Intelligent fire control method and system based on big data

文档序号：1923011 发布日期：2021-12-03 浏览：17次中文

阅读说明：本技术 基于大数据的智慧消防控制方法和系统 (Intelligent fire control method and system based on big data ) 是由王俊超于 2021-11-04 设计创作，主要内容包括：本发明公开的一种基于大数据的智慧消防控制方法和系统,其中方法包括：获取火情地点的现场信息,判断火情信息发送给消防救援队；基于道路行驶大数据信息获得所述火情地点周边路况位置信息,规划出目标行驶路径发送给所述消防救援队；基于消防资源补充点大数据信息获取所述火情地点预设范围内的消防资源补充点信息,发送给所述消防救援队。本发明基于大数据判断第一手的火情信息并进行发布,使得消防救援资源可以合理分配；同时在消防特种车辆在前往火灾现场的路径上,增加了筛选原则避免引起恐慌与惊扰；同时对基于大数据对备选的消防资源进行整合,进一步提高了灭火效率值,减少消防官兵的体力消耗。(The invention discloses an intelligent fire control method and system based on big data, wherein the method comprises the following steps: acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team; obtaining the position information of the road conditions around the fire place based on the road running big data information, planning a target running path and sending the target running path to the fire rescue team; and acquiring the fire fighting resource supplement point information in the preset range of the fire place based on the fire fighting resource supplement point big data information, and sending the fire fighting resource supplement point information to the fire rescue team. According to the fire rescue information issuing method, the fire information of the first hand is judged based on the big data and issued, so that fire rescue resources can be reasonably distributed; meanwhile, on the path of the special fire-fighting vehicle to the fire scene, a screening principle is added to avoid causing panic and disturbance; meanwhile, the fire-fighting resources which are selected based on the big data are integrated, the fire-fighting efficiency value is further improved, and the physical consumption of fire-fighting officers and soldiers is reduced.)

1. An intelligent fire-fighting control method based on big data is characterized by comprising the following steps:

acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team;

obtaining the position information of the road conditions around the fire place based on the road running big data information, planning a target running path and sending the target running path to the fire rescue team;

acquiring fire fighting resource supplement point information in a preset range of the fire place based on the fire fighting resource supplement point big data information, and sending the fire fighting resource supplement point information to the fire rescue team;

the acquiring of the scene information of the fire place specifically comprises the following steps:

acquiring the fire range of the fire condition through the result observed by the artificial observation satellite;

collecting the measurement information of the fire fighting equipment preset in the fire place, and judging the fire behavior of the fire;

acquiring voice information of a first alarm person to obtain the position and the reason of a fire at the fire place;

the fire condition information is judged and sent to a fire rescue team, and the method specifically comprises the following steps:

combining the fire range and the fire behavior of the fire into a dynamic fire behavior vector, and comparing the dynamic fire behavior vector with a preset threshold value, wherein,

if the dynamic fire vector value is larger than the preset threshold value, generating instruction information of a plurality of teams for reinforcing the fire place and sending the instruction information to the plurality of fire rescue teams;

if the dynamic fire vector value is smaller than or equal to the preset threshold value, generating instruction information for rescuing the fire place by a single team according to a near principle and sending the instruction information to the single fire rescue team.

2. The intelligent fire-fighting control method based on big data as claimed in claim 1, wherein the preset fire-fighting equipment includes one or more of detection devices such as temperature sensors, smoke concentration sensors and heat source tracing sensors installed in urban buildings, street cities and public places.

3. The intelligent fire control method based on big data as claimed in claim 1, wherein the information of the location of the road condition around the fire site is obtained based on the big data of road driving, a target driving path is planned and sent to the fire rescue team, specifically:

acquiring road condition position and lane information between the fire place and the fire rescue team, and planning three preselected paths;

acquiring the traffic accident occurrence frequency information of roads and intersections of each preselected path based on historical traffic big data information so as to acquire the time duration of the three preselected paths and perform descending order;

and screening a path which accords with a preset avoidance principle from the three preselected paths in descending order as the target driving path.

