Fireproof electronic display screen intelligent control system

Abstract

The invention relates to the technical field of fire fighting, and discloses an intelligent control system for a fireproof electronic display screen, and the system comprises a temperature monitoring module which collects the temperature data of each peripheral region in real time through a sensor array which is uniformly distributed in a region where the number of through holes at the back of a screen body exceeds a preset number; the smoke monitoring module collects the environment smoke concentration in real time through sensors installed at the positions of a plurality of through holes in the back of the screen body. The probe monitoring module acquires monitoring videos outside the screen body and at the perforation by means of a high-definition probe at the edge of the screen body or at the perforation position; the multi-source data analysis module establishes a three-dimensional temperature field model, a smoke diffusion track and fire source characteristic data based on temperature, smoke concentration and internal and external monitoring videos; and the intelligent control module triggers the fire-fighting linkage system according to the data and the multi-stage early warning rule, and intelligently controls the display screen at the same time. The intelligent level of fire prevention of the electronic display screen is improved, fire hazards can be automatically and efficiently dealt with without close attention of workers, and the management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fire protection, and in particular to an intelligent control system for a fire-proof electronic display screen. Background Art

[0002] In modern society, electronic displays are widely used in a variety of fields, including commercial advertising, traffic signs, and information dissemination. With the development of visual culture, fully enclosed displays and full-screen, immersive displays are creating a more immersive experience for viewers. However, during operation, electronic displays can be exposed to the risk of fires caused by external factors igniting the screen. Once a fire occurs, it not only damages the display itself but can also spread and cause larger accidents, posing a serious threat to life and property. Therefore, the development of an intelligent control system for fire-resistant electronic displays is of great significance. This system monitors key environmental indicators such as temperature and smoke levels in the surrounding environment of the electronic display in real time, and combined with video surveillance, it can promptly identify potential fire risks indoors and implement effective preventive and response measures. This not only protects electronic display equipment and extends its service life, but also significantly improves safety in public places and various application scenarios. With increasing awareness of safety issues, this intelligent control system has broad application prospects across various industries and is expected to become a standard technology for electronic display safety, driving the electronic display industry towards a safer and more reliable direction.

[0003] However, existing fire prevention methods for immersive electronic display screens have numerous shortcomings. For fire hazard monitoring, they lack the ability to integrate and analyze multi-source monitoring data. Ultimately, it's difficult to timely trigger the fire alarm system and intelligently control electronic display screens based on this critical information and multi-level warning rules, hindering effective prevention and response to indoor fires.

[0004] Therefore, the present invention proposes an intelligent control system for a fireproof electronic display screen. Summary of the Invention

[0005] The present invention provides an intelligent control system for fire-proof electronic display screens. Based on a variety of monitoring data, it establishes a three-dimensional spatial temperature field model, smoke diffusion trajectory, and fire source characteristic data. It can deeply analyze the spatial conditions of the electronic display screen, integrate scattered data into systematic and intuitive information, and accurately locate fire hazard points and development trends. The fire linkage system is triggered based on the analysis results and multi-level warning rules, which can quickly respond to fire hazards and take fire-fighting and other fire-fighting measures in a timely manner to reduce the losses caused by fire. At the same time, the fire-proof electronic display screen is intelligently controlled, such as shutting down the display screen in time at the early stage of a fire to avoid the risk of fire being exacerbated by electronic equipment failure. The overall design of the system improves the intelligent level of fire prevention for electronic display screens. It does not require close human supervision at all times and can automatically and efficiently respond to fire hazards, saving labor costs and improving management efficiency. The comprehensive monitoring and intelligent control functions of the system help to ensure the stable and safe operation of electronic display screens, extend their service life, and reduce equipment damage and economic losses caused by accidents such as fires.

[0006] The present invention provides a fire-proof electronic display screen intelligent control system, comprising: A temperature monitoring module is used to collect temperature data of various peripheral areas of the screen in real time based on a temperature sensor array evenly distributed in an area where the number of through holes behind the screen of the electronic display exceeds a preset number; The smoke monitoring module is used to collect real-time smoke concentrations at multiple locations within the environment where the screen is located based on smoke sensors installed at multiple through-hole positions behind the screen, with the sensing ports facing the air flow direction of the front through-holes; Probe monitoring module, used to obtain screen monitoring video based on high-definition probes; The multi-source data analysis module is used to establish a three-dimensional temperature field model of the space where the electronic display screen is located, smoke diffusion trajectory and fire source characteristic data based on the temperature data of each area around the screen, multiple smoke concentrations in the environment where the screen is located, and screen monitoring video; The intelligent control module is used to trigger the fire linkage system based on the three-dimensional spatial temperature field model of the space where the electronic display screen is located, the smoke diffusion trajectory, the fire source characteristic data and the multi-level warning rules, and at the same time, to intelligently control the fire-proof electronic display screen.

[0007] Preferably, the multi-source data analysis module includes: The temperature field model establishment submodule is used to interpolate and model the temperature data of each area around the screen to generate a three-dimensional temperature field model of the space where the electronic display screen is located; The smoke diffusion model establishment submodule is used to generate smoke diffusion trajectories based on the smoke concentrations at multiple locations around the screen; The fire source feature analysis submodule is used to analyze the fire source feature data in the screen monitoring video.

[0008] Preferably, the smoke diffusion model establishment submodule includes: The first sorting unit is configured to sort the monitoring positions of all smoke sensors according to the most recently acquired smoke concentrations at multiple locations in the environment where the screen is located, from large to small, to obtain a first position sequence; a second sorting unit, configured to calculate a concentration change trend value for each monitoring location based on a historical smoke concentration value sequence at the corresponding monitoring location monitored by each smoke sensor, and sort the monitoring locations of all smoke sensors based on a descending order of concentration change trend values ​​to obtain a second location sequence; an abnormality judgment unit, configured to calibrate the latest safety monitoring period based on a sequence of historical smoke concentration values ​​at corresponding monitoring locations monitored by all smoke sensors, and determine the earliest abnormal anchoring moment and abnormality degree of each smoke sensor within the latest safety monitoring period based on all abnormal smoke concentration values ​​occurring within the latest safety monitoring period in the sequence of historical smoke concentration values ​​at corresponding monitoring locations monitored by each smoke sensor; a priority value calculation unit, configured to calculate a priority value of a monitoring position of each smoke sensor based on the earliest abnormal anchoring moment and abnormality degree of each smoke sensor in a latest safety monitoring cycle, a ranking value of the corresponding monitoring position in the first position sequence, and a ranking value in the second position sequence; The trajectory simulation unit is used to generate a smoke diffusion trajectory based on the priority values ​​of the monitoring positions of all smoke sensors.

[0009] Preferably, the trajectory simulation unit includes: The starting point and circle range determination subunit is used to take the monitoring position corresponding to the maximum priority value among all the monitoring positions of the smoke sensors as the assumed starting point position, and construct a circle range area of ​​the pseudo starting point position with the pseudo starting point position as the circle center and the distance between the pseudo starting point position and the monitoring position corresponding to the second largest priority value as the radius; A first interpolation processing subunit is configured to, when the circular range includes the remaining monitoring positions excluding the false starting position and the monitoring position corresponding to the second largest priority value, perform interpolation processing on multiple interpolation positions within the circular range based on the historical smoke concentration value sequence at the false starting position, the historical smoke concentration value sequence at the monitoring position corresponding to the second largest priority value, and the historical smoke concentration value sequences of all remaining monitoring positions within the circular range excluding the false starting position and the monitoring position corresponding to the second largest priority value, to obtain the historical smoke concentration value sequences of the multiple interpolation positions within the current circular range; A priority value determination subunit, configured to determine a current priority value for each anchor position based on a historical smoke concentration value sequence of all interpolation positions and a historical smoke concentration value sequence of all monitoring positions; The first trajectory fitting subunit is used to fit the smoke diffusion trajectory based on the current priority values ​​of all anchor positions.

[0010] Preferably, the first trajectory fitting subunit includes: The starting point and circle range determination terminal is used to determine the latest false starting point based on the current priority values ​​of all anchor positions, and to construct a circle range area of ​​the latest false starting point with the latest false starting point as the center and the distance between the latest false starting point and the anchor position corresponding to the second largest current priority value as the radius; The trajectory fitting end is used to interpolate and calculate the priority value of the circular range area of ​​the latest false starting position based on the historical smoke concentration value sequence of the existing anchor position when the circular range area of ​​the latest false starting position contains the remaining anchor positions except the latest false starting position and the anchor position corresponding to the second largest current priority value, so as to obtain the latest anchor position set, until the latest circular range area obtained based on the latest obtained anchor position set does not contain the remaining anchor positions except the latest false starting position and the anchor position corresponding to the second largest latest priority value, then the latest false starting position and the anchor position corresponding to the second largest latest priority value are connected as a partial smoke diffusion trajectory, and the anchor position corresponding to the second largest latest priority value is updated as the false starting position, and the next connection position of the partial smoke diffusion trajectory is determined, until all anchor positions are connected to obtain the smoke diffusion trajectory.

