Intelligent fire-fighting online monitoring alarm system and method and storage medium

Abstract

The invention belongs to the technical field of fire-fighting supervision, and particularly relates to an intelligent fire-fighting online monitoring alarm system and method and a storage medium, and the system comprises a fire-fighting monitoring module, a fire-fighting analysis and prediction module, an emergency response alarm module, a regional threat analysis module and a fire-fighting management end. According to the invention, environment monitoring is carried out on a fire-fighting monitoring area through the fire-fighting monitoring module, the fire risk prediction model analyzes fire-fighting data to identify fire hazards, and when the fire hazards are identified, accurate alarm information is sent to the fire-fighting management terminal and personnel evacuation is notified, so that the accuracy and timeliness of fire early warning are significantly improved; fire-fighting threats of a fire-fighting monitoring area in a supervision period are analyzed through an area threat analysis module, and fire-fighting supervision of the fire-fighting monitoring area is enhanced when a fire-fighting high threat signal is generated, so that a fire-fighting management scheme of the fire-fighting monitoring area can be formulated timely and reasonably; and the scientificity of a fire-fighting management scheme and the regional safety of a fire-fighting monitoring region are ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of fire supervision, and specifically to an intelligent fire online monitoring and alarm system, method and storage medium. Background Art

[0002] With the acceleration of the urbanization process, fire safety issues have become increasingly prominent. Therefore, fire monitoring and alarm are required to reduce the harm caused by fire accidents. In a Chinese invention patent with the publication number CN118280090A, an artificial intelligence-based fire emergency monitoring and alarm management system and method are disclosed. The technical solution of this invention collects associated data in the environment in real time and determines whether to issue a fire warning. Moreover, by calculating the similarity between the fire in the real-time warning and each fire type in the database, the fire type in the real-time warning is further judged and a fire extinguishing plan is selected to complete fire extinguishing more efficiently. However, in the actual application process of the above-mentioned invention technical solution, it focuses on fire monitoring and early warning and automatic matching of fire extinguishing plans, and cannot reasonably analyze the degree of fire threat in the fire monitoring area. Moreover, it is difficult to accurately evaluate and timely warn the safety hazards of all fire hydrants and the smoothness of all fire channels in the fire monitoring area one by one, which is not conducive to ensuring fire safety in the fire monitoring area and significantly reducing the difficulty of regional fire management, and the intelligent level is low. In view of the above technical defects, a solution is proposed now. Summary of the Invention

[0003] The purpose of the present invention is to provide an intelligent fire online monitoring and alarm system, method and storage medium, which solves the problems that the prior art cannot reasonably analyze the degree of fire threat in the fire monitoring area, and it is difficult to accurately evaluate and timely warn the safety hazards of all fire hydrants and the smoothness of all fire channels in the fire monitoring area one by one, which is not conducive to ensuring fire safety and significantly reducing the difficulty of regional fire management.

[0004] To achieve the above purpose, the present invention provides the following technical solutions: An intelligent fire online monitoring and alarm system includes a fire monitoring module, a fire analysis and prediction module, an emergency response and alarm module, a regional threat analysis module and a fire management terminal; the fire monitoring module monitors the environment of the fire monitoring area through various types of sensors deployed in the fire monitoring area, and sends the collected fire data to the fire analysis and prediction module; the fire analysis and prediction module combines machine learning and deep learning algorithms, conducts in-depth learning on historical fire cases, establishes a fire risk prediction model, analyzes the fire data through the fire risk prediction model, identifies fire hazards accordingly and sends the identification information to the emergency response and alarm module; When a fire hazard is identified, the emergency response alarm module sends accurate alarm information to the fire management terminal, including the fire location, the size of the fire, and the situation of surrounding fire-fighting facilities, and notifies the residents in the fire monitoring area to evacuate through multiple methods including text messages, phone calls, or APP push; the regional threat analysis module is used to set a supervision period, analyze the fire threats in the fire monitoring area within the supervision period, generate a high fire threat signal or a low fire threat signal through analysis, and when a high fire threat signal is generated, send strong fire management information to the fire management terminal through the emergency response alarm module.