4. The intelligent fire control method based on big data as claimed in claim 1, wherein the obtaining of the fire fighting resource supplement point information within the preset range of the fire place based on the big data information of the fire fighting resource supplement point and sending the obtained information to the fire rescue team specifically comprises:

acquiring at least two fire fighting resource supplement points in the preset range of the fire place based on big data processing;

acquiring position information of each fire-fighting resource supplement point, and planning a supplement path;

and acquiring the material information of each fire-fighting resource supplement point, and sending the material information to the fire-fighting rescue team in a list form.

5. The intelligent fire-fighting control system based on the big data is characterized by comprising a memory and a processor, wherein the memory comprises a big data-based intelligent fire-fighting control method program, and the big data-based intelligent fire-fighting control method program realizes the following steps when being executed by the processor:

acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team;

the acquiring of the scene information of the fire place specifically comprises the following steps:

acquiring the fire range of the fire condition through the result observed by the artificial observation satellite;

collecting the measurement information of the fire fighting equipment preset in the fire place, and judging the fire behavior of the fire;

acquiring voice information of a first alarm person to obtain the position and the reason of a fire at the fire place;

the fire condition information is judged and sent to a fire rescue team, and the method specifically comprises the following steps: combining the fire range and the fire behavior of the fire into a dynamic fire vector, and comparing the dynamic fire vector with a preset threshold, wherein if the value of the dynamic fire vector is greater than the preset threshold, instruction information of a plurality of teams for reinforcing the fire place is generated and sent to the plurality of fire rescue teams; if the dynamic fire vector value is smaller than or equal to the preset threshold value, generating instruction information for rescuing the fire place by a single team according to a near principle and sending the instruction information to the single fire rescue team.

Technical Field

The invention relates to the technical field of data analysis and processing, in particular to an intelligent fire control method and system based on big data.

Background

"fire" occupies an important place in "long rivers in human history, it can bring warmth to human in cold winter, can cook food to eat thoroughly, also can carry on thermal power generation, but fire can also become the fatal threat of human-fire, it refers to the calamity that the burning that loses control on time or space causes, in the new standard, define the fire as burning that loses control on time or space, in various calamity at present, the fire is one of the main calamity that threatens public safety and social development most often, most commonly.

Along with the continuous development of industrialization and urbanization of economic society, the population gathering degree is higher and higher, the fire hazard of high-risk residential buildings is increased, the congestion of urban roads sometimes becomes a hindrance of fire rescue, in some suburb areas, flour processing plants, chemical plants and mountain forests are also places where fires frequently occur, how to reasonably rescue and reduce the casualties of fire officers and soldiers is a big problem, the experience needs to be continuously obtained from practice, and how to combine the fire with big data to realize efficient and intelligent fire extinguishing is a big breakthrough.

Disclosure of Invention

In view of the above problems, the present invention provides an intelligent fire control method and system based on big data, which can analyze and judge through the obtained big data to help fire officers to perform fire fighting rescue.

The invention provides an intelligent fire control method based on big data, which comprises the following steps:

acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team;

and acquiring the fire fighting resource supplement point information in the preset range of the fire place based on the fire fighting resource supplement point big data information, and sending the fire fighting resource supplement point information to the fire rescue team.

In this scheme, the acquiring of the scene information of the fire place specifically includes:

acquiring the fire range of the fire condition through the result observed by the artificial observation satellite;

collecting the measurement information of the fire fighting equipment preset in the fire place, and judging the fire behavior of the fire;

and acquiring voice information of a first alarm person to obtain the position and the reason of the fire at the fire place.

In this scheme, judge that condition of a fire information sends for fire rescue team, specifically do:

combining the fire range and the fire behavior of the fire into a dynamic fire behavior vector, and comparing the dynamic fire behavior vector with a preset threshold value, wherein,

In the scheme, the preset fire fighting equipment comprises one or more of detection devices such as temperature sensors, smoke concentration sensors and heat source tracking sensors arranged in urban buildings, streets and public places.

In the scheme, the information of the positions of the road conditions around the fire place is obtained based on the road driving big data information, a target driving path is planned and sent to the fire rescue team, and the method specifically comprises the following steps:

acquiring road condition position and lane information between the fire place and the fire rescue team, and planning three preselected paths;

and screening a path which accords with a preset avoidance principle from the three preselected paths in descending order as the target driving path.

