A warning processing method and system for intelligent safety and fire protection

Abstract

The present invention provides a warning processing method and system for intelligent fire safety and security, belonging to the technical field of warning devices. Specifically, it includes: determining potential fire-fighting devices among associated fire-fighting devices by using the analysis results of historical monitoring data of associated fire-fighting devices, obtaining distribution data of potential fire-fighting devices among associated fire-fighting devices in different fire hazard sub-areas, and combining the interval distances between different fire hazard sub-areas and different associated fire-fighting devices. When it is determined that there is no fire hazard sub-area where the fire control risk does not meet the requirements, determining the interval distances between different fire hazard sub-areas, and combining the fire control risks and fire hazard coefficients of different fire hazard sub-areas to determine whether to issue a warning signal, thereby improving the reliability of fire risk control management.

Description

Technical Field

[0001] The present invention belongs to the technical field of early warning devices, and in particular, relates to an early warning processing method and system for smart firefighting. Background Art

[0002] In order to achieve early warning of fire hazards, the invention patent application CN202111086614.2 "A safety early warning system for electric vehicle charging areas" monitors the temperature signal and smoke signal in the charging area in real time and transmits them to the control module. The control module monitors the charging current and power consumption of the charging pile in real time, and specifically controls the power off of the charging pile to minimize the possibility of harm. However, there are the following technical problems:

[0003] In the process of identifying fire hazards, in addition to fire hazard signals such as temperature signals and smoke signals, the operating status of the water pressure monitoring data of the fire-fighting equipment, the fire-fighting linkage early warning device, etc. are also crucial. Therefore, if the monitoring and analysis of multi-dimensional data cannot be achieved, the accuracy of the identification and processing of fire hazards cannot be guaranteed.

[0004] In response to the above technical problems, the present invention provides an early warning processing method and system for smart fire protection. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] According to one aspect of the present invention, a warning processing method for smart fire safety is provided.

[0007] A warning processing method for smart fire prevention and control, specifically comprising:

[0008] S1 determines the control sub-areas in the fire control area based on the distribution data of the fire hazard devices, obtains the setting data of the fire monitoring devices in different control sub-areas, and determines the fire hazard sub-areas and fire hazard coefficients in different control sub-areas based on the usage data of the fire hazard devices in different control sub-areas;

[0009] S2 determines associated fire-fighting devices of different fire-hazard sub-areas according to the distribution positions of different fire-hazard sub-areas, and determines fire-fighting devices with hidden dangers among the associated fire-fighting devices by using the analysis results of historical monitoring data of the associated fire-fighting devices;

[0010] S3 obtains the distribution data of the hidden danger fire-fighting devices in the associated fire-fighting devices of different fire-hazard sub-areas, and when it is determined that there is no fire-hazard sub-area where the fire control risk does not meet the requirements, based on the interval distances between different fire-hazard sub-areas and different associated fire-fighting devices, proceeds to the next step;

[0011] S4 determines the interval distance between different fire hazard sub - regions, and determines whether to issue a warning signal in combination with the fire control risk and fire hazard coefficient of different fire hazard sub - regions.

[0012] The beneficial effects of the present invention are as follows:

[0013] By using the analysis result of the historical monitoring data of associated fire protection devices to determine the potential fire protection devices in the associated fire protection devices, the identification of potential fire protection devices from the abnormal conditions of the historical monitoring data of associated fire protection devices is realized, which also lays a foundation for further identifying the fire risk of fire hazard sub - regions in combination with the potential situation of associated fire protection devices, and improves the accuracy of the identification and processing results of fire risk.

[0014] Determining whether to issue a warning signal based on the interval distance between different fire hazard sub - regions, the fire control risk of different fire hazard sub - regions, and the fire hazard coefficient not only takes into account the distribution density of fire hazard sub - regions caused by the interval distance between fire hazard sub - regions, but also takes into account the risk situation of fire protection devices and the potential situation of fire risk in different fire hazard sub - regions, realizes the generation of warning signals from multiple perspectives, and improves the reliability of the identification and processing of fire risk.