[0005] Further, the emergency response alarm module is communicatively connected to the fire hydrant hazard detection module. The fire hydrant hazard detection module obtains all the fire hydrants distributed in the fire monitoring area, marks the corresponding fire hydrant as i, and i is a natural number greater than 1; and conducts a one-by-one detection and analysis of all the fire hydrants existing in the fire monitoring area to identify obstructive fire hydrants through analysis. If there are obstructive fire hydrants in the fire monitoring area, a fire hydrant alarm signal is generated. If there are no obstructive fire hydrants in the fire monitoring area, a fire hydrant safety signal is generated; and the fire hydrant alarm signal and the position information of the corresponding fire hydrant are sent to the emergency response alarm module, and the emergency response alarm module generates corresponding alarm information and sends it to the fire management terminal.

[0006] Further, the specific analysis process for identifying obstructive fire hydrants through analysis includes: Obtain the existence duration of the fire hydrant i and mark it as the existence time detection value. When the fire hydrant i is impacted, collect the maximum value and average value of the impact force and the duration of the impact and mark them as the force amplitude value, the force table value, and the force duration value respectively. Obtain the force detection value through numerical calculation of the force amplitude value, the force table value, and the force duration value. Compare the force detection value with the preset force detection threshold value numerically. If the force detection value exceeds the preset force detection threshold value, assign the damage judgment symbol ZP-1 to the fire hydrant i. Obtain the number of times the damage judgment symbol ZP-1 is assigned to the fire hydrant i in the historical stage and mark it as the damage frequency detection value. Compare the existence time detection value and the damage frequency detection value with the preset existence time detection threshold value and the preset damage frequency detection threshold value respectively numerically. If the existence time detection value or the damage frequency detection value exceeds the corresponding preset threshold value, mark the fire hydrant i as an obstructive fire hydrant.

[0007] Further, if both the existence time detection value and the damage frequency detection value do not exceed the corresponding preset threshold values, collect the surface image of the fire hydrant i, capture the area with damage and rust on the surface of the fire hydrant i based on the surface image, mark the area of the corresponding damage and rust area as the damage and rust area, sum up the damage and rust areas of all the damage and rust areas to obtain the total damage and rust detection value, and mark the damage and rust area with the largest value as the damage and rust amplitude table value. Compare the total inspection value of damage and rust and the amplitude table value of damage and rust with the preset total inspection threshold of damage and rust and the preset amplitude table threshold of damage and rust respectively. If the total inspection value of damage and rust or the amplitude table value of damage and rust exceeds the corresponding preset threshold, mark the fire hydrant i as an obstacle fire hydrant.

[0008] Furthermore, if neither the total inspection value of damage and rust nor the amplitude table value of damage and rust exceeds the corresponding preset threshold, set several detection time points within a unit time, collect the water pressure inside the fire hydrant i at the corresponding detection time points, compare the water pressure with the preset water pressure range. If the water pressure is not within the corresponding preset water pressure range, mark the corresponding detection time point as an abnormal time point; Obtain the number of abnormal time points and calculate the ratio with the total number of detection time points to get the abnormal detection value. Mark the deviation value of the water pressure corresponding to the abnormal time point from the preset water pressure range as the water pressure risk detection value. Calculate the average value of all water pressure risk detection values within a unit time to get the water pressure risk table value, and mark the maximum water pressure risk detection value as the water pressure risk amplitude value; Calculate the water pressure evaluation value by numerically calculating the abnormal detection value, the water pressure risk table value, and the water pressure risk amplitude value. Compare the water pressure evaluation value with the preset water pressure evaluation threshold. If the water pressure evaluation value exceeds the preset water pressure evaluation threshold, mark the fire hydrant i as an obstacle fire hydrant.

[0009] Furthermore, the fire hydrant hidden danger detection module is communicatively connected to the fire passage smoothness analysis module. The fire hydrant hidden danger detection module sends the fire hydrant safety signal to the fire passage smoothness analysis module. When the fire passage smoothness analysis module receives the fire hydrant safety signal, it obtains all the fire passages in the fire monitoring area and marks the corresponding fire passage as e, and e is a natural number greater than 1; Conduct a smoothness evaluation analysis based on the monitoring video of the fire passage to identify low-smooth objects. If there are low-smooth objects in the fire monitoring area, generate a smoothness alarm signal, and send the smoothness alarm signal and the corresponding fire passage information to the emergency response alarm module. The emergency response alarm module generates the corresponding alarm information and sends it to the fire management terminal.

