A self-driven fine water mist spraying system and method for fire fighting based on Internet of Things technology

Abstract

The present invention discloses a self-driven fine water mist spraying system and method for fire fighting based on Internet of Things technology, which relates to the technical field of fire fighting facilities. Sensors are installed around the spraying equipment to monitor fire alarm parameters, and when an abnormality is found, the fire alarm index is calculated and the operating state of the spraying equipment is judged, and a fire handling record is generated when it is started; the information of fire source items in the historical fire handling records is obtained, and the records of the same category are summarized, a three-dimensional model is established, and the risk distance is analyzed, and the risk level is divided; the historical records are summarized according to the risk level, the fire extinguishing time and the fire handling index are extracted, and a fire extinguishing time prediction formula is established; a real-time three-dimensional model is constructed and the area is divided, and the item information is extracted to calculate the real-time risk level; real-time data is monitored, and when the spraying equipment is started, the regional risk level is obtained and the fire extinguishing time is predicted, and if the threshold is exceeded, the surrounding spraying equipment is started, so as to reduce the risk of fire loss.

Description

Technical Field

[0001] The present invention relates to the technical field of fire-fighting facilities, and in particular to a self-driven fine water mist spraying system and method for fire-fighting based on Internet of Things technology. Background Art

[0002] As the scale and functions of modern buildings become increasingly complex, fire protection has become an important issue in building design and operation management. Fires can not only cause casualties, but also cause serious property losses.

[0003] Water mist fire extinguishing technology is an emerging fire extinguishing technology. It atomizes water into extremely fine particles so that the water mist particles can quickly absorb heat and evaporate at the fire scene. It can not only effectively cool the fire source, but also isolate oxygen through water vapor, thereby extinguishing the fire. Compared with the traditional water sprinkler system, the water consumption of water mist is greatly reduced, and the fire extinguishing efficiency is higher, and the secondary damage caused by the fire is also lower;

[0004] When a fire occurs, usually all the sprinkler equipment will be operated at the same time, so objects far away from the fire source will also be sprayed, causing unnecessary property losses. If only the sprinkler equipment at the fire source is operated, it may lead to uncontrollable fire and increased fire extinguishing time. Therefore, through the sprinkler system, according to the on-site conditions, the use of sprinkler equipment is optimized, which can not only avoid uncontrollable fires, ensure the personal safety of people at the fire site, but also reduce unnecessary property losses. Summary of the invention

[0005] The purpose of the present invention is to provide a self-propelled fine water mist spraying system and method for fire fighting based on Internet of Things technology to solve the problems raised in the prior art.

[0006] In order to solve the above technical problems, the present invention provides the following technical solutions: a self-driven fine water mist spraying method for fire fighting based on Internet of Things technology, the method comprising:

[0007] Step S100: Install several sensors around the sprinkler equipment to monitor the fire alarm parameters collected by the sensors. When an abnormality is detected in the fire alarm parameters, the fire alarm index is calculated and the operating state of the sprinkler equipment is determined. When the sprinkler equipment is started, a fire handling record is generated.

[0008] Step S200: Acquire historical fire handling records, collect information about fire source objects in the historical fire handling records, confirm the categories of the fire source objects in the historical fire handling records, summarize the historical fire handling records with fire source objects of the same category, establish a three-dimensional model of the historical fire handling records, analyze the risk distance of the category, divide the risk distance into several risk levels, and determine a category set of a certain risk level;

[0009] Step S300: obtaining the risk level of historical fire handling records, summarizing a set of historical fire handling records of a certain risk level, obtaining sprinkler equipment parameters in a certain historical fire handling record, calculating the fire handling index of the historical fire handling record, and establishing a fire extinguishing time prediction formula for a certain risk level;

[0010] Step S400: Establish a real-time three-dimensional model of the site, divide the real-time three-dimensional model into several areas, extract information about items placed in a certain area, and calculate the real-time risk level of the area;

[0011] Step S500: monitor the real-time data collected by the sensor. When the sprinkler equipment is started, obtain the real-time risk level of the area where the sprinkler equipment is located, predict the fire extinguishing time, and when the predicted fire extinguishing time exceeds the fire extinguishing time threshold, start the surrounding sprinkler equipment.

[0012] Furthermore, step S100 includes:

[0013] Step S101: by placing a number of sensors around the sprinkler equipment in the venue, real-time collection of fire alarm parameters in the venue;

[0014] Step S102: Compare the collected value of a certain fire alarm parameter with the fire alarm parameter threshold range. When a fire alarm parameter does not meet the fire alarm parameter threshold range, calculate the fire alarm index according to the following formula:

[0015] ;

[0016] Among them, B represents the fire alarm index, A a Expressed as the value of the ath fire alarm parameter, C a It is represented as the weight of the ath fire alarm parameter, and n is represented as the total number of fire alarm parameters;

[0017] Step S103: comparing the fire alarm index with the fire alarm index threshold, when the fire alarm index exceeds the fire alarm index threshold, starting the sprinkler equipment, and generating a fire handling record in the sprinkler system at the same time;

[0018] Sensors include temperature sensors, smoke concentration sensors, flame sensors, etc. Fire alarm parameters include temperature, smoke concentration, flame intensity, etc.