[0015] A further technical solution lies in that the method for determining the fire hazard sub - regions in the control sub - region is as follows:

[0016] Based on the usage data of the fire hazard devices in the control sub - region, determine the cumulative usage duration of the fire hazard devices in the control sub - region;

[0017] Determine the defect data of the fire monitoring devices during the cumulative usage duration, and use the defect data to determine the defective usage duration during the cumulative usage duration;

[0018] Determine the fire hazard coefficient of the control sub - region according to the ratio of the defective usage duration to the cumulative usage duration in the control sub - region, and use the fire hazard coefficient to determine whether the control sub - region is a fire hazard sub - region.

[0019] A further technical solution lies in that the defective usage duration is the duration during which the operating state of the fire monitoring devices is abnormal during the cumulative usage duration.

[0020] A further technical solution lies in that determining whether to issue a warning signal specifically includes:

[0021] Based on the fire control risk and fire hazard coefficient of different fire hazard sub - regions, determine the comprehensive risk coefficient of different fire hazard sub - regions;

[0022] Based on the interval distances between different fire hazard sub - regions, determine the number of fire hazard sub - regions with interval distances within a preset interval distance range, and determine the distribution aggregation coefficient according to the proportion of the number of fire hazard sub - regions with interval distances within the preset interval distance range;

[0023] Use the weighted sum of the comprehensive risk coefficients of different fire hazard sub - regions to determine the risk coefficient, and determine the fire risk coefficient in combination with the distribution aggregation coefficient, and determine whether to issue a warning signal according to the fire risk coefficient.

[0024] A further technical solution lies in that the fire risk coefficient is determined according to the product of the risk coefficient and the distribution aggregation coefficient.

[0025] A further technical solution lies in that when the fire risk coefficient is less than a preset fire risk coefficient threshold, it is determined that a warning signal needs to be issued.

[0026] In a second aspect, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, and when the processor runs the computer program, it executes the above - mentioned warning processing method for intelligent safety and fire protection.

[0027] Other features and advantages will be described in the following description, and the objects and other advantages of the present invention are realized and obtained by the structures specifically pointed out in the description and the drawings.

[0028] To make the above - mentioned objects, features, and advantages of the present invention more obvious and understandable, the following specific embodiments are given, and in conjunction with the accompanying drawings, the detailed description is as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] By referring to the accompanying drawings and describing its exemplary embodiments in detail, the above - mentioned and other features and advantages of the present invention will become more obvious.

[0030] Figure 1 is a flowchart of a warning processing method for intelligent safety and fire protection;

[0031] Figure 2 is a flowchart of a method for determining fire hazard sub - regions in a control sub - region;

[0032] Figure 3 is a flowchart of a method for determining hazard - prone fire protection devices in associated fire protection devices;

[0033] Figure 4 is a flowchart of a method for determining the fire control risk of a fire hazard sub - region;

[0034] Figure 5It is a framework diagram of a computer system. Specific implementation manners

[0035] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the scope of protection of this specification.

[0036] During the process of identifying fire hazards, in addition to fire hazard signals such as temperature signals and smoke signals, the water pressure monitoring data of fire-fighting devices and the operating states of fire-fighting linkage warning devices, etc. are also crucial. Therefore, it is necessary to monitor and analyze multi-dimensional data to achieve the identification and processing of fire hazards.

[0037] Fire hazard coefficient in the controlled sub-region: Determine the fire hazard coefficient of the controlled sub-region based on the ratio of the defective usage duration to the cumulative usage duration of the fire hazard devices in the controlled sub-region, and determine the controlled sub-region with a fire hazard coefficient greater than 0.6 as the fire hazard sub-region.

[0038] Associated fire-fighting devices: Fire-fighting devices whose distance from the fire hazard sub-region is within the preset distance interval.

[0039] Hazardous fire-fighting devices in the associated fire-fighting devices: Take the moment when there are defects in the historical monitoring data in the associated fire-fighting devices as the monitoring data defect moment, and determine the monitoring data defect period based on the distribution data of the monitoring data defect moment. When the number of monitoring data defect periods is greater than 10, determine the associated fire-fighting devices as hazardous fire-fighting devices.

[0040] Fire control risk: Determine the control influence weight coefficient of different associated fire-fighting devices based on the distance between the fire hazard sub-region and different associated fire-fighting devices, obtain the proportion of the number of hazardous fire-fighting devices in the associated fire-fighting devices, and use the proportion of the number of hazardous fire-fighting devices in the associated fire-fighting devices to determine the hazard proportion coefficient. Determine the fire control risk of the fire hazard sub-region according to the sum of the control influence weight coefficients of different associated fire-fighting devices and the product of the hazard proportion coefficient. When the fire control risk is below 0.3, it is determined that the fire control risk of the fire hazard sub-region meets the requirements. When the fire control risk is above 0.3, it is determined that the fire control risk of the fire hazard sub-region does not meet the requirements.

