Intelligent fire alarm system and method based on regional monitoring

Abstract

The invention belongs to the technical field of fire-fighting supervision, and particularly relates to an intelligent fire-fighting alarm system and method based on regionalized monitoring, and the system comprises a regionalized monitoring network module, an intelligent data analysis module, an early warning information issuing module, an emergency evacuation plan module, a fire-fighting facility linkage module, and a regional fire-fighting supervision terminal. Environmental parameters in a target area are comprehensively collected in real time through the regionalized monitoring network module, the intelligent data analysis module identifies a fire disaster based on the collected data, quick response and emergency evacuation are performed after the fire disaster is identified, loss caused by the fire disaster is effectively reduced, and the safety of the fire disaster is improved. After fire early warning is removed, fire hazards are accurately analyzed and fed back in time, regional fire control management personnel can master the severity degree of each fire in detail, and regional fire control safety supervision is enhanced in time by comprehensively evaluating and analyzing the regional fire control potential safety hazard degree; the regional fire-fighting hidden danger is obviously reduced; and the regional fire-fighting management difficulty is reduced.

Description

Technical Field

[0001] The present invention relates to the field of fire monitoring technology, and in particular to an intelligent fire alarm system and method based on regional monitoring. Background Art

[0002] With the acceleration of urbanization and the increase in population density, fire safety has become an important link in urban management that cannot be ignored. A Chinese invention patent with publication number CN119068619A discloses a wireless network-based urban fire alarm system. The invention technical solution integrates smoke data, temperature and humidity data, and flame characteristics, and inputs them into a preset fire classifier to complete fire identification to obtain fire identification results, thereby improving the accuracy of fire monitoring and alarm.

[0003] However, in actual application, the above-mentioned technical solution only realizes the monitoring and identification of fires, but cannot accurately feedback the degree of harm of the corresponding fire after the fire is over, and it is difficult to comprehensively analyze and accurately output the degree of hidden dangers in fire safety management in the corresponding area, which is not conducive to the effective supervision of regional fire safety, and the regional fire hazards are high and the regional fire management is difficult;

[0004] In view of the above technical defects, a solution is now proposed. Summary of the invention

[0005] The purpose of the present invention is to provide an intelligent fire alarm system and method based on regional monitoring, which solves the problems that the prior art cannot accurately feedback the degree of hazard of the corresponding fire after the fire is over, and it is difficult to comprehensively analyze and accurately output the degree of fire safety management hazards in the corresponding area, and the regional fire hazards are high and the regional fire management is difficult.

[0006] To achieve the above object, the present invention provides the following technical solutions:

[0007] The intelligent fire alarm system based on regional monitoring includes a regional monitoring network module, an intelligent data analysis module, an early warning information release module, an emergency evacuation plan module, a fire facility linkage module and a regional fire supervision terminal; the regional monitoring network module forms a high-density, multi-dimensional monitoring network through smoke detectors, temperature sensors, flame detectors and gas leakage sensors deployed in the target area, collects environmental parameters in the target area in real time and sends the collected monitoring data to the intelligent data analysis module;

[0008] The intelligent data analysis module uses machine learning algorithms to conduct in-depth mining and analysis of the collected data to identify fire characteristic patterns; after identifying a fire, the early warning information release module pushes fire warning information to people in the area, and the emergency evacuation plan module automatically activates the corresponding evacuation plan according to the fire risk level, and sends the evacuation plan information to the regional fire supervision end. The fire facility linkage module activates the corresponding fire facilities in the area and sends the activation status information of each fire facility to the regional fire supervision end.

[0009] Furthermore, the intelligent data analysis module is communicated with the fire tracking and feedback module. After identifying the fire, the fire tracking and feedback module tracks the fire situation in the target area until the fire warning is lifted. After the fire warning is lifted, the corresponding fire is marked as a high-hazard fire or a low-hazard fire through accurate fire hazard analysis, and the marking information of the corresponding fire is sent to the regional fire supervision terminal.