[0019] The sensors can monitor temperature, smoke concentration, and flame intensity 24 hours a day, and can be flexibly arranged according to site conditions to ensure fire detection without blind spots. Through real-time comparison of fire alarm parameters and thresholds, they can respond quickly to fires as soon as they occur, avoiding delays caused by manual intervention. Fire alarm indicators are calculated through weighted calculation of multiple parameters, which can comprehensively reflect fire risks and effectively reduce false alarms. Records of each fire alarm event can help managers conduct subsequent analysis.

[0020] Further, step S200 includes:

[0021] Step S201: Obtain historical fire handling records in the sprinkler system, collect information about fire source items in a certain historical fire handling record, obtain the category corresponding to the fire source item, and aggregate historical fire handling records of fire source items of the same category to obtain a set of historical fire handling records of any category;

[0022] Step S202: In a certain category of historical fire handling record set, a picture of a fire scene in a certain historical fire handling record is collected, and the picture is input into a three-dimensional modeling software to obtain a three-dimensional model of the historical fire handling record;

[0023] Step S203: In the three-dimensional model, mark the position of the fire source object and the position of the object to which the fire spreads, obtain the coordinates of the position of the fire source object and the position of the object to which the fire spreads, and calculate the average distance between the fire source object and the object to which the fire spreads according to the following formula:

[0024] ;

[0025] Where d is the average distance between the fire source and the spread object, X e , Y e , Z e They are respectively represented by the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value of the e-th object affected by the fire, X, Y, and Z are respectively represented by the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value of the fire source object, and m is represented by the total number of objects affected by the fire;

[0026] Step S204: Collect the average distance between the fire source items and the affected items in all historical fire handling records in any category, and calculate the risk distance of the category according to the following formula:

[0027] ;

[0028] Where D represents the risk distance of the category, d f It is represented by the average distance between the fire source items and the spread items in the historical fire handling record of Article f, and h is represented by the historical fire handling record in the category;

[0029] Step S205: Divide the risk distance into several levels, obtain a risk distance range of a certain risk level, and aggregate the categories that meet the certain risk distance range to obtain a category set of a certain risk level;

[0030] The categories are aggregated to obtain a category set of a certain risk level;

[0031] Through sensors and pictures of the fire scene, it is possible to analyze which items are the source of the fire and which items are the objects that have been spread;

[0032] Categories of fire source items include plastics, wood, paper, textiles, etc.; the system relies on rich historical fire data to provide a scientific basis for risk assessment and decision-making, and reduce the impact of subjective judgment; with the help of three-dimensional modeling technology, the system can intuitively display the fire scene and enhance the understanding of the fire spread process; through precise mathematical calculations, the system can quantify the spatial relationship between fire source items and spread items, thereby improving the accuracy of calculating risk levels.

[0033] Furthermore, step S300 includes:

[0034] Step S301: Collect the fire source item category of a certain historical fire handling record, determine the risk level corresponding to the fire source item category according to the risk level category set, obtain the risk level of the historical fire handling record, and summarize the historical fire handling records of the same risk level to obtain a set of historical fire handling records of a certain risk level;

[0035] Step S302: In a set of historical fire handling records of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, wherein the sprinkler equipment parameters include sprinkler pressure, sprinkler range, and sprinkler equipment quantity, and calculate the sprinkler index according to the following formula:

[0036] ;

[0037] Among them, G represents the spray index, G i Represented as the value of the i-th spray equipment parameter, β i It is represented as the weight of the i-th spray equipment parameter, and q is represented as the number of spray equipment parameters;

[0038] Step S303: Obtain the fire alarm index and sprinkler index in a historical fire handling record, and calculate the fire handling index according to the following formula:

[0039] ;

[0040] Among them, K represents the fire handling index, P represents the weight of the fire handling index, and j represents the deviation value of the fire handling index;

[0041] Step S304: Obtain the fire extinguishing time and fire handling index in a certain historical fire handling record, and set the fire extinguishing time and fire handling index as a data group to obtain a data group of a certain historical fire handling record, perform function fitting on the data groups of several historical fire handling records in a certain risk level, and establish a fire extinguishing time prediction formula for a certain risk level:

[0042] ;

[0043] Among them, T represents the fire extinguishing time, α p It is represented as the weight of the fire extinguishing time prediction formula for the Qth risk level, γ p It is expressed as the deviation value of the fire extinguishing time prediction formula of the Qth risk level;

[0044] The system relies on historical fire handling records and parameter data to make the formulation of fire-fighting strategies scientific and reduce the influence of subjective judgment; through the classification and summary of risk levels, the system can intuitively display the risk situation of different categories of items and fire records, and facilitate the analysis of fire-fighting time prediction formulas at different levels. Through function fitting technology, the system can improve the real-time and accuracy of the model as new data is added.