In this scheme, the acquiring of the fire resource supplement point information within the preset range of the fire place based on the fire resource supplement point big data information specifically includes:

acquiring at least two fire fighting resource supplement points in the preset range of the fire place based on big data processing;

acquiring position information of each fire-fighting resource supplement point, and planning a supplement path;

and acquiring the material information of each fire-fighting resource supplement point, and sending the material information to the fire-fighting rescue team in a list form.

The second aspect of the present invention further provides an intelligent fire fighting control system based on big data, which includes a memory and a processor, wherein the memory includes an intelligent fire fighting control method program based on big data, and when executed by the processor, the intelligent fire fighting control method program based on big data implements the following steps:

acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team;

According to the intelligent fire control method and system based on the big data, fire information of a first hand is judged based on the big data and issued, so that fire rescue resources can be reasonably distributed; meanwhile, on the path of the special fire-fighting vehicle to the fire scene, a screening principle is added to avoid causing panic and disturbance; meanwhile, the fire-fighting resources which are selected based on the big data are integrated, the fire-fighting efficiency value is further improved, and the physical consumption of fire-fighting officers and soldiers is reduced.

Drawings

FIG. 1 is a flow chart illustrating a big data based intelligent fire control method according to the present application;

fig. 2 shows a block diagram of an intelligent fire-fighting control system based on big data according to the invention.

Detailed Description

In order that the above objects, features and advantages of the present invention can be more clearly understood, a more particular description of the invention will be rendered by reference to the appended drawings. It should be noted that the embodiments and features of the embodiments of the present application may be combined with each other without conflict.

In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, however, the present invention may be practiced in other ways than those specifically described herein, and therefore the scope of the present invention is not limited by the specific embodiments disclosed below.

Fig. 1 shows a flowchart of an intelligent fire-fighting control method based on big data.

As shown in fig. 1, the application discloses an intelligent fire-fighting control method based on big data, which comprises the following steps:

s102, acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team;

s104, obtaining the position information of the road conditions around the fire place based on the road running big data information, planning a target running path and sending the target running path to the fire rescue team;

and S106, acquiring the fire fighting resource supplement point information in the preset range of the fire place based on the big data information of the fire fighting resource supplement point, and sending the fire fighting resource supplement point information to the fire rescue team.

It should be noted that, in the present stage, when a fire and a fire occur, fire brigades all take action urgently after receiving an alarm telephone, and there are many problems in the process of giving an alarm, including that the size of the alarm is not matched with people who are giving action, for example, some residential buildings catch fire, only alarm is given according to the telephone of the public, only one fire brigade may be dispatched to the fire scene for rescue, because the number of the residential buildings is large, an escape passage is sealed, one fire brigade cannot meet the needs of on-site rescue, when the fire brigade arrives on the site and calls other fire brigades to support, the time is delayed, the time in the fire scene is life, and irreparable loss may be caused; in addition, for some fire dangerous areas, such as chemical plants or furniture processing plants, the fire serious hidden danger areas are generally issued by a plurality of rescue teams, one rescue team can meet the requirements only in the open fire initial stage of one small workshop of the furniture processing plant, too much fire trucks are issued to cause over-concentration of fire fighting resources, redundancy exists, so that the first hand fire information of the fire scene is of great importance, and the deployment of the fire fighting rescue resources can be well distributed.

In addition, when the fire rescue team goes to the fire scene from the base, the driver of the fire truck drives according to navigation or the driver records the road at the present stage, the fire truck is not in non-professional navigation, the situation that the fire truck is blocked on the road during rescue, so that rescue is not timely and irreparable is often caused, the phenomenon that the special fire truck is cut and rubbed by private cars is often caused due to unfamiliar road conditions, partial property loss is caused, or the road is limited in height and width, so that the fire truck cannot smoothly arrive at the fire scene at the first time, and how to select a proper driving path is further improved.

It is worth mentioning that in some fire rescue processes, as the storage of foam cars or water tank cars is reduced, rescue materials need to be supplemented immediately for rescue, two existing solutions exist, rescue is called from a base or local materials are used, the time for waiting for rescue is long, road conditions are uncertain, the preparation of the local materials is insufficient, other serious problems such as damage of pumping equipment and the like can be caused, and how to supplement fire fighting resources at the fastest is needed to be further improved.

