Intelligent fire-fighting remote management system

Abstract

The invention relates to the technical field of fire fighting, in particular to an intelligent fire fighting remote management system which comprises a server side and a user side. The server side comprises a multi-dimensional data acquisition module, a judgment module, a processing module, an early warning grade determination module, an alarm pushing module and a fire extinguishing control module, and the processing module is used for sending an alarm when a judgment result is that a fire occurs in a detected area at the current moment; if yes, determining a fire hazard degree corresponding to the detected area at the current moment according to temperature data, smoke data and flame data which are acquired in real time and correspond to the detected area; the early warning level determination module is used for determining a fire early warning level corresponding to the detected area at the current moment; and the alarm pushing module is used for calling a fire alarm pushing strategy corresponding to the fire early warning level from the database according to the determined fire early warning level corresponding to the detected area at the current moment, and executing the corresponding fire alarm pushing strategy to push an alarm signal to the corresponding user side.

Description

Technical Field

[0001] The present invention relates to the field of fire protection technology, and in particular to a smart fire protection remote management system. Background Art

[0002] In modern industrial production and various building environments, fire accidents have always been a major hidden danger that threatens the safety of life and property stability. With the acceleration of urbanization and the continuous expansion of industrial scale, the demand for fire prevention and control in factories, warehouses and other places is becoming increasingly urgent. For example, the factory corresponding to the carbon production system for electrolytic aluminum.

[0003] Traditional fire detection and prevention technologies have many limitations. As far as fire detection is concerned, common single-point smoke detectors and temperature detectors can only monitor a single parameter, and the detection range is limited, which is prone to missed reports and false alarms.

[0004] In terms of fire hazard assessment, existing technologies often lack a scientific and comprehensive assessment system. Most of them are based on single detection data or simple empirical judgments, and cannot accurately quantify the degree of fire hazard. This makes it difficult for relevant personnel to quickly and accurately judge the severity of the fire when a fire occurs, and thus cannot take effective countermeasures in time.

[0005] Based on this, there is an urgent need for a smart fire remote management system that can accurately identify fires in factory buildings and extinguish them remotely, thereby achieving early detection, early alarm, and early extinguishing of fire accidents. Summary of the invention

[0006] One of the purposes of the present invention is to provide an intelligent fire remote management system that can accurately identify fires in factory buildings and extinguish them remotely, thereby achieving early detection, early alarm, and early extinguishing of fire accidents.

[0007] In order to achieve the above-mentioned purpose, a smart fire remote management system is provided, including a server and a user end;

[0008] The server includes:

[0009] A multi-dimensional data acquisition module is used to acquire the fire detection data collected in real time by the intelligent multi-step image-based special fire detection device installed in the factory building, wherein the fire detection data includes temperature data, smoke data and flame data corresponding to the detected area;

[0010] The judgment module is used to judge whether a fire occurs in the detected area at the current moment based on the temperature data, smoke data and flame data corresponding to the detected area collected in real time and based on the preset fire judgment strategy;

[0011] A processing module, for determining the fire hazard degree corresponding to the detected area at the current moment based on the temperature data, smoke data and flame data corresponding to the detected area collected in real time and based on a preset fire hazard degree calculation formula when the judgment result is that a fire occurs in the detected area at the current moment;

[0012] The warning level determination module is used to determine the fire warning level corresponding to the detected area at the current moment according to the determined fire danger level corresponding to the detected area at the current moment and based on a preset fire warning level determination strategy;

[0013] The alarm push module is used to retrieve the fire alarm push strategy corresponding to the fire warning level from the database according to the fire warning level corresponding to the detected area at the current moment, and execute the corresponding fire alarm push strategy to push the alarm signal to the corresponding user terminal;

[0014] The fire extinguishing control module is used to receive the fire extinguishing control instruction fed back from the user end after pushing the alarm signal to the corresponding user end, and remotely start the corresponding fire extinguishing device in the detected area according to the corresponding fire extinguishing control instruction.

[0015] Technical principles and effects of this solution: In this solution, the temperature, smoke and flame data of the detected area are obtained in real time through the intelligent multi-level image-based special fire detection devices deployed in the factory. These devices have high-precision sensors and image acquisition functions, which can collect fire-related information from all directions and angles, providing a data basis for subsequent analysis and judgment.