[0010] Furthermore, the specific analysis process of the smoothness evaluation analysis is as follows: Capture the positions where sundries are stacked inside through the monitoring video in the fire passage e, mark the passing width of the corresponding positions as the passing width detection value, compare the passing width detection value with the preset passing width detection threshold. If the passing width detection value does not exceed the preset passing width detection threshold, mark the corresponding position as a blocked position; If there is a blocked position in the fire passage e, mark the fire passage e as a low-smooth object; If there is no blocked position in the fire passage, mark the total length of the paths with sundries piled up in the fire passage e as the blocked distance value, and mark the average value and the maximum value of the corresponding width detection values of the fire passage e as the width performance value and the width amplitude value respectively. Calculate the smoothness influence value by performing numerical calculations on the blocked distance value, the width performance value, and the width amplitude value. Compare the smoothness influence value with the preset smoothness influence threshold. If the smoothness influence value exceeds the preset smoothness influence threshold, mark the fire passage e as a low-smoothness object.

[0011] Further, the specific analysis process of the regional threat analysis module is as follows: Obtain the total number of fire hazards that occurred in the fire monitoring area during the supervision period and mark it as the fire recognition value, and mark the affected area and the damaged amount of the corresponding fire as the fire scope value and the fire loss amount value respectively. Compare the fire scope value and the fire loss amount value with the preset fire scope threshold and the preset fire loss amount threshold respectively. If the fire scope value or the fire loss amount value exceeds the corresponding preset threshold, mark the corresponding fire as a high-risk fire; Obtain the number of high-risk fires corresponding to the fire monitoring area during the supervision period and mark it as the high-risk fire value, mark the identification time of the corresponding fire hazard as the first time, and mark the elimination time of the corresponding fire hazard as the second time. Mark the time interval between the first time and the second time as the disaster elimination time; Calculate the average value of all the disaster elimination times during the supervision period to obtain the disaster elimination detection value, and mark the number of disaster elimination times that exceed the preset disaster elimination time threshold during the supervision period as the disaster elimination slow detection value; Calculate the regional threat value by performing numerical calculations on the fire recognition value, the high-risk fire value, the disaster elimination detection value, and the disaster elimination slow detection value. Compare the regional threat value with the preset regional threat value threshold. If the regional threat value exceeds the preset regional threat threshold, generate a high fire threat signal; if the regional threat value does not exceed the preset regional threat threshold, generate a low fire threat signal.

[0012] Further, a smart fire online monitoring and alarm method proposed by the present invention includes the following steps: Step 1: Monitor the environment of the fire monitoring area; Step 2: Analyze the fire data through a fire risk prediction model to identify fire hazards accordingly; Step 3: When a fire hazard is identified, send accurate alarm information to the fire management terminal and notify the residents in the fire monitoring area to evacuate; Step 4: Analyze the fire threats in the fire monitoring area during the supervision period to generate a high fire threat signal or a low fire threat signal through the analysis; Step 5: When a high fire threat signal is generated, send strong fire management information to the fire management terminal.

[0013] Further, a computer storage medium proposed by the present invention stores a computer program thereon. When the computer program is executed by a processor, the above-mentioned intelligent fire online monitoring and alarm method is implemented.

