A smart fire safety management system based on IoT data analysis

Abstract

The present invention relates to the field of fire safety management technology, and in particular to an intelligent fire safety management system based on Internet of Things data analysis, comprising a management platform, a fire supervision unit, a delay feedback unit, a safety supervision unit, a management matching unit, a management matching unit and an early warning processing unit; the present invention analyzes from two perspectives: a monitoring front end and an early warning back end, so as to reduce the influence of the monitoring front end and the early warning back end on subsequent firefighting, and at the same time, reasonably and targetedly manages the fire monitoring area in combination with the rescue impact situation, that is, accurately manages the fire monitoring area by means of information feedback, so as to reduce the influence of the monitoring front end, the early warning back end and the rescue impact situation on the subsequent firefighting and rescue in the fire monitoring area, which helps to reduce the degree of obstruction to subsequent firefighting and rescue, and at the same time helps to improve the rationality and overall safety of fire management in the fire monitoring area.

Description

Technical Field

[0001] The present invention relates to the technical field of fire safety management, and in particular to an intelligent fire safety management system based on Internet of Things data analysis. Background Art

[0002] Firefighting mainly includes the rescue of personnel at the fire scene, the rescue of important facilities and equipment, cultural relics, the security and rescue of important property, and the extinguishing of fires, etc. The purpose is to reduce the degree of damage caused by fires, reduce casualties and property losses; As people pay more attention to fire safety, more and more buildings are now equipped with fire alarms and fire protection systems; after a fire occurs, the fire alarm will sound an alarm, and the fire department will only dispatch police after receiving the fire alarm;

[0003] However, in the existing fire management process, it is impossible to conduct safety supervision on fire monitoring equipment, thereby reducing the timeliness of warning and operational safety of fire monitoring equipment, and it is impossible to conduct reasonable fire management in combination with warning delays and rescue road obstructions, thereby increasing the difficulty and delay of subsequent fire rescue. At the same time, it is impossible to conduct targeted control of the entire fire monitoring area in combination with warning delays and rescue road obstructions, resulting in reduced management effect of the entire fire monitoring area;

[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 safety management system based on Internet of Things data analysis to solve the above-mentioned technical defects. The present invention analyzes from the two perspectives of monitoring front-end and early warning back-end to reduce the impact of monitoring front-end and early warning back-end on subsequent firefighting, and at the same time, combines the rescue impact to carry out reasonable and targeted management of the fire monitoring area, that is, through information feedback to accurately manage the fire monitoring area, so as to reduce the impact of monitoring front-end, early warning back-end and rescue impact on subsequent firefighting and rescue in the fire monitoring area, which helps to reduce the degree of obstruction to subsequent firefighting and rescue, and at the same time helps to improve the rationality and overall safety of fire management in the fire monitoring area.

[0006] The object of the present invention can be achieved by the following technical solutions: A smart fire safety management system based on IoT data analysis, comprising a management platform, a fire supervision unit, a delay feedback unit, a safety supervision unit, a management matching unit, a management matching unit and an early warning processing unit;

[0007] When the management platform generates an operation management instruction, it sends the operation management instruction to the fire supervision unit and the delay feedback unit. When the fire supervision unit receives the operation management instruction, it immediately collects the management data of each fire monitoring device in the fire monitoring area. The management data includes equipment maintenance values ​​and data iteration values, and performs fire impact feedback analysis and data processing comparison analysis on the management data. The obtained normal signal is sent to the safety supervision unit and the delay feedback unit, and the obtained abnormal signal is sent to the early warning processing unit;

[0008] When the delay feedback unit receives the operation management instruction and the normal signal, it immediately collects the monitoring data of each fire monitoring device in the fire monitoring area. The monitoring data includes the transmission risk value and the early warning impact value, and performs fire management evaluation feedback analysis on the monitoring data. The obtained management impact evaluation coefficient G is sent to the management matching unit through the management platform;

[0009] When receiving a normal signal, the safety supervision unit immediately collects the fire hindrance data in the fire monitoring area, including the rescue hindrance value and the fire water supply value, and performs fire rescue management evaluation and analysis on the fire hindrance data, and sends the obtained risk signal to the early warning processing unit;

[0010] After receiving the management impact assessment coefficient G, the management matching unit immediately conducts an in-depth management matching analysis on the management impact assessment coefficient G, and sends the obtained first-level control signal, second-level control signal, and third-level control signal to the early warning processing unit via the management platform.