[0045] Furthermore, step S400 includes:

[0046] Step S401: collecting real-time pictures of the site where the sprinkler equipment is installed, establishing a real-time 3D model of the site through 3D modeling software, obtaining the operating range of the sprinkler equipment, and dividing the real-time 3D model into several areas according to the operating range;

[0047] Step S402: extract information about items placed in a certain area, obtain the category and quantity of the items placed, and calculate the real-time risk level of the area according to the following formula:

[0048] ;

[0049] Where W represents the real-time risk level of the region, H v Expressed as the number of items at the vth risk level, u v It is represented as the weight of the vth risk level, and S is represented as the area of ​​the region;

[0050] Through the three-dimensional model display, the system can clearly present the coverage and area division of the sprinkler equipment; comprehensively consider the category, quantity and area of ​​​​the items, provide comprehensive risk assessment results, and help identify the risk level of each area.

[0051] Furthermore, step S500 includes:

[0052] Step S501: monitoring the real-time fire alarm parameters collected by the sensor, and when the sprinkler equipment is started, obtaining the real-time risk level of the area where the sprinkler equipment is located, and obtaining the real-time fire alarm parameter value of the sensor;

[0053] Step S502: obtaining the real-time sprinkler parameter values ​​of the sprinkler, calculating the real-time fire handling index, and inputting it into the fire extinguishing duration prediction formula of the real-time risk level to obtain the predicted fire extinguishing duration;

[0054] Step S503: comparing the predicted fire extinguishing time with the fire extinguishing time threshold, and when the fire extinguishing time exceeds the fire extinguishing time threshold, starting the surrounding sprinkler equipment to run simultaneously;

[0055] The use of advanced prediction algorithms combined with real-time parameters ensures that the calculation of fire extinguishing time is accurate and reliable; it allows the setting of fire extinguishing time thresholds based on specific scenarios and needs, enhancing applicability and flexibility; by automatically starting surrounding sprinkler equipment, the system achieves efficient coordination of fire extinguishing equipment and maximizes the fire extinguishing effect.

[0056] In order to better implement the above method, a self-driven fine water mist spray system for fire fighting based on Internet of Things technology is also proposed. The system includes a fire handling record module, a risk level module, a fire extinguishing time prediction module, a regional risk level module and a real-time monitoring module;

[0057] Fire handling record module: Several sensors are installed around the sprinkler equipment to monitor the fire alarm parameters collected by the sensors. When abnormal fire alarm parameters are detected, the fire alarm index is calculated and the operating status of the sprinkler equipment is judged. When the sprinkler equipment is started, a fire handling record is generated;

[0058] Risk level module: obtain historical fire handling records, collect information on fire source items in historical fire handling records, confirm the categories of fire source items in the historical fire handling records, summarize historical fire handling records with fire source items of the same category, and establish a three-dimensional model of the historical fire handling records, analyze the risk distance of the category, and divide the risk distance into several risk levels, and determine the category set of a certain risk level;

[0059] Fire extinguishing time prediction module: obtain the risk level of historical fire handling records, summarize the historical fire handling record set of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, calculate the fire handling index of the historical fire handling record, and establish a fire extinguishing time prediction formula for a certain risk level;

[0060] Regional risk level module: establish a real-time 3D model of the site, divide the real-time 3D model into several areas, extract information about items placed in a certain area, and calculate the real-time risk level of the area;

[0061] Real-time monitoring module: monitors the real-time data collected by the sensor. When the sprinkler equipment is started, the real-time risk level of the area where the sprinkler equipment is located is obtained, and the fire extinguishing time is predicted. When the predicted fire extinguishing time exceeds the fire extinguishing time threshold, the surrounding sprinkler equipment is started.

[0062] Furthermore, the fire handling record module includes a fire alarm index calculation unit and a sprinkler equipment operation status determination unit;

[0063] Fire alarm index calculation unit: by placing a number of sensors around the sprinkler equipment in the venue, the fire alarm parameters in the venue are collected in real time, and the value of a certain fire alarm parameter collected is compared with the fire alarm parameter threshold range. When there is a fire alarm parameter that does not meet the fire alarm parameter threshold range, the fire alarm index is calculated;

[0064] The sprinkler equipment operation status judging unit compares the fire alarm index with the fire alarm index threshold value, and when the fire alarm index exceeds the fire alarm index threshold value, the sprinkler equipment is started.

[0065] Further, the risk level module includes a unit for establishing a three-dimensional model of the fire scene and a unit for calculating the risk distance;

[0066] Establishing a three-dimensional model unit of a fire scene: obtaining historical fire handling records in a sprinkler system, collecting information on fire source items in a certain historical fire handling record, obtaining the category of the fire source items, summarizing historical fire handling records of fire source items of the same category, obtaining a set of historical fire handling records of any category, collecting pictures of the fire scene in a certain historical fire handling record, inputting the pictures into a three-dimensional modeling software, and obtaining a three-dimensional model of the historical fire handling record;

[0067] Calculate risk distance unit: In the three-dimensional model, mark the location of the fire source item and the location of the spread item, obtain the coordinates of the location of the fire source item and the location of the spread item, calculate the average distance between the fire source item and the spread item, collect the average distance between the fire source item and the spread item in all historical fire handling records in any category, and calculate the risk distance of the category.