[0016] The judgment module analyzes the collected temperature, smoke and flame data according to the preset fire judgment strategy. This strategy may comprehensively consider factors such as single parameter threshold, multi-parameter comprehensive logic and time series, such as whether the temperature exceeds the set threshold, whether the smoke concentration and flame characteristics appear at the same time, etc., to accurately judge whether a fire has occurred in the detected area at the current moment. When it is judged that a fire has occurred, the processing module calculates the temperature, smoke and flame data based on the preset fire hazard calculation formula. According to the fire hazard, the warning level is divided according to the preset fire warning level determination strategy. Different hazard ranges correspond to different warning levels.

[0017] According to the determined warning level, the corresponding fire alarm push strategy is retrieved from the database. According to different warning levels, alarm signals are sent to the user end through various methods such as PC, mobile phone APP, SMS, etc., to notify various users and monitoring personnel so that timely response measures can be taken.

[0018] After sending the alarm signal to the user, the fire extinguishing control module receives the fire extinguishing control command fed back by the user, and remotely activates the fire extinguishing device in the detected area according to the command, so as to put out the fire in time and prevent the fire from spreading.

[0019] Multi-dimensional data collection and scientific fire judgment strategies can promptly detect hidden dangers in the early stages of a fire, accurately determine the occurrence of a fire, gain precious time for fire fighting and rescue, and reduce fire losses.

[0020] By calculating the fire danger level and dividing the warning levels, users and monitoring personnel can intuitively understand the severity of the fire so that they can take targeted countermeasures and improve emergency response efficiency.

[0021] A variety of alarm push methods ensure that information can be conveyed to relevant personnel in a timely manner. No matter where they are, they can obtain fire warning information in the first place to ensure personnel safety.

[0022] The fire extinguishing device can be remotely activated, and fire extinguishing can be carried out quickly without the need for personnel to arrive at the scene, effectively reducing the risk of casualties, improving fire extinguishing efficiency, and enhancing fire prevention and control capabilities. That is, the fire in the factory can be accurately identified and extinguished remotely, thereby achieving early detection, early alarm, and early extinguishing of fire accidents.

[0023] Furthermore, the preset fire judgment strategy is:

[0024] According to the temperature data, smoke data and flame data corresponding to the detected area collected at the current moment, identify the location information of the detected area in the factory building and the time period corresponding to the current moment in the day;

[0025] According to the location information of the detected area in the factory, determine the fire susceptibility of the factory equipment corresponding to the detected area and the importance of the factory equipment;

[0026] According to the time period corresponding to the current time in a day, the fire susceptibility and importance of the plant equipment in the detected area, determine the judgment thresholds corresponding to the temperature data, smoke data and flame data;

[0027] According to the judgment thresholds corresponding to the temperature data, smoke data and flame data, it is determined whether there are two or more data in each data that are greater than the corresponding judgment thresholds. If so, a fire may have occurred in the detected area at the current moment. Otherwise, no fire has occurred in the detected area at the current moment.

[0028] Beneficial effects: This strategy not only judges the fire situation based on temperature, smoke and flame data, but also combines the location information of the detected area and the time period. For example, the fire susceptibility of plant equipment in different locations is different. Some high-temperature operation areas or areas where flammable items are stored have higher fire risks. At the same time, the operating status of equipment and personnel activities vary in different time periods of the day. For example, when the equipment runs for a long time at night and there are fewer people, the fire hazard may be greater. By combining these factors, the fire risk can be assessed more comprehensively and accurately to avoid misjudgment or missed judgment caused by a single factor. The judgment threshold of each data is determined according to the location and time period of the detected area. In areas with high fire susceptibility and high equipment importance, the judgment threshold is lowered and the sensitivity is increased so that potential fire hazards can be discovered more promptly; while in areas with low fire risks, the threshold is appropriately increased to reduce unnecessary false alarms. This method of dynamically adjusting the threshold makes the fire judgment more in line with the actual situation, greatly improves the accuracy of the judgment, and enhances the targeted nature of fire prevention and control.