[0011] Preferably, it also includes: The second trajectory fitting subunit is used to connect the false starting position and the monitoring position corresponding to the second largest priority value as a partial smoke diffusion trajectory when the circular range does not contain the remaining monitoring positions except the false starting position and the monitoring position corresponding to the second largest priority value, and update the monitoring position corresponding to the second largest priority value to the false starting position, and determine the next connection position of the partial smoke diffusion trajectory until all anchor positions are connected to obtain the smoke diffusion trajectory.

[0012] Preferably, the fire source characteristic analysis submodule includes: A suspected flame area screening unit is used to identify all irregular areas surrounded by irregular edges in each video frame of the screen monitoring video based on an edge detection algorithm, and to screen out the suspected flame area in each video frame from all irregular areas in each video frame based on preset saturation thresholds and brightness thresholds; A physical space positioning unit is used to determine the three-dimensional coordinate range of each suspected flame area in the world coordinate system based on a triangulation positioning algorithm as the physical space range of each suspected flame area; a real flame region screening unit, configured to obtain, based on a multi-spectral fusion monitoring method, a signal intensity of a strong absorption peak signal within a preset wavelength range within the physical space of each suspected flame region, and determine, based on the signal intensity of the strong absorption peak signal within the preset wavelength range within the physical space of each suspected flame region, whether the corresponding suspected flame region is a real flame region, using the determination result for the corresponding suspected flame region as the determination result, and screening out all real flame regions based on the determination results of all suspected flame regions; An inter-frame correspondence unit is used to perform inter-frame correspondence on all real flame areas in all video frames in the screen monitoring video to obtain a sequence of real flame areas of all real fire sources; The fire source characteristic data extraction unit is used to extract fire source characteristic data based on the real flame area sequence of all real fire sources.

[0013] Preferably, the fire source characteristic data extraction unit includes: A physical space positioning subunit, configured to determine the location of each real fire source based on a triangulation method and a sequence of real flame areas of each real fire source; The flame spread direction analysis subunit is used to track the pixel motion vector of the real flame area sequence of each real fire source to obtain the flame spread direction of each real fire source; The flicker frequency analysis subunit is used to track the periodic changes in regional brightness of the real flame region sequence of each real fire source and obtain the flicker frequency of each real fire source; The diffusion speed analysis subunit is used to perform regional area diffusion trend analysis on the real flame area sequence of each real fire source to obtain the diffusion speed of each real fire source; The multi-dimensional feature summary sub-unit is used to treat the occurrence location, flame spread direction, flicker frequency, and spread speed of all real fire sources as fire source feature data.

[0014] Preferably, the intelligent control module includes: The fire intensity level calculation submodule is used to calculate the current fire intensity level based on the three-dimensional temperature field model, smoke diffusion trajectory, and fire source characteristic data within the space where the electronic display screen is located; The fire linkage trigger submodule is used to trigger the fire linkage system based on the current fire level value; The intelligent control submodule is used to intelligently control the fire protection electronic display screen based on the current fire level value.

[0015] Preferably, the intelligent control submodule includes: Model building unit, used to build an intelligent control model of an electronic display screen; The intelligent control unit is used to input the current fire level value into the intelligent control model of the electronic display screen, obtain the current intelligent control instructions of the fire-proof electronic display screen, and intelligently control the fire-proof electronic display screen based on the current intelligent control instructions.

[0016] The present invention offers the following advantages over existing technologies: Multi-module collaborative monitoring. The temperature monitoring module utilizes a temperature sensor array to collect real-time temperature data from various areas surrounding the screen, the smoke monitoring module uses smoke sensors at specific locations to obtain smoke concentration, and the probe monitoring module utilizes high-definition probes to generate surveillance video. This enables multi-dimensional, comprehensive, real-time status monitoring of the electronic display screen's surroundings, providing a rich data foundation for accurately identifying potential fire hazards. The multi-source data analysis module uses multiple monitoring data to build a three-dimensional spatial temperature field model, smoke diffusion trajectory, and fire source characteristic data. This allows for in-depth analysis of the spatial conditions surrounding the electronic display screen, integrating scattered data into systematic and intuitive information to accurately locate fire hazard points and development trends. The intelligent control module triggers the fire linkage system based on the analysis results and multi-level warning rules, enabling rapid response to fire hazards and timely implementation of firefighting measures, thereby reducing fire damage. Furthermore, intelligent control is implemented for fire-resistant electronic displays, such as shutting down the display in the early stages of a fire to prevent fire risks exacerbated by electronic equipment failures. The overall system design enhances the intelligent level of fire prevention for electronic display screens, eliminating the need for constant human oversight and enabling automatic and efficient response to fire hazards, saving labor costs and improving management efficiency. The system's comprehensive monitoring and intelligent control functions help ensure the stable and safe operation of electronic display screens, extend their service life, and reduce equipment damage and economic losses caused by accidents such as fire.

[0017] Other features and advantages of the present invention will be described in the following description, and in part will become apparent from the description, or will be understood by practicing the present invention. The purpose and other advantages of the present invention can be achieved and obtained through the structures specifically pointed out in this application document.

[0018] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] The accompanying 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 of the present invention. In the accompanying drawings: Figure 1 The following is a logic flow chart for implementing an intelligent control system for a fire-proof electronic display screen in an embodiment of the present invention. DETAILED DESCRIPTION

[0020] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0021] Example 1: The present invention provides a fire-proof electronic display screen intelligent control system, referring to Figure 1 ,include: A temperature monitoring module is used to collect temperature data of various peripheral areas of the screen in real time based on a temperature sensor array evenly distributed in an area where the number of through holes behind the screen of the electronic display exceeds a preset number; The smoke monitoring module is used to collect real-time smoke concentrations at multiple locations within the environment where the screen is located based on smoke sensors installed at multiple through-hole positions behind the screen, with the sensing ports facing the air flow direction of the front through-holes; Probe monitoring module, used to obtain screen monitoring video based on high-definition probes; The multi-source data analysis module is used to establish a three-dimensional temperature field model of the space where the electronic display screen is located, smoke diffusion trajectory and fire source characteristic data based on the temperature data of each area around the screen, multiple smoke concentrations in the environment where the screen is located, and screen monitoring video; The intelligent control module is used to trigger the fire linkage system based on the three-dimensional spatial temperature field model of the space where the electronic display screen is located, the smoke diffusion trajectory, the fire source characteristic data and the multi-level warning rules, and at the same time, to intelligently control the fire-proof electronic display screen.

[0022] In this embodiment, the temperature data of each peripheral area of ​​the screen is collected by the temperature monitoring module based on the temperature sensor array in the area where the number of through holes behind the screen exceeds a preset number, which is real-time temperature information about each area of ​​the electronic display screen.

[0023] In this embodiment, the inner portion of the screen specifically refers to the inner space immediately adjacent to or near the screen's power supply box. The smoke monitoring module installs multiple smoke sensors there, with the sensing ports facing the forward airflow direction. This allows for timely and accurate detection of fires caused by the surrounding environment igniting the screen.

[0024] In this embodiment, the smoke concentrations at multiple locations within the environment where the screen is located are information collected in real time by the smoke monitoring module using multiple groups of smoke sensors installed at specific positions on the back of the screen.

[0025] In this embodiment, screen surveillance video is captured by a high-definition camera mounted outside the screen. This video provides information about fire or smoke generation near the electronic display. Analysis of this video can reveal whether a fire has occurred near the screen, or whether any unusual human activity poses a safety threat to the display.

[0026] In this embodiment, the three-dimensional temperature field model, smoke diffusion trajectory and fire source characteristic data in the space where the electronic display screen is located are: The three-dimensional temperature field model visually displays the temperature distribution of the space where the electronic display screen is located in three dimensions, helping to identify potential overheating areas; The smoke diffusion trajectory shows the smoke propagation path in space, which is helpful for inferring the source and spread direction of the fire; Fire source characteristic data includes the location of the fire source, flame spread direction, flicker frequency, spread speed, etc.

[0027] In this embodiment, the fire linkage system is a collection of fire-related actions triggered by the intelligent control module based on a three-dimensional temperature field model of the space where the electronic display screen is located, smoke diffusion trajectories, fire source characteristics, and multi-level warning rules. This system may include activating fire-fighting equipment (such as sprinkler systems and fire extinguishers), issuing alarms to notify personnel to evacuate, and linking other fire-fighting facilities (such as fire shutters and smoke exhaust systems). The goal is to quickly take effective measures when a fire occurs to control the spread of the fire, minimize fire damage, and protect life and property.

[0028] In this embodiment, the fire linkage system is triggered, and at the same time, the fire-proof electronic display screen is intelligently controlled. For example, when a fire occurs, the power supply is turned off, and at the same time, the emergency power supply is started, the emergency light is turned on, and the sprinkler fire extinguishing system of the fire linkage system is triggered to extinguish the fire at the fire source, and the screen on the roof is opened like a door.