[0068] Furthermore, the fire extinguishing time prediction module includes a historical fire handling record unit for collecting risk levels and a fire extinguishing time prediction formula unit;

[0069] A unit for collecting historical fire handling records of risk level: collecting the category of fire source items in a certain historical fire handling record, determining the risk level corresponding to the category of fire source items according to a category set of risk levels, obtaining the risk level of the historical fire handling record, and summarizing the historical fire handling records of the same risk level to obtain a set of historical fire handling records of a certain risk level;

[0070] Establish a fire extinguishing time prediction formula unit: in a set of historical fire handling records of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, calculate the sprinkler index, obtain the fire alarm index and sprinkler index in a certain historical fire handling record, calculate the fire handling index, obtain the fire extinguishing time and fire handling index in a certain historical fire handling record, and set the fire extinguishing time and fire handling index as a data group to obtain a data group of a certain historical fire handling record, perform function fitting on the data groups of several historical fire handling records in a certain risk level, and establish a fire extinguishing time prediction formula for a certain risk level.

[0071] Compared with the prior art, the beneficial effects of the present invention are as follows: the present invention utilizes historical fire handling records and three-dimensional modeling technology, and the system can effectively analyze the risk characteristics of different types of fire sources, thereby performing accurate risk assessment and classification; by establishing a fire extinguishing time prediction formula, the system can scientifically predict the time required for fire extinguishing based on real-time data and historical records, ensuring the timeliness and effectiveness of fire extinguishing measures; real-time updated three-dimensional models and risk level calculations enable the system to dynamically monitor risk changes within the site, and when the predicted fire extinguishing time exceeds a threshold, the system can automatically start the surrounding sprinkler equipment to form a linkage response and improve the fire extinguishing capability. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] Figure 1 A schematic diagram of a process of a self-driven fine water mist spraying method for fire fighting based on Internet of Things technology of the present invention; DETAILED DESCRIPTION

[0073] 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.

[0074] See also Figure 1 The present invention provides a technical solution: a self-driven fine water mist spraying method for fire fighting based on Internet of Things technology, the method comprising:

[0075] Step S100: Install several sensors around the sprinkler equipment to monitor the fire alarm parameters collected by the sensors. When an abnormality is detected in the fire alarm parameters, the fire alarm index is calculated and the operating state of the sprinkler equipment is determined. When the sprinkler equipment is started, a fire handling record is generated.

[0076] Wherein, step S100 includes:

[0077] Step S101: by placing a number of sensors around the sprinkler equipment in the venue, real-time collection of fire alarm parameters in the venue;

[0078] Step S102: Compare the collected value of a certain fire alarm parameter with the fire alarm parameter threshold range. When a fire alarm parameter does not meet the fire alarm parameter threshold range, calculate the fire alarm index according to the following formula:

[0079] ;

[0080] Among them, B represents the fire alarm index, A a Expressed as the value of the ath fire alarm parameter, C a It is represented as the weight of the ath fire alarm parameter, and n is represented as the total number of fire alarm parameters;

[0081] Step S103: comparing the fire alarm index with the fire alarm index threshold, when the fire alarm index exceeds the fire alarm index threshold, starting the sprinkler equipment, and generating a fire handling record in the sprinkler system at the same time;

[0082] For example, the temperature threshold is set to 70°C, the smoke concentration threshold is set to 100 ppm, and the flame emphasis threshold is set to 1;

[0083] The temperature obtained in the first acquisition was 65°C, the smoke concentration was 95ppm, and the flame intensity was 0, all of which did not exceed the threshold;

[0084] The temperature obtained from the second collection is 85°C, the smoke concentration is 150 ppm, the flame intensity is 0, and the fire alarm parameters exceeding the threshold range are detected. The fire alarm index is calculated to be 385, and the fire alarm index threshold is 300. The sprinkler equipment is activated and a fire handling record is generated.

[0085] Step S200: Acquire historical fire handling records, collect information about fire source objects in the historical fire handling records, confirm the categories of the fire source objects in the historical fire handling records, summarize the historical fire handling records with fire source objects of the same category, establish a three-dimensional model of the historical fire handling records, analyze the risk distance of the category, divide the risk distance into several risk levels, and determine a category set of a certain risk level;

[0086] Wherein, step S200 includes:

[0087] Step S201: Obtain historical fire handling records in the sprinkler system, collect information about fire source items in a certain historical fire handling record, obtain the category corresponding to the fire source item, and aggregate historical fire handling records of fire source items of the same category to obtain a set of historical fire handling records of any category;

[0088] Step S202: In a certain category of historical fire handling record set, a picture of a fire scene in a certain historical fire handling record is collected, and the picture is input into a three-dimensional modeling software to obtain a three-dimensional model of the historical fire handling record;

