CN116013022A - Intelligent fire control system and method - Google Patents
Intelligent fire control system and method Download PDFInfo
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- CN116013022A CN116013022A CN202211742296.5A CN202211742296A CN116013022A CN 116013022 A CN116013022 A CN 116013022A CN 202211742296 A CN202211742296 A CN 202211742296A CN 116013022 A CN116013022 A CN 116013022A
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Abstract
The invention discloses an intelligent fire control system and method, and relates to the technical field of Internet of things; collecting video data of each area through a video monitoring module; the data acquisition module acquires concentration data and environment data of each region; the data processing module sets a concentration threshold value, and when the concentration data is equal to or larger than the concentration threshold value, the data processing module sends a primary early warning signal to the related owner families, property management personnel, community responsible persons and a fire-fighting alarm receiving command center; the data processing module acquires a monitoring reminding coefficient through a calculation formula; comparing the monitoring reminding coefficient with a monitoring reminding coefficient threshold value; when the monitoring reminding coefficient is larger than the monitoring reminding coefficient threshold, the data processing module sends a secondary early warning signal to the associated owner family and property management personnel according to the position information data processing module; the video monitoring fire is linked with the video monitoring, so that the community masses' strength of the base layer is fully mobilized, and the fire rescue efficiency is improved.
Description
Technical Field
The invention belongs to the field of intelligent fire control, relates to the technology of the Internet of things, and particularly relates to an intelligent fire control system and method.
Background
Fire safety is taken as the fundamental foundation of economic development, is the primary work for guaranteeing social stability and life and property safety of people, and is an important component of smart city construction. In recent years, the fire safety investment of various relevant units of various urban governments throughout the country is gradually increased, the construction of public fire-fighting facilities of the city is continuously improved, and the overall fire resistance of the city is greatly improved.
With the rapid development of technologies such as the Internet of things and cloud computing, the big data change era is silent. The fire-fighting work conforms to the development trend, meets the time requirement of pushing the construction of smart cities, makes full use of big data cloud computing to construct smart fire protection, and continuously improves the fire-fighting social control capability and fire prevention and control level.
For this purpose, an intelligent fire control system and method are provided.
Disclosure of Invention
The present invention aims to solve at least one of the technical problems existing in the prior art. Therefore, the invention provides an intelligent fire control system and method, which solve the problem of intelligent fire construction.
To achieve the above objective, an embodiment according to a first aspect of the present invention provides an intelligent fire control system, including a cloud platform, and a data acquisition module, a video monitoring module and a data processing module connected with the cloud platform; the modules perform information interaction based on digital signals;
the video monitoring module is used for collecting video data of each area and sending the video data to the cloud platform for storage;
the data acquisition module is used for acquiring concentration data and environment data of each region; wherein the environmental data includes temperature data, humidity data, and barometric pressure data;
the data acquisition module sends the acquired concentration data and the acquired environment data to the cloud platform for data storage;
the data processing module sends a data extraction signal to the cloud platform, and the cloud platform sends stored concentration data and environment data to the data processing module after receiving the data extraction signal sent by the data processing module;
the data processing module is used for performing correction processing on the received concentration data and the received environment data, and comprises the following steps of:
the data processing module sets a concentration threshold value, and compares the concentration data with the concentration threshold value;
when the concentration data is equal to or greater than the concentration threshold, the data processing module marks the corresponding area as a fire area and acquires corresponding position information;
the data processing module sends a video extraction signal to a cloud platform according to the position information, and the cloud platform sends stored video data to the data processing module after receiving the video extraction signal sent by the data processing module;
the data processing module sends a primary early warning signal to an associated owner family, property management personnel, community responsible persons and a fire-fighting alarm receiving command center;
the data processing module acquires a monitoring reminding coefficient through a calculation formula;
the data processing module sets a monitoring reminding coefficient threshold value and compares the monitoring reminding coefficient with the monitoring reminding coefficient threshold value;
when the monitoring reminding coefficient is larger than the monitoring reminding coefficient threshold value, the data processing module marks the corresponding area as a fire pre-occurrence area and acquires corresponding position information;
and the data processing module sends a secondary early warning signal to the associated owner family and property management personnel according to the position information.