[0041] Determine whether to issue a warning signal: Determine the comprehensive risk coefficient of different fire hazard sub - regions by multiplying the fire control risks and fire hazard coefficients of different fire hazard sub - regions. Based on the interval distances between different fire hazard sub - regions, determine the number of fire hazard sub - regions with interval distances within the preset interval distance range. Determine the distribution aggregation coefficient according to the proportion of the number of fire hazard sub - regions with interval distances within the preset interval distance range. Determine the risk coefficient by using the weighted sum of the comprehensive risk coefficients of different fire hazard sub - regions. Determine the fire risk coefficient by using the weighted sum of the risk coefficient and the distribution aggregation coefficient, and determine whether to issue a warning signal according to the fire risk coefficient.

[0042] Embodiment 1 To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, the first aspect is provided. The present invention provides a warning processing method for intelligent fire and safety, specifically including:

[0043] S1 Determine the control sub - regions in the fire control area based on the distribution data of fire hazard devices, obtain the setting data of fire monitoring devices in different control sub - regions, and combine the usage data of fire hazard devices in different control sub - regions to determine the fire hazard sub - regions and fire hazard coefficients in different control sub - regions;

[0044] S2 Determine the associated fire devices of different fire hazard sub - regions based on the distribution positions of different fire hazard sub - regions, and use the analysis results of the historical monitoring data of the associated fire devices to determine the hazard fire devices in the associated fire devices;

[0045] S3 Obtain the distribution data of the hazard fire devices in the associated fire devices of different fire hazard sub - regions, and combine the interval distances between different fire hazard sub - regions and different associated fire devices. When it is determined that there are no fire hazard sub - regions where the fire control risks do not meet the requirements, proceed to the next step;

[0046] S4 Determine the interval distances between different fire hazard sub - regions, and combine the fire control risks and fire hazard coefficients of different fire hazard sub - regions to determine whether to issue a warning signal.

[0047] Further, as Figure 2 shown, the method for determining the fire hazard sub - regions in the control sub - regions is as follows:

[0048] Determine the number of fire monitoring devices set in the control sub - regions based on the setting data of the fire monitoring devices in the control sub - regions;

[0049] Determine the cumulative usage duration of the fire hazard devices in the control sub - regions based on the usage data of the fire hazard devices in the control sub - regions;

[0050] Determine the fire hazard coefficient of the controlled sub-region based on the cumulative usage duration of the fire hazard devices and the number of fire monitoring devices set in the controlled sub-region, and use the fire hazard coefficient to determine whether the controlled sub-region is a fire hazard sub-region.

[0051] Optionally, the method for determining the fire hazard sub-region in the controlled sub-region is as follows:

[0052] Based on the usage data of the fire hazard devices in the controlled sub-region, determine the cumulative usage duration of the fire hazard devices in the controlled sub-region;

[0053] Determine the defect data of the fire monitoring devices during the cumulative usage duration, and use the defect data to determine the defective usage duration during the cumulative usage duration;

[0054] Determine the fire hazard coefficient of the controlled sub-region according to the ratio of the defective usage duration to the cumulative usage duration in the controlled sub-region, and use the fire hazard coefficient to determine whether the controlled sub-region is a fire hazard sub-region.

[0055] Furthermore, the defective usage duration is the duration during which the operating status of the fire monitoring devices is abnormal during the cumulative usage duration.

[0056] In another embodiment, the method for determining the fire hazard sub-region in the controlled sub-region is as follows:

[0057] S11 Based on the setting data of the fire monitoring devices in the controlled sub-region, determine the number of fire monitoring devices set in the controlled sub-region, and combine the defect durations of different fire monitoring devices to determine the monitoring hazard coefficient of the controlled sub-region;

[0058] Optionally, the following content is included in the above step S11:

[0059] S111 Based on the setting data of the fire monitoring devices in the controlled sub-region, determine the number of fire monitoring devices set in the controlled sub-region. When the number of fire monitoring devices set in the controlled sub-region meets the requirements, proceed to step S112; when the number of fire monitoring devices set in the controlled sub-region does not meet the requirements, proceed to step S113;