[0029] Furthermore, the preset fire risk calculation formula is:

[0030] H=αT W +∝S W +ρF W ,α+∝+ρ=1

[0031]

[0032] Where H is the fire hazard corresponding to the detected area, T W is the temperature danger level corresponding to the detected area, S W is the smoke hazard level corresponding to the detected area, F W is the flame hazard level corresponding to the detected area, and α,∝,ρ is the corresponding weighting coefficient;

[0033] T is the current temperature value; T0 is the normal ambient temperature value; T max is the highest temperature value when the fire occurred in the historical record; ΔT is the temperature difference between the current moment and the previous moment; Δt is the time interval; T i is the temperature value corresponding to the i-th time point in the past n time points; T avg is the average temperature of the past n time points; T std is the standard deviation of the temperature at the past n time points; β1 is the exponential correction coefficient of the temperature data; γ1 is the exponential correction coefficient of the temperature data change rate; δ1 is the exponential correction coefficient of the temperature data stability;

[0034] S is the smoke concentration value at the current moment; S0 is the smoke concentration value in the normal environment; S maxis the highest smoke density value when a fire occurs in the historical records; ΔS is the difference between the smoke density at the current moment and the previous moment; S i is the smoke concentration value corresponding to the i-th time point in the past m time points; S avg is the average value of smoke concentration at the past m time points; S std is the standard deviation of smoke concentration at the past m time points; β2 is the exponential correction coefficient of smoke data; γ2 is the exponential correction coefficient of the smoke data change rate; δ2 is the exponential correction coefficient of the smoke data stability;

[0035] F is the flame intensity value at the current moment; F0 is the flame intensity value under normal conditions; F max is the highest flame intensity value when a fire occurs in the historical record; ΔF is the difference between the flame intensity at the current moment and the previous moment; F i is the flame intensity value corresponding to the i-th time point in the past k time points; F avg is the average value of the flame intensity corresponding to the i-th time point in the past k time points; F std is the standard deviation of flame intensity at the past k time points; β3 is the exponential correction coefficient of flame data; γ3 is the exponential correction coefficient of flame data change rate; δ3 is the exponential correction coefficient of flame data stability.

[0036] Beneficial effects: The three key factors of temperature, smoke and flame are comprehensively considered. By calculating the temperature hazard, smoke hazard and flame hazard respectively and integrating them with the weighted coefficient, the fire hazard level of the detected area is fully reflected. In a warehouse storing flammable chemicals, smoke generation may be an important feature of the early stage of a fire, while in a high-temperature industrial production plant, temperature changes are more critical to fire hazard assessment. This formula can reasonably reflect the contribution of each factor to the fire hazard by adjusting the weighted coefficient according to different scenarios, avoiding the one-sidedness of single factor assessment.

[0037] By setting the index correction coefficient, the influence of each factor can be further refined, which makes the calculation of fire hazard more accurate. It can accurately quantify the fire hazard level according to slight changes in the data, providing a scientific basis for fire warning and emergency response.

[0038] The weighting coefficient can be flexibly set according to the fire risk characteristics of different places and equipment. In electronic equipment production plants, due to the high risk of electrical fires, a higher weight may be given to temperature factors; in textile factories, due to the flammable raw materials, the weight of smoke factors may be greater. This adjustability allows the calculation results of fire hazard to be more in line with the actual risk conditions of specific scenarios, thereby supporting fire departments and enterprises to make differentiated fire decisions, such as determining the allocation of fire resources in different areas and formulating targeted emergency plans.

[0039] Further, the preset fire warning level determination strategy is as follows:

[0040] If x ≤ H < y, the corresponding fire warning level is a first-level warning;

[0041] If y ≤ H < z, the corresponding fire warning level is a second-level warning;

[0042] If z ≤ H, the corresponding fire warning level is a third-level warning; the x, y, and z are dynamically adjustable interval points.

[0043] Beneficial effects: By setting dynamically adjustable interval points x, y, and z, different warning levels are divided according to the fire risk degree H. When a fire hazard first appears and H is in a lower interval, a first-level warning is triggered, which can timely remind relevant personnel to pay attention to potential risks and gain the initiative in dealing with the hazards.

[0044] Further, the server also includes a display module for visually displaying the temperature data, smoke data, and flame data corresponding to each detected area of each workshop.

[0045] Beneficial effects: The display module visually displays the temperature, smoke, and flame data of different detected areas of each workshop, converting complex data into intuitive charts, graphs, or dynamic images. This intuitive presentation method reduces the difficulty for staff to understand the data and enables them to quickly grasp the fire risk status of each area.

[0046] Staff can monitor the data changes of each area in real time through the visual interface. Once the temperature, smoke, or flame data in a certain area shows abnormal fluctuations, such as a sudden increase in temperature or a sharp rise in smoke concentration, the visual interface will immediately prompt the staff with a prominent color, flashing effect, or alarm. Compared with simply viewing digital data, visual display allows staff to detect abnormalities more quickly and take timely measures, such as checking the equipment operation status and investigating fire hazards, effectively preventing fires.