[0029] Example 2: Based on Example 1, the multi-source data analysis module includes: The temperature field model establishment submodule is used to interpolate and model the temperature data of each area around the screen to generate a three-dimensional temperature field model of the space where the electronic display screen is located; The smoke diffusion model establishment submodule is used to generate smoke diffusion trajectories based on the smoke concentration in multiple locations in the screen environment; The fire source feature analysis submodule is used to analyze the fire source feature data in the screen monitoring video.

[0030] In this embodiment, interpolation is used because the temperature sensor array only collects temperature data for discrete areas of the screen, while the temperature in real space varies continuously. Interpolation methods can be used to estimate the temperature of locations between known discrete points based on the temperature values. For example, algorithms such as linear interpolation and spline interpolation can be used to calculate approximate temperature values ​​for a series of intermediate locations between adjacent temperature sensor areas, thereby more comprehensively reflecting the temperature distribution of the entire space behind the screen.

[0031] The model is constructed by integrating richer temperature data obtained through interpolation processing to form a three-dimensional spatial temperature field model. This model intuitively presents the temperature conditions at various locations within the space where the electronic display is located in three dimensions, allowing relevant personnel to clearly see the temperature distribution and whether there are areas with abnormally high temperatures. For example, in the model, high-temperature areas may be represented by red and low-temperature areas by blue. Through the visualization of different colors and heights, the temperature distribution is clear at a glance.

[0032] The beneficial effects of these technologies are as follows: The temperature field modeling submodule interpolates and models temperature data to generate a three-dimensional spatial temperature field model, clearly displaying temperature distribution and providing early warning of fire risks caused by overheating. The smoke diffusion modeling submodule generates diffusion trajectories based on smoke concentration, helping to determine the location and spread of fires and facilitating early prevention and control. The fire source characteristic analysis submodule captures fire source characteristic data from surveillance video, providing a basis for accurately triggering the fire linkage system and improving firefighting efficiency. This modular subdivision makes data analysis more professional and efficient, enhancing the accuracy and reliability of judgments. It also improves the system's maintainability and scalability, facilitating long-term optimization and upgrades.

[0033] Example 3: Based on Example 2, a smoke diffusion model is established as a submodule, including: The first sorting unit is configured to sort the monitoring positions of all smoke sensors according to the most recently acquired smoke concentrations at multiple locations in the environment where the screen is located, from large to small, to obtain a first position sequence; a second sorting unit, configured to calculate a concentration change trend value for each monitoring location based on a historical smoke concentration value sequence at the corresponding monitoring location monitored by each smoke sensor, and sort the monitoring locations of all smoke sensors based on a descending order of concentration change trend values ​​to obtain a second location sequence; an abnormality judgment unit, configured to calibrate the latest safety monitoring period based on a sequence of historical smoke concentration values ​​at corresponding monitoring locations monitored by all smoke sensors, and determine the earliest abnormal anchoring moment and abnormality degree of each smoke sensor within the latest safety monitoring period based on all abnormal smoke concentration values ​​occurring within the latest safety monitoring period in the sequence of historical smoke concentration values ​​at corresponding monitoring locations monitored by each smoke sensor; a priority value calculation unit, configured to calculate a priority value of a monitoring position of each smoke sensor based on the earliest abnormal anchoring moment and abnormality degree of each smoke sensor in a latest safety monitoring cycle, a ranking value of the corresponding monitoring position in the first position sequence, and a ranking value in the second position sequence; The trajectory simulation unit is used to generate a smoke diffusion trajectory based on the priority values ​​of the monitoring positions of all smoke sensors.

[0034] In this embodiment, based on the historical smoke concentration value sequence of the corresponding monitoring location monitored by each smoke sensor, the concentration change trend value at each monitoring location is calculated. For example, a common method is to calculate the slope between adjacent data points. Assume that the historical smoke concentration value sequence is C1, C2, C3, ..., Cn, and the corresponding time points are t1, t2, t3, ..., tn. Taking the linear change trend as an example, two adjacent data points in the sequence (ti, Ci) and (ti+1, Ci+1) can be selected, and the average change rate of the smoke concentration between these two time points can be calculated using the formula (Ci+1-Ci) / (ti+1-ti). This is used as an approximation of the concentration change trend value within the time period.

[0035] If the calculated concentration change trend value is positive and large, it indicates that the smoke concentration at the corresponding monitoring location has increased rapidly during the time period, which may indicate that a fire is developing. If the concentration change trend value is negative, it indicates that the smoke concentration is decreasing, which may indicate that the fire is under control or the smoke is dissipating.

[0036] In this embodiment, the monitoring location refers to the specific point where the smoke sensor is placed.

[0037] In this embodiment, the historical smoke concentration value sequence is a smoke concentration data sequence continuously monitored and recorded by each smoke sensor over a period of time in the past.

[0038] In this embodiment, the latest safety monitoring period is calibrated based on the historical smoke concentration value sequence of the corresponding monitoring positions monitored by all smoke sensors. This is done by analyzing the historical smoke concentration value sequence to find a time period in which the smoke concentration fluctuation is small and within the normal range, and setting it as the latest safety monitoring period.

[0039] In this embodiment, an abnormal smoke concentration value refers to a value detected by the smoke sensor during the most recent safety monitoring cycle that significantly deviates from the normal smoke concentration range for that cycle. The presence of these abnormal values ​​may indicate a potential fire, as fires often cause dramatic changes in smoke concentration. For example, if the normal smoke concentration range at a monitoring location during the most recent safety monitoring cycle is between 0 and 5 units, and a smoke concentration of 15 is suddenly detected, then the value of 15 can be considered an abnormal smoke concentration value.

[0040] In this embodiment, based on all abnormal smoke concentration values ​​that occurred in the latest safety monitoring cycle in the historical smoke concentration value sequence of the corresponding monitoring location monitored by each smoke sensor, the earliest abnormal anchoring time and abnormality degree of each smoke sensor in the latest safety monitoring cycle are determined: The earliest abnormal anchoring moment indicates the time point when the abnormal smoke concentration value first appears in the latest safety monitoring cycle; The degree of abnormality is determined by calculating the difference between all abnormal smoke concentration values ​​and the upper limit of the normal range, or the average of the proportional relationship with the mean of the normal range.

[0041] In this embodiment, the priority value of the monitoring position of each smoke sensor is calculated based on the earliest abnormal anchoring time and abnormality degree of each smoke sensor in the latest safety monitoring cycle, the ranking value of the corresponding monitoring position in the first position sequence, and the ranking value in the second position sequence: The product of the ratio of the difference between the earliest abnormal anchoring moment of each smoke sensor in the latest safety monitoring cycle and the current moment to the duration of the latest safety monitoring cycle, the degree of abnormality, the ratio of the maximum ranking value in the first position sequence to the ranking value of the corresponding monitoring position in the first position sequence, and the ratio of the maximum ranking value in the second position sequence to the ranking value in the second position sequence is used as the priority value of the monitoring position of each smoke sensor.

[0042] The beneficial effects of the above technology are as follows: by sorting the smoke sensor monitoring positions according to the latest smoke concentration through the first sorting unit, the area with high current smoke concentration can be quickly located, providing preliminary clues for determining the source of the smoke. The second sorting unit calculates the concentration change trend value and sorts it, which can clearly present the smoke concentration change situation at each location and help capture the area where the smoke spreads rapidly. The abnormality judgment unit calibrates the latest safety monitoring cycle and determines the earliest abnormal anchor time and the degree of abnormality, which helps to accurately analyze the starting time and severity of the smoke abnormality, and provide key time nodes and severity information for prevention and control. The priority value calculation unit calculates the priority value of each monitoring location based on multiple data, comprehensively considering the impact of various factors on smoke diffusion, making the assessment of the importance of each location in smoke diffusion more accurate. The trajectory simulation unit generates a smoke diffusion trajectory based on the priority value, which can more accurately and intuitively display the smoke diffusion path, providing a more reliable basis for fire linkage and personnel evacuation, and greatly improving the comprehensiveness, accuracy and practicality of the system's smoke diffusion analysis.

[0043] Example 4: Based on Example 3, the trajectory simulation unit includes: The starting point and circle range determination subunit is used to take the monitoring position corresponding to the maximum priority value among all the monitoring positions of the smoke sensors as the assumed starting point position, and construct a circle range area of ​​the pseudo starting point position with the pseudo starting point position as the circle center and the distance between the pseudo starting point position and the monitoring position corresponding to the second largest priority value as the radius; A first interpolation processing subunit is configured to, when the circular range includes the remaining monitoring positions excluding the false starting position and the monitoring position corresponding to the second largest priority value, perform interpolation processing on multiple interpolation positions within the circular range based on the historical smoke concentration value sequence at the false starting position, the historical smoke concentration value sequence at the monitoring position corresponding to the second largest priority value, and the historical smoke concentration value sequences of all remaining monitoring positions within the circular range excluding the false starting position and the monitoring position corresponding to the second largest priority value, to obtain the historical smoke concentration value sequences of the multiple interpolation positions within the current circular range; A priority value determination subunit, configured to determine a current priority value for each anchor position based on a historical smoke concentration value sequence of all interpolation positions and a historical smoke concentration value sequence of all monitoring positions; The first trajectory fitting subunit is used to fit the smoke diffusion trajectory based on the current priority values ​​of all anchor positions.