[0060] S112 Determine the defect durations of different fire monitoring devices based on the defect data of the fire monitoring devices in different controlled sub-regions. When there is no fire monitoring device with a defect duration greater than the preset defect duration, it is determined that the controlled sub-region does not belong to the fire hazard sub-region; when there is a fire monitoring device with a defect duration greater than the preset defect duration, proceed to step S113;

[0061] S113 determines the monitoring hidden danger coefficient of the control sub-region based on the number of fire monitoring devices set in the control sub-region and the defect duration of different fire monitoring devices. When the monitoring hidden danger coefficient of the monitoring sub-region is less than the preset hidden danger coefficient threshold, it is determined that the control sub-region does not belong to the fire hidden danger sub-region. When the monitoring hidden danger coefficient of the monitoring sub-region is not less than the preset hidden danger coefficient threshold, it proceeds to step S12.

[0062] S12 determines the cumulative usage duration of the fire hidden danger devices in the control sub-region based on the usage data of the fire hidden danger devices in the control sub-region, and determines the fire defect coefficient of the control sub-region in combination with the defective usage duration in the cumulative usage duration of the fire hidden danger devices in the control sub-region;

[0063] Optionally, the above step S12 includes the following content:

[0064] S121 When the monitoring hidden danger coefficient of the monitoring sub-region is within the preset hidden danger coefficient interval, it proceeds to step S122. When the monitoring hidden danger coefficient of the monitoring sub-region is not within the preset hidden danger coefficient interval, it proceeds to step S124;

[0065] S122 determines the cumulative usage duration of the fire hidden danger devices in the control sub-region based on the usage data of the fire hidden danger devices in the control sub-region. When the cumulative usage duration of the fire hidden danger devices in the control sub-region is not greater than the preset usage duration, it is determined that the control sub-region does not belong to the fire hidden danger sub-region. When the cumulative usage duration of the fire hidden danger devices in the control sub-region is greater than the preset usage duration, it proceeds to step S123;

[0066] S123 obtains the defective usage duration in the cumulative usage duration of the fire hidden danger devices in the control sub-region. When the defective usage duration in the cumulative usage duration of the fire hidden danger devices is less than the preset defective duration threshold, it is determined that the control sub-region does not belong to the fire hidden danger sub-region. When the defective usage duration in the cumulative usage duration of the fire hidden danger devices is not less than the preset defective duration threshold, it proceeds to step S124;

[0067] S124 determines the fire defect coefficient of the control sub-region based on the cumulative usage duration of the fire hidden danger devices in the control sub-region and the defective usage duration in the cumulative usage duration of the fire hidden danger devices in the control sub-region. When both the fire defect coefficient and the monitoring hidden danger coefficient of the control sub-region are within the preset coefficient interval, it is determined that the control sub-region does not belong to the fire hidden danger sub-region. When any one of the fire defect coefficient and the monitoring hidden danger coefficient of the control sub-region is not within the preset coefficient interval, it proceeds to step S13.

[0068] S13 determines the fire hazard coefficient of the control sub-region according to the monitoring hazard coefficient and the fire defect coefficient in the control sub-region, and determines whether the control sub-region is a fire hazard sub-region by using the fire hazard coefficient.

[0069] It should be noted that the associated fire protection devices of the fire hazard sub-region are the fire protection devices whose distance from the fire hazard sub-region is within a preset interval distance range.

[0070] Specifically, as Figure 3 shown, the method for determining the hazard fire protection devices among the associated fire protection devices is as follows:

[0071] Based on the analysis result of the historical monitoring data of the associated fire protection devices, determine the moment when the historical monitoring data of the associated fire protection devices is defective, and use it as the monitoring data defect moment;

[0072] Determine the monitoring data defect period based on the distribution data of the monitoring data defect moments;

[0073] Determine whether the associated fire protection device is a hazard fire protection device according to the number of the monitoring data defect periods.

[0074] Furthermore, the monitoring data defect period is determined according to the number of monitoring data defect moments within a preset time period. Specifically, the preset time period with the number of monitoring data defect moments greater than the preset moment number is used as the monitoring data defect period.

[0075] In addition, it should be noted that when the number of the monitoring data defect periods is greater than the preset period number, it is determined that the associated fire protection device is a hazard fire protection device.