[0047] Further, the fire alarm push strategy is as follows:

[0048] When the fire warning level is a first-level warning, an alarm signal is sent to the user terminals corresponding to the area responsible person and the monitoring personnel associated with the detected area at the first signal sending frequency f1;

[0049] When the fire warning level is a second-level warning, an alarm signal is sent to the user terminals corresponding to the area responsible person and the monitoring personnel associated with the detected area at the second signal sending frequency f2;

[0050] When the fire warning level is at the third-level warning, an alarm signal is sent to the user terminals corresponding to the person in charge of the area and the monitoring personnel associated with the detected area at the third signal transmission frequency f3; at the same time, the display module of the server displays the alarm signal and emits an alarm sound; f1 < f2 < f3.

[0051] Beneficial effects: Different signal transmission frequencies are set according to different fire warning levels. When the first-level warning is issued, the alarm signal is sent at a lower frequency f1, which can not only timely inform the person in charge of the area and the monitoring personnel of potential risks, but also cause no excessive interference, giving them enough time to initially check for potential hazards. As the warning level increases, such as when the second-level warning is issued at frequency f2, it can strengthen the reach of information and ensure that relevant personnel continue to pay attention. When it comes to the third-level warning, it is sent at the highest frequency f3, which can quickly and repeatedly remind in case of an emergency, ensuring that key personnel will not miss important alarms, maximizing the timely transmission of information, and争取 time for taking countermeasures.

[0052] At the third-level warning, in addition to sending the alarm signal at a high frequency, the display module of the server also displays the alarm signal and emits an alarm sound. This multi-dimensional alarm method can simultaneously attract the high attention of the person in charge of the area and the monitoring personnel visually and auditorily. In the case of a severe fire situation, it ensures that they can quickly respond and immediately take actions, such as activating fire extinguishing equipment and organizing personnel evacuation, effectively improving the emergency response speed and reducing fire losses.

[0053] Setting the signal transmission frequencies of f1 < f2 < f3 conforms to the logic of the gradually increasing fire risk. This hierarchical and progressive alarm push strategy makes the warning system more scientific and reasonable. It can flexibly adjust the alarm method and intensity according to the change of the fire danger level, avoiding over-alarming and causing personnel to become numb in case of low risks, and fully attracting attention in case of high risks, thus improving the effectiveness of the entire fire alarm and response system. Description of the Drawings

[0054] Figure 1 It is the logic block diagram of the intelligent fire remote management system in the first embodiment of the present invention. Detailed Implementation Manner

[0055] The following is further detailed through specific implementation manners:

[0056] Embodiment 1

[0057] The intelligent fire remote management system is basically as Figure 1 shown, including a server and user terminals;

[0058] The server includes:

[0059] The multi-dimensional data acquisition module is used to acquire the fire detection data collected by the intelligent multi-step image type special fire detection device in real time according to the intelligent multi-step image type special fire detection device set in the factory. The fire detection data includes temperature data, smoke data and flame data corresponding to the detected area; in this embodiment, the intelligent multi-step image type special fire detection device has a dust explosion-proof function, and the detection equipment adopts video processing technology combined with three-composite multi-spectral imaging technology. It adopts high-transmittance all-germanium optical passive athermal difference technology to work in an ultra-wide temperature range of -40℃ to 60℃, and has a waterproof and sealed design. In this embodiment, with the help of high-precision positioning technology, such as indoor positioning system (combined with Bluetooth, Wi-Fi and geomagnetic positioning), the position of the detected area in the factory is accurately determined to a specific coordinate point, and is associated with the electronic map of the factory to clarify its functional division (such as production area, storage area, office area, etc.). Through the system clock and time synchronization technology, the time period corresponding to the current moment in a day is accurately obtained, accurate to the minute level. At the same time, it records information such as the operating status of factory equipment and personnel activities in different time periods to provide comprehensive data support for subsequent fire risk assessments.