[0014] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. In the present invention, the fire monitoring module monitors the environment of the fire monitoring area, and the fire risk prediction model analyzes the fire data to identify fire hazards. When a fire hazard is identified, accurate alarm information is sent to the fire management terminal and personnel evacuation is notified, significantly improving the accuracy and timeliness of fire early warning. Moreover, the regional threat analysis module analyzes the fire threats in the fire monitoring area during the supervision period, and strengthens the fire supervision of the fire monitoring area when a high fire threat signal is generated, ensuring the scientific nature of the fire management plan and the regional safety of the fire monitoring area; 2. In the present invention, the fire hydrant hidden danger detection module reasonably analyzes and accurately evaluates the fire hydrants with safety risks in the fire monitoring area and gives early warnings in a timely manner to remind the fire administrator to check, repair and replace the corresponding fire hydrants in a timely manner. Moreover, the fire passage accessibility analysis module reasonably analyzes and accurately evaluates the accessibility status of each fire passage based on the monitoring video of the fire passage, which is conducive to the fire administrator to dredge the corresponding fire passage in a timely manner, significantly reducing the fire safety hazards in the fire monitoring area and reducing the difficulty of regional fire management, with a high level of intelligence. Description of the Drawings

[0015] For the convenience of those skilled in the art to understand, the present invention will be further described below with reference to the accompanying drawings; Figure 1 It is the system block diagram of Embodiment 1 in the present invention; Figure 2 It is the system block diagram of Embodiment 2 and Embodiment 3 in the present invention; Figure 3 It is the method flow chart of Embodiment 4 in the present invention. Detailed Embodiments

[0016] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0017] Embodiment 1: As Figure 1As shown in the figure, a smart fire online monitoring and alarm system proposed by the present invention includes a fire monitoring module, a fire analysis and prediction module, an emergency response and alarm module, a regional threat analysis module, and a fire management terminal; The fire monitoring module monitors the environment of the fire monitoring area through a variety of sensors (such as smoke sensors, temperature sensors, flame detectors, gas concentration sensors, etc.) deployed at several locations in the fire monitoring area, and sends the collected fire data to the fire analysis and prediction module; the fire analysis and prediction module combines machine learning and deep learning algorithms to perform in-depth learning on historical fire cases, establish a fire risk prediction model, analyze the fire data through the fire risk prediction model, identify fire hazards accordingly, and send the identification information to the emergency response and alarm module; When a fire hazard is identified, the emergency response and alarm module immediately triggers the alarm mechanism, sends accurate alarm information to the fire management terminal, including information such as the fire location, the size of the fire, and the situation of surrounding fire facilities, and notifies the residents in the fire monitoring area to evacuate through various methods including text messages, phone calls, and APP push; the present invention can quickly transmit fire information, shorten the response time, reduce fire losses, significantly improve the accuracy and timeliness of fire warnings, and has a high level of intelligence and automation.

[0018] The regional threat analysis module is used to set a supervision period. Preferably, the supervision period is six months; analyze the fire threats in the fire monitoring area within the supervision period, generate a high fire threat signal or a low fire threat signal through the analysis, and when a high fire threat signal is generated, send strong fire management information to the fire management terminal through the emergency response and alarm module. When the fire management terminal receives the high fire threat signal, it strengthens the fire supervision in the fire monitoring area, which is conducive to formulating a scientific fire management plan for the fire monitoring area in a timely and reasonable manner, thereby ensuring the scientific nature of the fire management plan and the regional safety of the fire monitoring area; the specific analysis process of the regional threat analysis module is as follows: Obtain the total number of fire hazards that occurred in the fire monitoring area within the supervision period and mark it as the fire identification value, and mark the affected area and the damaged amount of the corresponding fire as the fire range value and the fire loss amount value, respectively. Numerically compare the fire range value and the fire loss amount value with the preset fire range threshold and the preset fire loss threshold respectively. If the fire range value or the fire loss amount value exceeds the corresponding preset threshold, mark the corresponding fire as a high-risk fire; Obtain the number of high-risk fires corresponding to the fire monitoring area during the supervision period and mark it as the high-risk fire value, mark the identification moment of the corresponding fire hazard as the first moment, mark the elimination moment of the corresponding fire hazard as the second moment, and mark the time interval between the first moment and the second moment as the disaster elimination time; among them, the larger the value of the disaster elimination time, the less timely the response to the corresponding fire hazard; calculate the average value of all disaster elimination times during the supervision period to obtain the disaster elimination detection value, and mark the number of disaster elimination times exceeding the preset disaster elimination time threshold during the supervision period as the disaster elimination delay detection value; Perform numerical calculation on the fire identification value TP, high-risk fire value YG, disaster elimination detection value ZF, and disaster elimination delay detection value WP through the formula GS = c1×TP + c2×YG + c3×ZF + c4×WP to obtain the regional threat value GS; where c1, c2, c3, and c4 are preset proportionality coefficients with values greater than zero, and moreover, the larger the value of the regional threat value GS, the higher the comprehensive fire threat level of the fire monitoring area during the supervision period; Perform a numerical comparison between the regional threat value GS and the preset regional threat value threshold. If the regional threat value GS exceeds the preset regional threat threshold, it indicates that the comprehensive fire threat level of the fire monitoring area during the supervision period is relatively high, and it is necessary to strengthen the fire supervision of the fire monitoring area, then generate a high fire threat signal; if the regional threat value GS does not exceed the preset regional threat threshold, it indicates that the comprehensive fire threat level of the fire monitoring area during the supervision period is relatively low, then generate a low fire threat signal.

