CN112329608A - Smart fire monitoring management cloud platform based on big data analysis - Google Patents
Smart fire monitoring management cloud platform based on big data analysis Download PDFInfo
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- 238000012544 monitoring process Methods 0.000 title claims abstract description 69
- 238000007405 data analysis Methods 0.000 title claims abstract description 14
- 239000000779 smoke Substances 0.000 claims abstract description 194
- 238000001514 detection method Methods 0.000 claims abstract description 49
- 238000004458 analytical method Methods 0.000 claims abstract description 22
- 238000012545 processing Methods 0.000 claims abstract description 22
- 238000000605 extraction Methods 0.000 claims abstract description 16
- RAHZWNYVWXNFOC-UHFFFAOYSA-N Sulphur dioxide Chemical compound O=S=O RAHZWNYVWXNFOC-UHFFFAOYSA-N 0.000 claims description 54
- LELOWRISYMNNSU-UHFFFAOYSA-N hydrogen cyanide Chemical compound N#C LELOWRISYMNNSU-UHFFFAOYSA-N 0.000 claims description 52
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- VEXZGXHMUGYJMC-UHFFFAOYSA-N Hydrochloric acid Chemical compound Cl VEXZGXHMUGYJMC-UHFFFAOYSA-N 0.000 claims description 27
- 229910002091 carbon monoxide Inorganic materials 0.000 claims description 27
- 229910000041 hydrogen chloride Inorganic materials 0.000 claims description 27
- IXCSERBJSXMMFS-UHFFFAOYSA-N hydrogen chloride Substances Cl.Cl IXCSERBJSXMMFS-UHFFFAOYSA-N 0.000 claims description 27
- JCXJVPUVTGWSNB-UHFFFAOYSA-N nitrogen dioxide Inorganic materials O=[N]=O JCXJVPUVTGWSNB-UHFFFAOYSA-N 0.000 claims description 27
- 239000000470 constituent Substances 0.000 claims description 3
- 238000012216 screening Methods 0.000 claims description 3
- 238000004364 calculation method Methods 0.000 claims description 2
- 238000012549 training Methods 0.000 description 3
- 238000005516 engineering process Methods 0.000 description 2
- JMANVNJQNLATNU-UHFFFAOYSA-N oxalonitrile Chemical compound N#CC#N JMANVNJQNLATNU-UHFFFAOYSA-N 0.000 description 2
- 206010000369 Accident Diseases 0.000 description 1
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- 238000007792 addition Methods 0.000 description 1
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- 238000010586 diagram Methods 0.000 description 1
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- 238000006467 substitution reaction Methods 0.000 description 1
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Abstract
The invention discloses a smart fire monitoring management cloud platform based on big data analysis, which comprises a region dividing module, a monitoring point arrangement module, a smoke component detection module, a smoke component analysis module, an image acquisition module, an image processing module, a feature extraction module, a cloud server, an evacuation route setting module, an alarm display terminal and a cloud database, wherein the region dividing module is used for dividing a fire area; the invention arranges monitoring points for each classroom subregion in each classroom building region in a school, detects the concentration of each smoke component of each classroom subregion in each classroom building region, calculates the smoke concentration coefficient of each classroom subregion in each classroom building region, analyzes whether the smoke concentration of each classroom subregion exceeds standard, acquires images for each classroom subregion with the exceeding smoke concentration, analyzes whether fire occurs in each classroom subregion, sets an evacuation route for each classroom subregion with the fire, and gives an alarm and displays, thereby increasing the fire safety performance of the school.
Description
Technical Field
The invention relates to the field of fire protection monitoring management, in particular to an intelligent fire protection monitoring management cloud platform based on big data analysis.
Background
Along with the rapid development of high education in China, the school scale is continuously enlarged, the accompanying fire accidents and accident losses also show a growing trend, the fire fighting pressure of schools is continuously increased, and the fire fighting safety of schools faces serious challenges and troubles.