[0010] Furthermore, the specific analysis process of fire hazard precision analysis is as follows:

[0011] The occurrence time of the corresponding fire and the time when the fire warning is lifted are collected and marked as the hazard time and the danger relief time, and the interval between the danger relief time and the hazard relief time is marked as the danger relief time; and the spread area of ​​the corresponding fire in the region is collected and marked as the spread detection value, and the amount of economic loss caused by the corresponding fire is marked as the loss detection value;

[0012] The tracking feature value is calculated by weighted summing up the time to eliminate danger, the spread detection value and the loss detection value, and the tracking feature value is numerically compared with the preset tracking feature threshold. If the tracking feature value exceeds the preset tracking feature threshold, the corresponding fire is marked as a high-hazard fire; if the tracking feature value does not exceed the preset tracking feature threshold, the corresponding fire is marked as a low-hazard fire.

[0013] Furthermore, the fire tracking and feedback module is communicatively connected to the fire safety impact assessment module. The fire safety impact assessment module is used to set a supervision cycle. The fire tracking and feedback module sends all fire information occurring in the target area within the supervision cycle to the fire safety impact assessment module. The fire safety impact assessment module generates a high-impact fire safety signal or a low-impact fire safety signal through regional fire safety impact analysis, and sends the high-impact fire safety signal or the low-impact fire safety signal to the regional fire supervision terminal. When the regional fire supervision terminal receives the high-impact fire safety signal, it issues a corresponding warning.

[0014] Furthermore, the specific analysis process of regional fire safety impact analysis is as follows:

[0015] The number of fires in the target area during the supervision period and the number of fires marked as high-hazard fires are obtained and defined as the total fire frequency value and the high-risk fire value, respectively. The total fire frequency value and the high-risk fire value are numerically compared with the preset total fire frequency threshold and the preset high-risk fire threshold, respectively. If the total fire frequency value or the high-risk fire value exceeds the corresponding preset threshold, a high-impact signal for fire safety is generated;

[0016] If both the total fire frequency value and the high fire risk value do not exceed the corresponding preset thresholds, the tracking characteristic values ​​of all fires occurring in the target area during the supervision period are averaged to obtain the regional disaster table value, and the fire impact initial inspection value is obtained by numerically calculating the total fire frequency value, the high fire risk value and the regional disaster table value. The fire impact initial inspection value is numerically compared with the preset fire impact initial inspection threshold. If the fire impact initial inspection value exceeds the preset fire impact initial inspection threshold, a fire safety high impact signal is generated.

[0017] Furthermore, if the fire impact initial inspection value does not exceed the preset fire impact initial inspection threshold, the fire dispatch value and the facility control value are obtained, and the fire dispatch value and the facility control value are numerically compared with the preset fire dispatch threshold and the preset facility control threshold respectively. If the fire dispatch value or the facility control value exceeds the corresponding preset threshold, a high fire safety impact signal is generated; if both the fire dispatch value and the facility control value do not exceed the corresponding preset threshold, a low fire safety impact signal is generated.

[0018] Furthermore, the fire safety impact assessment module is connected to the fire emergency analysis module and the fire facility management and evaluation module in communication. The fire emergency analysis module analyzes the fire emergency management status of the target area within the supervision period, obtains the fire dispatch value through the analysis, and sends the fire dispatch value to the fire safety impact assessment module;

[0019] The fire protection facility management and evaluation module analyzes the management status of fire protection facilities in the target area during the supervision period, obtains the facility control value through analysis, and sends the facility control value to the fire safety impact assessment module.

[0020] Furthermore, the specific analysis process of the fire emergency analysis module is as follows:

[0021] When a fire occurs in the target area, the arrival delay time of the firefighters is collected, and the arrival delay time is compared with the preset arrival delay time threshold. If the arrival delay time exceeds the preset arrival delay time threshold, the corresponding arrival delay time is marked as the arrival time, and the average of all arrival delay times corresponding to the target area within the supervision period is calculated to obtain the arrival time.

[0022] The number of deviation times within the supervision period is obtained and marked as deviation detection values, and the fire dispatch value is obtained by numerically calculating the deviation detection value and the deviation time.

[0023] Furthermore, the specific analysis process of the fire protection facility management and evaluation module is as follows:

[0024] All firefighting facilities in the target area are obtained, and the corresponding firefighting facilities are marked as i, where i is a natural number greater than or equal to 1; when a firefighting facility i fails, timing is performed until the corresponding failure is resolved, and the facility failure duration value is obtained accordingly, and all facility failure duration values ​​of the firefighting facility i within the supervision period are obtained and summed up to obtain the facility failure characteristic value, and the facility failure duration value is numerically compared with the preset facility failure duration threshold value. If the facility failure duration value exceeds the preset facility failure duration threshold value, the corresponding facility failure duration value is marked as the facility failure high duration value;