[0044] In this embodiment, interpolation processing is performed on multiple interpolation positions within the circular range based on the historical smoke concentration value sequence at the pseudo starting position, the historical smoke concentration value sequence at the monitoring position corresponding to the second-highest priority value, and the historical smoke concentration value sequences of all remaining monitoring positions within the circular range, excluding the pseudo starting position and the monitoring position corresponding to the second-highest priority value. This yields a historical smoke concentration value sequence for multiple interpolation positions within the current circular range. After determining a circular range with the pseudo starting position as the center and a specific spacing as the radius, since other monitoring positions may exist within the range in addition to the pseudo starting position and the monitoring position corresponding to the second-highest priority value, these discrete monitoring positions cannot fully reflect the continuous changes in smoke concentration within the range. Therefore, interpolation processing is performed on multiple interpolation positions within the circular range using the three related historical smoke concentration value sequences. In this way, the smoke concentration at these interpolation positions at different time points over a period of time can be inferred, thereby obtaining a historical smoke concentration value sequence for multiple interpolation positions within the current circular range. For example, assuming that the smoke concentrations at the false starting point, the monitoring position corresponding to the second largest priority value, and the other remaining monitoring positions at a certain moment are A, B, C, etc., respectively, the smoke concentration at the interpolation position within the circle at that moment is calculated through a specific interpolation algorithm (such as linear interpolation, spline interpolation, etc.), forming a data point in the historical smoke concentration value sequence of the interpolation position. Repeat this process to obtain the historical smoke concentration value sequence of multiple interpolation positions.

[0045] In this embodiment, based on the historical smoke density value sequences of all interpolation positions and the historical smoke density value sequences of all monitoring positions, the current priority value of each anchor position is determined: The anchor positions include the interpolation positions within the circular range and the original monitoring positions. Taking into account the historical smoke concentration value sequences of all interpolation positions and monitoring positions, these sequences are analyzed and combined with the relevant factors that previously determined the priority values ​​(such as the earliest abnormal anchoring moment, the degree of abnormality, the ranking value in the sequence of different positions, etc.), the current priority value of each anchor position is re-determined. This means that the importance of each position in the smoke diffusion process is re-evaluated taking into account the richer data after interpolation. For example, the priority value of a monitoring position was originally determined only based on its own monitoring data, but after adding the data of the interpolation position, it was found that the smoke concentration changes at the monitoring position were closely related to those at the surrounding interpolation positions, and its current priority value may be adjusted.

[0046] The beneficial effects of the above technology are as follows: the starting point and circular range determination subunit uses the monitoring position corresponding to the maximum priority value as the assumed starting point position, and constructs the circular range area according to specific rules, thereby defining the key range for subsequent analysis, and can focus on the core area of ​​smoke diffusion, making the analysis more targeted and improving the efficiency of analysis. When the first interpolation processing subunit contains other monitoring positions within the circular range area, it performs interpolation processing to obtain a sequence of historical smoke concentration values ​​for multiple interpolation positions, effectively filling the data gaps in the area, enriching the data details, and making the analysis of smoke concentration changes in the area more accurate. The priority value determination subunit combines the historical smoke concentration value sequences of the interpolation position and the monitoring position to determine the current priority value of each anchor position, and comprehensively considers multiple data to make the evaluation of the importance of each position in smoke diffusion more comprehensive and reasonable. The first trajectory fitting subunit fits the smoke diffusion trajectory based on the current priority values ​​of all anchor positions. Using the optimized priority value information, it can present a smoke diffusion path that is more in line with the actual situation, providing a more reliable and accurate reference basis for fire fighting decision-making and personnel evacuation planning, thereby significantly improving the accuracy and practicality of the system's simulation of smoke diffusion trajectories, and further enhancing the ability of the entire fire-proof electronic display screen intelligent control system to deal with fire hazards.

[0047] Example 5: Based on Example 4, the first trajectory fitting subunit includes: The starting point and circle range determination terminal is used to determine the latest false starting point based on the current priority values ​​of all anchor positions, and to construct a circle range area of ​​the latest false starting point with the latest false starting point as the center and the distance between the latest false starting point and the anchor position corresponding to the second largest current priority value as the radius; The trajectory fitting end is used to interpolate and calculate the priority value of the circular range area of ​​the latest false starting position based on the historical smoke concentration value sequence of the existing anchor position when the circular range area of ​​the latest false starting position contains the remaining anchor positions except the latest false starting position and the anchor position corresponding to the second largest current priority value, so as to obtain the latest anchor position set, until the latest circular range area obtained based on the latest obtained anchor position set does not contain the remaining anchor positions except the latest false starting position and the anchor position corresponding to the second largest latest priority value, then the latest false starting position and the anchor position corresponding to the second largest latest priority value are connected as a partial smoke diffusion trajectory, and the anchor position corresponding to the second largest latest priority value is updated as the false starting position, and the next connection position of the partial smoke diffusion trajectory is determined, until all anchor positions are connected to obtain the smoke diffusion trajectory.

[0048] In this embodiment, the latest pseudo starting point is determined based on the current priority values ​​of all anchor positions. This is to continuously update the starting point of the smoke diffusion trajectory simulation. By comparing the current priority values ​​of all anchor positions (including previously determined interpolated positions and monitoring positions), the anchor position with the largest current priority value is selected as the latest pseudo starting point.

[0049] In this embodiment, a circular region around the latest pseudo-starting point is interpolated and priority values ​​are calculated based on the historical smoke concentration value sequence of the existing anchor positions to obtain the latest set of anchor positions. After determining the latest pseudo-starting point, a circular region is constructed with this location as the center and the distance between it and the anchor position corresponding to the second-highest current priority value as the radius. Then, using the historical smoke concentration value sequence of the existing anchor position, interpolation is performed within this circular region. Similar to the previous processing of the other circular regions, an interpolation algorithm is used to estimate smoke concentrations at more locations within the circular region, resulting in new interpolated positions and their corresponding historical smoke concentration value sequences. Next, based on these new interpolated positions and the existing anchor positions, priority values ​​are recalculated, taking into account various factors (such as anomalies and concentration trends), to obtain the latest set of anchor positions. This process continuously refines and updates information about smoke diffusion locations, resulting in more accurate smoke diffusion simulations. For example, within the new circular range, the smoke concentration information of multiple new locations is obtained through interpolation. Then, based on the relationship between these locations and other anchor locations and the changes in smoke concentration, their priority values ​​are calculated to determine the latest set of anchor locations.

[0050] In this embodiment, the latest circular range area obtained based on the latest set of anchor positions does not contain any remaining anchor positions other than the latest pseudo starting position and the anchor position corresponding to the second largest latest priority value. This is a judgment condition. When only the latest pseudo starting position and the anchor position corresponding to the second largest latest priority value remain in the latest circular range area constructed, and there are no other remaining anchor positions, it means that within this local range, the construction of the smoke diffusion trajectory has reached a relatively complete state at the current stage, and the next connection operation can be carried out. The judgment of this condition helps to determine when to stop operations such as interpolation and priority value calculation within the circular range area and enter the trajectory connection stage to gradually complete the construction of the entire smoke diffusion trajectory.

[0051] In this embodiment, the anchor position corresponding to the second largest and most recent priority value is updated as a pseudo-starting position, and the next connection position of the partial smoke diffusion trajectory is determined until all anchor positions are connected to obtain the smoke diffusion trajectory. When the above judgment conditions are met, the anchor position corresponding to the second largest and most recent priority value is set as the new pseudo-starting position, and then the next anchor position connected to this position is determined as the next connection position of the partial smoke diffusion trajectory. In this way, the operation is repeated continuously, each time constructing a circular range area with the newly determined pseudo-starting position, performing interpolation processing, priority value calculation, judgment conditions, and connection operations until all anchor positions are connected, and finally forming a complete smoke diffusion trajectory. This process proceeds step by step, from the local to the overall, accurately depicting the diffusion path of the smoke in space, representing the approximate trajectory of the smoke diffusion, and intuitively showing the possible propagation direction and range of the smoke.

