained using a formula.

[0050] Real-time visual monitoring of fire source risks is achieved through a graphical interface, including a circular warning zone, wind rose diagram, and warning text.

[0051] Based on the multispectral sensor and the flameout monitoring rules, the ember area is monitored, and different safety responses are triggered according to changes in the state of the ember area.

[0052] The beneficial effects of this invention are as follows: By constructing a closed-loop active fire protection system integrated into a vehicle platform, it effectively overcomes the inherent defects of existing camping fire safety monitoring technologies, such as passivity, static nature, and blind spots. Firstly, it improves the accuracy and foresight of fire risk perception and identification. Through a multispectral collaborative identification algorithm that integrates visible light and thermal imaging data, combined with confidence judgments based on flame flicker characteristics and temperature fields, environmental interference is effectively eliminated, achieving accurate and rapid identification of real fire sources, laying the foundation for subsequent risk assessment. Secondly, it enables dynamic quantitative prediction and early warning of fire risks. The constructed multi-factor dynamic risk model, for the first time, quantitatively integrates multiple environmental variables such as fire source size, real-time wind speed, vegetation dryness, and distance to flammable materials, and calculates a dynamically adjusted safe distance based on the environment. This completely changes the lag and rigidity of traditional fixed threshold alarms, enabling users to take targeted preventative measures based on real-time risk levels. Finally, a closed-loop safety monitoring system covering the entire lifecycle of fire use was formed. The system not only provides dynamic early warnings during the open flame use stage, but also continuously monitors the smoldering state after the flame is extinguished through the dual threshold determination method of ember temperature and time and the multi-sensor cross-verification mechanism until the risk is completely eliminated. This fundamentally solves the major hidden danger of fire caused by ember reignition and significantly improves the overall safety of outdoor camping activities. Attached Figure Description

[0053] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. Wherein:

[0054] Figure 1 This is a structural diagram of the vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system of the present invention; Figure 2 This is a flowchart of the vehicle-mounted integrated camping fire safety monitoring and fire risk early warning method of the present invention. Detailed Implementation

[0055] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. All other embodiments obtained by those skilled in the art based on the described embodiments of the present invention are within the scope of protection of the present invention.

[0056] like Figure 1As shown, this is an embodiment of the present invention, which provides a vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system, including: a multi-source sensing module, a fire source identification module, a risk assessment module, a dynamic safety module, and a fire shutdown monitoring module.

[0057] The multi-source sensing module revolves around the central processing unit (or domain controller), which is responsible for scheduling, synchronizing, and processing data from the sensors. A multispectral sensor is typically an integrated device combining a visible light lens and a thermal imaging lens, mounted on the roof or in a wide-view location such as the rearview mirror. The visible light lens continuously captures color (RGB) video streams of the scene, outputting visible light image data. This data is subsequently used not only for fire source identification, but its images (in the HSV / HSL color space) are also specifically used to analyze vegetation color. By calculating the proportion of withered yellow and brown pixels in the image and referring to a pre-defined lookup table, vegetation dryness data (I) is indirectly derived (see later sections for details). The thermal imaging lens is aligned with or tightly integrated with the visible light lens's optical axis. It detects the mid- and far-infrared radiation emitted by the object itself, generating thermal imaging data (usually a temperature matrix or pseudo-color image). This temperature information is crucial for distinguishing between real fire and reflections, as well as identifying embers. The wind speed sensor is a standalone physical sensor, typically mounted on the roof, trunk lid, or roof rack to minimize interference from the vehicle body on airflow measurement. It measures wind speed (V) in real time and outputs it via the vehicle's Controller Area Network (CAN) bus in a standardized data frame format. The CAN bus serves as the "highway" for communication between sensors and control units within the vehicle. The 3D vision sensor is a binocular stereo camera, structured light, or Time-of-Flight (ToF) sensor that outputs a color image stream and corresponding depth maps and point cloud data. Built-in visual recognition algorithms (such as deep learning-based object detection models) analyze the color image stream in real time, identifying "fire sources" and preset categories of "flammable materials" (such as tents, vehicles, and haystacks). Once a target is identified, the system immediately extracts its 3D coordinates (X, Y, Z) from the synchronized depth information. For a identified fire source, its coordinates (X_f, Y_f, Z_f) are used to calculate the distance (D) from the fire source to the vehicle. For each identified flammable material, the distance data D_comb is calculated using a formula.