Nowadays, the fire safety management level is improved, but most of the school fire monitoring management technologies are relatively lagged behind on the whole. According to the existing school fire monitoring management, people collect different types of data on site through different devices and then detect the data through a field computer processing mode, the data cannot be collected and processed immediately and monitored automatically, the intelligent degree is low, the fire cannot be detected timely, tragic training that small fire causes big disasters occurs, and therefore huge loss is caused.
Disclosure of Invention
The invention aims to provide a smart fire-fighting monitoring management cloud platform based on big data analysis, which is characterized in that monitoring points are distributed on each classroom subregion in each teaching building region in a school through a monitoring point distribution module, the concentration of each smoke component of each classroom subregion in each teaching building region in the school is detected, the smoke concentration coefficient of each classroom subregion in each classroom region in the school is calculated, whether the smoke concentration of each classroom subregion exceeds the standard or not is analyzed, image acquisition is carried out on each classroom subregion with the smoke concentration exceeding the standard is analyzed, whether fire occurs in each classroom subregion with the smoke concentration exceeding the standard or not is analyzed through a cloud server, evacuation routes are set for each classroom subregion with the fire, and alarm and display are carried out, so that the problems in the background technology are solved.
The purpose of the invention can be realized by the following technical scheme:
a smart fire monitoring management cloud platform based on big data analysis comprises a region dividing module, a monitoring point arrangement module, a smoke component detection module, a smoke component analysis module, an image acquisition module, an image processing module, a feature extraction module, a cloud server, an evacuation route setting module, an alarm display terminal and a cloud database;
the cloud server is respectively connected with the smoke component analysis module, the image acquisition module, the feature extraction module, the evacuation route setting module and the cloud database, the cloud database is respectively connected with the region division module, the smoke component analysis module and the evacuation route setting module, the smoke component detection module is respectively connected with the monitoring point arrangement module and the smoke component analysis module, the image processing module is respectively connected with the image acquisition module and the feature extraction module, and the evacuation route setting module is connected with the alarm display terminal;
the area dividing module is used for dividing each teaching building area of a school, dividing each teaching building area in the school into a plurality of classroom subareas according to a set sequence, numbering the classroom subareas in sequence, and sending the numbers of the classroom subareas in each teaching building area in the school to the cloud database;
the monitoring point arrangement module is used for arranging monitoring points for all the classroom sub-areas in all the teaching building areas in the school, arranging a plurality of monitoring points at the central points of all the classroom sub-areas in all the teaching building areas in the school in an evenly distributed mode, enabling all the monitoring points to correspond to all the classroom sub-areas one by one, and sending the monitoring points of all the classroom sub-areas in all the teaching building areas in the school to the smoke component detection module;
the smoke component detection module is used for receiving the monitoring points of all the classroom sub-areas in all the classroom building areas in the school sent by the monitoring point arrangement module, detecting smoke of all the classroom sub-areas in all the classroom building areas in the school, detecting the concentration of carbon monoxide, the concentration of nitrogen dioxide, the concentration of sulfur dioxide, the concentration of hydrogen chloride and the concentration of hydrogen cyanide in main smoke components of all the classroom sub-areas, counting the concentration of all the smoke components of all the classroom sub-areas in all the classroom building areas in the school, and forming a smoke component concentration set W of all the classroom sub-areas in all the classroom building areas in the schooliR(wi1r,wi2r,...,wijr,...,wimr)，wijr is the concentration of the ith smoke component in the jth classroom subregion in the ith classroom building region in the school, and r is r1,r2,r3,r4,r5， r1,r2,r3,r4,r5Respectively representing carbon monoxide, nitrogen dioxide, sulfur dioxide, hydrogen chloride and hydrogen cyanide in main smoke components, and sending the concentration of each smoke component of each classroom subregion in each teaching building region in the school to a smoke component analysis module;