[0060] The judgment module is used to judge whether a fire occurs in the detected area at the current moment based on the temperature data, smoke data and flame data corresponding to the detected area collected in real time and based on the preset fire judgment strategy;

[0061] The preset fire judgment strategy is:

[0062] According to the temperature data, smoke data and flame data corresponding to the detected area collected at the current moment, identify the location information of the detected area in the factory building and the time period corresponding to the current moment in the day;

[0063] According to the location information of the detected area in the factory, determine the fire susceptibility of the factory equipment corresponding to the detected area and the importance of the factory equipment;

[0064] According to the time period corresponding to the current time in a day, the fire susceptibility and importance of the plant equipment in the detected area, determine the judgment thresholds corresponding to the temperature data, smoke data and flame data;

[0065] According to the judgment thresholds corresponding to the temperature data, smoke data and flame data, it is judged whether there are two or more data in each data that are greater than the corresponding judgment thresholds. If so, a fire may occur in the detected area at the current moment. Otherwise, no fire occurs in the detected area at the current moment. In this embodiment, after the temperature, smoke and flame data are obtained, they are first compared with the corresponding judgment thresholds. If there are two or more data greater than their respective thresholds, the system automatically triggers a preliminary fire warning. At this time, the secondary confirmation mechanism is started, and the data of more detection devices in the surrounding area are retrieved for cross-verification. At the same time, the video analysis of the scene is performed using image recognition technology to determine whether there are signs of fire. If the secondary confirmation result is still that a fire may occur, it is determined that a fire occurs in the detected area at the current moment, and the subsequent early warning, alarm and fire extinguishing control process is immediately started; if the secondary confirmation excludes the possibility of fire, the preliminary warning is lifted and the data continues to be monitored in real time.

[0066] A processing module, for determining the fire hazard degree corresponding to the detected area at the current moment based on the temperature data, smoke data and flame data corresponding to the detected area collected in real time and based on a preset fire hazard degree calculation formula when the judgment result is that a fire occurs in the detected area at the current moment;

[0067] The preset fire risk calculation formula is:

[0068] H=αT W +∝S W +ρF W ,α+∝+ρ=1

[0069]

[0070] Where H is the fire hazard corresponding to the detected area, T W is the temperature danger level corresponding to the detected area, S W is the smoke hazard level corresponding to the detected area, F W is the flame hazard degree corresponding to the detected area, and α,∝,ρ is the corresponding weighting coefficient; in this embodiment, α,∝,ρ is dynamically changing and is dynamically adjusted according to different time and different positions.

[0071] T is the current temperature value; T0 is the normal ambient temperature value; T max is the highest temperature value when the fire occurred in the historical record; ΔT is the temperature difference between the current moment and the previous moment; Δt is the time interval; T i is the temperature value corresponding to the i-th time point in the past n time points; T avg is the average temperature of the past n time points; T stdis the standard deviation of the temperature at the past n time points; β1 is the exponential correction coefficient of the temperature data; γ1 is the exponential correction coefficient of the temperature data change rate; δ1 is the exponential correction coefficient of the temperature data stability;

[0072] S is the smoke concentration value at the current moment; S0 is the smoke concentration value in the normal environment; S max is the highest smoke concentration value during a fire in the historical record; ΔS is the difference in smoke concentration between the current moment and the previous moment; S i is the smoke concentration value corresponding to the i-th time point among the past m time points; S avg is the average value of the smoke concentration at the past m time points; S std is the standard deviation of the smoke concentration at the past m time points; β2 is the exponential correction coefficient of the smoke data; γ2 is the exponential correction coefficient of the smoke data change rate; δ2 is the exponential correction coefficient of the smoke data stability;

[0073] F is the flame intensity value at the current moment; F0 is the flame intensity value in the normal environment; F max is the highest flame intensity value during a fire in the historical record; ΔF is the difference in flame intensity between the current moment and the previous moment; F i is the flame intensity value corresponding to the i-th time point among the past k time points; F avg is the average value of the flame intensity corresponding to the i-th time point among the past k time points; F std is the standard deviation of the flame intensity at the past k time points; β3 is the exponential correction coefficient of the flame data; γ3 is the exponential correction coefficient of the flame data change rate; δ3 is the exponential correction coefficient of the flame data stability.

[0074] An early warning level determination module, configured to determine the fire early warning level corresponding to the detected area at the current moment based on a preset fire early warning level determination strategy according to the determined fire risk degree corresponding to the detected area at the current moment;

[0075] The preset fire early warning level determination strategy is:

[0076] If x ≤ H < y, the corresponding fire early warning level is a first-level early warning;

[0077] If y ≤ H < z, the corresponding fire early warning level is a second-level early warning;

[0078] If z ≤ H, the corresponding fire early warning level is a third-level early warning; where x, y, z are dynamically adjustable interval points.