[0089] Step S203: In the three-dimensional model, mark the position of the fire source object and the position of the object to which the fire spreads, obtain the coordinates of the position of the fire source object and the position of the object to which the fire spreads, and calculate the average distance between the fire source object and the object to which the fire spreads according to the following formula:

[0090] ;

[0091] Where d is the average distance between the fire source and the spread object, X e , Y e , Z e They are respectively represented by the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value of the e-th object affected by the fire, X, Y, and Z are respectively represented by the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value of the fire source object, and m is represented by the total number of objects affected by the fire;

[0092] Step S204: Collect the average distance between the fire source items and the affected items in all historical fire handling records in any category, and calculate the risk distance of the category according to the following formula:

[0093] ;

[0094] Where D represents the risk distance of the category, d f It is represented by the average distance between the fire source items and the spread items in the historical fire handling record of Article f, and h is represented by the historical fire handling record in the category;

[0095] Step S205: Divide the risk distance into several levels, obtain a risk distance range of a certain risk level, and aggregate the categories that meet the certain risk distance range to obtain a category set of a certain risk level.

[0096] Step S300: obtaining the risk level of historical fire handling records, summarizing a set of historical fire handling records of a certain risk level, obtaining sprinkler equipment parameters in a certain historical fire handling record, calculating the fire handling index of the historical fire handling record, and establishing a fire extinguishing time prediction formula for a certain risk level;

[0097] Wherein, step S300 includes:

[0098] Step S301: Collect the fire source item category of a certain historical fire handling record, determine the risk level corresponding to the fire source item category according to the risk level category set, obtain the risk level of the historical fire handling record, and summarize the historical fire handling records of the same risk level to obtain a set of historical fire handling records of a certain risk level;

[0099] Step S302: In a set of historical fire handling records of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, wherein the sprinkler equipment parameters include sprinkler pressure, sprinkler range, and sprinkler equipment quantity, and calculate the sprinkler index according to the following formula:

[0100] ;

[0101] Among them, G represents the spray index, G i Represented as the value of the i-th spray equipment parameter, β i It is represented as the weight of the i-th spray equipment parameter, and q is represented as the number of spray equipment parameters;

[0102] Step S303: Obtain the fire alarm index and sprinkler index in a historical fire handling record, and calculate the fire handling index according to the following formula:

[0103] ;

[0104] Among them, K represents the fire handling index, P represents the weight of the fire handling index, and j represents the deviation value of the fire handling index;

[0105] Step S304: Obtain the fire extinguishing time and fire handling index in a certain historical fire handling record, and set the fire extinguishing time and fire handling index as a data group to obtain a data group of a certain historical fire handling record, perform function fitting on the data groups of several historical fire handling records in a certain risk level, and establish a fire extinguishing time prediction formula for a certain risk level:

[0106] ;

[0107] Among them, T represents the fire extinguishing time, α p It is represented as the weight of the fire extinguishing time prediction formula for the Qth risk level, γ p It is expressed as the deviation value of the fire extinguishing time prediction formula for the Qth risk level.

[0108] Step S400: Establish a real-time three-dimensional model of the site, divide the real-time three-dimensional model into several areas, extract information about items placed in a certain area, and calculate the real-time risk level of the area;

[0109] Wherein, step S400 includes:

[0110] Step S401: collecting real-time pictures of the site where the sprinkler equipment is installed, establishing a real-time 3D model of the site through 3D modeling software, obtaining the operating range of the sprinkler equipment, and dividing the real-time 3D model into several areas according to the operating range;

[0111] Step S402: extract information about items placed in a certain area, obtain the category and quantity of the items placed, and calculate the real-time risk level of the area according to the following formula:

[0112] ;

[0113] Where W represents the real-time risk level of the region, H v Expressed as the number of items at the vth risk level, u v It is represented as the weight of the vth risk level, and S is represented as the area of ​​the region.

[0114] Step S500: monitoring the real-time data collected by the sensor, when the sprinkler equipment is started, obtaining the real-time risk level of the area where the sprinkler equipment is located, predicting the fire extinguishing time, and when the predicted fire extinguishing time exceeds the fire extinguishing time threshold, starting the surrounding sprinkler equipment;

[0115] Wherein, step S500 includes:

[0116] Step S501: monitoring the real-time fire alarm parameters collected by the sensor, and when the sprinkler equipment is started, obtaining the real-time risk level of the area where the sprinkler equipment is located, and obtaining the real-time fire alarm parameter value of the sensor;

[0117] Step S502: obtaining the real-time sprinkler parameter values ​​of the sprinkler, calculating the real-time fire handling index, and inputting it into the fire extinguishing duration prediction formula of the real-time risk level to obtain the predicted fire extinguishing duration;

[0118] Step S503: Compare the predicted fire extinguishing time with the fire extinguishing time threshold, and when the fire extinguishing time exceeds the fire extinguishing time threshold, start the surrounding sprinkler equipment to run simultaneously.