[0058]

[0059] In the formula, This is distance data for flammable materials. For fire source coordinate, For fire source coordinate, For fire source coordinate, Flammable coordinate, Flammable coordinate, Flammable coordinate.

[0060] When the 3D vision sensor identifies an object as a "tent" or a "vehicle," the system uses its category label as an index to look up a pre-defined flammability coefficient lookup table, as shown in Table 1, Flammability Coefficient Lookup Table:

[0061] Table 1 Flammability Coefficient Lookup Table

[0062] This lookup table is stored in system memory, thereby assigning a quantified flammability coefficient k to each identified flammable substance.

[0063] To achieve "time synchronization," the central processing unit (CPU) adds a high-precision timestamp based on a unified system clock to all incoming sensor data streams, or uses hardware-triggered synchronization. The CPU sends a synchronization pulse signal to simultaneously trigger the multispectral sensor and the 3D vision sensor to acquire data, thus ensuring that the image and 3D data are strictly aligned at the time of acquisition. Wind speed data is then correlated with the most recent image frame through its timestamp.

[0064] The system acquires RGB format color images in real time from the vehicle's onboard visible light imaging unit. Using pre-trained semantic segmentation models (such as DeepLab and UNet), it identifies vegetation categories such as "grass," "shrubs," and "trees" in the images and uses their pixel regions as target regions. Based on the installation perspective of the onboard system and typical camping scenarios, a fixed region of interest (e.g., a fan-shaped area with a radius of 20 meters around the vehicle) is defined in the image, assuming this region contains the main surface vegetation. The RGB values ​​of each pixel within the target region are converted to the HSV (hue, saturation, lightness) color space. The HSV color space is closer to human color perception, facilitating segmentation based on color features. The conversion formula is standardized to ensure that the H (hue) range is between 0° and 360° (or quantization scales such as 0-255, 0-180, etc.). The S (saturation) and V (brightness) values ​​range from 0% to 100% (or 0-255). Simple preprocessing, such as Gaussian filtering, is applied to the image to reduce noise. In the HSV color space, a numerical range representing the "yellowish state" of vegetation is defined, including two typical withered color intervals: "yellow" and "brown." Each pixel within the target vegetation area is traversed, and it is determined whether the HSV value falls within any of the threshold ranges for the "yellowish state." The total number of yellowish pixels, N_dry, and the total number of vegetation pixels in the target area, N_total, are calculated. The proportion of yellowish pixels, Ratio = N_dry / N_total, is then calculated. An internal "dryness lookup table" is pre-defined, defining the mapping relationship from the proportion of yellowish pixels to the vegetation dryness data I (usually between 0.1 and 1.0), as shown in Table 2, Dryness Lookup Table.

[0065] Table 2 Dryness Index Lookup Table

[0066] Input the calculated percentage of withered yellow pixels (Ratio) into the dryness lookup table to obtain vegetation dryness data.

[0067] After receiving time-synchronized visible light image data and thermal imaging data from the multi-source sensing module, the fire source identification module continuously analyzes consecutive video frames and uses inter-frame difference or background subtraction algorithms to detect areas in the image that suddenly appear or move continuously. For example, the moment a campfire is lit or a flame swaying in the wind will produce significant pixel changes in the image sequence. Within the detected dynamic areas, color thresholds are further applied for filtering: the typical characteristics of flames in the RGB (red, green, blue) color space are: the value of the red component is greater than 200, the value of the green component is less than 150, and the value of the blue component is less than 100. Each pixel in the visible light image data is evaluated, and all pixels that meet the above conditions are marked to form a "flame-colored region" mask. Simultaneously, thermal imaging data is analyzed to calculate the ambient background temperature of the current image (e.g., taking the average temperature of the non-central area around the image), searching for areas with temperatures significantly higher than the ambient background, as flame temperatures are typically much higher. Only pixel regions that simultaneously meet the criteria of being "moving," "flame-colored," and "high-temperature" are ultimately identified as candidate fire source regions. The core visual characteristic of a flame is irregular flickering. Within a short period (e.g., analyzing 10 consecutive frames of visible light images), the number of pixels within the candidate fire source region that experience drastic and irregular brightness changes is counted, denoted as A_flicker. The area of ​​the fire source pixels in the candidate fire source region is denoted as A_region, and the flicker characteristic value is... / The higher the value, the larger the proportion of flashing pixels in the candidate fire source area, and the more it resembles a real fire. The highest temperature point within the candidate fire source area is found from the thermal imaging data, and the difference between the temperature and the ambient temperature, ΔT_max, is calculated. A weighted fusion method is used to combine the two features into a flame confidence score between 0 and 1. The expression is:

[0068]

[0069] In the formula, A_flicker is the number of flickering pixels in the candidate fire source region, A_region is the area of ​​fire source pixels in the candidate fire source region, ΔT_max is the maximum temperature difference between the highest temperature in the candidate fire source region and the ambient temperature, and the coefficients 0.6 and 0.4 represent the weights of flickering characteristics and temperature characteristics, respectively.

[0070] Preset a confidence threshold, such as If the confidence level of the flame in the candidate fire source area exceeds the threshold, the fire source identification module determines that the candidate fire source area is a real flame; if it is below the threshold, it is determined to be interference and is excluded.

[0071] After confirming that it is a real flame, calculate the flame size rating L and the distance D from the fire source to the vehicle;

[0072] The flame size level L is based on the flame source pixel area A_region in the visible light image data. A pre-stored flame size level lookup table is consulted, which categorizes flame sizes according to their pixel area, such as:

[0073] If the area of ​​the fire source pixel is less than the preset value A, then L=1;

[0074] If preset value A ≤ fire source pixel area < preset value B, then L=2;

[0075] If the area of ​​the fire source pixel is greater than or equal to the preset value B, then L=3;

[0076] A and B are pre-set values ​​based on factors such as camera focal length and typical fire source distance.

[0077] The principle of monocular vision ranging is used to calculate the distance D between the fire source and the vehicle. The core idea is: given the actual size of the object and its size in the image, combined with the camera's focal length, the distance D between the fire source and the vehicle can be calculated. The formula is:

[0078]

[0079] In the formula, f is the camera focal length, W_actual is the actual physical size of the reference object, and W_pixels is the pixel size of the fire source in the image.

[0080] The risk assessment module integrates multi-source data from sensors, flame size level L and distance from the fire source to the vehicle D obtained through the above calculations, and calculates a comprehensive fire risk index R using a risk formula.

[0081]

[0082] In the formula, As a risk index, The fire source identification module typically classifies fire source size into three levels: 1 (small), 2 (medium), and 3 (large). The wind speed data comes from the wind speed sensor in the multi-source sensing module, and the unit is meters per second (m / s). The vegetation aridity data are coefficients obtained from visible light image analysis by a multi-source sensing module, typically ranging from 0.1 (humid) to 1.0 (extremely dry). The distance between the fire source and the vehicle is from the fire source identification module, and the unit is meters (m). This is the flammability coefficient, derived from the multi-source sensing module. It is obtained by querying a preset table after identifying the type of flammable material using 3D vision. For example, a tent has a coefficient of 0.3, and a haystack has a coefficient of 0.9. The distance data for flammable materials comes from the multi-source sensing module and is calculated by the three-dimensional vision sensor as the three-dimensional straight-line distance from the fire source to the specific flammable material. The unit is meters (m).

[0083] The dynamic safety module primarily calculates and updates the recommended minimum safe distance in real time based on environmental conditions, and transforms abstract risk data into intuitive graphics, charts, and text prompts on the vehicle's infotainment screen.

[0084] The dynamic safety module obtains the fire source size rating L, wind speed data V, and vegetation dryness I from the risk assessment module or sensors; and uses the minimum safe distance formula:

[0085]

[0086] In the formula, 4 represents the minimum safe distance, and 4 is the safety factor. For fire source size rating, For wind speed data, This is data on vegetation aridity.