[0079] An alarm push module, configured to retrieve a fire alarm push policy corresponding to the fire warning level of the detected area at the determined current moment from a database according to the determined fire warning level of the detected area at the current moment, and execute the corresponding fire alarm push policy to push an alarm signal to the corresponding client;

[0080] The fire alarm push policy is as follows:

[0081] When the fire warning level is a first-level warning, an alarm signal is sent to the clients corresponding to the area person in charge and the monitoring personnel associated with the detected area at the first signal sending frequency f1;

[0082] When the fire warning level is a second-level warning, an alarm signal is sent to the clients corresponding to the area person in charge and the monitoring personnel associated with the detected area at the second signal sending frequency f2;

[0083] When the fire warning level is a third-level warning, an alarm signal is sent to the clients corresponding to the area person in charge and the monitoring personnel associated with the detected area at the third signal sending frequency f3; meanwhile, the display module of the server displays the alarm signal and emits an alarm sound; f1 < f2 < f3. For example, the entire display module interface switches to the warning mode, and the warning information is prominently displayed with a striking red background and a flashing effect. The office phone numbers of relevant person in charge are automatically dialed, and a voice warning notice is played after the call is connected.

[0084] A fire extinguishing control module, configured to receive a fire extinguishing control instruction fed back by the client after pushing the alarm signal to the corresponding client, and remotely start the corresponding fire extinguishing device in the detected area according to the corresponding fire extinguishing control instruction. In this embodiment, the fire extinguishing device uses a foam + water spraying method for fire extinguishing, and it is recommended to use -35°C low-temperature-resistant aqueous film-forming foam liquid, which will not freeze even when extinguishing fires in winter and has low maintenance costs. The spray nozzles corresponding to the fire extinguishing device adopt iron mesh high-pressure nozzles, and a deluge valve is installed on the front branch pipe of the nozzle around each intelligent multi-step image-type special fire detection device. In this embodiment, the clients corresponding to the fire extinguishing control instructions fed back by the client include the clients of remote personnel and the clients on the scene. The fire extinguishing device can be started only through synchronous control of multiple clients.

[0085] The server further includes a display module, configured to visually display the temperature data, smoke data, and flame data corresponding to each detected area of each factory building.

[0086] The above is only an embodiment of the present invention. The common sense such as the known specific structure and characteristics in the scheme is described too much here. The ordinary technicians in the relevant field know all the common technical knowledge in the technical field of the invention before the application date or priority date, can know all the existing technologies in the field, and have the ability to apply the conventional experimental means before that date. The ordinary technicians in the relevant field can improve and implement this scheme in combination with their own abilities under the enlightenment given by this application. Some typical known structures or known methods should not become obstacles for ordinary technicians in the relevant field to implement this application. It should be pointed out that for those skilled in the art, without departing from the structure of the present invention, several deformations and improvements can be made, which should also be regarded as the protection scope of the present invention, which will not affect the effect of the implementation of the present invention and the practicality of the patent. The protection scope required by this application shall be based on the content of its claims, and the specific implementation methods and other records in the specification can be used to interpret the content of the claims.

Claims

1. Smart fire remote management system, characterized by: It includes a server and a client; The server includes: A multi-dimensional data acquisition module, which is used to obtain the fire detection data collected in real time by the intelligent multi-level image-type special fire detection device set in the factory building. The fire detection data includes temperature data, smoke data, and flame data corresponding to the detected area; A judgment module, which is used to judge whether a fire has occurred in the detected area at the current moment based on the preset fire judgment strategy according to the temperature data, smoke data, and flame data corresponding to the detected area collected in real time; A processing module, which is used to determine the fire risk level corresponding to the detected area at the current moment based on the preset fire risk calculation formula according to the temperature data, smoke data, and flame data corresponding to the detected area collected in real time when the judgment result is that a fire has occurred in the detected area at the current moment; A fire warning level determination module, which is used to determine the fire warning level corresponding to the detected area at the current moment based on the preset fire warning level determination strategy according to the determined fire risk level corresponding to the detected area at the current moment; An alarm push module, which is used to retrieve the fire alarm push strategy corresponding to the fire warning level from the database according to the determined fire warning level corresponding to the detected area at the current moment, and execute the corresponding fire alarm push strategy to push an alarm signal to the corresponding client; A fire extinguishing control module, which is used to receive the fire extinguishing control instruction fed back by the client after pushing the alarm signal to the corresponding client, and remotely start the fire extinguishing device corresponding to the detected area according to the corresponding fire extinguishing control instruction.