[0052] The beneficial effects of this technology include: the starting point and circular range determination end re-determines the latest pseudo-starting point location and constructs the circular range based on the current priority values ​​of all anchor positions. This dynamic updating of the starting point and range allows for continuous adjustment of key analysis areas based on real-time data, better tracking the core path of smoke diffusion and making the smoke diffusion trajectory simulation more accurate to actual dynamic changes. When additional anchor positions exist within the circular range, the trajectory fitting end performs interpolation and priority value calculations, continuously optimizing the set of anchor positions and refining the trajectory details to ensure a more accurate smoke diffusion trajectory, providing more precise information for determining the specific direction of smoke diffusion. Through continuous iteration, the smoke diffusion trajectory is generated by connecting all anchor positions. This gradual refinement and improvement makes the smoke diffusion trajectory generation process more rigorous, fully accounting for the relationships between various positions and the complexities of the smoke diffusion process. This series of operations effectively improves the accuracy and completeness of the smoke diffusion trajectory simulation, providing a more reliable basis for firefighters to formulate scientific and reasonable response strategies, helping to improve the efficiency and effectiveness of fire prevention and control, and enhancing the comprehensiveness and in-depth analysis of fire hazards within the entire fire protection electronic display intelligent control system.

[0053] Example 6: Based on Example 1, further comprising: The second trajectory fitting subunit is used to connect the false starting position and the monitoring position corresponding to the second largest priority value as a partial smoke diffusion trajectory when the circular range does not contain the remaining monitoring positions except the false starting position and the monitoring position corresponding to the second largest priority value, and update the monitoring position corresponding to the second largest priority value to the false starting position, and determine the next connection position of the partial smoke diffusion trajectory until all anchor positions are connected to obtain the smoke diffusion trajectory.

[0054] In this embodiment, the monitoring location corresponding to the second-highest priority value is updated as the pseudo-starting location, and the next connecting location for the partial smoke diffusion trajectory is determined until all anchor locations are connected to obtain a smoke diffusion trajectory. This operation is performed when the circular range determined in a certain step does not contain any remaining monitoring locations other than the pseudo-starting location and the monitoring location corresponding to the second-highest priority value. The monitoring location corresponding to the second-highest priority value is updated as the pseudo-starting location because it has a higher priority in the current stage of the smoke diffusion simulation and may be a key node in smoke diffusion. For example, smoke may have spread from the previous pseudo-starting location to this location and then continue to spread from this location as the new "center." The determination of the next connecting location for the partial smoke diffusion trajectory requires specific rules or algorithms, such as the priority values ​​of surrounding anchor locations, their distance from the current pseudo-starting location, and the trend of smoke concentration changes. For example, the anchor location closest to the current pseudo-starting location and with the highest priority value is selected as the next connecting location. This process is repeated repeatedly, connecting the updated pseudo starting position to the next connection position each time to form a partial smoke diffusion trajectory. The newly connected position is then used as the pseudo starting position for the next round, and the search for the next connection position continues. This cycle continues until all anchor positions are connected, ultimately obtaining a complete smoke diffusion trajectory.

[0055] The beneficial effect of this technology is that, even when there are no redundant monitoring locations within the circular area, it can quickly connect the pseudo-starting location with the monitoring location corresponding to the second-highest priority value as a partial smoke diffusion trajectory. This allows the system to quickly construct the basic framework of the smoke diffusion trajectory under certain conditions, avoiding interruptions in trajectory generation due to data distribution. By updating the monitoring location corresponding to the second-highest priority value as the pseudo-starting location and continuously determining the next connection location, all anchor locations are gradually connected to form a complete trajectory. This coherent processing method ensures the integrity of the smoke diffusion trajectory generation and ensures that the entire smoke diffusion process is properly represented. This helps operators fully understand the smoke diffusion path and obtain reliable trajectory information even when the data distribution is relatively simple. Furthermore, this unit works in conjunction with other related modules to enrich the response strategies for smoke diffusion trajectory generation and improve the system's adaptability to different data situations. This provides more comprehensive and flexible support for subsequent decision-making based on smoke diffusion trajectories, such as fire rescue deployment and evacuation planning, and enhances the ability of the entire fire protection electronic display intelligent control system to cope with various scenarios.

[0056] Example 7: Based on Example 2, the fire source characteristic analysis submodule includes: A suspected flame area screening unit is used to identify all irregular areas surrounded by irregular edges in each video frame of the screen monitoring video based on an edge detection algorithm, and to screen out the suspected flame area in each video frame from all irregular areas in each video frame based on preset saturation thresholds and brightness thresholds; A physical space positioning unit is used to determine the three-dimensional coordinate range of each suspected flame area in the world coordinate system based on a triangulation positioning algorithm as the physical space range of each suspected flame area; a real flame region screening unit, configured to obtain, based on a multi-spectral fusion monitoring method, a signal intensity of a strong absorption peak signal within a preset wavelength range within the physical space of each suspected flame region, and determine, based on the signal intensity of the strong absorption peak signal within the preset wavelength range within the physical space of each suspected flame region, whether the corresponding suspected flame region is a real flame region, using the determination result for the corresponding suspected flame region as the determination result, and screening out all real flame regions based on the determination results of all suspected flame regions; An inter-frame correspondence unit is used to perform inter-frame correspondence on all real flame areas in all video frames in the screen monitoring video to obtain a sequence of real flame areas of all real fire sources; The fire source characteristic data extraction unit is used to extract fire source characteristic data based on the real flame area sequence of all real fire sources.

[0057] In this embodiment, the edge detection algorithm is, for example, a canny edge detection operator.

[0058] In this embodiment, all irregular regions in each video frame are screened for suspected flame regions based on preset saturation and brightness thresholds. This is a further step in the identification of irregular regions by the edge detection algorithm. Flames typically have high saturation and brightness characteristics, and the preset saturation and brightness thresholds are numerical standards set based on these typical characteristics of flames. For each irregular region identified by the edge detection algorithm, the system calculates its average saturation and brightness values ​​and compares them with preset thresholds. If the average saturation of an irregular region exceeds the saturation threshold and the average brightness exceeds the brightness threshold, the region is considered to have some characteristics of a flame and is thus screened as a suspected flame region. For example, assuming a preset saturation threshold of 0.8 and a brightness threshold of 150, an irregular region with an average saturation of 0.85 and an average brightness of 160 is identified as a suspected flame region. This screening method effectively eliminates some irregular regions that are not flames, such as the edges of ordinary objects, further focusing on possible flame regions, thereby improving the accuracy of flame detection.

[0059] In this embodiment, the three-dimensional coordinate range of each suspected flame area in the world coordinate system is determined using a triangulation algorithm. The triangulation algorithm uses the principles of geometric triangulation to determine the spatial position of an object. In this system, surveillance video is captured using at least two cameras with different viewing angles (e.g., high-definition cameras at the edge of the screen and at the perforation location). For each suspected flame area, the triangulation algorithm is used to calculate the three-dimensional coordinate range of that area in the world coordinate system based on the camera position and angle, as well as the positional information of the suspected flame area in the image. This allows accurate determination of the specific location of the suspected flame in physical space, providing critical information for the precise implementation of subsequent firefighting measures. For example, this can help firefighters quickly locate the source of a fire or precisely guide firefighting equipment toward the source in an automatic fire extinguishing system.

[0060] In this embodiment, the signal intensity of the strong absorption peak signal within a preset wavelength range within the physical space of each suspected flame area is obtained based on a multi-spectral fusion monitoring method. The multi-spectral fusion monitoring method comprehensively utilizes information from multiple different spectral bands for monitoring. Flames will produce strong absorption peak signals within certain specific wavelength ranges. By analyzing the signal intensity within these wavelength ranges, the authenticity of the flame can be further confirmed. The system will use the corresponding spectral sensor to obtain spectral information within the preset wavelength range within the physical space of each suspected flame area, and then analyze these spectral data to find the strong absorption peak signal and measure its signal intensity. For example, for a specific type of flame, there will be obvious strong absorption peaks at certain wavelengths in the infrared band. By detecting the signal intensity at these wavelengths, more accurate information about the flame characteristics can be obtained, providing a stronger basis for determining whether the suspected flame area is a real flame.

[0061] In this embodiment, the preset wavelength range is, for example, 200-280 nm.

[0062] In this embodiment, the final step in confirming the suspected flame region is to determine whether the suspected flame region is a real flame region based on the signal intensity of the strong absorption peak signal within a preset wavelength range within the physical spatial range of each suspected flame region. Because a real flame produces a strong absorption peak signal with a specific intensity characteristic within the preset wavelength range, the obtained strong absorption peak signal intensity can be compared with a pre-set standard to determine the suspected flame region. If the signal intensity is within the expected range and consistent with the characteristics of a real flame within this wavelength range, the suspected flame region is likely a real flame region. Conversely, if the signal intensity deviates significantly from the standard, the suspected flame region is determined to be a false flame region (possibly a false flame source such as light or reflective lighting). For example, it is known that the strong absorption peak signal intensity of a real flame within a preset wavelength range is typically between 80 and 120 units. If the signal intensity detected in a suspected flame region within this wavelength range is 100 units, the region can be preliminarily determined to be a real flame region.