[0087] Draw three concentric rings with the vehicle icon as the center of the screen. The radii of these three concentric rings are based on the minimum safe distance. Dynamic scaling;

[0088] Red inner ring (high-risk area): radius = Any object (especially a source of fire) entering this area represents a breach of the safety boundary and poses an extremely high risk.

[0089] Yellow inner ring (warning zone): radius = 1.5 * The system indicates that we are approaching a dangerous area and need to be more vigilant.

[0090] Green outer ring (safe zone): radius = 2 * Or larger, indicating relative safety.

[0091] Each new minimum safe distance received Upon receiving the value, the radius of the three rings is immediately recalculated, the vehicle's graphics drawing interface is invoked, the old rings are cleared, and new rings are drawn using the corresponding colors (red, yellow, and green) and transparency. Icons for fire sources and flammable materials are drawn at the corresponding positions in the ring-shaped warning zone based on their actual distance and direction. For example, a fire source 10 meters away from the vehicle... If it's 15 meters, it will be drawn outside the red ring and inside the yellow ring.

[0092] The wind direction and speed are synchronously acquired from the wind speed sensor. A "rose diagram" base (circular dial) is drawn at a fixed position in one corner of the screen (such as the upper right corner). An arrow is drawn at the center of the circle, pointing in the direction the wind is blowing (for example, the arrow points to the bottom of the screen if it is a north wind). The length of the arrow is proportional to the wind speed. The greater the wind speed, the longer the arrow. Flammable materials identified by the 3D vision sensor are marked with specific icons (such as a small tent icon) on the corresponding angle scale of the rose diagram according to their actual azimuth angle relative to the vehicle (such as a tent in the northeast direction of 30°). Therefore, it is easy to see at a glance which way the wind is blowing and in which direction the flammable materials are located from the fire source (upwind or downwind).

[0093] For text prompts, display "Current minimum safe distance is..." directly on the vehicle's infotainment screen or main control screen. "rice", among which It is the calculated minimum safe distance value (usually rounded to an integer or one decimal place), and it is refreshed every 3 seconds.

[0094] The flameout monitoring module is responsible for continuously monitoring the temperature and determining the status of the ember area after the user confirms that the flameout has been extinguished, preventing smoldering and reignition, and forming a "closed loop" for fire safety.

[0095] The vehicle's infotainment screen or main control screen displays a "Voltage Off Confirmation" button. When the user clicks it manually, the module receives a trigger signal and also provides a "Force End" button, allowing the user to terminate monitoring in advance. Centered on the last known fire source location, a rectangular area 1.5 times larger than the original candidate fire source area is designated as the "ember area." The sampling frequency of the multispectral sensor (especially the thermal imaging unit) is adjusted to 1Hz, focusing on the ember area for continuous monitoring for 30 minutes. During these 30 minutes, the module enters a continuous loop, executing the following detection process: reading the temperature matrix of the ember monitoring area from the thermal imaging unit, calculating the highest temperature T_max in the area, and if T_max > 80°C, triggering a level one response: broadcasting "Warning, ember temperature too high, please confirm complete extinguishment," and displaying a yellow warning icon and real-time temperature value on the vehicle's infotainment system; maintaining a 10-second temperature sliding window, calculating the difference ΔT between the current temperature and the temperature 10 seconds ago, and if ΔT > 30°C (i.e., heating rate > 3°C / second), it indicates a rapid increase in the ember area temperature, and the flame color threshold (R > 200, G < 150) from the fire source identification module is applied to the ember area. If B < 100, analyze the texture features (using a grayscale co-occurrence matrix) and color features (grayish-white tones, saturation below the threshold) of the ember area to determine whether flames and smoke appear in the ember area; if the temperature of the ember area rises sharply and flames and smoke appear in the ember area, it is determined to be reignition, triggering a secondary response: activate a 1000Hz high-frequency buzzer (higher than the normal warning tone of 800Hz), control the in-vehicle LED warning lights to flash red at a frequency of 5Hz, activate the emergency recording mode, save 30 seconds of video before and after the determination of reignition, and switch the vehicle screen or main control screen to a full-screen red warning, displaying "Reignition risk detected! Please take immediate action!"; when T_max < At 50°C, a 5-minute safety countdown begins. During these 5 minutes, it is still necessary to verify every second whether T_max remains below 50°C. If the temperature of each sampling point is below 50°C within 5 minutes, it is considered safe and a safety response is triggered: push notification: "Embers have cooled safely, monitoring ended.", all alerts are turned off, the monitoring loop is exited, and the monitoring log for this session, including the highest temperature curve and event records, is saved.