[0011] Preferably, the fire impact feedback analysis process of the fire supervision unit is as follows:

[0012] The duration of a period of time after the start of generating the operation management instruction is collected and marked as the time threshold, and the equipment maintenance value of each fire monitoring equipment in the fire monitoring area within the time threshold is obtained. The equipment maintenance value represents the ratio of the average maintenance inspection interval between the maintenance times and the connection times after data normalization, and the equipment maintenance value is compared and analyzed with the stored preset equipment maintenance value threshold. If the equipment maintenance value is greater than the preset equipment maintenance value threshold, the part of the equipment maintenance value greater than the preset equipment maintenance value threshold is marked as the equipment risk value;

[0013] The data iteration value of each fire monitoring device in the fire monitoring area within the time threshold is obtained. The data iteration value represents the product of the part of the monitoring data update interval mean value greater than the preset update interval mean value threshold and the number of values ​​corresponding to the operating characteristic parameters exceeding the preset threshold after data normalization. The operating characteristic parameters include voltage fluctuation frequency and operating temperature mean. The fire monitoring equipment is marked as g, where g is a natural number greater than zero. The equipment risk value and the data iteration value are labeled SFg and SGg, respectively.

[0014] Preferably, the data processing, comparison and analysis process of the fire monitoring unit is as follows:

[0015] According to the formula The fire impact assessment coefficient of each fire monitoring device is obtained, where a1 and a2 are the preset proportional factor coefficients of the equipment risk value and the data iteration value, respectively. Both a1 and a2 are positive numbers greater than zero. a3 is the preset fault tolerance factor coefficient, which is 1.222. Pg is the fire impact assessment coefficient of each fire monitoring device. The fire impact assessment coefficient Pg is compared and analyzed with the preset fire impact assessment coefficient threshold value stored in the internal input:

[0016] If the fire impact assessment coefficient Pg is less than the preset fire impact assessment coefficient threshold, a normal signal is generated;

[0017] If the fire impact assessment coefficient Pg is greater than or equal to the preset fire impact assessment coefficient threshold, an abnormal signal is generated.

[0018] Preferably, the fire management evaluation feedback analysis process of the delay feedback unit is as follows:

[0019] S1: Obtain the transmission risk value within the time threshold. The transmission risk value represents the product of the damaged length of the transmission line sheath and the number of bulges after data normalization, and the product of the transmission external factor value after data normalization. The transmission external factor value represents the sum of the part of the corresponding value of the environmental interference data that exceeds the preset threshold. The environmental interference data includes the mean value of environmental electromagnetic interference and the environmental temperature change value.

[0020] S2: Obtain the warning impact value within the time threshold. The analysis process of the warning impact value is as follows: obtain the number of warning delays of the warning device, obtain the average interval duration between the connected times, and at the same time obtain the number of interval durations whose average value is less than the stored preset interval duration average threshold, and mark it as an abnormal number, and obtain the failure frequency of the warning device, and then obtain the product value of the abnormal number and the failure frequency after data normalization, and label the transmission risk value and the warning impact value as CF and YJ respectively;

[0021] S3: Obtain the management impact assessment coefficient G according to the formula.

[0022] Preferably, the fire rescue management assessment and analysis process of the safety supervision unit is as follows:

[0023] T1: Obtain the rescue obstacle value in the fire monitoring area within the time threshold. The rescue obstacle value represents the product of the maximum width of obstacles on the rescue road and the accumulated volume of obstacles after data normalization. The rescue obstacle value is compared with the stored preset rescue obstacle value threshold. If the rescue obstacle value is greater than the preset rescue obstacle value threshold, the ratio between the part and the preset rescue obstacle value threshold is marked as the obstacle multiplier value;

[0024] T2: Obtain the fire water supply value in the fire monitoring area within the time threshold. The fire water supply value represents the product of the number of fire hydrants and the number of fire cabinets in the fire monitoring area after data normalization, and then the product of the average water supply pressure after data normalization. The fire water supply value is compared with the stored preset fire water supply value for analysis. If the fire water supply value is greater than the preset fire water supply value threshold, it is marked as a water supply risk value;

[0025] T3: Compare and analyze the obstruction ratio value and water supply risk value with the preset obstruction ratio value threshold and preset water supply risk value threshold that are stored internally:

[0026] If the obstruction multiplier value is less than the preset obstruction multiplier value threshold, and the water supply risk value is less than the preset water supply risk value threshold, and no signal is generated;

[0027] If the obstruction multiplier value is greater than or equal to the preset obstruction multiplier value threshold, or the water supply risk value is greater than or equal to the preset water supply risk value threshold, a risk signal is generated.