[0076] Optionally, the method for determining the hazard fire protection devices among the associated fire protection devices is as follows:

[0077] Based on the analysis result of the historical monitoring data of the associated fire protection devices, determine the moment when the historical monitoring data of the associated fire protection devices is defective, and use it as the monitoring data defect moment;

[0078] Determine the number of monitoring data defect moments based on the distribution data of the monitoring data defect moments;

[0079] Determine whether the associated fire protection device is a hazard fire protection device according to the number of the monitoring data defect moments.

[0080] Optionally, the method for determining the hazard fire protection devices among the associated fire protection devices is as follows:

[0081] S21 determines the moment when there are defects in the historical monitoring data in the associated fire protection device based on the analysis result of the historical monitoring data of the associated fire protection device, and uses it as the monitoring data defect moment;

[0082] S22 determines the monitoring data defect time period based on the distribution data of the monitoring data defect moments, determines the distribution data of the monitoring data defect moments in different monitoring data defect time periods, and combines the interval duration between the monitoring data defect time period and the adjacent monitoring data defect time period to determine the monitoring data anomaly coefficient of different monitoring data defect time periods;

[0083] S23 determines the comprehensive data anomaly coefficient based on the monitoring data anomaly coefficients of different monitoring data defect time periods, and uses the comprehensive data anomaly coefficient to determine whether the associated fire protection device is a potential fire hazard device.

[0084] Specifically, as Figure 4 shown, the method for determining the fire control risk of the fire hazard sub-region is:

[0085] Determine the control influence weight coefficients of different associated fire protection devices based on the interval distances between the fire hazard sub-region and different associated fire protection devices;

[0086] Obtain the proportion of the number of potential fire hazard devices in the associated fire protection devices, and use the proportion of the number of potential fire hazard devices in the associated fire protection devices to determine the potential hazard proportion coefficient;

[0087] Determine the fire control risk of the fire hazard sub-region according to the sum of the control influence weight coefficients of different associated fire protection devices and the potential hazard proportion coefficient.

[0088] Furthermore, the fire control risk of the fire hazard sub-region is determined according to the product of the sum of the control influence weight coefficients of different associated fire protection devices and the potential hazard proportion coefficient.

[0089] In addition, it should be noted that the value range of the fire control risk of the fire hazard sub-region is between 0 and 1. When the fire control risk of the fire hazard sub-region is greater than the preset control risk coefficient, it is determined that the fire control risk of the fire hazard sub-region does not meet the requirements.

[0090] Determine that there is no fire hazard sub-region where the fire control risk does not meet the requirements

[0091] Furthermore, when there is a fire hazard sub-region where the fire control risk does not meet the requirements, it is determined that a warning signal needs to be issued.

[0092] Optionally, the method for determining the fire control risk of the fire hazard sub-region is:

[0093] Obtain the quantity of associated fire protection devices in the sub - area with fire hazards. When the quantity of the associated fire protection devices is not within the preset device quantity range, it is determined that the fire control risk of the sub - area with fire hazards does not meet the requirements;

[0094] When the quantity of the associated fire protection devices is within the preset device quantity range:

[0095] Obtain the proportion of the quantity of fire - hazard devices among the associated fire protection devices. When the proportion of the quantity of fire - hazard devices among the associated fire protection devices is greater than the preset quantity proportion, it is determined that the fire control risk of the sub - area with fire hazards does not meet the requirements;

[0096] When the proportion of the quantity of fire - hazard devices among the associated fire protection devices is not greater than the preset quantity proportion: Take the associated fire protection devices excluding the fire - hazard devices as normal fire protection devices. When the quantity of the normal fire protection devices does not meet the requirements, it is determined that the fire control risk of the sub - area with fire hazards does not meet the requirements;

[0097] When the quantity of the normal fire protection devices meets the requirements:

[0098] Based on the interval distances between the sub - area with fire hazards and different associated fire protection devices, determine the control influence weight coefficients of different associated fire protection devices. When the sum of the control influence weight coefficients of the normal fire protection devices does not meet the requirements, it is determined that the fire control risk of the sub - area with fire hazards does not meet the requirements;

[0099] When the sum of the control influence weight coefficients of the normal fire protection devices meets the requirements:

[0100] Obtain the proportion of the quantity of fire - hazard devices among the associated fire protection devices, and use the proportion of the quantity of fire - hazard devices among the associated fire protection devices to determine the hazard proportion coefficient;

[0101] Determine the fire control risk of the sub - area with fire hazards based on the sum of the control influence weight coefficients of different associated fire protection devices and the hazard proportion coefficient.