[0096] Based on the aforementioned engine shutdown monitoring module, an emergency linkage module is derived. This emergency linkage module continuously monitors the data streams from the risk assessment module and the wind speed sensor, receiving the risk index R (from the risk assessment module) and wind speed data V (from the CAN bus, updated 10 times per second) in real time. A 3-second sliding window is used; if the risk index R > 0.5 and the wind speed data V > 10 within the window... When the speed reaches m / s and lasts for 3 seconds, the alarm is activated. First, the emergency channel of the vehicle's audio system is invoked, playing a pre-recorded 120-decibel alarm sound consisting of three short horn beeps (0.5 seconds on, 0.2 seconds off) followed by a 1-second pause, repeating in a loop. The in-vehicle screen flashes red (1Hz) across the entire screen, all control buttons are hidden, and only the emergency information is displayed. The vehicle's hazard warning lights (double flashers) are activated outside the vehicle; if supported, the headlights flash at a high frequency. Second, a picture-in-picture video is generated, with the main image showing visible light and a small window displaying thermal imaging and risk data overlaid. The video file is saved to a protected storage partition, marked "read-only - emergency" to prevent it from being overwritten. Finally, a remote alarm signal is sent using the vehicle's 4G / 5G network. The T-BOX connects to the user's mobile phone via Bluetooth and communicates using mobile network and satellite communication modules (such as those in vehicles). A simplified warning package is sent to a designated contact and uploaded to the cloud service. This simplified warning package includes at least: a high-risk fire notification, the current vehicle location, the risk index, real-time wind speed, and the time. If transmission fails, it retryes every 60 seconds, up to a maximum of 3 times. After the alarm is triggered, a "Confirm Safety" button is displayed on the vehicle's screen or the user's mobile phone; the alarm is deactivated only by the user manually clicking it. If a risk index R <= 0.4 and wind speed V < 8 m / s are subsequently detected and remain so for 3 seconds, the alarm is automatically canceled.

[0097] like Figure 2 As shown, this is the second embodiment of the present invention, which provides a vehicle-mounted integrated camping fire safety monitoring and fire risk early warning method, including:

[0098] Acquire and synchronize multi-source data related to fire risk monitoring in real time, and output standardized multi-source data, including: visible light image data, thermal imaging data, wind speed data, vegetation dryness data, flammability coefficient data, and flammable material distance data;

[0099] Based on the visible light image data and thermal imaging data, the flame confidence level is calculated through multispectral collaborative calculation. When it is a real flame, the size level of the fire source and the distance of the fire source from the vehicle are obtained based on the visible light data.

[0100] Based on the fire source size level, fire source distance from vehicle, wind speed data, vegetation dryness data, flammability coefficient, and flammability distance data, a risk index is obtained according to the risk formula.

[0101] Based on the fire source size rating, wind speed data, and vegetation dryness data, the minimum safe distance is obtained using a formula.

[0102] Real-time visual monitoring of fire source risks is achieved through a graphical interface, including a circular warning zone, wind rose diagram, and warning text.

[0103] Based on the multispectral sensor and the flameout monitoring rules, the ember area is monitored, and different safety responses are triggered according to changes in the state of the ember area.

[0104] In summary, this invention achieves proactive safety protection throughout the entire lifecycle of camping fire prevention, from identification, assessment, and early warning to post-fire monitoring, through multi-source sensor fusion intelligent algorithms. Its beneficial effects are significant: First, it innovatively integrates a multispectral fire source identification algorithm combining visible light and thermal imaging, and uses flame flicker and temperature field characteristics for confidence level determination, effectively eliminating environmental interference and significantly improving the accuracy and robustness of fire source detection. Second, it breaks through the limitations of traditional passive monitoring and static alarms. By constructing a dynamic risk model that integrates fire source size, wind speed, dryness, and distance to flammable materials, it achieves real-time quantitative assessment and prediction of fire risk. Furthermore, it establishes for the first time a method for calculating and visually indicating safe distances that dynamically adjust with meteorological conditions, making early warning information scientific and intuitive. Finally, the system forms a complete fire safety closed loop. Specifically targeting the major hazard of ember reignition, it designs a post-fire-extinguishing continuous monitoring and reignition cross-verification mechanism based on temperature-time dual thresholds, and coordinates with an emergency linkage module. This allows for automatic activation of multi-level alarms and evidence collection under high-risk conditions, fundamentally improving fire prevention capabilities for outdoor camping activities.