the smoke component analysis module is used for receiving the smoke component concentration sets of all classroom sub-areas in all classroom areas in the school, which are generated by the smoke component detection module, extracting the safe concentration of carbon monoxide, the safe concentration of nitrogen dioxide, the safe concentration of sulfur dioxide, the safe concentration of hydrogen chloride and the safe concentration of hydrogen cyanide in main indoor smoke components stored in the cloud database, comparing the smoke component concentration of all classroom sub-areas in all classroom areas in the school with the corresponding safe concentration of smoke components, and obtaining the smoke component concentration contrast difference value set delta W of all classroom sub-areas in all classroom areas in the schooliR(Δwi1r,Δwi2r,...,Δwijr,...,Δwimr)，Δwijr is expressed as a comparison difference value between the concentration of the r-th smoke component of the jth classroom subregion in the ith teaching building region in the school and the corresponding safety concentration of the smoke component, and the comparison difference values of the concentrations of the smoke components of all the classroom subregions in all the teaching building regions in the school are sent to the cloud server in a set manner;
the cloud server is used for receiving a smoke component concentration contrast difference set of each classroom subregion in each classroom of the school, which is sent by the smoke component analysis module, extracting a contrast coefficient of each main smoke component stored in the cloud database, calculating a smoke concentration coefficient of each classroom subregion in each classroom region in the school, when the smoke concentration coefficient of a certain classroom subregion in a certain classroom region in the school is greater than a set smoke concentration coefficient threshold value, indicating that the smoke concentration of the classroom subregion exceeds the standard, counting classroom numbers of each subregion in each classroom region with the excessive smoke concentration, and sending each classroom subregion number in each classroom region with the excessive smoke concentration to the image acquisition module;
the image acquisition module is used for receiving numbers of all classroom sub-areas in all classroom building areas with the smoke concentration exceeding the standard, which are sent by the cloud server, acquiring images of all classroom sub-areas in all classroom building areas with the received smoke concentration exceeding the standard, and sending all the acquired images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard to the image processing module;
the image processing module is used for receiving the images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard, which are sent by the image acquisition module, normalizing the images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard into images with consistent size and no deflection angle, performing image enhancement processing on the processed images to obtain enhanced images of all the classroom sub-areas in all the classroom areas with the smoke concentration exceeding the standard, and sending the enhanced images of all the classroom sub-areas in all the classroom areas with the smoke concentration exceeding the standard to the feature extraction module;
the characteristic extraction module is used for receiving the enhanced images of the classroom sub-areas in the teaching areas with the smoke concentration exceeding the standard, which are sent by the image processing module, extracting the characteristics of the enhanced images of the classroom sub-areas in the teaching areas with the smoke concentration exceeding the standard, extracting the characteristics of the enhanced images of the classroom sub-areas in the teaching building areas with the smoke concentration exceeding the standard, and sending the characteristics of the enhanced images of the classroom sub-areas in the teaching building areas with the smoke concentration exceeding the standard to the cloud server;
the cloud server is used for receiving the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard, extracting the standard image characteristics of the indoor fire, stored in the cloud database, comparing the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard image characteristics of the indoor fire, counting the similarity between the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard image characteristics of the indoor fire, if the similarity of the contrast of each enhanced image characteristic of a certain classroom subregion is less than or equal to a set similarity threshold, indicating that the classroom subregion has no fire, and if the similarity of the contrast of a certain enhanced image characteristic of a certain classroom subregion is greater than the set similarity threshold, indicating that the classroom subregion has fire, counting numbers of all classroom subareas in each teaching building area with the fire, and sending the numbers of all classroom subareas in each teaching building area with the fire to an evacuation route setting module;