Preferably, the data acquisition module adopts a periodic acquisition mode when acquiring concentration data and environment data, and the acquisition period is set by the cloud platform; and when the concentration data and the environment data are sent to the cloud platform, the acquired period is numbered, I is marked as 1,2,3 and … … I, and I is the total acquisition times.
Preferably, the data processing module obtains the monitoring reminding coefficient through a calculation formula, and the method comprises the following steps:
the data processing module receives the concentration data and marks the concentration data as C i ；
The data processing module receives the environmental data and marks the temperature data, the humidity data and the air pressure data as W respectively i 、S i P i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i represents the number of the acquisition period;
the data processing module obtains an environment association value by using a calculation formula, and marks the environment association value as HJ i ；
The data processing module obtains a monitoring reminding coefficient by using a calculation formula, and marks the monitoring reminding coefficient as TX i 。
Preferably, the calculation formula of the environment correlation value is as follows:
wherein, alpha, beta and gamma are temperature correction coefficient, humidity correction coefficient and air pressure correction factor respectively, and alpha, beta and gamma are real numbers larger than zero.
Preferably, the calculation formula of the monitoring reminding coefficient is as follows: TX (transmission x) i ＝a×C i +b×HJ i ；
Wherein a and b are influencing factors.
Preferably, the present system employs a smoke sensor based on NB-IoT technology.
Preferably, the system further comprises a device detection module;
the equipment detection module is used for detecting state information of the fire-fighting equipment; wherein the state information includes a normal state and an abnormal state;
when the fire-fighting equipment is in an abnormal condition, the equipment detection module sends an equipment maintenance signal to the intelligent terminal of the corresponding responsible person to inform the responsible person to maintain the fire-fighting equipment in the abnormal condition.
Preferably, the cloud platform is in communication and/or electrical connection with the data acquisition module;
the cloud platform is in communication and/or electrical connection with the video monitoring module;
the cloud platform is in communication and/or electrical connection with the data processing module.
An intelligent fire control method comprises the following steps:
step one: collecting video data and sending the video data to a cloud platform for storage;
step two: collecting concentration data and environment data of each area; the concentration data and the environment data are sent to a cloud platform for data storage;
step three: setting a concentration threshold value, and comparing the concentration data with the concentration threshold value; when the concentration data is equal to or greater than the concentration threshold value, marking the corresponding area as a fire area, and acquiring corresponding position information; sending a first-level early warning signal to the associated owner families, property management personnel, community responsible persons and a fire-fighting alarm receiving command center; starting an audible and visual alarm in the corresponding area to perform audible and visual alarm;
step four: monitoring a reminding coefficient by using a calculation formula, setting a monitoring reminding coefficient threshold value, and comparing the monitoring reminding coefficient with the monitoring reminding coefficient threshold value; when the monitoring reminding coefficient is larger than the threshold value of the monitoring reminding coefficient, marking the corresponding area as a fire pre-occurrence area, and acquiring corresponding position information; the secondary early warning signals are sent to the associated owner families and property management staff according to the position information data processing module; and starting an audible and visual alarm in the corresponding area to perform audible and visual alarm.
Compared with the prior art, the invention has the beneficial effects that:
the invention collects the video data of each area through the video monitoring module; the data acquisition module acquires concentration data and environment data of each region; the data processing module sets a concentration threshold value, and when the concentration data is equal to or larger than the concentration threshold value, the data processing module sends a primary early warning signal to the related owner families, property management personnel, community responsible persons and a fire-fighting alarm receiving command center; the data processing module acquires a monitoring reminding coefficient through a calculation formula; comparing the monitoring reminding coefficient with a monitoring reminding coefficient threshold value; when the monitoring reminding coefficient is larger than the monitoring reminding coefficient threshold, the data processing module sends a secondary early warning signal to the associated owner family and property management personnel according to the position information data processing module; the video monitoring fire is linked with the video monitoring, so that the community masses' strength of the base layer is fully mobilized, and the fire rescue efficiency is improved.
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FIG. 1 is a schematic diagram of the present invention;
fig. 2 is a flow chart of the present invention.