[0028] Preferably, the in-depth management matching analysis process of the management matching unit is as follows:

[0029] Obtain the obstruction multiplier value and the water supply risk value within the time threshold, and label the obstruction multiplier value and the water supply risk value as ZA and GS respectively;

[0030] According to the formula The fire safety risk coefficient is obtained, where v1, v2 and v3 are the preset influencing factor coefficients of the internal obstruction multiplier value, water supply risk value and management impact assessment coefficient respectively, v1, v2 and v3 are all positive numbers greater than zero, v4 is the preset compensation factor coefficient, and its value is 1.216, R is the fire safety risk coefficient, and the fire safety risk coefficient R is compared and analyzed with the preset fire safety risk coefficient interval stored in the internal input:

[0031] If the fire safety risk factor R is greater than the maximum value in the preset fire safety risk factor range, a first-level control signal is generated;

[0032] If the fire safety risk factor R belongs to the preset fire safety risk factor range, a secondary control signal is generated;

[0033] If the fire safety risk coefficient R is less than the minimum value in the preset fire safety risk coefficient range, a third-level control signal is generated.

[0034] The beneficial effects of the present invention are as follows:

[0035] (1) The present invention analyzes from two perspectives: the monitoring front end and the early warning back end, so as to reduce the influence of the monitoring front end and the early warning back end on the subsequent firefighting. At the same time, the fire monitoring area is reasonably and targetedly managed in combination with the rescue impact. That is, the fire monitoring area is accurately managed through information feedback to reduce the influence of the monitoring front end, the early warning back end and the rescue impact on the subsequent firefighting and rescue in the fire monitoring area, which helps to reduce the degree of obstruction to the subsequent firefighting and rescue, and at the same time helps to improve the rationality of fire management and overall safety in the fire monitoring area;

[0036] (2) The present invention analyzes from the perspective of the monitoring front end, that is, performs fire impact feedback analysis on the management data to determine whether the management of the fire monitoring equipment has an impact on the subsequent fire supervision, so as to carry out early warning management in a timely manner to ensure the safety of the use of the fire monitoring equipment and the timeliness of the early warning. The fire rescue management evaluation analysis is performed on the fire hindrance data to determine whether the fire hindrance situation in the fire monitoring area is too large, so as to carry out management in a timely manner to ensure the timeliness of the subsequent rescue. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] The present invention will be further described below in conjunction with the accompanying drawings;

[0038] Figure 1 It is a flowchart of the system of the present invention;

[0039] Figure 2 It is a local analysis reference diagram of the present invention. DETAILED DESCRIPTION

[0040] 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. Embodiment 1

[0041] See also Figure 1 to Figure 2As shown, the present invention is a smart fire safety management system based on Internet of Things data analysis, including a management platform, a fire supervision unit, a delay feedback unit, a safety supervision unit, a management matching unit, a management matching unit and an early warning processing unit. The management platform is connected to the fire supervision unit in a one-way communication, the management platform is connected to the delay feedback unit and the management matching unit in a two-way communication, the fire supervision unit is connected to the delay feedback unit and the safety supervision unit in a one-way communication, the safety supervision unit is connected to the management matching unit in a one-way communication, and the fire supervision unit is connected to the early warning processing unit in a one-way communication;

[0042] When the management platform generates an operation and management instruction, it sends the operation and management instruction to the fire supervision unit and the delay feedback unit. When the fire supervision unit receives the operation and management instruction, it immediately collects the management data of each fire monitoring device in the fire monitoring area. The management data includes equipment maintenance values ​​and data iteration values, and performs fire impact feedback analysis on the management data to determine whether the management of fire monitoring equipment has an impact on subsequent fire supervision, so as to carry out early warning management in a timely manner to ensure the use effect and safety of fire monitoring equipment. The specific fire impact feedback analysis process is as follows:

[0043] The duration of a period of time after the start of generating the operation and management instruction is collected and marked as the time threshold, and the equipment maintenance value of each fire monitoring device in the fire monitoring area within the time threshold is obtained. The equipment maintenance value represents the ratio of the average maintenance inspection interval between the maintenance times and the connection times after data normalization, and the equipment maintenance value is compared and analyzed with the stored preset equipment maintenance value threshold. If the equipment maintenance value is greater than the preset equipment maintenance value threshold, the part of the equipment maintenance value greater than the preset equipment maintenance value threshold is marked as the equipment risk value. It should be noted that the larger the value of the equipment risk value, the higher the risk of fire abnormality and the higher the risk of impact on subsequent fire operations;

[0044] The data iteration value of each fire monitoring device in the fire monitoring area within the time threshold is obtained. The data iteration value represents the product of the portion of the monitoring data update interval duration that is greater than the preset update interval duration threshold and the number of values ​​corresponding to the operating characteristic parameters that exceed the preset threshold after data normalization. The operating characteristic parameters include the voltage fluctuation frequency, the operating temperature mean, etc. It should be noted that the larger the data iteration value, the higher the fire abnormality risk. The fire monitoring device is marked as g, where g is a natural number greater than zero, and the device risk value and the data iteration value are labeled as SFg and SGg, respectively;

[0045] According to the formula The fire impact assessment coefficient of each fire monitoring device is obtained, where a1 and a2 are the preset proportional factor coefficients of the equipment risk value and the data iteration value respectively. The proportional factor coefficient is used to correct the deviation of various parameters in the formula calculation process, so as to make the calculation result more accurate. Both a1 and a2 are positive numbers greater than zero. A3 is the preset fault tolerance factor coefficient, which is 1.222. Pg is the fire impact assessment coefficient of each fire monitoring device. The fire impact assessment coefficient Pg is compared and analyzed with the preset fire impact assessment coefficient threshold value stored in the internal input:

[0046] If the fire impact assessment coefficient Pg is less than the preset fire impact assessment coefficient threshold, a normal signal is generated and sent to the safety supervision unit and the delay feedback unit;

[0047] If the fire impact assessment coefficient Pg is greater than or equal to the preset fire impact assessment coefficient threshold, an abnormal signal is generated and sent to the early warning processing unit. After receiving the abnormal signal, the early warning processing unit immediately performs the preset early warning operation corresponding to the abnormal signal, so as to timely maintain and manage the fire monitoring equipment, so as to reduce the impact of the fire equipment on subsequent firefighting, and help improve the use effect and safety of the fire monitoring equipment;

[0048] When the delay feedback unit receives the operation management instruction and normal signal, it immediately collects the monitoring data of each fire monitoring device in the fire monitoring area. The monitoring data includes the transmission risk value and the early warning impact value, and performs fire management evaluation feedback analysis on the monitoring data to understand the impact of data transmission and early warning on fire management, so as to provide data support for subsequent management. The specific fire management evaluation feedback analysis process is as follows:

[0049] The transmission risk value within the time threshold is obtained. The transmission risk value represents the product of the damaged length of the transmission line outer skin and the number of bulges after data normalization, and the product of the transmission external factor value after data normalization. The transmission external factor value represents the sum of the parts of the corresponding values ​​of the environmental interference data that exceed the preset threshold. The environmental interference data includes the mean value of environmental electromagnetic interference, the environmental temperature change value, etc. It should be noted that the larger the value of the transmission risk value, the greater the risk of data failure;

[0050] The warning impact value within the time threshold is obtained. The analysis process of the warning impact value is as follows: the number of warning delays of the warning device is obtained, the average interval duration between the connected times is obtained, and the number of interval durations whose average duration is less than the stored preset interval duration average threshold is obtained, and it is marked as an abnormal number, and the failure frequency of the warning device is obtained, and then the product value of the abnormal number and the failure frequency after data normalization is obtained. It should be noted that the larger the value of the warning impact value, the greater the risk of data failure. The transmission risk value and the warning impact value are labeled CF and YJ respectively;

[0051] According to the formula The management impact assessment coefficient is obtained, where f1 and f2 are the preset weight factor coefficients of the transmission risk value and the warning impact value respectively, f1 and f2 are both positive numbers greater than zero, f3 is the preset correction factor coefficient, and its value is 2.118, G is the management impact assessment coefficient, and the management impact assessment coefficient G is sent to the management matching unit via the management platform. Embodiment 2