the evacuation route setting module is used for receiving numbers of all classroom sub-areas in all classroom building areas where the fire disaster occurs, which are sent by the cloud server, extracting three-dimensional models of all classroom building in the school, which are stored in the cloud database, obtaining model positions of all classroom sub-areas in all classroom building areas where the fire disaster occurs, simultaneously extracting all fire fighting channel positions in all three-dimensional models of all classroom building in the school, which are stored in the cloud database, screening the fire fighting channel closest to the model position of each classroom sub-area in all classroom building areas where the fire disaster occurs, setting evacuation routes of all classroom sub-areas in all classroom building areas where the fire disaster occurs, and sending the evacuation routes of all classroom sub-areas in all classroom building areas where the fire disaster occurs to the alarm display terminal;
the alarm display terminal is used for receiving the evacuation routes of all classroom sub-areas in the building area where the fire breaks out and sent by the evacuation route setting module, alarming and displaying, evacuating the personnel in and near the classroom sub-areas where the fire breaks out according to the displayed evacuation routes, and simultaneously giving an alarm to rescue timely fire fighters after receiving the alarm notification;
the cloud database is used for receiving the numbers of the classroom subareas in each teaching building area in the school sent by the area division module, and simultaneously storing the safe concentration of carbon monoxide, the safe concentration of nitrogen dioxide, the safe concentration of sulfur dioxide, the safe concentration of hydrogen chloride and cyanogen in the main components of indoor smokeThe safe concentration of hydrogen sulfide, the contrast coefficient of the main components of the stored smoke are respectively recorded as
Storing standard image characteristics of fire in a room, and storing three-dimensional models of various teaching buildings in a school and the positions of various fire fighting channels in the three-dimensional models;
further, the area division module divides each teaching building into areas, and the method comprises the following steps:
s1, numbering the teaching building areas in the school in sequence, wherein the numbering is 1,2, i, n;
s2, dividing each teaching building area into a plurality of classroom subareas from left to right and from bottom to top;
s3, sequentially numbering a plurality of classroom subareas, wherein the numbers of the classroom subareas are 1,2, a, j, a, m;
s4, forming a number set A of each classroom subregion in each classroom teaching building region in schooli(ai1,ai2,...,aij,...,aim)，aijThe number of the jth classroom subregion in the ith teaching building region in the school is represented;
further, the smoke component detection module comprises a carbon monoxide concentration detection unit, a nitrogen dioxide concentration detection unit, a sulfur dioxide concentration detection unit, a hydrogen chloride concentration detection unit and a hydrogen cyanide concentration detection unit;
furthermore, the carbon monoxide concentration detection unit is a carbon monoxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the carbon monoxide concentration of each classroom subregion in real time; the nitrogen dioxide concentration detection unit is a nitrogen dioxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the nitrogen dioxide concentration of each classroom subregion in real time; the sulfur dioxide concentration detection unit is a sulfur dioxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the sulfur dioxide concentration of each classroom subregion in real time; the hydrogen chloride concentration detection unit is a hydrogen chloride concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the hydrogen chloride of each classroom subregion in real time; the hydrogen cyanide concentration detection unit is a hydrogen cyanide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the hydrogen cyanide concentration of each classroom subregion in real time;
further, the smoke concentration coefficient calculation formula of each classroom subregion in each classroom building region in the school is
ξijExpressed as the smoke concentration coefficient of the jth classroom subregion in the ith classroom building region in school, e is expressed as a natural number, equal to 2.718,
respectively expressed as the contrast coefficients, Δ w, of carbon monoxide, nitrogen dioxide, sulfur dioxide, hydrogen chloride and hydrogen cyanide in the main constituents of the smokeijr is the comparison difference between the concentration of the ith smoke component in the ith classroom subregion in the ith classroom building region in the school and the corresponding safe concentration of the smoke component, and r is r1,r2,r3,r4,r5，w0r is expressed as the safe concentration of the r-th major smoke component in the room;
furthermore, the image acquisition module comprises a plurality of high-definition cameras, wherein the high-definition cameras are respectively installed at monitoring points of all classroom sub-areas and correspond to the classroom sub-areas one by one, and images of all directions in all classroom sub-areas with standard exceeding smoke concentration are acquired by adjusting the shooting direction of the high-definition cameras.