[0119] In order to better implement the above method, a self-driven fine water mist spray system for fire fighting based on Internet of Things technology is also proposed. The system includes a fire handling record module, a risk level module, a fire extinguishing time prediction module, a regional risk level module and a real-time monitoring module;

[0120] Fire handling record module: Several sensors are installed around the sprinkler equipment to monitor the fire alarm parameters collected by the sensors. When abnormal fire alarm parameters are detected, the fire alarm index is calculated and the operating status of the sprinkler equipment is judged. When the sprinkler equipment is started, a fire handling record is generated;

[0121] Among them, the fire handling record module includes a fire alarm index calculation unit and a sprinkler equipment operation status judgment unit;

[0122] Fire alarm index calculation unit: by placing a number of sensors around the sprinkler equipment in the venue, the fire alarm parameters in the venue are collected in real time, and the value of a certain fire alarm parameter collected is compared with the fire alarm parameter threshold range. When there is a fire alarm parameter that does not meet the fire alarm parameter threshold range, the fire alarm index is calculated;

[0123] The sprinkler equipment operation status judging unit compares the fire alarm index with the fire alarm index threshold value, and when the fire alarm index exceeds the fire alarm index threshold value, the sprinkler equipment is started.

[0124] Risk level module: obtain historical fire handling records, collect information on fire source items in historical fire handling records, confirm the categories of fire source items in the historical fire handling records, summarize historical fire handling records with fire source items of the same category, and establish a three-dimensional model of the historical fire handling records, analyze the risk distance of the category, and divide the risk distance into several risk levels, and determine the category set of a certain risk level;

[0125] Among them, the risk level module includes a unit for establishing a three-dimensional model of the fire scene and a unit for calculating the risk distance;

[0126] Establishing a three-dimensional model unit of a fire scene: obtaining historical fire handling records in a sprinkler system, collecting information on fire source items in a certain historical fire handling record, obtaining the category of the fire source items, summarizing historical fire handling records of fire source items of the same category, obtaining a set of historical fire handling records of any category, collecting pictures of the fire scene in a certain historical fire handling record, inputting the pictures into a three-dimensional modeling software, and obtaining a three-dimensional model of the historical fire handling record;

[0127] Calculate risk distance unit: In the three-dimensional model, mark the location of the fire source item and the location of the spread item, obtain the coordinates of the location of the fire source item and the location of the spread item, calculate the average distance between the fire source item and the spread item, collect the average distance between the fire source item and the spread item in all historical fire handling records in any category, and calculate the risk distance of the category.

[0128] Fire extinguishing time prediction module: obtain the risk level of historical fire handling records, summarize the historical fire handling record set of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, calculate the fire handling index of the historical fire handling record, and establish a fire extinguishing time prediction formula for a certain risk level;

[0129] Among them, the fire extinguishing time prediction module includes a historical fire handling record unit for collecting risk levels and a fire extinguishing time prediction formula unit;

[0130] A unit for collecting historical fire handling records of risk level: collecting the category of fire source items in a certain historical fire handling record, determining the risk level corresponding to the category of fire source items according to a category set of risk levels, obtaining the risk level of the historical fire handling record, and summarizing the historical fire handling records of the same risk level to obtain a set of historical fire handling records of a certain risk level;

[0131] Establish a fire extinguishing time prediction formula unit: in a set of historical fire handling records of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, calculate the sprinkler index, obtain the fire alarm index and sprinkler index in a certain historical fire handling record, calculate the fire handling index, obtain the fire extinguishing time and fire handling index in a certain historical fire handling record, and set the fire extinguishing time and fire handling index as a data group to obtain a data group of a certain historical fire handling record, perform function fitting on the data groups of several historical fire handling records in a certain risk level, and establish a fire extinguishing time prediction formula for a certain risk level.

[0132] Regional risk level module: establish a real-time 3D model of the site, divide the real-time 3D model into several areas, extract information about items placed in a certain area, and calculate the real-time risk level of the area;

[0133] Real-time monitoring module: monitors the real-time data collected by the sensor. When the sprinkler equipment is started, the real-time risk level of the area where the sprinkler equipment is located is obtained, and the fire extinguishing time is predicted. When the predicted fire extinguishing time exceeds the fire extinguishing time threshold, the surrounding sprinkler equipment is started.

[0134] It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above and that the invention can be implemented in other specific forms without departing from the spirit or essential features of the invention. Therefore, the embodiments should be considered exemplary and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description, and it is intended that all variations falling within the meaning and scope of the equivalent elements of the claims be included in the invention. Any reference numeral in a claim should not be considered as limiting the claim to which it relates.