It should be noted that, the invention obtains the site information of the fire place, judges the fire information at the first time and sends the fire information to the fire rescue teams, responds to different fire situations by different numbers of the fire rescue teams, plans the rescue driving path of each fire rescue team based on big data information, avoids road congestion and road limitation of height and width limitation, and can supplement at the first time according to the big data information of the fire-fighting resource supplement point under the condition that resources are lacked in the rescue process to save fire, thereby forming a portable and intelligent fire rescue mechanism.

According to the embodiment of the invention, the acquiring of the scene information of the fire place specifically comprises the following steps:

acquiring the fire range of the fire condition through the result observed by the artificial observation satellite;

collecting the measurement information of the fire fighting equipment preset in the fire place, and judging the fire behavior of the fire;

and acquiring voice information of a first alarm person to obtain the position and the reason of the fire at the fire place.

It should be noted that, for some large-area fires, such as mountain fires and grassland fires, due to the limitation of the range of the momentum of human eyes, the fire range of the fire can be obtained through the pictures shot by the artificial observation satellite; the preset fire fighting equipment comprises one or more of detection devices such as temperature sensors, smoke concentration sensors and heat source tracking sensors arranged in urban buildings, streets and public places, first-hand information of fire in the fire scene is obtained according to various preset sensors in the fire scene so as to judge the fire behavior of the fire scene, and meanwhile, after an alarm telephone is received, the fire starting point position and the fire starting reason of the fire scene are obtained.

It is worth mentioning that with the wide application of unmanned aerial vehicles, the fire scene of an unmanned aerial vehicle team can be adopted to carry out approaching reconnaissance to obtain the fire range and the fire trend.

According to the embodiment of the invention, the information for judging the fire condition is sent to a fire rescue team, and the method specifically comprises the following steps:

combining the fire range and the fire behavior of the fire into a dynamic fire behavior vector, and comparing the dynamic fire behavior vector with a preset threshold value, wherein,

It should be noted that the dynamic fire vectorDynamic_fireIs represented by (,) Wherein the fire range vector isThe fire vector of the fire isCalculating the dynamic fire vectorDynamic_fireThe formula is as follows:

；

the dynamic fire condition vector is measuredDynamic_fireValue of (A)Comparing with a preset threshold value, wherein the preset threshold value is a fixed value and is 60 percent, and when the dynamic fire vector value is in the range ofGenerating instruction information of a plurality of teams for reinforcing the fire place and sending the instruction information to a plurality of fire rescue teams, so that the fire rescue teams can simultaneously reinforce the fire place, deal with the dangerous case in time and save the loss; when the dynamic fire vector valueAnd generating instruction information of a single team for rescuing the fire place according to a proximity principle and sending the instruction information to the single fire rescue team, wherein the proximity principle is that the fire rescue team closest to the fire place is selected as a target.

According to the embodiment of the invention, the obtaining of the road condition position information around the fire place based on the road running big data information, the planning of the target running path and the sending of the target running path to the fire rescue team are specifically as follows:

acquiring road condition position and lane information between the fire place and the fire rescue team, and planning three preselected paths;

and screening a path which accords with a preset avoidance principle from the three preselected paths in descending order as the target driving path.

It should be noted that after the fire rescue team is confirmed, the firefighter needs to take the fire fighting truck to go to the fire scene, the vehicles in the same trip also include other special fire fighting vehicles, the road condition position and lane information between the fire place and the fire rescue team is obtained based on the road big data information, three preselected paths are planned, it is worth mentioning that the three preselected paths are the driving paths derived by common navigation, on the basis of the three preset paths, the road and intersection accident occurrence frequency information of each preselected path is obtained based on the historical traffic big data information, so as to obtain the time duration of the three preselected paths and perform descending order arrangement, it is worth mentioning that, generally, on the basis, the preselected path with the shortest required time duration can be directly selected as the target driving path, in the embodiment, a path meeting the preset avoidance principle is screened from the three preselected paths in descending order arrangement to be used as the target driving path And the preset avoidance principle is that on the basis of position big data information, three preselected paths are selected, and a primary and secondary school, a large commercial aggregate and a key mechanism are taken as avoidance factors and are respectively represented as、、AThe selection is made according to the following formula,

；

wherein the content of the first and second substances,and selecting the path with the least evasion factors from the three preselected paths as the target driving path for the number of the evasion factors, so as to avoid disturbing students on class or exams, avoid causing crowd panic and avoid causing unnecessary disturbance and trouble.