Has the advantages that:
(1) the invention provides a smart fire-fighting monitoring management cloud platform based on big data analysis, which is characterized in that monitoring points are distributed on each classroom subregion in each teaching building area in a school through a monitoring point distribution module, the concentration of each smoke component of each classroom subregion in each teaching building area in the school is detected, so that the real-time collection processing and automatic monitoring of data are realized, the intelligent degree is improved, reliable parameter data are provided for the smoke concentration coefficient of each classroom subregion in each teaching building area in the school in a later period, simultaneously the smoke concentration coefficient of each classroom subregion in each classroom building area in the school is calculated, whether the smoke concentration of each classroom subregion exceeds the standard or not is analyzed, the image collection is carried out on each classroom subregion with the smoke concentration exceeding the standard, and a cloud server is used for analyzing whether a fire disaster occurs in each classroom subregion with the smoke concentration exceeding the standard or not, thereby avoiding the problem of tragic training of a big disaster caused by small fire and reducing the loss caused by fire.
(2) According to the invention, the evacuation route is set for each classroom subarea where a fire disaster occurs through the evacuation route setting module, and the alarm and display are carried out through the alarm display terminal, so that the problem of people evacuation in a hurry is avoided, the personnel evacuation time is reduced, the fire alarm efficiency of fire fighters is improved, the fire safety performance of schools is improved, and the normal teaching, working and living orders of the schools are maintained.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the intelligent fire-fighting monitoring management cloud platform based on big data analysis comprises a region dividing module, a monitoring point arrangement module, a smoke component detection module, a smoke component analysis module, an image acquisition module, an image processing module, a feature extraction module, a cloud server, an evacuation route setting module, an alarm display terminal and a cloud database;
the cloud server is respectively connected with the smoke component analysis module, the image acquisition module, the feature extraction module, the evacuation route setting module and the cloud database, the cloud database is respectively connected with the region division module, the smoke component analysis module and the evacuation route setting module, the smoke component detection module is respectively connected with the monitoring point arrangement module and the smoke component analysis module, the image processing module is respectively connected with the image acquisition module and the feature extraction module, and the evacuation route setting module is connected with the alarm display terminal.
The area dividing module is used for dividing each teaching building area of a school, dividing each teaching building area in the school into a plurality of classroom subareas according to a set sequence, numbering the classroom subareas in sequence, and sending the numbers of the classroom subareas in each teaching building area in the school to the cloud database;
the region division module divides each teaching building region, and comprises the following steps:
s1, numbering the teaching building areas in the school in sequence, wherein the numbering is 1,2, i, n;
s2, dividing each teaching building area into a plurality of classroom subareas from left to right and from bottom to top;
s3, sequentially numbering a plurality of classroom subareas, wherein the numbers of the classroom subareas are 1,2, a, j, a, m;
s4, forming a number set A of each classroom subregion in each classroom teaching building region in schooli(ai1,ai2,...,aij,...,aim)，aijAnd is shown as the number of the jth classroom subregion in the ith teaching building region in the school.