[0102] Furthermore, determine whether to issue a warning signal, specifically including:

[0103] Based on the fire control risks and fire hazard coefficients of different sub - areas with fire hazards, determine the comprehensive risk coefficients of different sub - areas with fire hazards;

[0104] Based on the interval distances between different sub - areas with fire hazards, determine the quantity of sub - areas with fire hazards whose interval distances are within the preset interval distance range. Determine the distribution aggregation coefficient according to the proportion of the quantity of sub - areas with fire hazards whose interval distances are within the preset interval distance range;

[0105] Determine the risk coefficient by using the weighted sum of the comprehensive risk coefficients of different sub-regions of fire hazards, determine the fire risk coefficient in combination with the distribution aggregation coefficient, and determine whether to issue a warning signal according to the fire risk coefficient.

[0106] Specifically, the fire risk coefficient is determined according to the product of the risk coefficient and the distribution aggregation coefficient.

[0107] It should be noted that when the fire risk coefficient is less than the preset fire risk coefficient threshold, it is determined that a warning signal needs to be issued.

[0108] Embodiment 2 Second aspect, as Figure 5 shown, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, and when the processor runs the computer program, it executes the above-mentioned warning processing method for intelligent fire safety.

[0109] Optionally, the above step S21 includes the following content:

[0110] S211 Based on the analysis result of the historical monitoring data of the associated fire protection device, determine the moment when the historical monitoring data in the associated fire protection device is defective, and use it as the monitoring data defect moment;

[0111] S212 When the number of the monitoring data defect moments does not meet the requirements, determine that the associated fire protection device is a potential fire hazard device, and when the number of the monitoring data defect moments meets the requirements, proceed to step S213;

[0112] S213 Obtain the number of monitoring data defect moments in the most recent preset time period. When the proportion of the number of monitoring data defect moments in the most recent preset time period does not meet the requirements, determine that the associated fire protection device is a potential fire hazard device. When the proportion of the number of monitoring data defect moments in the most recent preset time period meets the requirements, proceed to step S22.

[0113] Optionally, the above step S22 includes the following content:

[0114] S221 Use the distribution data of the monitoring data defect moments to determine the monitoring data defect time period. When the number of the monitoring data defect time periods does not meet the requirements, determine that the associated fire protection device is a potential fire hazard device. When the number of the monitoring data defect time periods meets the requirements, proceed to step S222;

[0115] S222 Obtain the interval duration between different monitoring data defect time periods, and use the interval duration to determine the continuous defect time periods in the monitoring data defect time periods. When the number of continuous defect time periods does not meet the requirements, determine the associated fire protection device as a potential hazard fire protection device. When the number of continuous defect time periods meets the requirements, proceed to step S223;

[0116] S223 Use the distribution data of the monitoring data defect moments in different monitoring data defect time periods, and combine the interval duration between the monitoring data defect time periods and the adjacent monitoring data defect time periods to determine the monitoring data anomaly coefficient of different monitoring data defect time periods. When there are monitoring data defect time periods with monitoring data anomaly coefficients that do not meet the requirements, proceed to step S224. When there are no monitoring data defect time periods with monitoring data anomaly coefficients that do not meet the requirements, proceed to step S23;

[0117] S224 Take the monitoring data defect time periods with monitoring data anomaly coefficients that do not meet the requirements as abnormal time periods. When the number of abnormal time periods does not meet the requirements, determine the associated fire protection device as a potential hazard fire protection device. When the number of abnormal time periods meets the requirements, proceed to step S23.

[0118] Each embodiment in this specification is described in a progressive manner. The same or similar parts among the embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple. For the relevant parts, refer to the partial description of the method embodiments.