2. The intelligent fire remote management system according to claim 1 is characterized in that: The preset fire judgment strategy is: According to the temperature data, smoke data, and flame data corresponding to the detected area collected at the current moment, identify the location information of the detected area in the factory building and the time period corresponding to the current moment in a day; According to the identified location information of the detected area in the factory building, determine the fire occurrence probability of the factory building equipment corresponding to the detected area and the importance of the factory building equipment; According to the time period corresponding to the current moment in a day, the fire occurrence probability of the factory building equipment where the detected area is located, and the importance, determine the judgment thresholds corresponding to the temperature data, smoke data, and flame data respectively; According to the judgment thresholds corresponding to the temperature data, smoke data, and flame data respectively, judge whether there are two or more of these data greater than their respective judgment thresholds. If so, a fire may occur in the detected area at the current moment. Otherwise, no fire has occurred in the detected area at the current moment.

3. The intelligent fire remote management system according to claim 2 is characterized in that: The preset fire risk calculation formula is: H=αT W +∝S W +ρF W ,α+∝+ρ=1 Where H is the fire risk corresponding to the detected area, T W is the temperature danger level corresponding to the detected area, S W is the smoke hazard level corresponding to the detected area, F W is the flame hazard level corresponding to the detected area, and α,∝,ρ is the corresponding weighting coefficient; T is the temperature value at the current moment; T0 is the normal ambient temperature; T max is the highest temperature value when the fire occurred in the historical record; ΔT is the temperature difference between the current moment and the previous moment; Δt is the time interval; T i is the temperature value corresponding to the i-th time point in the past n time points; T avg is the average temperature of the past n time points; T std is the standard deviation of the temperature at the past n time points; β1 is the exponential correction coefficient of the temperature data; γ1 is the exponential correction coefficient of the temperature data change rate; δ1 is the exponential correction coefficient of the temperature data stability; S is the smoke concentration value at the current moment; S0 is the smoke concentration value in the normal environment; S max is the highest smoke density value when a fire occurs in the historical records; ΔS is the difference between the smoke density at the current moment and the previous moment; S i is the smoke concentration value corresponding to the i-th time point in the past m time points; S avg is the average value of smoke concentration at the past m time points; S std is the standard deviation of smoke concentration at the past m time points; β2 is the exponential correction coefficient of smoke data; γ2 is the exponential correction coefficient of the smoke data change rate; δ2 is the exponential correction coefficient of the smoke data stability; F is the flame intensity value at the current moment; F0 is the flame intensity value under normal conditions; F max is the highest flame intensity value when a fire occurs in the historical record; ΔF is the difference between the flame intensity at the current moment and the previous moment; F i is the flame intensity value corresponding to the i-th time point in the past k time points; F avg is the average value of the flame intensity corresponding to the i-th time point in the past k time points; F std is the standard deviation of flame intensity at the past k time points; β3 is the exponential correction coefficient of flame data; γ3 is the exponential correction coefficient of flame data change rate; δ3 is the exponential correction coefficient of flame data stability.

4. The intelligent fire remote management system according to claim 3 is characterized in that: The preset fire warning level determination strategy is: If x ≤ H < y, the corresponding fire warning level is a first-level warning; If y ≤ H < z, the corresponding fire warning level is a second-level warning; If z ≤ H, the corresponding fire warning level is a third-level warning; x, y, and z are dynamically adjustable interval points.

5. The intelligent fire remote management system according to claim 4 is characterized in that: The server also includes a display module for visually displaying the temperature data, smoke data and flame data corresponding to each detected area corresponding to each factory building.

6. The intelligent fire remote management system according to claim 5 is characterized in that: The fire alarm push strategy is: When the fire warning level is level one, an alarm signal is sent to the user terminals corresponding to the area manager and monitoring personnel associated with the detected area according to the first signal sending frequency f1; When the fire warning level is level 2, an alarm signal is sent to the user terminals corresponding to the area manager and monitoring personnel associated with the detected area according to the second signal sending frequency f2; When the fire warning level is level 3, an alarm signal is sent to the user end corresponding to the area manager and monitoring personnel associated with the detected area according to the third signal sending frequency f3; at the same time, the display module of the service end displays the alarm signal and sounds an alarm; f1 <f2<f3。

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