[0063] In this embodiment, inter-frame correspondence is performed on all real flame regions in all video frames of the screen monitoring video to obtain a sequence of real flame regions for all real fire sources. This step is intended to consistently track the evolution of real flames over time. Due to the dynamic changes of flames, the position and shape of flames may vary in different video frames. Through inter-frame correspondence technology, the system can match and correlate real flame regions in adjacent video frames to determine whether they originate from the same real fire source. For example, image feature matching algorithms (such as SIFT and SURF) are used to compare the shape, texture, and position of real flame regions in different frames, identifying regions with similar features as manifestations of the same fire source at different times. By performing this processing on the real flame regions in all video frames, a sequence of real flame regions for all real fire sources can be obtained. This sequence records the flame region information of each real fire source at different points in time, demonstrating the flame's development process, such as its spread and flickering. This provides a continuous information foundation for analyzing fire source characteristic data (such as flame spread direction, flicker frequency, and spread speed), facilitating a more comprehensive understanding of fire development trends and providing a more detailed and accurate basis for firefighting decision-making.

[0064] The beneficial effects of these technologies include: The suspected flame area screening unit uses an edge detection algorithm to identify irregular areas and, combined with preset saturation and brightness thresholds, screens suspected flame areas. This narrows the analysis scope, improves processing efficiency, avoids interference from large, irrelevant areas, and quickly focuses on potential fire sources. The physical space positioning unit uses a triangulation algorithm to determine the three-dimensional coordinate range (physical spatial extent) of the suspected flame area in the world coordinate system, accurately locating the fire source. This provides critical information for firefighters to quickly reach the fire source, significantly improving the accuracy and timeliness of rescue operations. The real flame area screening unit employs a multispectral fusion monitoring method to determine the authenticity of flames based on the signal intensity of strong absorption peaks within a preset wavelength range. This effectively reduces misjudgments and accurately identifies the real flame area, providing a reliable basis for subsequent decision-making and avoiding wasted resources or delayed rescue operations due to misjudgments. The inter-frame correspondence unit performs inter-frame correspondence on the real flame areas in each video frame, forming a sequence of real flame areas that coherently presents the dynamic changes of the fire source, enabling analysts to understand the fire source's development and providing strong support for pre-emptive response strategy planning. The fire source characteristic data extraction unit extracts data based on the flame area sequence, providing rich key data for triggering the fire linkage system. This helps to accurately formulate fire extinguishing plans, improve the pertinence and efficiency of fire extinguishing operations, and comprehensively enhance the fire protection system's ability to analyze and respond to fire sources, effectively protecting people's lives and property safety.

[0065] Example 8: Based on Example 7, the fire source feature data extraction unit includes: A physical space positioning subunit, configured to determine the location of each real fire source based on a triangulation method and a sequence of real flame areas of each real fire source; The flame spread direction analysis subunit is used to track the pixel motion vector of the real flame area sequence of each real fire source to obtain the flame spread direction of each real fire source; The flicker frequency analysis subunit is used to track the periodic changes in regional brightness of the real flame region sequence of each real fire source and obtain the flicker frequency of each real fire source; The diffusion speed analysis subunit is used to perform regional area diffusion trend analysis on the real flame area sequence of each real fire source to obtain the diffusion speed of each real fire source; The multi-dimensional feature summary sub-unit is used to treat the occurrence location, flame spread direction, flicker frequency, and spread speed of all real fire sources as fire source feature data.

[0066] In this embodiment, the location of each real fire source is determined based on triangulation and the sequence of its actual flame area. Triangulation leverages geometric principles and utilizes video information captured from different angles by multiple cameras (such as high-definition cameras at the screen edge and perforations). The sequence of actual flame areas contains information about the flame area of ​​each real fire source across different video frames. Based on the camera position and angle, as well as the pixel position of the actual flame area in each video frame, the system uses triangulation to accurately determine the three-dimensional coordinates of the real fire source in real space, i.e., its location. For example, just as determining a target point in space by the intersection of rays from different directions, capturing the flame area from different camera angles and performing triangulation calculations can pinpoint the fire source's location near the electronic display screen. This is crucial for firefighters to quickly locate and extinguish the fire.

[0067] In this embodiment, pixel motion vector tracking is performed on the real flame area sequence of each real fire source to obtain the flame spread direction of each real fire source. This process is achieved by analyzing the movement of the flame area pixels in each video frame in the real flame area sequence. The system tracks the displacement of pixels in the flame area between adjacent video frames and calculates the pixel motion vector. The combined direction of a large number of pixel motion vectors represents the flame spread direction. For example, if most of the pixels in the flame area move toward the upper right, then the flame spread direction is the upper right. Accurately obtaining the flame spread direction helps to plan evacuation routes and deploy fire-fighting equipment in advance, preventing people and equipment from being in the path of flame spread.

[0068] In this embodiment, the periodic changes in regional brightness of the real flame area sequence of each real fire source are tracked to obtain the flicker frequency of each real fire source. Flame flicker is manifested as periodic changes in regional brightness. The system monitors the flame area brightness of each video frame in the real flame area sequence and records the brightness changes. By analyzing the brightness fluctuations over time and determining the time interval from one peak brightness to the next peak brightness, the flicker frequency is calculated. For example, if the flame area brightness reaches a peak every 0.5 seconds, the flicker frequency is 2 times / second. The flicker frequency can be used as a reference for judging the nature and intensity of the fire source. Different types of fire sources may have different flicker frequency characteristics.

[0069] In this embodiment, a regional area diffusion trend analysis is performed on the sequence of real flame areas for each real fire source to determine the diffusion rate of each real fire source. The system measures the area of ​​the flame area in each video frame of the real flame area sequence and compares the changes in the flame area between different video frames. The diffusion rate is calculated by calculating the increase in the flame area per unit time. For example, if the flame area increases from 100 square pixels to 150 square pixels in 1 second, the diffusion rate is 50 square pixels / second. Understanding the diffusion rate can help assess the speed of fire development, allowing for timely adjustments to firefighting strategies and the rational allocation of resources to respond to fires.

[0070] The beneficial effects of the above technologies are as follows: The physical space positioning subunit uses the triangulation positioning method combined with the real flame area sequence to determine the actual location of the fire source, providing accurate fire source positioning information for fire rescue, enabling rescue forces to quickly and accurately reach the fire point, and improving rescue efficiency. The flame spread direction analysis subunit tracks the real flame area sequence through pixel motion vectors to obtain the flame spread direction, helping firefighters to predict the flame spread trend in advance, rationally plan evacuation routes and deploy firefighting forces, and effectively reduce the losses caused by fire. The flicker frequency analysis subunit tracks the periodic changes in regional brightness to obtain the real fire source flicker frequency. This feature can assist in determining the type of fire source, the size of the fire, etc., and provide a basis for formulating targeted firefighting strategies. The diffusion speed analysis subunit analyzes the regional area diffusion trend to obtain the real fire source diffusion speed, allowing the fire department to timely grasp the speed of fire development, thereby rationally allocating resources and taking more effective firefighting measures. The multi-dimensional feature summary sub-unit summarizes the occurrence location, flame spread direction, flicker frequency, and spread speed into fire source feature data, forming a comprehensive and systematic fire source information collection, providing rich and accurate data support for the comprehensive decision-making of the fire-proof electronic display screen intelligent control system, and comprehensively improving the system's response capabilities to fires and the scientific nature of its decision-making.

[0071] Example 9: Based on Example 1, the intelligent control module includes: The fire intensity level calculation submodule is used to calculate the current fire intensity level based on the three-dimensional temperature field model, smoke diffusion trajectory, and fire source characteristic data within the space where the electronic display screen is located; The fire linkage trigger submodule is used to trigger the fire linkage system based on the current fire level value; The intelligent control submodule is used to intelligently control the fire protection electronic display screen based on the current fire level value.

[0072] In this embodiment, the current fire severity value is calculated based on the three-dimensional temperature field model of the space where the electronic display screen is located, the smoke diffusion trajectory, and the fire source characteristic data. For example, by setting a specific algorithm and weighting, parameters such as the area of ​​the high-temperature area, the smoke diffusion speed, and the flame diffusion speed are calculated to obtain a numerical value representing the current fire severity, namely the current fire severity value: First, determine the parameters involved in the calculation and their meanings: High temperature area (A): Obtained from the 3D temperature field model, in square meters. Assume that a high temperature area is defined as an area where the temperature exceeds a certain threshold (e.g., 80°C).

[0073] Smoke diffusion speed (Vsmoke): Calculated through smoke diffusion trajectory analysis, in meters per minute.

[0074] Flame spread speed (Vflame): extracted from fire source characteristic data, in meters per minute.

[0075] Flame Spread Direction Consistency (D): Analyzes the flame spread direction and calculates the degree of consistency in each direction. For example, if the flames mostly spread in the same direction, the degree of consistency is high; if the flame spreads in a chaotic manner, the degree of consistency is low. The value range is [0, 1], where 0 indicates complete inconsistency and 1 indicates complete consistency.