The monitoring point arrangement module is used for arranging monitoring points for all the classroom sub-areas in all the teaching building areas in the school, arranging a plurality of monitoring points at the central points of all the classroom sub-areas in all the teaching building areas in the school in an evenly distributed mode, enabling all the monitoring points to correspond to all the classroom sub-areas one by one, and sending the monitoring points of all the classroom sub-areas in all the teaching building areas in the school to the smoke component detection module;
the smoke component detection module is used for receiving the monitoring points of all the classroom sub-areas in all the classroom building areas in the school sent by the monitoring point arrangement module, detecting smoke of all the classroom sub-areas in all the classroom building areas in the school, detecting the concentration of carbon monoxide, the concentration of nitrogen dioxide, the concentration of sulfur dioxide, the concentration of hydrogen chloride and the concentration of hydrogen cyanide in main smoke components of all the classroom sub-areas, counting the concentration of all the smoke components of all the classroom sub-areas in all the classroom building areas in the school, and forming a smoke component concentration set W of all the classroom sub-areas in all the classroom building areas in the schooliR(wi1r,wi2r,...,wijr,...,wimr)，wijr is the concentration of the ith smoke component in the jth classroom subregion in the ith classroom building region in the school, and r is r1,r2,r3,r4,r5， r1,r2,r3,r4,r5Respectively representing carbon monoxide, nitrogen dioxide, sulfur dioxide, hydrogen chloride and hydrogen cyanide in main smoke components, and sending the concentration of each smoke component of each classroom subregion in each teaching building region in the school to a smoke component analysis module;
the smoke component detection module comprises a carbon monoxide concentration detection unit, a nitrogen dioxide concentration detection unit, a sulfur dioxide concentration detection unit, a hydrogen chloride concentration detection unit and a hydrogen cyanide concentration detection unit, wherein the carbon monoxide concentration detection unit is a carbon monoxide concentration sensor and is arranged at a monitoring point of each classroom subregion for detecting the carbon monoxide concentration of each classroom subregion in real time; the nitrogen dioxide concentration detection unit is a nitrogen dioxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the nitrogen dioxide concentration of each classroom subregion in real time; the sulfur dioxide concentration detection unit is a sulfur dioxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the sulfur dioxide concentration of each classroom subregion in real time; the hydrogen chloride concentration detection unit is a hydrogen chloride concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the hydrogen chloride of each classroom subregion in real time; the hydrogen cyanide concentration detection unit is a hydrogen cyanide concentration sensor, is arranged at the monitoring point of each classroom subregion, and is used for detecting the hydrogen cyanide concentration of each classroom subregion in real time, thereby realizing the real-time collection and processing and automatic monitoring of data and improving the intelligent degree.
The smoke component analysis module is used for receiving the smoke component concentration sets of all classroom sub-areas in all classroom areas in the school, which are generated by the smoke component detection module, extracting the safe concentration of carbon monoxide, the safe concentration of nitrogen dioxide, the safe concentration of sulfur dioxide, the safe concentration of hydrogen chloride and the safe concentration of hydrogen cyanide in main indoor smoke components stored in the cloud database, comparing the smoke component concentration of all classroom sub-areas in all classroom areas in the school with the corresponding safe concentration of smoke components, and obtaining the smoke component concentration contrast difference value set delta W of all classroom sub-areas in all classroom areas in the schooliR(Δwi1r,Δwi2r,...,Δwijr,...,Δwimr)，ΔwijAnd r is expressed as a contrast difference value between the concentration of the r-th smoke component of the jth classroom subregion in the ith teaching building region in the school and the corresponding safety concentration of the smoke component, reliable parameter data are provided for the smoke concentration coefficient of each classroom subregion in each classroom building region in the later-period computer school, and the contrast difference values of each smoke component concentration of each classroom subregion in each classroom building region in the school are collectively sent to the cloud server.
The cloud server is used for receiving the smoke component concentration contrast difference value sets of all classroom sub-areas in all classroom areas in the school sent by the smoke component analysis module, extracting the contrast coefficients of all main smoke components stored in the cloud database, calculating the smoke concentration coefficients of all classroom sub-areas in all classroom areas in the school, and calculating the smoke concentration coefficients of all classroom sub-areas in all classroom areas in all teaching buildings in the schoolThe smoke concentration coefficient of each classroom subregion in the region is calculated by the formula
ξijExpressed as the smoke concentration coefficient of the jth classroom subregion in the ith classroom building region in school, e is expressed as a natural number, equal to 2.718,
respectively expressed as the contrast coefficients, Δ w, of carbon monoxide, nitrogen dioxide, sulfur dioxide, hydrogen chloride and hydrogen cyanide in the main constituents of the smokeijr is the comparison difference between the concentration of the ith smoke component in the ith classroom subregion in the ith classroom building region in the school and the corresponding safe concentration of the smoke component, and r is r1,r2,r3,r4,r5，w0r is the safe concentration of the main component of the ith smoke in the room, when the smoke concentration coefficient of a classroom subarea in a classroom area in a school is larger than a set smoke concentration coefficient threshold value, the smoke concentration of the classroom subarea exceeds the standard, the number of each classroom subarea in each classroom area with the smoke concentration exceeding the standard is counted, and the number of each classroom subarea in each classroom area with the smoke concentration exceeding the standard is sent to the image acquisition module.