[0019] Embodiment 2: As Figure 2 shown, the difference between this embodiment and Embodiment 1 is that the emergency response alarm module is communicatively connected to the fire hydrant hidden danger detection module. The fire hydrant hidden danger detection module obtains all the fire hydrants distributed in the fire monitoring area, marks the corresponding fire hydrant as i, and i is a natural number greater than 1; and performs a one-by-one detection and analysis on all the fire hydrants existing in the fire monitoring area, and identifies the obstacle fire hydrants existing in the fire monitoring area through the analysis; If there are obstacle fire hydrants in the fire monitoring area, then generate a fire hydrant alarm signal. If there are no obstacle fire hydrants in the fire monitoring area, then generate a fire hydrant safety signal; and send the fire hydrant alarm signal and the position information of the corresponding fire hydrant to the emergency response alarm module. The emergency response alarm module generates the corresponding alarm information and sends it to the fire management end, which can reasonably analyze and accurately evaluate the fire hydrants with safety risks in the fire monitoring area and give early warnings in a timely manner to remind the fire administrator to timely check, repair, and replace the corresponding fire hydrants, significantly reducing the fire safety hidden dangers in the fire monitoring area; the specific analysis process is as follows: Obtain the existence duration of the fire hydrant i (i.e., the time interval from the installation date to the current date) and mark it as the existence duration detection value. When the fire hydrant i is impacted, collect the maximum value and average value of the impact force and the duration of the impact, and mark them as the force amplitude value, the force table value, and the force duration value respectively; Perform numerical calculation on the force amplitude value WFi, the force table value TSi, and the force duration value YLi through the formula XPi = (a1×WFi + a2×TSi) / 2 + a3×YLi to obtain the force detection value XPi; where a1, a2, and a3 are preset weight coefficients greater than zero. Moreover, the larger the value of the force detection value XPi, the greater the damage caused by the corresponding impact to the fire hydrant i; Perform a numerical comparison between the force detection value XPi and the preset force detection threshold. If the force detection value XPi exceeds the preset force detection threshold, indicating that the corresponding impact causes greater damage to the fire hydrant i, then assign the damage judgment symbol ZP - 1 to the fire hydrant i, and obtain the number of times the fire hydrant i has been assigned the damage judgment symbol ZP - 1 in the historical stage and mark it as the damage frequency detection value; Perform numerical comparisons between the existence duration detection value and the damage frequency detection value with the preset existence duration detection threshold and the preset damage frequency detection threshold respectively. If the existence duration detection value or the damage frequency detection value exceeds the corresponding preset threshold, the safety risk of continued use of the fire hydrant i is relatively high, and mark the fire hydrant i as an obstacle fire hydrant; If both the existence duration detection value and the damage frequency detection value do not exceed the corresponding preset thresholds, collect the surface image of the fire hydrant i, capture the area with damage and rust on the surface of the fire hydrant i based on the surface image, mark the area of the corresponding damage and rust area as the damage and rust area, sum up the damage and rust areas of all damage and rust areas to obtain the total damage and rust detection value, and mark the damage and rust area with the largest value as the damage and rust amplitude table value; Perform numerical comparisons between the total damage and rust detection value and the damage and rust amplitude table value with the preset total damage and rust detection threshold and the preset damage and rust amplitude table threshold respectively. If the total damage and rust detection value or the damage and rust amplitude table value exceeds the corresponding preset threshold, indicating that the surface condition of the fire hydrant i is poor and the safety risk of continued use is relatively high, then mark the fire hydrant i as an obstacle fire hydrant.