Detailed Description
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is obvious that the described embodiments are only some embodiments of the present invention, not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
As shown in fig. 1, the intelligent fire control system comprises a cloud platform, and a data acquisition module, a video monitoring module and a data processing module which are connected with the cloud platform; the modules perform information interaction based on digital signals;
the video monitoring module is used for collecting video data of each area and sending the video data to the cloud platform for storage;
the data acquisition module is used for acquiring concentration data and environment data of each region; wherein the environmental data includes temperature data, humidity data, and barometric pressure data; it should be further noted that the concentration data is the smoke concentration in the air;
the data acquisition module sends the acquired concentration data and the acquired environment data to the cloud platform for data storage;
specifically, when the data acquisition module acquires concentration data and environment data, a periodic acquisition mode is adopted, and the acquisition period is set by the cloud platform; and when the concentration data and the environment data are sent to the cloud platform, the acquired period is numbered, I is marked as 1,2,3 and … … I, and I is the total acquisition times.
The data processing module sends a data extraction signal to the cloud platform, and the cloud platform sends stored concentration data and environment data to the data processing module after receiving the data extraction signal sent by the data processing module.
The data processing module is used for performing correction processing on the received concentration data and the received environment data, and comprises the following steps of:
the data processing module receives the concentration data and marks the concentration data as C i ；
The data processing module receives the environmental data and marks the temperature data, the humidity data and the air pressure data as W respectively i 、S i P i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i represents the number of the acquisition period;
the data processing module sets a concentration threshold value, and compares the concentration data with the concentration threshold value; it should be further noted that the concentration threshold is set by a professional;
when the concentration data is equal to or greater than the concentration threshold, the data processing module marks the corresponding area as a fire area and acquires corresponding position information;
the data processing module sends a video extraction signal to a cloud platform according to the position information, and the cloud platform sends stored video data to the data processing module after receiving the video extraction signal sent by the data processing module;
the data processing module sends a primary early warning signal to an associated owner family, property management personnel, community responsible persons and a fire-fighting alarm receiving command center;
the data processing module starts an audible and visual alarm in the corresponding area to perform audible and visual alarm;
when the concentration data is smaller than the concentration threshold value, the data processing module does not perform other processing;
the system can monitor and eliminate the control situation continuously in all weather, when a fire occurs, the smoke sensor based on the NB-IoT technology triggers the alarm, and immediately uploads the fire position information to the cloud platform in a wireless mode; meanwhile, the platform is correspondingly linked with the video monitoring to assist in confirming fire; in addition, the platform can inform the owners, property management personnel, community responsible persons and fire-fighting and police-receiving command centers of the mobile phone APP, voice telephone and the like at the first time, so that the community masses' strength of the basic level is fully mobilized;
the data processing module obtains an environment association value by using a calculation formula, and marks the environment association value as HJ i ；
The calculation formula of the environment association value is as follows:
wherein alpha, beta and gamma are temperature correction factors, humidity correction factors and air pressure correction factors respectively, and alpha, beta and gamma are real numbers larger than zero;
the data processing module obtains a monitoring reminding coefficient by using a calculation formula, and marks the monitoring reminding coefficient as TX i ；
The calculation formula of the monitoring reminding coefficient is as follows: TX (transmission x) i ＝a×C i +b×HJ i ；
Wherein a and b are influencing factors;
the data processing module sets a monitoring reminding coefficient threshold value and compares the monitoring reminding coefficient with the monitoring reminding coefficient threshold value;
when the monitoring reminding coefficient is larger than the monitoring reminding coefficient threshold value, the data processing module marks the corresponding area as a fire pre-occurrence area and acquires corresponding position information;
the data processing module sends a secondary early warning signal to the associated owner family and property management personnel according to the position information;
the data processing module starts an audible and visual alarm in the corresponding area to perform audible and visual alarm;
and when the monitoring reminding coefficient is smaller than or equal to the monitoring reminding coefficient threshold value, the data processing module does not process.