Claims

1. A self-driven fine water mist spraying method for fire fighting based on Internet of Things technology, characterized in that: Step S100: Install several sensors around the sprinkler equipment to monitor the fire alarm parameters collected by the sensors. When an abnormality is detected in the fire alarm parameters, the fire alarm index is calculated and the operating state of the sprinkler equipment is determined. When the sprinkler equipment is started, a fire handling record is generated. Step S200: Acquire historical fire handling records, collect information about fire source objects in the historical fire handling records, confirm the categories of the fire source objects in the historical fire handling records, summarize the historical fire handling records with fire source objects of the same category, establish a three-dimensional model of the historical fire handling records, analyze the risk distance of the category, divide the risk distance into several risk levels, and determine a category set of a certain risk level; Step S300: obtaining the risk level of historical fire handling records, summarizing a set of historical fire handling records of a certain risk level, obtaining sprinkler equipment parameters in a certain historical fire handling record, calculating the fire handling index of the historical fire handling record, and establishing a fire extinguishing time prediction formula for a certain risk level; The step S300 includes: Step S301: Collect the fire source item category of a certain historical fire handling record, determine the risk level corresponding to the fire source item category according to the risk level category set, obtain the risk level of the historical fire handling record, and summarize the historical fire handling records of the same risk level to obtain a set of historical fire handling records of a certain risk level; Step S302: In a set of historical fire handling records of a certain risk level, obtain the sprinkler equipment parameters in a certain historical fire handling record, wherein the sprinkler equipment parameters include sprinkler pressure, sprinkler range, and sprinkler equipment quantity, and calculate the sprinkler index according to the following formula: ； Among them, G represents the spray index, G i Represented as the value of the i-th spray equipment parameter, β i It is represented as the weight of the i-th spray equipment parameter, and q is represented as the number of spray equipment parameters; Step S303: Obtain the fire alarm index and sprinkler index in a historical fire handling record, and calculate the fire handling index according to the following formula: ； Among them, K represents the fire handling index, P represents the weight of the fire handling index, and j represents the deviation value of the fire handling index; Step S304: Obtain the fire extinguishing time and fire handling index in a certain historical fire handling record, and set the fire extinguishing time and fire handling index as a data group to obtain a data group of a certain historical fire handling record, perform function fitting on the data groups of several historical fire handling records in a certain risk level, and establish a fire extinguishing time prediction formula for a certain risk level: ； Among them, T represents the fire extinguishing time, α Q It is represented as the weight of the fire extinguishing time prediction formula for the Qth risk level, γ Q It is expressed as the deviation value of the fire extinguishing time prediction formula for the Qth risk level; Step S400: Establish a real-time three-dimensional model of the site, divide the real-time three-dimensional model into several areas, extract information about items placed in a certain area, and calculate the real-time risk level of the area; Step S500: monitor the real-time data collected by the sensor. When the sprinkler equipment is started, obtain the real-time risk level of the area where the sprinkler equipment is located, predict the fire extinguishing time, and when the predicted fire extinguishing time exceeds the fire extinguishing time threshold, start the surrounding sprinkler equipment.

2. According to claim 1, a self-driven fine water mist spraying method for fire fighting based on Internet of Things technology is characterized in that: The step S100 includes the following steps: Step S101: by placing a number of sensors around the sprinkler equipment in the venue, real-time collection of fire alarm parameters in the venue; Step S102: Calculate the fire alarm index according to the following formula: ； Among them, B represents the fire alarm index, A a Expressed as the value of the ath fire alarm parameter, C a It is represented as the weight of the ath fire alarm parameter, and n is represented as the total number of fire alarm parameters; Step S103: Compare the fire alarm index with the fire alarm index threshold. When the fire alarm index exceeds the fire alarm index threshold, start the sprinkler equipment and generate a fire handling record in the sprinkler system at the same time.

3. The self-driving fine water mist spraying method for fire fighting based on Internet of Things technology according to claim 2 is characterized in that: The step S200 includes the following steps: Step S201: Obtain historical fire handling records in the sprinkler system, collect information about fire source items in a certain historical fire handling record, obtain the category corresponding to the fire source item, and aggregate historical fire handling records of fire source items of the same category to obtain a set of historical fire handling records of any category; Step S202: In a certain category of historical fire handling record set, a picture of a fire scene in a certain historical fire handling record is collected, and the picture is input into a three-dimensional modeling software to obtain a three-dimensional model of the historical fire handling record; Step S203: In the three-dimensional model, mark the position of the fire source object and the position of the object to which the fire spreads, obtain the coordinates of the position of the fire source object and the position of the object to which the fire spreads, and calculate the average distance between the fire source object and the object to which the fire spreads according to the following formula: ； Where d is the average distance between the fire source and the objects to be spread, X e , Y e , Z e They are respectively represented by the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value of the e-th object affected by the fire, X, Y, and Z are respectively represented by the X-axis coordinate value, Y-axis coordinate value, and Z-axis coordinate value of the fire source object, and m is represented by the total number of objects affected by the fire; Step S204: Collect the average distance between the fire source items and the affected items in all historical fire handling records in any category, and calculate the risk distance of the category according to the following formula: ； Where D represents the risk distance of the category, d f It is represented by the average distance between the fire source items and the spread items in the historical fire handling record of Article f, and h is represented by the historical fire handling record in the category; Step S205: Divide the risk distance into several levels, obtain a risk distance range of a certain risk level, and aggregate the categories that meet the certain risk distance range to obtain a category set of a certain risk level.