[0025] The number of high-value facility failures corresponding to firefighting facility i in the supervision period is obtained and marked as facility failure abnormal values, and the facility failure characteristic value and the facility failure abnormal value are numerically compared with the preset facility failure characteristic threshold and the preset facility failure abnormal threshold, respectively. If the facility failure characteristic value or the facility failure abnormal value exceeds the corresponding preset threshold, the firefighting facility i is marked as a warning facility;

[0026] The number of warning facilities in the target area is obtained and the ratio thereof is calculated with the total number of fire-fighting facilities to obtain the facility alarm value, and all the survey times of on-site survey for fire-fighting facility i within the supervision period are collected, the time difference between two adjacent groups of survey times is calculated to obtain the survey time difference, the mean of all survey time differences corresponding to fire-fighting facility i within the supervision period is calculated to obtain the survey analysis value, and the survey time difference is numerically compared with the preset survey time difference threshold. If the survey time difference exceeds the preset survey time difference threshold, the corresponding survey time difference is marked as an abnormal time difference;

[0027] The number of abnormal time differences corresponding to firefighting facility i within the supervision period is obtained and marked as abnormal time measurement values, and the abnormal time measurement values ​​of all firefighting facilities in the target area within the supervision period are averaged to obtain abnormal time condition values, and the survey and analysis values ​​of all firefighting facilities in the target area within the supervision period are averaged to obtain survey performance values; the facility control value is obtained by numerically calculating the facility alarm value, abnormal time condition value and survey performance value.

[0028] Furthermore, the present invention also proposes a smart fire alarm method based on regional monitoring, comprising the following steps:

[0029] Step 1: Collect environmental parameters in the target area in real time and comprehensively through a high-density, multi-dimensional monitoring network;

[0030] Step 2: Use machine learning algorithms to deeply mine and analyze the collected data to identify fire characteristic patterns, and then proceed to Steps 3, 4, and 5 after the fire is identified;

[0031] Step 3: Push fire warning information to people in the area;

[0032] Step 4: Automatically start the corresponding evacuation plan according to the fire risk level, and send the evacuation plan information to the regional fire supervision terminal;

[0033] Step 5: Start the corresponding fire-fighting facilities in the target area and send the start-up status information of each fire-fighting facility to the regional fire-fighting supervision terminal.

[0034] Compared with the prior art, the present invention has the following beneficial effects:

[0035] 1. In the present invention, the environmental parameters in the target area are collected in real time and comprehensively through the regional monitoring network module, and the intelligent data analysis module identifies the fire based on the collected data. After identifying the fire, the fire warning information is pushed to the personnel in the area and the corresponding evacuation plan and fire-fighting facilities are automatically started, so as to achieve rapid response and emergency evacuation, effectively reduce the losses caused by the fire, and help ensure the safety of the target area. After the fire warning is lifted, the fire hazard is accurately analyzed and timely feedback is given, which is conducive to the regional fire management personnel to grasp the severity of each fire in detail;

[0036] 2. In the present invention, the fire emergency analysis module is used to perform analysis to accurately feedback the fire response efficiency performance, the fire facility management and evaluation module is used to perform analysis to accurately feedback the management performance of the fire facilities in the target area during the supervision period, and the fire safety impact assessment module is used to conduct a comprehensive assessment and analysis of the regional fire safety hazard level. When a fire safety high impact signal is generated, the regional fire management personnel are reminded to strengthen the regional fire safety supervision, significantly reduce the regional fire hazards and reduce the difficulty of regional fire management. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to facilitate understanding by those skilled in the art, the present invention is further described below in conjunction with the accompanying drawings;

[0038] Figure 1 This is a system block diagram of Embodiment 1 of the present invention;

[0039] Figure 2 It is a system block diagram of Embodiment 2 and Embodiment 3 of the present invention;

[0040] Figure 3 This is a flow chart of the method of Embodiment 4 of the present invention. DETAILED DESCRIPTION

[0041] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0042] Embodiment 1: Figure 1 As shown, the intelligent fire alarm system based on regional monitoring proposed in the present invention includes a regional monitoring network module, an intelligent data analysis module, a fire tracking feedback module, an early warning information release module, an emergency evacuation plan module, a fire facility linkage module and a regional fire supervision terminal;