According to the embodiment of the invention, the acquiring of the fire fighting resource supplement point information in the preset range of the fire place based on the fire fighting resource supplement point big data information and the sending of the fire fighting resource supplement point information to the fire rescue team specifically comprise:

acquiring at least two fire fighting resource supplement points in the preset range of the fire place based on big data processing;

acquiring position information of each fire-fighting resource supplement point, and planning a supplement path;

and acquiring the material information of each fire-fighting resource supplement point, and sending the material information to the fire-fighting rescue team in a list form.

It should be noted that, in the rescue process, rescue resources need to be supplemented in time, at least two fire fighting resource supplement points within the preset range of the fire place are obtained based on big data processing, position information of each fire fighting resource supplement point is obtained, a supplement path is planned, the method for planning the supplement path and the method for planning the target driving path obtain material information of each fire fighting resource supplement point and generate the material information in a list form to the fire fighting team, and a fire commander of the fire fighting team selects one of the at least two fire fighting resource supplement points as a first resource supplement point to supply fire fighters for continuous fighting according to the information provided by the list and the distance of the path.

According to the embodiment of the invention, the method further comprises the following steps:

translating the acquired voice information of the first alarm person in a fire control measurement and control center measuring and calculating platform to obtain a fire information threshold;

according to the fire range observed by the artificial observation satellite and the fire measured by the preset fire fighting equipment, measuring and calculating on a fire measurement and control center measuring and calculating platform to obtain a fire storage value;

comparing the threshold value according to the translated fire information threshold value and the fire storage value;

if the fire information threshold is smaller than the fire storage value, judging that the fire alarm information of the first alarm person is accurate;

otherwise, judging that the fire alarm information of the first alarm person is inaccurate;

the fire fighting measurement and control center measuring and calculating platform extracts fire fighting facility information data of fire scene buildings or areas as fire situation basis information.

It should be noted that, in order to verify the accuracy of the fire situation information of the alarm, a fire situation information provided by the alarm is set with a threshold value through the fire monitoring and control center measurement platform, then a fire situation storage value is obtained through measurement and control in the fire monitoring and control center measurement platform according to the fire range observed by the artificial observation satellite and the fire situation measured by the preset fire equipment, threshold value comparison is carried out according to the translated fire situation information threshold value and the fire situation storage value, if the fire situation information threshold value is smaller than the fire situation storage value, it is judged that the first alarm fire alarm information of the alarm is accurate, otherwise, it is judged that the first alarm fire situation measurement and control information of the alarm is inaccurate, and the fire monitoring and control center measurement platform extracts fire facility information data of a fire site building or an area as fire situation basis information.

According to the embodiment of the invention, the method further comprises the following steps:

establishing an urban fire-fighting database;

the urban fire-fighting database comprises a building fire-fighting data set, a public fire-fighting environment data set and a regional fire-fighting data set, wherein each data set comprises a branch data stream of each building or region in an urban area;

the sub data stream of the building fire-fighting data set comprises people flow information data, material storage data, fire-fighting facility information data and site attribute data in each building of a city;

the sub data stream of the public fire-fighting environment data set comprises fire-fighting equipment distribution data, power laying data and flammable and explosive point data of the periphery of each building, the street and the public places of a city;

the sub data stream of the regional fire-fighting data set comprises data of each important fire-fighting region of a city, data of the important city region and data of regional population distribution;

establishing a fire safety threshold of the sub data stream according to the building fire data set, the public fire environment data set and the sub data stream of each building or region of the regional fire data set;

establishing a fire safety threshold set for the building fire data set, the public fire environment data set, and the regional fire data set based on the fire safety threshold set for the fractional data stream;

the fire safety threshold value set comprises a first fire safety threshold value interval, a second fire safety threshold value interval and a third fire safety threshold value interval;

and establishing an urban fire-fighting database according to the fire-fighting safety threshold value set framework.