[0020] Furthermore, if both the total damage and rust detection value and the damage and rust amplitude table value do not exceed the corresponding preset thresholds, indicating that the surface condition of the fire hydrant i is good, then set several detection time points within a unit time, and the time intervals between adjacent two detection time points are the same; collect the water pressure inside the fire hydrant i at the corresponding detection time points, perform a numerical comparison between the water pressure and the preset water pressure range. If the water pressure is not within the corresponding preset water pressure range, indicating that the internal water pressure of the fire hydrant i is abnormal at the corresponding detection time point, then mark the corresponding detection time point as an internal abnormality time point; Obtain the number of endometriosis time points and calculate the ratio with the total number of detection time points to obtain the endometriosis detection value. Mark the deviation value of the water pressure corresponding to the endometriosis time point compared to the preset water pressure range as the water pressure detection value. Calculate the average value of all water pressure detection values within a unit time to obtain the water pressure risk table value, and mark the largest water pressure detection value as the water pressure risk amplitude; Perform numerical calculations on the endometriosis detection value TWi, the water pressure risk table QXi value, and the water pressure risk amplitude YFi through the formula SLi = uy×TWi + (ew×QXi + ng×YFi) / 2 to obtain the water pressure evaluation value SLi, where uy, ew, and ng are preset proportionality coefficients, and uy > ew > ng > 0; moreover, the larger the numerical value of the water pressure evaluation value SLi, the worse the internal water pressure condition of the fire hydrant i within a unit time; compare the water pressure evaluation value SLi with the preset water pressure evaluation threshold. If the water pressure evaluation value SLi exceeds the preset water pressure evaluation threshold, indicating that the internal water pressure condition of the fire hydrant i within a unit time is poor, then mark the fire hydrant i as an obstacle fire hydrant.

[0021] Embodiment 3: As Figure 2 shown, the difference between this embodiment and Embodiment 1 and Embodiment 2 is that the fire hydrant hidden danger detection module is communicatively connected to the fire passage smoothness analysis module. The fire hydrant hidden danger detection module sends the fire hydrant safety signal to the fire passage smoothness analysis module. When the fire passage smoothness analysis module receives the fire hydrant safety signal, it obtains all the fire passages in the fire monitoring area and marks the corresponding fire passage as e, where e is a natural number greater than 1; based on the monitoring video of the fire passage, perform smoothness evaluation and analysis to identify low-smooth objects; If there are low-smooth objects in the fire monitoring area, generate a smoothness alarm signal, and send the smoothness alarm signal and the corresponding fire passage information to the emergency response alarm module. The emergency response alarm module generates the corresponding alarm information and sends it to the fire management terminal, which not only realizes the effective monitoring of all fire passages in the fire monitoring area but also can reasonably analyze and accurately evaluate the smoothness condition of each fire passage, facilitating the fire administrator to promptly dredge the corresponding fire passage, further reducing the fire safety hidden dangers in the fire monitoring area and significantly reducing the difficulty of regional fire management; the specific analysis process of the smoothness evaluation and analysis is as follows: Capture the positions with sundries stacked inside through the monitoring video in the fire passage e, mark the passing width of the corresponding positions as the passing width detection value, compare the passing width detection value with the preset passing width detection threshold. If the passing width detection value does not exceed the preset passing width detection threshold, then mark the corresponding position as a blocked position; if there is a blocked position in the fire passage e, indicating that the smoothness of the fire passage e is poor, then mark the fire passage e as a low-smooth object; If there is no blocked position in the fire passage, mark the total length of the paths with sundries piled up in the fire passage e as the blocked distance value, and mark the average value and the maximum value of the width detection value corresponding to the fire passage e as the width performance value and the width amplitude value respectively; Perform numerical calculations on the blocked distance value QYe, the width performance value HNe, and the width amplitude value TRe through the formula YMe = sw×QYe + (tu×HNe + en×TRe) / 2 to obtain the smoothness influence value YMe. Among them, sw, tu, and en are preset proportionality coefficients greater than zero. Moreover, the larger the numerical value of the smoothness influence value YMe, the worse the overall smoothness of the fire passage e, and the more unfavorable it is for the rapid evacuation of personnel; Perform a numerical comparison between the smoothness influence value YMe and the preset smoothness influence threshold. If the smoothness influence value YMe exceeds the preset smoothness influence threshold, indicating that the overall smoothness of the fire passage e is poor and it is not conducive to the rapid evacuation of personnel, then mark the fire passage e as a low-smoothness object.