[0052] When receiving a normal signal, the safety supervision unit immediately collects the fire hindrance data in the fire monitoring area. The fire hindrance data includes the rescue hindrance value and the fire water supply value, and performs fire rescue management evaluation and analysis on the fire hindrance data to determine whether the fire hindrance situation in the fire monitoring area is too large, so as to carry out timely management to ensure the timeliness of subsequent rescue. The specific fire rescue management evaluation and analysis process is as follows:

[0053] Obtain the rescue obstruction value in the fire monitoring area within the time threshold, which represents the product of the maximum width of obstacles on the rescue road and the accumulated volume of obstacles after data normalization, and compare and analyze the rescue obstruction value with the stored preset rescue obstruction value threshold. If the rescue obstruction value is greater than the preset rescue obstruction value threshold, the ratio between the part and the preset rescue obstruction value threshold is marked as the obstruction multiplier value. It should be noted that the larger the value of the obstruction multiplier value, the higher the risk of impact on subsequent fire rescue;

[0054] The fire water supply value in the fire monitoring area within the time threshold is obtained. The fire water supply value represents the product value obtained by normalizing the number of fire hydrants and the number of fire cabinets in the fire monitoring area, and then the product value obtained by normalizing the mean value of the water supply pressure. The fire water supply value is compared and analyzed with the stored preset fire water supply value. If the fire water supply value is greater than the preset fire water supply value threshold, it is marked as a water supply risk value. It should be noted that the larger the water supply risk value, the higher the risk of impact on subsequent fire rescue;

[0055] Compare and analyze the obstruction ratio value and water supply risk value with the preset obstruction ratio value threshold and preset water supply risk value threshold that are stored internally:

[0056] If the obstruction multiplier value is less than the preset obstruction multiplier value threshold, and the water supply risk value is less than the preset water supply risk value threshold, and no signal is generated;

[0057] If the obstruction multiplier value is greater than or equal to the preset obstruction multiplier value threshold, or the water supply risk value is greater than or equal to the preset water supply risk value threshold, and a risk signal is generated, and the risk signal is sent to the early warning processing unit, the early warning processing unit immediately performs the preset early warning operation corresponding to the risk signal after receiving the risk signal, so as to carry out management in a timely manner to ensure the timeliness of subsequent rescue;

[0058] After receiving the management impact assessment coefficient G, the management matching unit immediately conducts an in-depth management matching analysis on the management impact assessment coefficient G, so as to conduct reasonable and targeted management of the fire monitoring area, so as to improve the subsequent fire supervision effect, and at the same time, through the overall safety of the fire monitoring area, the specific in-depth management matching analysis process is as follows:

[0059] Obtain the obstruction multiplier value and the water supply risk value within the time threshold, and label the obstruction multiplier value and the water supply risk value as ZA and GS respectively;

[0060] According to the formula The fire safety risk coefficient is obtained, where v1, v2 and v3 are the preset influencing factor coefficients of the internal obstruction multiplier value, water supply risk value and management impact assessment coefficient respectively, v1, v2 and v3 are all positive numbers greater than zero, v4 is the preset compensation factor coefficient, and its value is 1.216, R is the fire safety risk coefficient, and the fire safety risk coefficient R is compared and analyzed with the preset fire safety risk coefficient interval stored in the internal input:

[0061] If the fire safety risk factor R is greater than the maximum value in the preset fire safety risk factor range, a first-level control signal is generated;

[0062] If the fire safety risk factor R belongs to the preset fire safety risk factor range, a secondary control signal is generated;

[0063] If the fire safety risk coefficient R is less than the minimum value in the preset fire safety risk coefficient interval, a three-level control signal is generated, wherein the control degrees corresponding to the first-level control signal, the second-level control signal and the third-level control signal are successively reduced, and the first-level control signal, the second-level control signal and the third-level control signal are sent to the early warning processing unit via the management platform. After receiving the first-level control signal, the second-level control signal and the third-level control signal, the early warning processing unit immediately displays the preset early warning text corresponding to the first-level control signal, the second-level control signal and the third-level control signal, so as to carry out reasonable and targeted management of the fire monitoring area, so as to improve the subsequent fire supervision effect, and at the same time, through the overall safety of the fire monitoring area;