It should be noted that, in order to digitize and digitize fire protection information of buildings and areas in the city to realize city data fire protection, an urban fire protection database is established, the fire protection database is divided into three module data sets, each building and area in the city are correspondingly divided into three module data sets for statistics, the three module data sets are subjected to content data fragmentation according to specific contents under the modules to obtain a branch data stream under each module data set, fragment data fluidization is performed on data modules of each building or area in the city, then fire protection safety thresholds of the branch data streams of each building or area are set, the fire protection safety thresholds of the three modules are combined into fire protection safety threshold sets corresponding to the three module data sets according to the fire protection safety thresholds of the branch data streams, and the fire protection safety threshold set frameworks of the three modules are integrated to obtain the urban fire protection database, specifically: establishing an urban fire-fighting database, which comprises a building fire-fighting data set, a public fire-fighting environment data set and a regional fire-fighting data set, wherein each data set comprises a branch data stream of each building or region in an urban region, the branch data stream of the building fire-fighting data set comprises people stream information data, material storage data, fire-fighting facility information data and site attribute data in each building in the city, the branch data stream of the public fire-fighting environment data set comprises fire-fighting equipment distribution data, power laying data and flammable and explosive data of the periphery, the street city and the public place of each building in the city, the branch data stream of the regional fire-fighting data set comprises important fire-fighting region data, important city region data and regional population distribution data in the city, and establishing a fire-fighting safety threshold of the branch data stream according to the building fire-fighting data set, the public fire-fighting environment data set and the branch data stream of each building or region in the regional fire-fighting data set, building fire-fighting data sets, public fire-fighting environment data sets and fire-fighting safety threshold sets of regional fire-fighting data sets are established based on fire-fighting safety threshold sets of the sub data streams, the fire-fighting safety threshold sets comprise first fire-fighting safety threshold intervals, second fire-fighting safety threshold intervals and third fire-fighting safety threshold intervals, an urban fire-fighting database is established according to the fire-fighting safety threshold set framework, digital fire information and fire scene environment information can be conveniently obtained through achieving urban fire-fighting information digitization, and fire conditions and fire fighting can be conveniently judged according to the digitized information.

According to the embodiment of the invention, the method further comprises the following steps:

when acquiring the fire information of a certain building or area;

the fire fighting measurement and control center measuring and calculating platform acquires a real-time building fire fighting data set, a public fire fighting environment data set and a regional fire fighting data set around a building or a region where a fire occurs;

the real-time building fire-fighting data set of the building with the fire comprises real-time people flow information data, material storage data, fire-fighting facility information data and site attribute data in the building;

according to the real-time building fire-fighting data set, the public fire-fighting environment data set and the regional fire-fighting data set around the building or the region where the fire occurs, carrying out measurement and calculation processing in a trained measurement and calculation neural network model to obtain a fire threshold;

the fire fighting measurement and control center measuring and calculating platform extracts a building fire fighting data set, a public fire fighting environment data set and a fire fighting safety threshold set of a regional fire fighting data set of the periphery of a building or a region where a fire occurs from an urban fire fighting database;

comparing the interval threshold value according to the fire condition threshold value obtained by measurement and calculation processing and the extracted fire safety threshold value set;

when the fire condition threshold value is in a first fire safety threshold value interval of the fire safety threshold value set, the fire control measurement and control center starts first-level and second-level fire condition responses;

when the fire condition threshold value is in a second fire safety threshold value interval of the fire safety threshold value set, the fire control measurement and control center starts three-level fire condition response;

when the fire threshold value is in the third fire safety threshold value interval of the fire safety threshold value set, the fire monitoring and controlling center starts the fourth-level and fifth-level fire response;

and when the fire threshold value is larger than the third fire safety threshold value interval of the fire safety threshold value set, the fire control measurement and control center starts disaster event fire response.