The image acquisition module comprises a plurality of high-definition cameras, wherein the high-definition cameras are respectively installed at monitoring points of all classroom sub-areas, correspond to all the classroom sub-areas one by one and are used for receiving numbers of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard sent by the cloud server, acquiring images of all directions in all the classroom sub-areas in all the classroom building areas with the received smoke concentration exceeding the standard by adjusting the shooting direction of the high-definition cameras, and sending all the images of all the sub-area classrooms in all the classroom building areas with the collected smoke concentration exceeding the standard to the image processing module;
the image processing module is used for receiving the images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard, which are sent by the image acquisition module, normalizing the images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard into images with consistent size and no deflection angle, performing image enhancement processing on the processed images to obtain enhanced images of all the classroom sub-areas in all the classroom areas with the smoke concentration exceeding the standard, and sending the enhanced images of all the classroom sub-areas in all the classroom areas with the smoke concentration exceeding the standard to the feature extraction module;
the characteristic extraction module is used for receiving the enhanced images of the classroom sub-areas in the teaching areas with the smoke concentration exceeding the standard, which are sent by the image processing module, extracting the characteristics of the enhanced images of the classroom sub-areas in the teaching areas with the smoke concentration exceeding the standard, extracting the characteristics of the enhanced images of the classroom sub-areas in the teaching building areas with the smoke concentration exceeding the standard, and sending the characteristics of the enhanced images of the classroom sub-areas in the teaching building areas with the smoke concentration exceeding the standard to the cloud server.
The cloud server is used for receiving the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard, extracting the standard image characteristics of the indoor fire, stored in the cloud database, comparing the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard image characteristics of the indoor fire, counting the similarity between the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard image characteristics of the indoor fire, if the similarity of the contrast of each enhanced image characteristic of a certain classroom subregion is less than or equal to a set similarity threshold, indicating that the classroom subregion has no fire, and if the similarity of the contrast of a certain enhanced image characteristic of a certain classroom subregion is greater than the set similarity threshold, indicating that the classroom subregion has fire, therefore, the problem of tragic training of a big disaster caused by small fire can be solved, the loss caused by fire is reduced, the numbers of the classroom subareas in each teaching building area in which the fire occurs are counted, and the numbers of the classroom subareas in each teaching building area in which the fire occurs are sent to the evacuation route setting module.
The evacuation route setting module is used for receiving numbers of all classroom sub-areas in all classroom building areas where the fire disaster occurs and sent by the cloud server, extracting three-dimensional models of all classroom building in schools stored in the cloud database, obtaining model positions of all classroom sub-areas in all classroom building areas where the fire disaster occurs, simultaneously extracting all fire fighting access positions in all three-dimensional models of all classroom building in schools stored in the cloud database, screening fire fighting access closest to the model positions of all classroom sub-areas in all classroom building areas where the fire disaster occurs, setting evacuation routes of all classroom sub-areas in all classroom building areas where the fire disaster occurs, and sending the evacuation routes of all classroom sub-areas in all classroom building areas where the fire disaster occurs to the alarm display terminal.
The alarm display terminal is used for receiving the evacuation routes of all classroom sub-areas in the building area where the fire disaster occurs and sending the evacuation routes to the alarm display terminal for alarm and display, and people in the classroom sub-areas and nearby people in the fire disaster evacuate according to the displayed evacuation routes, so that the problem of people evacuating in a hurry is avoided, the personnel evacuation time is reduced, and meanwhile, the fire fighters can timely give an alarm to rescue after receiving the alarm notification, so that the fire fighting efficiency of the fire fighters is improved, the fire fighting safety performance of schools is improved, and the normal teaching, working and living order of the schools is maintained.