[0043] The regional monitoring network module forms a high-density, multi-dimensional monitoring network through various types of sensors such as smoke detectors, temperature sensors, flame detectors and gas leakage sensors deployed in the target area, collects environmental parameters in the target area in real time and comprehensively, and uploads data in real time through low-power wide area network or 5G communication technology, and sends the collected monitoring data to the intelligent data analysis module; the intelligent data analysis module uses machine learning algorithms to deeply mine and analyze the collected data, identify fire characteristic patterns, that is, identify fires, and improve the accuracy of early warning;

[0044] After identifying a fire, the warning information release module pushes fire warning information to people in the area through text messages, APP push, etc. The emergency evacuation plan module automatically activates the corresponding evacuation plan according to the fire risk level, and sends the evacuation plan information to the regional fire supervision end. The fire facility linkage module activates the corresponding fire facilities in the area and sends the activation status information of each fire facility to the regional fire supervision end, realizing rapid response and emergency evacuation, effectively reducing the losses caused by the fire, and ensuring the safety of the target area.

[0045] After identifying a fire, the fire tracking and feedback module tracks the fire situation in the target area until the fire warning is lifted. After the fire warning is lifted, the corresponding fire is marked as a high-hazard fire or a low-hazard fire through accurate fire hazard analysis, and the marking information of the corresponding fire is sent to the regional fire supervision end, so as to achieve accurate analysis of fire hazards and timely feedback, which is conducive to the regional fire management personnel to grasp the severity of each fire in detail and facilitate the adaptive adjustment of the fire monitoring management plan in the future; the specific analysis process of accurate fire hazard analysis is as follows:

[0046] The occurrence time of the corresponding fire and the time when the fire warning is lifted are collected and marked as the hazard time and the danger relief time, and the interval between the danger relief time and the hazard relief time is marked as the danger relief time; and the spread area of ​​the corresponding fire in the region is collected and marked as the spread detection value, and the amount of economic loss caused by the corresponding fire is marked as the loss detection value;

[0047] The tracking characteristic value ZP is calculated by weighted summing the emergency relief time SY, the spread detection value HY and the loss detection value QY through the formula ZP=up×SY+eq×HY+re×QY; wherein up, eq, and re are preset weight coefficients with values ​​greater than zero, and the larger the value of the tracking characteristic value ZP, the higher the degree of hazard of the corresponding fire in the target area;

[0048] The tracking feature value ZP is numerically compared with the preset tracking feature threshold. If the tracking feature value ZP exceeds the preset tracking feature threshold, it indicates that the hazard level of the corresponding fire in the target area is high, and the corresponding fire is marked as a high-hazard fire; if the tracking feature value ZP does not exceed the preset tracking feature threshold, it indicates that the hazard level of the corresponding fire in the target area is low, and the corresponding fire is marked as a low-hazard fire.

[0049] Embodiment 2: Figure 2 As shown, the difference between this embodiment and the first embodiment is that the fire tracking and feedback module is connected to the fire safety impact assessment module in communication, the fire safety impact assessment module is used to set the supervision cycle, the fire tracking and feedback module sends all fire information occurring in the target area within the supervision cycle to the fire safety impact assessment module, and the fire safety impact assessment module generates a high fire safety impact signal or a low fire safety impact signal through regional fire safety impact analysis;

[0050] And send the fire safety high impact signal or fire safety low impact signal to the regional fire supervision end. When the regional fire supervision end receives the fire safety high impact signal, it will issue a corresponding warning to remind the regional fire management personnel to strengthen the regional fire safety supervision and adjust the regional fire supervision plan in time, significantly reduce the regional fire hazards and reduce the difficulty of regional fire management. The intelligent level is high; the specific analysis process of regional fire safety impact analysis is as follows:

[0051] The number of fires in the target area during the supervision period and the number of fires marked as high-hazard fires are obtained and defined as the total fire frequency value and the high-risk fire value, respectively. The total fire frequency value and the high-risk fire value are numerically compared with the preset total fire frequency threshold and the preset high-risk fire threshold, respectively. If the total fire frequency value or the high-risk fire value exceeds the corresponding preset threshold, a high-impact signal for fire safety is generated;

[0052] If both the total fire frequency value and the high fire risk value do not exceed the corresponding preset threshold value, the tracking characteristic values ​​of all fires occurring in the target area during the supervision period are averaged to obtain the regional disaster table value, and the total fire frequency value FW, the high fire risk value GP and the regional disaster table value YS are numerically calculated by the formula XL=0.5×(tw×FW+hu×GP)+wq×YS to obtain the fire impact preliminary inspection value XL; wherein tw, hu, and wq are preset weight coefficients with values ​​greater than zero, hu>tw>wq; and the larger the value of the fire impact preliminary inspection value XL, the more serious the fire safety hazard in the target area during the supervision period is.