It should be noted that, in order to realize the data collection and fire information level judgment of the urban fire information, a fire digital processing is carried out by establishing a fire measurement and control center measuring and calculating platform based on the established urban fire database, the platform comprises a server, a storage, a reader, an information transceiver and the like, a real-time building fire protection data set, a public fire protection environment data set and a regional fire protection data set around a building or a region where a fire occurs are collected through the platform, the collected data sets are measured and calculated through a trained measuring and calculating neural network model to obtain a fire threshold, then interval threshold comparison is carried out according to a preset fire safety threshold set around the building or the region where the fire occurs and extracted from the fire database and the fire threshold obtained through the measuring and calculating processing, fire response of corresponding level is started according to the comparison result, the data collection and the fire level judgment of the fire information are realized, the method specifically comprises the following steps: when fire information of a certain building or area is acquired, a fire measurement and control center measuring and controlling platform acquires a real-time building fire data set, a public fire protection environment data set and an area fire protection data set of the periphery of the building or area where the fire occurs, wherein the real-time building fire protection data set of the building where the fire occurs includes real-time people stream information data, material storage data, fire protection facility information data and site attribute data in the building, the fire threshold value is obtained by measuring and controlling the real-time building fire data set, the public fire protection environment data set and the area fire protection data set of the periphery of the building or area where the fire occurs in a trained measuring and controlling neural network model, the fire measurement and control center measuring and controlling platform extracts the building fire data set, the public fire protection environment data set and the fire protection safety threshold value set of the area fire protection data set of the periphery of the building or area where the fire occurs in an urban fire database, comparing the fire threshold obtained by measurement and calculation with the extracted fire safety threshold set, starting first-level and second-level fire responses by the fire measurement and control center when the fire threshold is in the first fire safety threshold interval of the fire safety threshold set, starting third-level fire responses by the fire measurement and control center when the fire threshold is in the second fire safety threshold interval of the fire safety threshold set, starting fourth-level and fifth-level fire responses by the fire measurement and control center when the fire threshold is in the third fire safety threshold interval of the fire safety threshold set, and starting catastrophic event fire responses by the fire measurement and control center when the fire threshold is greater than the third fire safety threshold interval of the fire safety threshold set.

According to the embodiment of the invention, the method further comprises the following steps:

respectively presetting a building fire-fighting data set, a public fire-fighting environment data set and a warning preset value of a regional fire-fighting data set of each building or region in an urban area according to an urban fire-fighting database;

the warning preset value of the building fire-fighting data set of each building is set according to people flow information data, material storage data, fire-fighting facility information data and site attribute data in each building in a city;

the warning preset value of the public fire-fighting environment data set of each building or region is set according to fire-fighting equipment distribution data, power laying data and flammable and explosive point data of the periphery, the city and the public places of each building;

the preset warning value of the regional fire-fighting data set of each region is set according to the data of each important fire-fighting region of the city, the data of the important city region and the data of regional population distribution;

when a fire occurs in a certain building or area, the fire measurement and control center measurement and control platform performs fire measurement and control and data acquisition according to the building fire-fighting data set, the public fire-fighting environment data set and the area fire-fighting data set of the building or area to obtain a first fire information parameter, a second fire information parameter and a third fire information parameter corresponding to the building fire-fighting data set, the public fire-fighting environment data set and the area fire-fighting data set of the building or area;

comparing the first fire information parameters collected by measurement and calculation with a warning preset value of a building fire-fighting data set of the building to obtain a first comparison result;

comparing the second fire information parameters collected by measurement and calculation with a warning preset value of a public fire-fighting environment data set of the building or the area to obtain a second comparison result;

comparing the third fire information parameters collected according to measurement and calculation with warning preset values of the regional fire-fighting data sets of the regions to obtain a third comparison result;

if at least two comparison results of the first comparison result, the second comparison result and the third comparison result exceed preset values, starting a major fire emergency response, and responding by a fire control organization of an urban area;

if the comparison result is less than two, the emergency response of the general fire is started, and the fire chief or the local chief in the urban area organizes the response.