[0064] To summarize, the present invention analyzes from two perspectives, the monitoring front end and the early warning back end, to reduce the impact of the monitoring front end and the early warning back end on subsequent firefighting, and at the same time, combines the rescue impact to manage the fire monitoring area in a reasonable and targeted manner, that is, accurately manage the fire monitoring area through information feedback to reduce the impact of the monitoring front end, the early warning back end and the rescue impact on the subsequent firefighting and rescue in the fire monitoring area, which helps to reduce the degree of hindrance to subsequent firefighting and rescue, and helps to improve the rationality and overall safety of fire management in the fire monitoring area. By analyzing from the perspective of the monitoring front end, that is, performing fire impact feedback analysis on the management data, it is determined whether the management of the fire monitoring equipment has an impact on the subsequent fire supervision, so as to carry out early warning management in a timely manner to ensure the safety of the use of the fire monitoring equipment and the timeliness of the early warning, and performing fire rescue management evaluation and analysis on the fire hindrance data to determine whether the fire hindrance in the fire monitoring area is too large, so as to carry out timely management to ensure the timeliness of subsequent rescue.

[0065] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by technicians in this field for each group of sample data; as long as it does not affect the proportional relationship between the parameter and the quantized value.

[0066] The above formulas are obtained by collecting a large amount of data for software simulation and selecting a formula that is close to the actual value. The coefficients in the formula are set by technical personnel in this field according to actual conditions. The above is only a preferred specific implementation manner of the present invention, but the protection scope of the present invention is not limited to this. Any technical personnel familiar with the technical field within the technical scope disclosed by the present invention, according to the technical solution and the inventive concept of the present invention, make equivalent replacement or change, which should be covered within the protection scope of the present invention.

Claims

1. A smart fire safety management system based on IoT data analysis, characterized in that: It includes management platform, fire supervision unit, delay feedback unit, safety supervision unit, management matching unit, management matching unit and early warning processing unit; When the management platform generates an operation management instruction, it sends the operation management instruction to the fire supervision unit and the delay feedback unit. When the fire supervision unit receives the operation management instruction, it immediately collects the management data of each fire monitoring device in the fire monitoring area. The management data includes equipment maintenance values ​​and data iteration values, and performs fire impact feedback analysis and data processing comparison analysis on the management data. The obtained normal signal is sent to the safety supervision unit and the delay feedback unit, and the obtained abnormal signal is sent to the early warning processing unit; When the delay feedback unit receives the operation management instruction and the normal signal, it immediately collects the monitoring data of each fire monitoring device in the fire monitoring area. The monitoring data includes the transmission risk value and the early warning impact value, and performs fire management evaluation feedback analysis on the monitoring data. The obtained management impact evaluation coefficient G is sent to the management matching unit through the management platform; When receiving a normal signal, the safety supervision unit immediately collects the fire hindrance data in the fire monitoring area, including the rescue hindrance value and the fire water supply value, and performs fire rescue management evaluation and analysis on the fire hindrance data, and sends the obtained risk signal to the early warning processing unit; After receiving the management impact assessment coefficient G, the management matching unit immediately performs an in-depth management matching analysis on the management impact assessment coefficient G, and sends the obtained first-level control signal, second-level control signal, and third-level control signal to the early warning processing unit via the management platform; The fire impact feedback analysis process of the fire supervision unit is as follows: The duration of a period of time after the start of generating the operation management instruction is collected and marked as the time threshold, and the equipment maintenance value of each fire monitoring equipment in the fire monitoring area within the time threshold is obtained. The equipment maintenance value represents the ratio of the average maintenance inspection interval between the maintenance times and the connection times after data normalization, and the equipment maintenance value is compared and analyzed with the stored preset equipment maintenance value threshold. If the equipment maintenance value is greater than the preset equipment maintenance value threshold, the part of the equipment maintenance value greater than the preset equipment maintenance value threshold is marked as the equipment risk value; The data iteration value of each fire monitoring device in the fire monitoring area within the time threshold is obtained. The data iteration value represents the product of the portion of the monitoring data update interval duration that is greater than the preset update interval duration threshold and the number of values ​​corresponding to the operating characteristic parameters that exceed the preset threshold after data normalization. The operating characteristic parameters include the voltage fluctuation frequency and the operating temperature mean. The fire monitoring device is marked as g, where g is a natural number greater than zero, and the equipment risk value and the data iteration value are labeled as SFg and SGg, respectively. The data processing, comparison and analysis process of the fire monitoring unit is as follows: According to the formula The fire impact assessment coefficient of each fire monitoring device is obtained, where a1 and a2 are the preset proportional factor coefficients of the equipment risk value and the data iteration value, respectively. Both a1 and a2 are positive numbers greater than zero. a3 is the preset fault tolerance factor coefficient, which is 1.