[0076] Flame flicker frequency (Fflicker): obtained from the fire source characteristic data, in times / second.

[0077] Then, set the specific algorithm and weights: High temperature area weight: wA=0.3, smoke diffusion speed weight: wsmoke=0.2, flame diffusion speed weight: wflame=0.2, flame diffusion direction consistency weight: wD=0.15, flame flicker frequency weight: wflicker=0.15; These weights are set based on the relative importance of each parameter in the fire severity assessment and can be adjusted in actual applications based on a large amount of experimental data and fire characteristics analysis.

[0078] Redefine the normalization function: Normalization of high temperature area: Assuming that the maximum high temperature area in previous monitoring data is Amax = 15 square meters, the normalized high temperature area Anorm is calculated as: Anorm = A ÷ Amax.

[0079] Normalization of smoke diffusion speed: Assuming the maximum smoke diffusion speed is Vsmokemax = 8 m / min, the normalized smoke diffusion speed Vsmokenorm = Vsmoke ÷ Vsmokemax.

[0080] Normalization of flame spread speed: Assuming the maximum flame spread speed is Vflamemax = 4 m / min, the normalized flame spread speed Vflamenorm = Vflame ÷ Vflamemax.

[0081] Normalization of flame flicker frequency: Assuming that the maximum value of flame flicker frequency in previous data is Fflickermax = 10 times / second, the normalized flame flicker frequency Fflickernorm = Fflicker ÷ Fflickermax.

[0082] Then calculate the current fire level value (F) through weighted summation: F=wA×Anorm+wsmoke×Vsmokenorm+wflame×Vflamenorm+wD×D+wflicker×Fflickernorm; For example, in one monitoring: The area of ​​the high temperature area A = 9 square meters, then Anorm = 9 ÷ 15 = 0.6; Smoke diffusion speed Vsmoke = 5 m / min, then Vsmokenorm = 5 ÷ 8 = 0.625; Flame spread speed Vflame = 2.5 m / min, then Vflamenorm = 2.5 ÷ 4 = 0.625; By analyzing the flame diffusion direction, it is found that the flame diffusion direction consistency D=0.8; The flame flicker frequency Fflicker = 6 times / second, then Fflickernorm = 6 ÷ 10 = 0.6; Substituting these values ​​into the formula yields: F=0.3×0.6+0.2×0.625+0.2×0.625+0.15×0.8+0.15×0.6=0.18+0.125+0.125+0.12+0.09=0.64; The value of 0.64 is the current fire severity value calculated this time. It comprehensively considers the fire severity represented by multiple factors, including the area of ​​the high-temperature area, smoke diffusion rate, flame spread rate, flame spread direction consistency, and flame flicker frequency. Similarly, different thresholds can be set to classify fire severity based on actual conditions. For example, 0-0.4 is a low fire severity, 0.4-0.7 is a medium fire severity, and 0.7-1 is a high fire severity. This allows the system to take appropriate firefighting measures based on the fire severity.

[0083] In this embodiment, triggering the fire linkage system based on the current fire level value means that the system takes corresponding firefighting measures according to the calculated fire level. When the fire level value reaches a certain threshold, a series of fire-related operations will be automatically initiated. For example, if the fire level is low, the alarm system may be triggered first to notify nearby personnel to pay attention; if the fire level is high, in addition to the alarm, fire-fighting equipment such as automatic sprinkler fire-fighting systems and gas fire-fighting devices will be activated, and other fire-fighting facilities such as the lowering of fire curtains and the opening of smoke exhaust systems will be linked at the same time. These measures are used to control the spread of the fire and ensure the safety of people and property. This method of accurately triggering the fire linkage system according to the fire level can rationally allocate fire-fighting resources and improve the efficiency of responding to fires.

[0084] The beneficial effects of the above technology are as follows: The fire severity calculation submodule integrates a three-dimensional temperature field model of the space where the electronic display screen is located, smoke diffusion trajectory, and fire source characteristic data to calculate the current fire severity. This multi-dimensional data fusion calculation method can more comprehensively and accurately reflect the actual fire situation, providing a reliable basis for subsequent decision-making. The fire linkage triggering submodule triggers the fire linkage system based on the calculated current fire severity, enabling precise initiation of firefighting measures based on the fire intensity, avoiding over- or under-response, improving the efficiency of firefighting resources, and effectively controlling the spread of fire in a timely manner, thereby protecting lives and property. The intelligent control submodule intelligently controls the fire protection electronic display screen based on the current fire severity, enabling the screen to dynamically adjust its display content according to the fire intensity. For example, it can display evacuation guidance information when the fire is relatively small, while highlighting warning information when the fire is severe, providing more effective information support for evacuation and rescue command. The three submodules work together to form a complete and intelligent fire response system, enhancing the comprehensive response capabilities of the fire protection electronic display screen intelligent control system in fire scenarios and improving the overall intelligence and practicality of the system.

[0085] Example 10: Based on Example 9, the intelligent control submodule includes: Model building unit, used to build an intelligent control model of an electronic display screen; The intelligent control unit is used to input the current fire level value into the intelligent control model of the electronic display screen, obtain the current intelligent control instructions of the fire-proof electronic display screen, and intelligently control the fire-proof electronic display screen based on the current intelligent control instructions.

[0086] In this embodiment, building an intelligent control model for electronic display screens involves constructing a mathematical model or algorithmic framework for intelligently controlling fire-resistant electronic display screens. This model is pre-trained using a large number of fire prevention and control instances within the spaces where the electronic display screens are located (the current fire severity level is calculated based on data from these instances), as well as intelligent control instructions for the electronic display screens determined by fire control personnel based on the actual fire conditions recorded in these instances. The current fire severity level calculated based on data from these instances serves as the model input, while the intelligent control instructions for the electronic display screens determined by fire control personnel based on the actual fire conditions recorded in these instances serve as the model output.

[0087] For example, the model might output that when a fire is small, the electronic display screen switches to displaying evacuation instructions; as the fire intensifies, it adjusts to highlighting warning messages. By integrating the logical relationships between these factors, the model can accurately output control instructions for the electronic display screen based on the current fire intensity input. This provides a standardized and intelligent foundation for the intelligent control of electronic display screens in fire scenarios, making the control process more scientific and efficient.

[0088] In this embodiment, the current intelligent control command is a specific operational instruction calculated by the electronic display's intelligent control model based on input parameters such as the current fire severity level. This command specifies how the fire-resistant electronic display should respond to changes in the fire intensity. For example, the command might be "Adjust the display brightness to maximum and display 'Fire Danger, Evacuate Quickly'" or "Disable some non-critical display areas to reduce power consumption and focus on displaying emergency warning information."

[0089] In this embodiment, intelligent control of the fire-proof electronic display screen based on the current intelligent control instruction is to perform corresponding operations on the electronic display screen according to the instructions obtained from the intelligent control model. After receiving the current intelligent control instruction, the control system of the electronic display screen adjusts the various parameters and display content of the display screen according to the requirements of the instruction. For example, if the instruction requires a change in the display brightness and content, the control system will control the backlight brightness adjustment module and display content output module of the display screen to achieve brightness adjustment and display of specific information. In this way, the fire-proof electronic display screen can respond to changes in the fire in real time, provide necessary information support for personnel evacuation and firefighting work, and enhance the overall fire response capability.

[0090] The beneficial effects of the above technology are as follows: The model-building unit constructs an intelligent control model for electronic display screens, providing a standardized and intelligent framework for intelligent control of fire-prevention electronic display screens. This model integrates various relevant factors and logical relationships, laying the foundation for accurate control command generation. The intelligent control unit inputs the current fire severity level into the constructed intelligent control model to obtain the current intelligent control command for the fire-prevention electronic display screen. This model-based command generation method is efficient and accurate, enabling rapid and precise control instructions based on the fire severity. Intelligent control of the fire-prevention electronic display screen based on the current intelligent control command enables the display screen to respond appropriately and in real time to changes in the fire severity, such as displaying different emergency signs and escape route guidance based on different fire severity levels. This greatly enhances the relevance and effectiveness of the fire-prevention electronic display screen's information transmission in fire scenarios. Through the close coordination of model building and intelligent control, the intelligent control system for fire-prevention electronic display screens has been significantly improved, providing personnel with more scientific and reasonable information guidance when a fire occurs, further improving the overall effectiveness of the entire system in responding to fires.

[0091] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the present invention and its equivalents, the present invention is intended to include these modifications and variations.