[0022] Example 4: As Figure 3 shown, the difference between this embodiment and Embodiment 1, Embodiment 2, and Embodiment 3 is that a smart fire online monitoring and alarm method proposed by the present invention includes the following steps: Step 1, perform environmental monitoring on the fire monitoring area; Step 2, analyze the fire data through a fire risk prediction model to identify fire hazards accordingly; Step 3, when a fire hazard is identified, send accurate alarm information to the fire management terminal and notify the residents in the fire monitoring area to evacuate; Step 4, analyze the fire threats in the fire monitoring area during the supervision period, and generate a high fire threat signal or a low fire threat signal through the analysis; Step 5, when a high fire threat signal is generated, send strong fire management information to the fire management terminal.

[0023] The present invention also proposes a computer storage medium, on which a computer program is stored. When the computer program is executed by a processor, the above-mentioned smart fire online monitoring and alarm method is implemented. Those of ordinary skill in the art can understand that all or part of the steps of implementing the above method embodiments can be completed by hardware related to the computer program. The foregoing computer program can be stored in a computer-readable storage medium. When the program is executed, it executes the steps including the above method embodiments; and the foregoing storage medium includes: various media such as ROM, RAM, magnetic disk, or optical disc that can store program codes.

[0024] Working principle of the present invention: During use, the fire monitoring module monitors the environment of the fire monitoring area. The fire analysis and prediction module analyzes the fire data through the fire risk prediction model to identify potential fire hazards. When a potential fire hazard is identified, the emergency response alarm module sends accurate alarm information to the fire management terminal and notifies personnel to evacuate, which can quickly transmit fire information, shorten the response time, reduce fire losses, significantly improve the accuracy and timeliness of fire warning, and analyze the fire threats in the fire monitoring area during the supervision period through the regional threat analysis module. When a high fire threat signal is generated, the fire supervision in the fire monitoring area is strengthened, which is conducive to formulating a scientific fire management plan for the fire monitoring area in a timely and reasonable manner, ensuring the scientific nature of the fire management plan and the regional safety of the fire monitoring area.

[0025] All the above formulas are dimensionless and take their numerical values for calculation. The formulas are obtained by collecting a large amount of data and performing software simulation to get a formula closest to the actual situation. The preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the present invention disclosed above are only used to help illustrate the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to only the specific implementation manners. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments to better explain the principle and practical application of the present invention, so that those skilled in the relevant technical fields can understand and utilize the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. An intelligent fire online monitoring and alarm system, characterized in that It includes a fire monitoring module, a fire analysis and prediction module, an emergency response and alarm module, a regional threat analysis module, and a fire management terminal; the fire monitoring module monitors the environment of the fire monitoring area, and the fire analysis and prediction module analyzes the fire data through a fire risk prediction model to identify potential fire hazards accordingly. When potential fire hazards are identified, the emergency response and alarm module sends accurate alarm information to the fire management terminal and notifies the residents in the fire monitoring area to evacuate; the regional threat analysis module analyzes the fire threats in the fire monitoring area during the supervision period, and when a high fire threat signal is generated, it sends strong fire management information to the fire management terminal through the emergency response and alarm module.