[0053] The fire impact initial inspection value is numerically compared with the preset fire impact initial inspection threshold. If the fire impact initial inspection value exceeds the preset fire impact initial inspection threshold, it indicates that the fire safety hazards in the target area during the supervision period are serious, and a fire safety high impact signal is generated.

[0054] Furthermore, if the fire impact initial inspection value does not exceed the preset fire impact initial inspection threshold, the fire dispatch value DX and the facility control value YX are obtained, and the fire dispatch value DX and the facility control value YX are numerically compared with the preset fire dispatch threshold and the preset facility control threshold respectively;

[0055] If the fire dispatch value DX or the facility control value YX exceeds the corresponding preset threshold, indicating that the fire safety hazard in the target area during the supervision period is serious, a high impact fire safety signal is generated; if the fire dispatch value DX and the facility control value YX do not exceed the corresponding preset threshold, indicating that the fire risk in the target area during the supervision period is small, a low impact fire safety signal is generated.

[0056] Embodiment 3: Figure 2 As shown, the difference between this embodiment and the first and second embodiments is that the fire safety impact assessment module is connected to the fire emergency analysis module and the fire facility management and evaluation module in communication. The fire emergency analysis module analyzes the fire emergency management status of the target area during the supervision period, obtains the fire dispatch value through analysis, and sends the fire dispatch value to the fire safety impact assessment module, which can not only accurately feedback the response efficiency performance of the fire in the target area during the supervision period, but also provide data support for the analysis process of the fire safety impact assessment module to ensure the accuracy of its analysis results; the specific analysis process of the fire emergency analysis module is as follows:

[0057] When a fire occurs in the target area, the arrival delay time of the firefighters is collected, and the arrival delay time is compared with the preset arrival delay time threshold. If the arrival delay time exceeds the preset arrival delay time threshold, it indicates that the response to the corresponding fire is not timely, and the corresponding arrival delay time is marked as the arrival time, and the average of all arrival delay times corresponding to the target area within the supervision period is calculated to obtain the arrival time;

[0058] The number of abnormal time durations within the supervision period is obtained and marked as the abnormal detection value, and the abnormal detection value TP and the table time duration QN are numerically calculated by the formula DX=a×TP+b×QN to obtain the fire dispatch value DX; wherein a and b are preset weight coefficients whose values ​​are greater than zero, and the larger the value of the fire dispatch value DX, the more untimely the response to the fire in the target area during the supervision period is, and the greater the safety risk brought about.

[0059] Furthermore, the fire protection facility management and evaluation module analyzes the management status of fire protection facilities in the target area during the supervision period, obtains the facility control value through analysis, and sends the facility control value to the fire safety impact assessment module, which can not only accurately feedback the management performance of fire protection facilities in the target area during the supervision period, but also provide data support for the analysis process of the fire safety impact assessment module, further ensuring the accuracy of its analysis results; the specific analysis process of the fire protection facility management and evaluation module is as follows:

[0060] All firefighting facilities in the target area are obtained, and the corresponding firefighting facilities are marked as i, where i is a natural number greater than or equal to 1; when a firefighting facility i fails, timing is performed until the corresponding failure is resolved, and the facility failure duration value is obtained accordingly, and all facility failure duration values ​​of the firefighting facility i within the supervision period are obtained and summed up to obtain the facility failure characteristic value, and the facility failure duration value is numerically compared with the preset facility failure duration threshold value. If the facility failure duration value exceeds the preset facility failure duration threshold value, the corresponding facility failure duration value is marked as the facility failure high duration value;

[0061] The number of high-value facility failures corresponding to firefighting facility i in the supervision period is obtained and marked as facility failure abnormal values, and the facility failure characteristic value and the facility failure abnormal value are numerically compared with the preset facility failure characteristic threshold and the preset facility failure abnormal threshold, respectively. If the facility failure characteristic value or the facility failure abnormal value exceeds the corresponding preset threshold, the firefighting facility i is marked as a warning facility;