It should be noted that, the preset warning values corresponding to each building or area in the urban area are set according to the urban fire-fighting database, and the fire information parameters collected by measuring and calculating the building or area where the fire occurs are compared one by one, fire emergency responses of different levels are started according to the comparison result, fire-fighting level emergency response datamation in the urban area is established, and urban digital fire fighting is realized, specifically: the method comprises the steps that according to a city fire database, warning preset values of building fire protection data sets, public fire protection environment data sets and regional fire protection data sets of buildings or regions in a city area are preset respectively, the warning preset values of the building fire protection data sets of the buildings are set according to people flow information data, material storage data, fire protection facility information data and site attribute data in the buildings of the city, the warning preset values of the public fire protection environment data sets of the buildings or the regions are set according to fire protection equipment distribution data, power laying data and flammable and explosive point data of the periphery, the street city and the public places of the buildings, the warning preset values of the regional fire protection data sets of the regions are set according to fire protection region data, city key region data and regional population distribution data of the city, and when a fire condition occurs in a certain building or region, a fire protection center measuring and calculating platform is used for measuring and calculating according to the building fire protection data sets, public fire protection environment data sets and regional fire protection data of the buildings or the regions, The public fire fighting environment data set and the regional fire fighting data set are subjected to fire measurement and data acquisition to obtain a building fire fighting data set of a building or a region, a first fire information parameter, a second fire information parameter and a third fire information parameter corresponding to the public fire fighting environment data set and the regional fire fighting data set, a first comparison result is obtained by comparing the first fire information parameter acquired by measurement and calculation with a warning preset value of the building fire fighting data set of the building, a second comparison result is obtained by comparing the second fire information parameter acquired by measurement and calculation with a warning preset value of the public fire fighting environment data set of the building or the region, a third comparison result is obtained by comparing the third fire information parameter acquired by measurement and calculation with a warning preset value of the regional fire fighting data set of the region, and if at least two comparison results among the first comparison result, the second comparison result and the third comparison result exceed the preset values, a major fire emergency response is started, the general fire emergency response is started if the two comparison results exceed the preset value, and the urban regional fire chief or local chief organizes the response.

Fig. 2 shows a block diagram of an intelligent fire-fighting control system based on big data according to the invention.

As shown in fig. 2, the present invention discloses an intelligent fire-fighting control system based on big data, which includes a memory and a processor, wherein the memory includes an intelligent fire-fighting control method program based on big data, and when executed by the processor, the intelligent fire-fighting control method program based on big data implements the following steps:

acquiring the site information of the fire place, judging the fire information and sending the fire information to a fire rescue team;

According to the embodiment of the invention, the acquiring of the scene information of the fire place specifically comprises the following steps:

acquiring the fire range of the fire condition through the result observed by the artificial observation satellite;

collecting the measurement information of the fire fighting equipment preset in the fire place, and judging the fire behavior of the fire;

and acquiring voice information of a first alarm person to obtain the position and the reason of the fire at the fire place.

It should be noted that, for some large-area fires, such as mountain fires and grassland fires, due to the limitation of the range of the momentum of human eyes, the fire range of the fire can be obtained through the pictures shot by the artificial observation satellite; the preset fire fighting equipment comprises a temperature sensor, a smoke concentration sensor and a heat source tracking sensor, first hand information of fire in a fire scene is obtained according to various sensors preset in the fire scene so as to judge the fire behavior of the fire, and meanwhile, after an alarm telephone is received, the position and the reason of the fire at the fire scene are obtained.

According to the embodiment of the invention, the information for judging the fire condition is sent to a fire rescue team, and the method specifically comprises the following steps:

combining the fire range and the fire behavior of the fire into a dynamic fire behavior vector, and comparing the dynamic fire behavior vector with a preset threshold value, wherein,

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acquiring road condition position and lane information between the fire place and the fire rescue team, and planning three preselected paths;

and screening a path which accords with a preset avoidance principle from the three preselected paths in descending order as the target driving path.

It should be noted that after the fire rescue team is confirmed, the firefighter needs to take the vehicle of the fire truck which is going to the fire scene and is traveling togetherThe vehicle also comprises other special fire-fighting vehicles, road position and lane information between the fire situation place and the fire rescue team are obtained based on road big data information, three preselected paths are planned, particularly, the three preselected paths are driving paths derived by common navigation, on the basis of the three preset paths, road and intersection traffic accident occurrence frequency information of each preselected path is obtained based on historical traffic big data information, so as to obtain the time duration of the three preselected paths and carry out descending order arrangement, particularly, on the basis, generally, the preselected path with the shortest required time duration can be directly selected as the target driving path, the embodiment also comprises the step of screening the paths which accord with the preset principle from the three preselected paths which are arranged in descending order as the target driving path, the preset avoidance principle is that on the basis of position big data information, three preselected paths are respectively represented as avoidance factors by using schools of middle and primary schools, large commercial aggregates and key mechanisms as avoidance factors、、AThe selection is made according to the following formula,