[0105] In the above embodiments, implementation can be achieved, in whole or in part, through software, hardware, firmware, or any other combination thereof. When implemented in software, it can be implemented, in whole or in part, as a computer program product, which includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions according to this application are generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transferred from one computer-readable storage medium to another.

[0106] Furthermore, the functional units in the various embodiments of this application can be integrated into a processing module, or each unit can exist physically separately, or two or more units can be integrated into a module. The integrated module can be implemented in hardware or as a software functional module. If the integrated module is implemented as a software functional module and sold or used as an independent product, it can also be stored in a computer-readable storage medium. This storage medium can be a read-only memory, a disk, or an optical disk, etc.

[0107] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any person skilled in the art can easily conceive of various variations or substitutions within the technical scope disclosed in this application, and these should all be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system, characterized in that, include: Multi-source sensing module: used to acquire and time-synchronize multi-source data related to fire risk monitoring, and output standardized multi-source data, including: visible light image data, thermal imaging data, wind speed data, vegetation dryness data, flammability coefficient and flammable distance data; Fire source identification module: Based on the visible light image data and thermal imaging data, the flame confidence level is calculated through multispectral collaborative calculation. When it is a real flame, the size level of the fire source and the distance of the fire source from the vehicle are obtained based on the visible light data. Risk assessment module: Based on the fire source size level, distance of fire source from vehicle, wind speed data, vegetation dryness data, flammability coefficient, and distance of flammable material data, a risk index is obtained according to the risk formula; Dynamic safety module: includes a safety distance calculation unit and a graphical interface generation unit; The safe distance calculation unit calculates the minimum safe distance based on the fire source size level, wind speed data, and vegetation dryness data using a formula; the image interface generation unit is used for real-time visual fire source risk monitoring, including a ring-shaped warning zone, a wind rose diagram, and warning text. Flameout monitoring module: Used to monitor the ember area and trigger different safety responses based on changes in the state of the ember area.

2. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 1, characterized in that, The multi-source sensing module includes: Multispectral sensor: includes a visible light imaging unit for capturing ambient light reflected by the scene and generating visible light image data; a thermal imaging unit for detecting mid- and far-infrared radiation emitted by the object itself and generating thermal imaging data; and analysis of vegetation areas based on the visible light imaging unit, as well as obtaining vegetation dryness data by querying a dryness lookup table. Wind speed sensor: Located on the roof, trunk door or roof rack, used to collect wind speed data and output it through the controller area network bus; 3D vision sensor: Used to acquire the distance to flammable materials and ignition sources; based on a color image stream, it identifies flammable materials and ignition sources in the field of view through a built-in visual recognition algorithm, and acquires the corresponding 3D spatial coordinates. The distance data of flammable materials is then obtained according to a formula. ； In the formula, This is distance data for flammable materials. For fire source coordinate, For fire source coordinate, For fire source coordinate, Flammable coordinate, Flammable coordinate, Flammable coordinate.

3. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 2, characterized in that, Based on the flammable material, the flammable material coefficient is obtained according to a preset flammable material coefficient lookup table.

4. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 2, characterized in that, The fire source identification module includes: Based on the visible light image data and thermal imaging data, regions that suddenly appear or continuously move in the image are analyzed, and regions matching the flame color are selected according to a preset flame color threshold. Candidate fire source regions are then obtained based on the temperature of these regions. The flame color threshold includes: in the red-green-blue color space, the red component value is greater than 200, the green component value is less than 150, and the blue component value is less than 100. A flame confidence level is then obtained based on the candidate fire source regions. The expression is: ； In the formula, A_flicker is the number of flickering pixels in the candidate region, A_region is the total number of pixels in the candidate region, ΔT_max is the maximum temperature difference between the highest temperature in the candidate region and the ambient temperature, and the coefficients 0.6 and 0.4 represent the weights of flickering characteristics and temperature characteristics, respectively. When the flame confidence level exceeds a preset value, the candidate fire source area is considered a real flame. Based on the visible light image data, the flame size level L is obtained through a flame size level lookup table, and the distance D from the fire source to the vehicle is calculated according to the monocular vision ranging principle. The expression is: ； In the formula, f is the camera focal length, W_actual is the actual physical size of the reference object, and W_pixels is the pixel size of the fire source in the image.

5. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 1, characterized in that, The risk formula is: ； In the formula, As a risk index, For fire source size rating, For wind speed data, This is data on vegetation aridity. The distance between the fire source and the vehicle. For flammability coefficient, This is distance data for flammable materials.

6. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 1, characterized in that, In the dynamic safety module, the minimum safe distance is calculated using the following formula: ； In the formula, 4 represents the minimum safe distance, and 4 is the safety factor. For fire source size rating, For wind speed data, This is data on vegetation aridity. The image interface generation unit includes: The ring-shaped warning zone is divided into three color rings: red, yellow, and green, each corresponding to a different level of fire risk, and is installed on the vehicle's infotainment screen. The wind rose diagram displays the current wind direction, wind speed, and location of flammable materials in real time. The prompt text displays the current minimum safe distance in real time.

7. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 2, characterized in that, The engine shutdown monitoring module includes: When the "Confirm Extinguishing" button is pressed, monitoring of the ember area will begin according to the preset time. Based on the multispectral sensor, when the temperature of the ember area is greater than 80 degrees, an early warning is output; if the temperature is less than 80 degrees, the system remains silent and continues to monitor. When the temperature rise rate in the ember area exceeds the preset value and flame or smoke characteristics are captured simultaneously, a high-frequency audible and visual alarm is activated and the recording function is automatically started. When the highest temperature in the ember area is below 50 degrees Celsius and this condition persists for 5 minutes, the push notification indicates that the area is in a safe state.

8. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 7, characterized in that, It also includes an emergency linkage module: if the risk index is greater than 0.5 and the wind speed data is greater than 10 meters per second, then the sound and light alarm is activated, video recording is started, and an alarm signal is sent.

9. The vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system according to claim 2, characterized in that, The vegetation aridity data includes: Based on the visible light unit, the visible light imaging data of the vegetation area is analyzed. In the hue-saturation-brightness color space, the yellow and brown ranges are set as the withered yellow state. The number of all pixels belonging to the withered yellow state is counted. By calculating the ratio of the number of withered yellow state pixels to the total number of pixels in the vegetation area, the real-time percentage of withered yellow state pixels is obtained. The percentage of withered yellow state pixels is input into a preset dryness lookup table to obtain vegetation dryness data.

10. A vehicle-mounted integrated camping fire safety monitoring and fire risk early warning method, applied to the vehicle-mounted integrated camping fire safety monitoring and fire risk early warning system as described in any one of claims 1-9, characterized in that, include: Acquire and synchronize multi-source data related to fire risk monitoring in real time, and output standardized multi-source data, including: visible light image data, thermal imaging data, wind speed data, vegetation dryness data, flammability coefficient data, and flammable material distance data; Based on the visible light image data and thermal imaging data, the flame confidence level is calculated through multispectral collaborative calculation. When it is a real flame, the size level of the fire source and the distance of the fire source from the vehicle are obtained based on the visible light data. Based on the fire source size level, fire source distance from vehicle, wind speed data, vegetation dryness data, flammability coefficient, and flammability distance data, a risk index is obtained according to the risk formula. Based on the fire source size rating, wind speed data, and vegetation dryness data, the minimum safe distance is obtained using a formula. Real-time visual monitoring of fire source risks is achieved through a graphical interface, including a circular warning zone, wind rose diagram, and warning text. Based on the multispectral sensor and the flameout monitoring rules, the ember area is monitored, and different safety responses are triggered according to changes in the state of the ember area.

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