4. The self-driving fine water mist spraying method for fire fighting based on Internet of Things technology according to claim 1 is characterized in that: The step S400 includes the following steps: Step S401: collecting real-time pictures of the site where the sprinkler equipment is installed, establishing a real-time 3D model of the site through 3D modeling software, obtaining the operating range of the sprinkler equipment, and dividing the real-time 3D model into several areas according to the operating range; Step S402: extract information about items placed in a certain area, obtain the category and quantity of the items placed, and calculate the real-time risk level of the area according to the following formula: ； Where W represents the real-time risk level of the region, H v Expressed as the number of items at the vth risk level, u v It is represented as the weight of the vth risk level, and S is represented as the area of ​​the region.

5. The self-driving fine water mist spraying method for fire fighting based on Internet of Things technology according to claim 4 is characterized in that: The step S500 includes the following steps: Step S501: monitoring the real-time fire alarm parameters collected by the sensor, and when the sprinkler equipment is started, obtaining the real-time risk level of the area where the sprinkler equipment is located, and obtaining the real-time fire alarm parameter value of the sensor; Step S502: obtaining the real-time sprinkler parameter values ​​of the sprinkler, calculating the real-time fire handling index, and inputting it into the fire extinguishing duration prediction formula of the real-time risk level to obtain the predicted fire extinguishing duration; Step S503: Compare the predicted fire extinguishing time with the fire extinguishing time threshold, and when the fire extinguishing time exceeds the fire extinguishing time threshold, start the surrounding sprinkler equipment to run simultaneously.

6. A self-driving fine water mist spraying system for fire fighting based on Internet of Things technology, used to implement a self-driving fine water mist spraying method for fire fighting based on Internet of Things technology as described in any one of claims 1 to 5, characterized in that: The system includes: a fire handling record module, a risk level module, a fire extinguishing time prediction module, a regional risk level module and a real-time monitoring module; The fire handling record module: installs several sensors around the sprinkler equipment to monitor the fire alarm parameters collected by the sensors. When an abnormality is detected in the fire alarm parameters, the fire alarm index is calculated and the operating status of the sprinkler equipment is judged. When the sprinkler equipment is started, a fire handling record is generated; The risk level module: obtains historical fire handling records, collects information on fire source items in the historical fire handling records, confirms the categories of the fire source items in the historical fire handling records, summarizes historical fire handling records with fire source items of the same category, and establishes a three-dimensional model of the historical fire handling records, analyzes the risk distance of the category, and divides the risk distance into several risk levels, and determines a category set of a certain risk level; The fire extinguishing time prediction module: obtains the risk level of historical fire handling records, summarizes a set of historical fire handling records of a certain risk level, obtains sprinkler equipment parameters in a certain historical fire handling record, calculates the fire handling index of the historical fire handling record, and establishes a fire extinguishing time prediction formula for a certain risk level; The regional risk level module: establishes a real-time three-dimensional model of the site, divides the real-time three-dimensional model into several areas, extracts information about items placed in a certain area, and calculates the real-time risk level of the area; The real-time monitoring module monitors the real-time data collected by the sensor. When the sprinkler equipment is started, the real-time risk level of the area where the sprinkler equipment is located is obtained, and the fire extinguishing time is predicted. When the predicted fire extinguishing time exceeds the fire extinguishing time threshold, the surrounding sprinkler equipment is started.

7. The self-driving water mist spray system for fire fighting based on Internet of Things technology according to claim 6 is characterized in that: The fire handling record module includes a fire alarm index calculation unit and a sprinkler equipment operation status judgment unit; The fire alarm index calculation unit: by placing a number of sensors around the sprinkler equipment in the venue, the fire alarm parameters in the venue are collected in real time to calculate the fire alarm index; The unit for determining the operating state of the sprinkler equipment compares the fire alarm index with the fire alarm index threshold, and starts the sprinkler equipment when the fire alarm index exceeds the fire alarm index threshold.

8. The self-driving water mist spray system for fire fighting based on Internet of Things technology according to claim 6 is characterized in that: The risk level module includes a unit for establishing a three-dimensional model of the fire scene and a unit for calculating the risk distance; The fire scene three-dimensional model building unit: obtains historical fire handling records in the sprinkler system, collects information about fire source items in a certain historical fire handling record, obtains the category of the fire source items, summarizes historical fire handling records of fire source items of the same category, obtains a set of historical fire handling records of any category, collects a picture of the fire scene in a certain historical fire handling record, inputs the picture into a three-dimensional modeling software, and obtains a three-dimensional model of the historical fire handling record; The risk distance calculation unit marks the location of the fire source item and the location of the spread item in the three-dimensional model, obtains the coordinates of the location of the fire source item and the location of the spread item, calculates the average distance between the fire source item and the spread item, collects the average distance between the fire source item and the spread item in all historical fire handling records in any category, and calculates the risk distance of the category.

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