In this embodiment, the present system employs a smoke sensor based on NB-IoT technology; it needs to be further explained that the smoke sensor based on NB-IoT technology adopts the wireless communication technology module of NB-IoT internet of things, is self-charged (can work continuously for 3-6 years), automatically transmits information to the server through the narrowband internet of things when encountering an alarm, has the advantages of ultra-low power consumption, wide coverage, stronger signal penetrating power and the like, can achieve the effects of ultra-long standby, stable transmission and the like of the whole life cycle of the equipment, and solves the problems of electricity consumption and wiring. The method is suitable for independent equipment of the Internet of things, which is applied in scattered, long-time and long-distance areas.
In this embodiment, the system further includes an equipment detection module;
the equipment detection module is used for detecting state information of the fire-fighting equipment; wherein the state information includes a normal state and an abnormal state;
when the fire-fighting equipment is in an abnormal condition, the equipment detection module sends an equipment maintenance signal to the intelligent terminal of the corresponding responsible person to inform the responsible person to maintain or replace the fire-fighting equipment in the abnormal condition.
In this embodiment, the cloud platform is in communication and/or electrical connection with the data acquisition module;
the cloud platform is in communication and/or electrical connection with the video monitoring module;
the cloud platform is in communication and/or electrical connection with the data processing module.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas which are obtained by acquiring a large amount of data and performing software simulation to obtain the closest actual situation, and preset parameters and preset thresholds in the formulas are set by a person skilled in the art according to the actual situation or are obtained by simulating a large amount of data.
As shown in fig. 2, an intelligent fire control method includes the following steps:
step one: collecting video data and sending the video data to a cloud platform for storage;
step two: collecting concentration data and environment data of each area; the concentration data and the environment data are sent to a cloud platform for data storage;
step three: setting a concentration threshold value, and comparing the concentration data with the concentration threshold value; when the concentration data is equal to or greater than the concentration threshold value, marking the corresponding area as a fire area, and acquiring corresponding position information; sending a first-level early warning signal to the associated owner families, property management personnel, community responsible persons and a fire-fighting alarm receiving command center; starting an audible and visual alarm in the corresponding area to perform audible and visual alarm;
step four: monitoring a reminding coefficient by using a calculation formula, setting a monitoring reminding coefficient threshold value, and comparing the monitoring reminding coefficient with the monitoring reminding coefficient threshold value; when the monitoring reminding coefficient is larger than the threshold value of the monitoring reminding coefficient, marking the corresponding area as a fire pre-occurrence area, and acquiring corresponding position information; the secondary early warning signals are sent to the associated owner families and property management staff according to the position information data processing module; and starting an audible and visual alarm in the corresponding area to perform audible and visual alarm.
The above embodiments are only for illustrating the technical method of the present invention and not for limiting the same, and it should be understood by those skilled in the art that the technical method of the present invention may be modified or substituted without departing from the spirit and scope of the technical method of the present invention.
Claims (9)
1. The intelligent fire control system is characterized by comprising a cloud platform, and a data acquisition module, a video monitoring module and a data processing module which are connected with the cloud platform; the modules perform information interaction based on digital signals;
the video monitoring module is used for collecting video data of each area and sending the video data to the cloud platform for storage;
the data acquisition module is used for acquiring concentration data and environment data of each region; wherein the environmental data includes temperature data, humidity data, and barometric pressure data;
the data acquisition module sends the acquired concentration data and the acquired environment data to the cloud platform for data storage;
the data processing module sends a data extraction signal to the cloud platform, and the cloud platform sends stored concentration data and environment data to the data processing module after receiving the data extraction signal sent by the data processing module;
the data processing module is used for performing correction processing on the received concentration data and the received environment data, and comprises the following steps of:
the data processing module sets a concentration threshold value, and compares the concentration data with the concentration threshold value;
when the concentration data is equal to or greater than the concentration threshold, the data processing module marks the corresponding area as a fire area and acquires corresponding position information;
the data processing module sends a video extraction signal to a cloud platform according to the position information, and the cloud platform sends stored video data to the data processing module after receiving the video extraction signal sent by the data processing module;
the data processing module sends a primary early warning signal to an associated owner family, property management personnel, community responsible persons and a fire-fighting alarm receiving command center;
the data processing module acquires a monitoring reminding coefficient through a calculation formula;
the data processing module sets a monitoring reminding coefficient threshold value and compares the monitoring reminding coefficient with the monitoring reminding coefficient threshold value;
when the monitoring reminding coefficient is larger than the monitoring reminding coefficient threshold value, the data processing module marks the corresponding area as a fire pre-occurrence area and acquires corresponding position information;
and the data processing module sends a secondary early warning signal to the associated owner family and property management personnel according to the position information.