[0119] The above describes specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order than in the embodiments and still achieve the desired result. Additionally, the processes depicted in the figures do not necessarily require the specific order or continuous order shown to achieve the desired result. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0120] The above is only one or more embodiments of this specification and is not used to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various changes and modifications. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. A warning processing method for intelligent security and fire protection, characterized in that, Specifically include: Determine the control sub-areas in the fire control area based on the distribution data of fire hazard devices, obtain the setting data of fire monitoring devices in different control sub-areas, and combine the usage data of fire hazard devices in different control sub-areas to determine the fire hazard sub-areas and fire hazard coefficients in different control sub-areas; Determine the associated fire devices of different fire hazard sub-areas based on the distribution locations of different fire hazard sub-areas, and determine the hazard fire devices in the associated fire devices using the analysis results of the historical monitoring data of the associated fire devices; Obtain the distribution data of the hazard fire devices in the associated fire devices of different fire hazard sub-areas, and combine the interval distances between different fire hazard sub-areas and different associated fire devices. When it is determined that there is no fire control risk not meeting the requirements in the fire hazard sub-areas, proceed to the next step; Determine the interval distances between different fire hazard sub-areas, and combine the fire control risks and fire hazard coefficients of different fire hazard sub-areas to determine whether to issue a warning signal; The method for determining the fire hazard sub-areas in the control sub-areas is as follows: Determine the cumulative usage duration of the fire hazard devices in the control sub-areas based on the usage data of the fire hazard devices in the control sub-areas; Determine the defect data of the fire monitoring devices during the cumulative usage duration, and use the defect data to determine the defective usage duration during the cumulative usage duration; Determine the fire hazard coefficient of the control sub-areas according to the ratio of the defective usage duration to the cumulative usage duration in the control sub-areas, and use the fire hazard coefficient to determine whether the control sub-areas are fire hazard sub-areas; Determine whether to issue a warning signal, specifically including: Based on the fire control risks and fire hazard coefficients of different fire hazard sub-areas, determine the comprehensive risk coefficients of different fire hazard sub-areas; Based on the interval distances between different fire hazard sub-areas, determine the number of fire hazard sub-areas with interval distances within the preset interval distance range, and determine the distribution aggregation coefficient according to the proportion of the number of fire hazard sub-areas with interval distances within the preset interval distance range; Determine the risk coefficient using the weighted sum of the comprehensive risk coefficients of different fire hazard sub-areas, determine the fire risk coefficient in combination with the distribution aggregation coefficient, and determine whether to issue a warning signal according to the fire risk coefficient; The method for determining the fire control risk of the fire hazard sub-areas is as follows: Based on the interval distances between the fire hazard sub-areas and different associated fire devices, determine the control influence weight coefficients of different associated fire devices; Obtain the proportion of the number of hazard fire devices in the associated fire devices, and use the proportion of the number of hazard fire devices in the associated fire devices to determine the hazard proportion coefficient; Determine the fire control risk of the fire hazard sub-areas according to the sum of the control influence weight coefficients of different associated fire devices and the hazard proportion coefficient.

2. The early warning processing method for intelligent safety and fire protection according to claim 1, characterized in that, The defective usage duration is the duration during which the operating state of the fire monitoring devices is abnormal during the cumulative usage duration.

3. The early warning processing method for intelligent security and fire protection according to claim 1, wherein, The associated fire protection device of the fire hazard sub-region is a fire protection device whose distance from the fire hazard sub-region is within a preset distance range.

4. The early warning processing method for intelligent security and fire protection according to claim 1, wherein The method for determining the fire hazard device among the associated fire protection devices is as follows: Based on the analysis result of the historical monitoring data of the associated fire protection device, determine the moment when the historical monitoring data of the associated fire protection device is defective, and use it as the monitoring data defect moment; Determine the monitoring data defect period based on the distribution data of the monitoring data defect moments; Determine whether the associated fire protection device is a fire hazard device according to the number of the monitoring data defect periods.

5. The early warning processing method for intelligent safety and fire protection according to claim 4, characterized in that, The monitoring data defect period is determined according to the number of monitoring data defect moments within a preset duration. Specifically, the preset duration with the number of monitoring data defect moments greater than the preset moment number is used as the monitoring data defect period.

6. The warning processing method for intelligent security and fire protection according to claim 4, wherein, When the number of the monitoring data defect periods is greater than the preset period number, it is determined that the associated fire protection device is a fire hazard device.

7. The early warning processing method for intelligent security and fire protection according to claim 1, characterized in that, The fire risk coefficient is determined according to the product of the risk coefficient and the distribution aggregation coefficient.

8. A computer system, comprising: A memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, wherein when the processor runs the computer program, it executes the early warning processing method for intelligent fire and safety according to any one of claims 1-7.

Images