2. The intelligent fire online monitoring and alarm system according to claim 1, characterized in that, The emergency response and alarm module is communicatively connected to a fire hydrant hidden danger detection module. The fire hydrant hidden danger detection module obtains all the fire hydrants distributed in the fire monitoring area, marks the corresponding fire hydrant as i, and i is a natural number greater than 1; and conducts a one-by-one detection and analysis of all the fire hydrants existing in the fire monitoring area to identify obstructive fire hydrants through the analysis. If there are obstructive fire hydrants in the fire monitoring area, a fire hydrant alarm signal is generated; if there are no obstructive fire hydrants in the fire monitoring area, a fire hydrant safety signal is generated.

3. An intelligent fire online monitoring and alarm system according to claim 2, characterized in that, The specific analysis process for identifying obstructive fire hydrants through analysis includes: Obtain the number of times the fire hydrant i was given the damage judgment symbol ZP-1 in the historical stage and mark it as the damage frequency detection value. If the existence detection value or the damage frequency detection value exceeds the corresponding preset threshold, mark the fire hydrant i as an obstructive fire hydrant.

4. A smart fire online monitoring and alarm system according to claim 3, characterized in that, If both the existence detection value and the damage frequency detection value do not exceed the corresponding preset thresholds, then numerically compare the total damage and corrosion inspection value and the damage and corrosion amplitude table value with the preset total damage and corrosion inspection threshold and the preset damage and corrosion amplitude table threshold respectively. If the total damage and corrosion inspection value or the damage and corrosion amplitude table value exceeds the corresponding preset threshold, mark the fire hydrant i as an obstructive fire hydrant.

5. An intelligent fire online monitoring and alarm system according to claim 4, characterized in that, If both the total damage and corrosion inspection value and the damage and corrosion amplitude table value do not exceed the corresponding preset thresholds, then calculate the water pressure evaluation value by numerically calculating the internal difference detection value, the water pressure risk table value, and the water pressure risk amplitude value. If the water pressure evaluation value exceeds the preset water pressure evaluation threshold, mark the fire hydrant i as an obstructive fire hydrant.

6. The intelligent fire online monitoring and alarm system according to claim 5, characterized in that, The fire hydrant hidden danger detection module is communicatively connected to a fire passage accessibility analysis module. The fire hydrant hidden danger detection module sends the fire hydrant safety signal to the fire passage accessibility analysis module. When the fire passage accessibility analysis module receives the fire hydrant safety signal, it obtains all the fire passages in the fire monitoring area, marks the corresponding fire passage as e, and e is a natural number greater than 1. Based on the monitoring video of the fire passage, conduct an accessibility evaluation analysis to identify low-accessibility objects. If there are low-accessibility objects in the fire monitoring area, a accessibility alarm signal is generated.

7. An intelligent fire online monitoring and alarm system according to claim 6, characterized in that, The specific analysis process of the accessibility evaluation analysis is as follows: Capture the positions where sundries are stacked inside through the monitoring video in the fire passage e. If there is a blocked position in the fire passage e, mark the fire passage e as a low-passage object; if there is no blocked position in the fire passage, calculate the smoothness influence value by performing numerical calculations on the blocked road distance value, the width performance value, and the width table amplitude value. If the smoothness influence value exceeds the preset smoothness influence threshold, mark the fire passage e as a low-passage object.

8. An intelligent fire online monitoring and alarm system according to claim 1, characterized in that, The specific analysis process of the regional threat analysis module is as follows: Calculate the regional threat value by performing numerical calculations on the fire recognition value, the high-risk fire value, the disaster elimination detection value, and the disaster elimination delay inspection value. If the regional threat value exceeds the preset regional threat threshold, generate a high fire threat signal; If the regional threat value does not exceed the preset regional threat threshold, generate a low fire threat signal.

9. An online monitoring and alarm method for intelligent fire protection, characterized in that, It includes the following steps: Step 1, regional environmental monitoring; Step 2, fire hazard identification; Step 3, when a fire hazard is identified, send accurate alarm information and notify personnel to evacuate; Step 4, regional fire threat analysis; Step 5, when a high fire threat signal is generated, send strong fire management information to the fire management terminal.

10. A computer storage medium, on which a computer program is stored, characterized in that, When the computer program is executed by a processor, it implements the intelligent fire online monitoring and alarm method as described in claim 9.

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