Claims

1. A fire-proof electronic display screen intelligent control system, characterized in that: include: A temperature monitoring module is used to collect temperature data of various peripheral areas of the screen in real time based on a temperature sensor array evenly distributed in an area where the number of through holes behind the electronic display screen exceeds a preset number; The smoke monitoring module is used to collect real-time smoke concentrations at multiple locations within the environment where the screen is located based on smoke sensors installed at multiple through-hole positions behind the screen, with the sensing ports facing the air flow direction of the front through-holes; Probe monitoring module, used to obtain screen monitoring video based on high-definition probes; The multi-source data analysis module is used to establish a three-dimensional temperature field model of the space where the electronic display screen is located, smoke diffusion trajectory and fire source characteristic data based on the temperature data of each area around the screen, multiple smoke concentrations in the environment where the screen is located, and screen monitoring video; The intelligent control module is used to trigger the fire linkage system based on the three-dimensional spatial temperature field model of the space where the electronic display screen is located, the smoke diffusion trajectory, the fire source characteristic data and the multi-level warning rules, and at the same time, to intelligently control the fire-proof electronic display screen.

2. The fire-proof electronic display screen intelligent control system according to claim 1 is characterized in that: Multi-source data analysis module, including: The temperature field model establishment submodule is used to interpolate and model the temperature data of each area around the screen to generate a three-dimensional temperature field model of the space where the electronic display screen is located; The smoke diffusion model establishment submodule is used to generate smoke diffusion trajectories based on the smoke concentrations at multiple locations around the screen; The fire source feature analysis submodule is used to analyze the fire source feature data in the screen monitoring video.

3. The fire-proof electronic display screen intelligent control system according to claim 2 is characterized in that smoke Diffusion model establishment submodule, including: The first sorting unit is configured to sort the monitoring positions of all smoke sensors according to the most recently acquired smoke concentrations at multiple locations in the environment where the screen is located, from large to small, to obtain a first position sequence; a second sorting unit, configured to calculate a concentration change trend value for each monitoring location based on a sequence of historical smoke concentration values ​​at the corresponding monitoring location monitored by each smoke sensor, and sort the monitoring locations of all smoke sensors based on a descending order of concentration change trend values ​​to obtain a second location sequence; an abnormality judgment unit, configured to calibrate the latest safety monitoring period based on a sequence of historical smoke concentration values ​​at corresponding monitoring locations monitored by all smoke sensors, and determine the earliest abnormal anchoring moment and abnormality degree of each smoke sensor within the latest safety monitoring period based on all abnormal smoke concentration values ​​occurring within the latest safety monitoring period in the sequence of historical smoke concentration values ​​at corresponding monitoring locations monitored by each smoke sensor; a priority value calculation unit, configured to calculate a priority value of a monitoring position of each smoke sensor based on the earliest abnormal anchoring moment and abnormality degree of each smoke sensor in a latest safety monitoring cycle, a ranking value of the corresponding monitoring position in the first position sequence, and a ranking value in the second position sequence; The trajectory simulation unit is used to generate a smoke diffusion trajectory based on the priority values ​​of the monitoring positions of all smoke sensors.

4. The fire-proof electronic display screen intelligent control system according to claim 3 is characterized in that: Trajectory simulation unit, including: The starting point and circle range determination subunit is used to take the monitoring position corresponding to the maximum priority value among all the monitoring positions of the smoke sensors as the assumed starting point position, and construct a circle range area of ​​the pseudo starting point position with the pseudo starting point position as the circle center and the distance between the pseudo starting point position and the monitoring position corresponding to the second largest priority value as the radius; A first interpolation processing subunit is configured to, when the circular range includes the remaining monitoring positions excluding the false starting position and the monitoring position corresponding to the second largest priority value, perform interpolation processing on multiple interpolation positions within the circular range based on the historical smoke concentration value sequence at the false starting position, the historical smoke concentration value sequence at the monitoring position corresponding to the second largest priority value, and the historical smoke concentration value sequences of all remaining monitoring positions within the circular range excluding the false starting position and the monitoring position corresponding to the second largest priority value, to obtain the historical smoke concentration value sequences of the multiple interpolation positions within the current circular range; A priority value determination subunit, configured to determine a current priority value for each anchor position based on a historical smoke concentration value sequence of all interpolation positions and a historical smoke concentration value sequence of all monitoring positions; The first trajectory fitting subunit is used to fit the smoke diffusion trajectory based on the current priority values ​​of all anchor positions.

5. The fire-proof electronic display screen intelligent control system according to claim 4 is characterized in that: The first trajectory fitting subunit includes: The starting point and circle range determination terminal is used to determine the latest false starting point based on the current priority values ​​of all anchor positions, and to construct a circle range area of ​​the latest false starting point with the latest false starting point as the center and the distance between the latest false starting point and the anchor position corresponding to the second largest current priority value as the radius; The trajectory fitting end is used to interpolate and calculate the priority value of the circular range area of ​​the latest false starting position based on the historical smoke concentration value sequence of the existing anchor position when the circular range area of ​​the latest false starting position contains the remaining anchor positions except the latest false starting position and the anchor position corresponding to the second largest current priority value, so as to obtain the latest anchor position set, until the latest circular range area obtained based on the latest obtained anchor position set does not contain the remaining anchor positions except the latest false starting position and the anchor position corresponding to the second largest latest priority value, then the latest false starting position and the anchor position corresponding to the second largest latest priority value are connected as a partial smoke diffusion trajectory, and the anchor position corresponding to the second largest latest priority value is updated as the false starting position, and the next connection position of the partial smoke diffusion trajectory is determined, until all anchor positions are connected to obtain the smoke diffusion trajectory.

6. The fire-proof electronic display screen intelligent control system according to claim 1 is characterized in that: Also includes: The second trajectory fitting subunit is used to connect the false starting position and the monitoring position corresponding to the second largest priority value as a partial smoke diffusion trajectory when the circular range does not contain the remaining monitoring positions except the false starting position and the monitoring position corresponding to the second largest priority value, and update the monitoring position corresponding to the second largest priority value to the false starting position, and determine the next connection position of the partial smoke diffusion trajectory until all anchor positions are connected to obtain the smoke diffusion trajectory.

7. The fire-proof electronic display screen intelligent control system according to claim 2 is characterized in that: Fire source characteristic analysis submodule, including: A suspected flame area screening unit is used to identify all irregular areas surrounded by irregular edges in each video frame of the screen monitoring video based on an edge detection algorithm, and to screen out the suspected flame area in each video frame from all irregular areas in each video frame based on preset saturation thresholds and brightness thresholds; A physical space positioning unit is used to determine the three-dimensional coordinate range of each suspected flame area in the world coordinate system based on a triangulation positioning algorithm as the physical space range of each suspected flame area; a real flame region screening unit, configured to obtain, based on a multi-spectral fusion monitoring method, a signal intensity of a strong absorption peak signal within a preset wavelength range within the physical space of each suspected flame region, and determine, based on the signal intensity of the strong absorption peak signal within the preset wavelength range within the physical space of each suspected flame region, whether the corresponding suspected flame region is a real flame region, using the determination result for the corresponding suspected flame region as the determination result, and screening out all real flame regions based on the determination results of all suspected flame regions; An inter-frame correspondence unit is used to perform inter-frame correspondence on all real flame areas in all video frames in the screen monitoring video to obtain a sequence of real flame areas of all real fire sources; The fire source characteristic data extraction unit is used to extract fire source characteristic data based on the real flame area sequence of all real fire sources.

8. The fire-proof electronic display screen intelligent control system according to claim 7 is characterized in that: Fire source characteristic data extraction unit, including: A physical space positioning subunit, configured to determine the location of each real fire source based on a triangulation method and a sequence of real flame areas of each real fire source; The flame spread direction analysis subunit is used to track the pixel motion vector of the real flame area sequence of each real fire source to obtain the flame spread direction of each real fire source; The flicker frequency analysis subunit is used to track the periodic changes in regional brightness of the real flame region sequence of each real fire source and obtain the flicker frequency of each real fire source; The diffusion speed analysis subunit is used to perform regional area diffusion trend analysis on the real flame area sequence of each real fire source to obtain the diffusion speed of each real fire source; The multi-dimensional feature summary sub-unit is used to treat the occurrence location, flame spread direction, flicker frequency, and spread speed of all real fire sources as fire source feature data.

9. The fire-proof electronic display screen intelligent control system according to claim 1, characterized in that: Intelligent control module, including: The fire intensity level calculation submodule is used to calculate the current fire intensity level based on the three-dimensional temperature field model, smoke diffusion trajectory, and fire source characteristic data within the space where the electronic display screen is located; The fire linkage trigger submodule is used to trigger the fire linkage system based on the current fire level value; The intelligent control submodule is used to intelligently control the fire protection electronic display screen based on the current fire level value.

10. The fire-proof electronic display screen intelligent control system according to claim 9, characterized in that: Intelligent control submodule, including: Model building unit, used to build an intelligent control model of an electronic display screen; The intelligent control unit is used to input the current fire level value into the intelligent control model of the electronic display screen, obtain the current intelligent control instructions of the fire-proof electronic display screen, and intelligently control the fire-proof electronic display screen based on the current intelligent control instructions.

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