[0062] The number of warning facilities in the target area is obtained and the ratio thereof is calculated with the total number of fire-fighting facilities to obtain the facility alarm value, and all the survey times of on-site survey for fire-fighting facility i within the supervision period are collected, the time difference between two adjacent groups of survey times is calculated to obtain the survey time difference, the mean of all survey time differences corresponding to fire-fighting facility i within the supervision period is calculated to obtain the survey analysis value, and the survey time difference is numerically compared with the preset survey time difference threshold. If the survey time difference exceeds the preset survey time difference threshold, the corresponding survey time difference is marked as an abnormal time difference;

[0063] The number of abnormal time differences corresponding to firefighting facility i within the supervision period is obtained and marked as abnormal time measurement values, and the abnormal time measurement values ​​of all firefighting facilities in the target area within the supervision period are averaged to obtain abnormal time condition values, and the survey and analysis values ​​of all firefighting facilities in the target area within the supervision period are averaged to obtain survey performance values;

[0064] The facility alarm value HM, abnormal condition value LW and survey performance value GF are numerically calculated using the formula YX=ry×HM+fq×LW+ng×GF to obtain the facility control value YX; wherein ry, fq, and ng are preset weight coefficients whose values ​​are greater than zero, and the larger the value of the facility control value YX, the worse the management performance of the fire-fighting facilities in the target area during the supervision period, and the more serious the fire safety hazards in the target area.

[0065] Embodiment 4: Figure 3 As shown, the difference between this embodiment and the first, second and third embodiments is that the intelligent fire alarm method based on regional monitoring proposed in the present invention includes the following steps:

[0066] Step 1: Collect environmental parameters in the target area in real time and comprehensively through a high-density, multi-dimensional monitoring network;

[0067] Step 2: Use machine learning algorithms to deeply mine and analyze the collected data to identify fire characteristic patterns, and then proceed to Steps 3, 4, and 5 after the fire is identified;

[0068] Step 3: Push fire warning information to people in the area;

[0069] Step 4: Automatically start the corresponding evacuation plan according to the fire risk level, and send the evacuation plan information to the regional fire supervision terminal;

[0070] Step 5: Start the corresponding fire-fighting facilities in the target area and send the start-up status information of each fire-fighting facility to the regional fire-fighting supervision terminal.

[0071] The working principle of the present invention is as follows: when in use, the environmental parameters in the target area are collected in real time and comprehensively through the regional monitoring network module, the intelligent data analysis module identifies the fire based on the collected data, and after identifying the fire, pushes the fire warning information to the personnel in the area and automatically starts the corresponding evacuation plan and fire-fighting facilities, so as to achieve rapid response and emergency evacuation, effectively reduce the losses caused by the fire, and help to ensure the safety of the target area, and after identifying the fire, the fire tracking and feedback module is used to track the fire situation in the target area until the fire warning is lifted, and after the fire warning is lifted, the fire hazards are accurately analyzed and timely fed back, which is conducive to the regional fire management personnel to grasp the severity of each fire in detail, and the fire safety impact assessment module is used to comprehensively evaluate and analyze the degree of regional fire safety hazards, and when a high-impact fire safety signal is generated, the regional fire management personnel are reminded to strengthen regional fire safety supervision, significantly reduce regional fire hazards and reduce the difficulty of regional fire management, and the intelligence level is high.

[0072] The above formulas are all dimensionless and numerical calculations. The formula is a formula obtained by collecting a large amount of data and performing software simulation to obtain the most recent real situation. The preset parameters in the formula are set by technicians in this field according to actual conditions. The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the contents of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that technicians in the relevant technical field can understand and use the present invention well. The present invention is only limited by the claims and their full scope and equivalents.

Claims

1. The intelligent fire alarm system based on regional monitoring is characterized by: It includes a regional monitoring network module, an intelligent data analysis module, an early warning information release module, an emergency evacuation plan module, a fire facility linkage module and a regional fire supervision terminal; the regional monitoring network module collects environmental parameters in the target area in real time and comprehensively through a high-density, multi-dimensional monitoring network deployed in the target area, and sends the collected monitoring data to the intelligent data analysis module; The intelligent data analysis module uses machine learning algorithms to conduct in-depth mining and analysis of the collected data to identify fire characteristic patterns; after identifying a fire, the early warning information release module pushes fire warning information to people in the area, and the emergency evacuation plan module automatically activates the corresponding evacuation plan according to the fire risk level, and sends the evacuation plan information to the regional fire supervision end. The fire facility linkage module activates the corresponding fire facilities in the area and sends the activation status information of each fire facility to the regional fire supervision end.