222. Pg is the fire impact assessment coefficient of each fire monitoring device. The fire impact assessment coefficient Pg is compared and analyzed with the preset fire impact assessment coefficient threshold value stored in the internal input: If the fire impact assessment coefficient Pg is less than the preset fire impact assessment coefficient threshold, a normal signal is generated; If the fire impact assessment coefficient Pg is greater than or equal to the preset fire impact assessment coefficient threshold, an abnormal signal is generated; The fire management evaluation feedback analysis process of the delay feedback unit is as follows: S1: Obtain the transmission risk value within the time threshold. The transmission risk value represents the product of the damaged length of the transmission line sheath and the number of bulges after data normalization, and the product of the transmission external factor value after data normalization. The transmission external factor value represents the sum of the part of the corresponding value of the environmental interference data that exceeds the preset threshold. The environmental interference data includes the mean value of environmental electromagnetic interference and the environmental temperature change value. S2: Obtain the warning impact value within the time threshold. The analysis process of the warning impact value is as follows: obtain the number of warning delays of the warning device, obtain the average interval duration between the connected times, and at the same time obtain the number of interval durations whose average value is less than the stored preset interval duration average threshold, and mark it as an abnormal number, and obtain the failure frequency of the warning device, and then obtain the product value of the abnormal number and the failure frequency after data normalization, and label the transmission risk value and the warning impact value as CF and YJ respectively; S3: According to the formula The management impact assessment coefficient G is obtained, where f1 and f2 are the preset weight factor coefficients of the transmission risk value and the warning impact value, respectively, and both f1 and f2 are positive numbers greater than zero, and f3 is the preset correction factor coefficient, which is 2.118; The fire rescue management assessment and analysis process of the safety supervision unit is as follows: T1: Obtain the rescue obstacle value in the fire monitoring area within the time threshold. The rescue obstacle value represents the product of the maximum width of obstacles on the rescue road and the accumulated volume of obstacles after data normalization. The rescue obstacle value is compared with the stored preset rescue obstacle value threshold. If the rescue obstacle value is greater than the preset rescue obstacle value threshold, the ratio between the part and the preset rescue obstacle value threshold is marked as the obstacle multiplier value; T2: Obtain the fire water supply value in the fire monitoring area within the time threshold. The fire water supply value represents the product of the number of fire hydrants and the number of fire cabinets in the fire monitoring area after data normalization, and then the product of the average water supply pressure after data normalization. The fire water supply value is compared with the stored preset fire water supply value for analysis. If the fire water supply value is greater than the preset fire water supply value threshold, it is marked as a water supply risk value; T3: Compare and analyze the obstruction ratio value and water supply risk value with the preset obstruction ratio value threshold and preset water supply risk value threshold that are stored internally: If the obstruction multiplier value is less than the preset obstruction multiplier value threshold, and the water supply risk value is less than the preset water supply risk value threshold, and no signal is generated; If the obstruction multiplier value is greater than or equal to the preset obstruction multiplier value threshold, or the water supply risk value is greater than or equal to the preset water supply risk value threshold, a risk signal is generated.

2. According to claim 1, a smart fire safety management system based on Internet of Things data analysis is characterized in that: The in-depth management matching analysis process of the management matching unit is as follows: Obtain the obstruction multiplier value and the water supply risk value within the time threshold, and label the obstruction multiplier value and the water supply risk value as ZA and GS respectively; According to the formula The fire safety risk coefficient is obtained, where v1, v2 and v3 are the preset influencing factor coefficients of the internal obstruction multiplier value, water supply risk value and management impact assessment coefficient respectively, v1, v2 and v3 are all positive numbers greater than zero, v4 is the preset compensation factor coefficient, and its value is 1.216, R is the fire safety risk coefficient, and the fire safety risk coefficient R is compared and analyzed with the preset fire safety risk coefficient interval stored in the internal input: If the fire safety risk factor R is greater than the maximum value in the preset fire safety risk factor range, a first-level control signal is generated; If the fire safety risk factor R belongs to the preset fire safety risk factor range, a secondary control signal is generated; If the fire safety risk coefficient R is less than the minimum value in the preset fire safety risk coefficient range, a third-level control signal is generated.

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