2. The intelligent fire control system according to claim 1, wherein the data acquisition module adopts a periodic acquisition mode when acquiring concentration data and environment data, and the acquisition period is set by the cloud platform; and when the concentration data and the environment data are sent to the cloud platform, the acquired period is numbered, I is marked as 1,2,3 and … … I, and I is the total acquisition times.
3. The intelligent fire control system according to claim 2, wherein the data processing module obtains the monitoring reminding coefficient through a calculation formula, and the method comprises the following steps:
the data processing module receives the concentration data and marks the concentration data as C i ；
The data processing module receives the environmental data and marks the temperature data, the humidity data and the air pressure data as W respectively i 、S i P i The method comprises the steps of carrying out a first treatment on the surface of the Wherein i represents the number of the acquisition period;
the data processing module obtains an environment association value by using a calculation formula, and marks the environment association value as HJ i ；
The data processing module obtains a monitoring reminding coefficient by using a calculation formula, and marks the monitoring reminding coefficient as TX i 。
4. A smart fire control system as claimed in claim 3, wherein the calculation formula of the environment-related value is:
wherein, alpha, beta and gamma are temperature correction coefficient, humidity correction coefficient and air pressure correction factor respectively, and alpha, beta and gamma are real numbers larger than zero.
5. The intelligent fire control system according to claim 3, wherein the calculation formula of the monitoring reminding coefficient is: TX (transmission x) i ＝a×C i +b×HJ i ；
Wherein a and b are influencing factors.
6. The intelligent fire control system of claim 1, wherein the system employs a smoke sensor based on NB-IoT technology.
7. The intelligent fire control system of claim 1, further comprising an equipment detection module;
the equipment detection module is used for detecting state information of the fire-fighting equipment; wherein the state information includes a normal state and an abnormal state;
when the fire-fighting equipment is in an abnormal condition, the equipment detection module sends an equipment maintenance signal to the intelligent terminal of the corresponding responsible person to inform the responsible person to maintain the fire-fighting equipment in the abnormal condition.
8. The intelligent fire control system of claim 1, wherein the cloud platform is in communication and/or electrical connection with a data acquisition module;
the cloud platform is in communication and/or electrical connection with the video monitoring module;
the cloud platform is in communication and/or electrical connection with the data processing module.
9. An intelligent fire control method is characterized by comprising the following steps:
step one: collecting video data and sending the video data to a cloud platform for storage;
step two: collecting concentration data and environment data of each area; the concentration data and the environment data are sent to a cloud platform for data storage;
step three: setting a concentration threshold value, and comparing the concentration data with the concentration threshold value; when the concentration data is equal to or greater than the concentration threshold value, marking the corresponding area as a fire area, and acquiring corresponding position information; sending a first-level early warning signal to the associated owner families, property management personnel, community responsible persons and a fire-fighting alarm receiving command center;
step four: monitoring a reminding coefficient by using a calculation formula, setting a monitoring reminding coefficient threshold value, and comparing the monitoring reminding coefficient with the monitoring reminding coefficient threshold value; when the monitoring reminding coefficient is larger than the threshold value of the monitoring reminding coefficient, marking the corresponding area as a fire pre-occurrence area, and acquiring corresponding position information; and sending a secondary early warning signal to the associated owner families and property management personnel according to the position information data processing module.
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| CN202211742296.5A CN116013022A (en) | 2022-12-31 | 2022-12-31 | Intelligent fire control system and method |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117122859A (en) * | 2023-09-08 | 2023-11-28 | 广州鸿蒙信息科技有限公司 | Intelligent voice interaction fire-fighting guard system and method |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117122859A (en) * | 2023-09-08 | 2023-11-28 | 广州鸿蒙信息科技有限公司 | Intelligent voice interaction fire-fighting guard system and method |
| CN117122859B (en) * | 2023-09-08 | 2024-03-01 | 广州普鸿信息科技服务有限公司 | Intelligent voice interaction fire-fighting guard system and method |
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