2. The intelligent fire alarm system based on regional monitoring according to claim 1 is characterized in that: The intelligent data analysis module is communicated with the fire tracking and feedback module. After identifying a fire, the fire tracking and feedback module tracks the fire situation in the target area until the fire warning is lifted. After the fire warning is lifted, the corresponding fire is marked as a high-hazard fire or a low-hazard fire through accurate fire hazard analysis, and the marking information of the corresponding fire is sent to the regional fire supervision terminal.

3. The intelligent fire alarm system based on regional monitoring according to claim 2 is characterized in that: The specific analysis process of accurate fire hazard analysis is as follows: the tracking feature value is calculated by weighted summing up the time to clear the danger, the spread detection value and the loss detection value. If the tracking feature value exceeds the preset tracking feature threshold, the corresponding fire is marked as a high-hazard fire; otherwise, the corresponding fire is marked as a low-hazard fire.

4. The intelligent fire alarm system based on regional monitoring according to claim 2 is characterized in that: The fire tracking and feedback module is communicatively connected to the fire safety impact assessment module. The fire safety impact assessment module is used to set the supervision cycle. The fire tracking and feedback module sends all fire information occurring in the target area within the supervision cycle to the fire safety impact assessment module. The fire safety impact assessment module generates a high fire safety impact signal or a low fire safety impact signal through regional fire safety impact analysis, and sends the high fire safety impact signal or the low fire safety impact signal to the regional fire supervision terminal.

5. The intelligent fire alarm system based on regional monitoring according to claim 4 is characterized in that: The specific analysis process of regional fire safety impact analysis is as follows: if the total fire frequency value or the high fire risk value exceeds the corresponding preset threshold, a fire safety high impact signal is generated; if both the total fire frequency value and the high fire risk value do not exceed the corresponding preset threshold, the fire impact initial inspection value is obtained by numerically calculating the total fire frequency value, the high fire risk value and the regional disaster table value; if the fire impact initial inspection value exceeds the preset fire impact initial inspection threshold, a fire safety high impact signal is generated.

6. The intelligent fire alarm system based on regional monitoring according to claim 5 is characterized in that: If the fire impact initial inspection value does not exceed the preset fire impact initial inspection threshold, the fire dispatch value and facility control value are obtained. If the fire dispatch value or the facility control value exceeds the corresponding preset threshold, a high fire safety impact signal is generated; otherwise, a low fire safety impact signal is generated.

7. The intelligent fire alarm system based on regional monitoring according to claim 6 is characterized in that: The fire safety impact assessment module is communicatively connected to the fire emergency analysis module and the fire facility management and evaluation module. The fire emergency analysis module obtains the fire dispatch value through analysis and sends the fire dispatch value to the fire safety impact assessment module; the fire facility management and evaluation module obtains the facility control value through analysis and sends the facility control value to the fire safety impact assessment module.

8. The intelligent fire alarm system based on regional monitoring according to claim 7 is characterized in that: The specific analysis process of the fire emergency analysis module is as follows: the average of all arrival delay times corresponding to the target area within the supervision period is calculated to obtain the arrival time, the number of arrival deviation times within the supervision period is obtained and marked as the arrival deviation detection value, and the fire dispatch value is obtained by numerically calculating the arrival deviation detection value and the arrival time.

9. The intelligent fire alarm system based on regional monitoring according to claim 8 is characterized in that: The specific analysis process of the fire protection facility management and evaluation module is as follows: All firefighting facilities in the target area are obtained, and the corresponding firefighting facilities are marked as i, where i is a natural number greater than or equal to 1; the facility fault characteristic value and the facility fault abnormal value are numerically compared with the preset facility fault characteristic threshold and the preset facility fault abnormal threshold, respectively; if the facility fault characteristic value or the facility fault abnormal value exceeds the corresponding preset threshold, the firefighting facility i is marked as a warning facility; The number of warning facilities in the target area is obtained and the ratio is calculated with the total number of fire-fighting facilities to obtain the facility alarm value. The facility control value is obtained by numerically calculating the facility alarm value, abnormal condition value and survey performance value.

10. The intelligent fire alarm method based on regional monitoring is characterized by: The method adopts the intelligent fire alarm system based on regional monitoring as described in any one of claims 1-9.

Images