The cloud database is used for receiving the numbers of the classroom subregions in each teaching building region in the school sent by the region division module, simultaneously storing the safe concentration of carbon monoxide, the safe concentration of nitrogen dioxide, the safe concentration of sulfur dioxide, the safe concentration of hydrogen chloride and the safe concentration of hydrogen cyanide in the main components of indoor smoke, and storing the contrast coefficients of the main components of the smoke, which are respectively recorded as
And storing the standard image characteristics of the fire in the room, and storing the three-dimensional models of the teaching buildings in the school and the positions of the fire fighting channels in the three-dimensional models.
The foregoing is merely exemplary and illustrative of the principles of the present invention and various modifications, additions and substitutions of the specific embodiments described herein may be made by those skilled in the art without departing from the principles of the present invention or exceeding the scope of the claims set forth herein.
Claims (6)
1. The utility model provides an wisdom fire control monitoring management cloud platform based on big data analysis which characterized in that: the system comprises a region dividing module, a monitoring point arrangement module, a smoke component detection module, a smoke component analysis module, an image acquisition module, an image processing module, a feature extraction module, a cloud server, an evacuation route setting module, an alarm display terminal and a cloud database;
the cloud server is respectively connected with the smoke component analysis module, the image acquisition module, the feature extraction module, the evacuation route setting module and the cloud database, the cloud database is respectively connected with the region division module, the smoke component analysis module and the evacuation route setting module, the smoke component detection module is respectively connected with the monitoring point arrangement module and the smoke component analysis module, the image processing module is respectively connected with the image acquisition module and the feature extraction module, and the evacuation route setting module is connected with the alarm display terminal;
the area dividing module is used for dividing each teaching building area of a school, dividing each teaching building area in the school into a plurality of classroom subareas according to a set sequence, numbering the classroom subareas in sequence, and sending the numbers of the classroom subareas in each teaching building area in the school to the cloud database;
the monitoring point arrangement module is used for arranging monitoring points for all the classroom sub-areas in all the teaching building areas in the school, arranging a plurality of monitoring points at the central points of all the classroom sub-areas in all the teaching building areas in the school in an evenly distributed mode, enabling all the monitoring points to correspond to all the classroom sub-areas one by one, and sending the monitoring points of all the classroom sub-areas in all the teaching building areas in the school to the smoke component detection module;
the smoke component detection module is used for receiving all the smoke components in the school sent by the monitoring point arrangement moduleMonitoring points of all classroom subareas in each classroom building area in the school are used for detecting smoke of all classroom subareas in each classroom building area in the school, detecting the concentration of carbon monoxide, the concentration of nitrogen dioxide, the concentration of sulfur dioxide, the concentration of hydrogen chloride and the concentration of hydrogen cyanide in main components of smoke of all classroom subareas, counting the concentration of all smoke components of all classroom subareas in each classroom building area in the school, and forming a smoke component concentration set W of all classroom subareas in all classroom building areas in the schooliR(wi1r,wi2r,...,wijr,...,wimr)，wijr is the concentration of the ith smoke component in the jth classroom subregion in the ith classroom building region in the school, and r is r1,r2,r3,r4,r5，r1,r2,r3,r4,r5Respectively representing carbon monoxide, nitrogen dioxide, sulfur dioxide, hydrogen chloride and hydrogen cyanide in main smoke components, and sending the concentration of each smoke component of each classroom subregion in each teaching building region in the school to a smoke component analysis module;
the smoke component analysis module is used for receiving the smoke component concentration sets of all classroom sub-areas in all classroom areas in the school, which are generated by the smoke component detection module, extracting the safe concentration of carbon monoxide, the safe concentration of nitrogen dioxide, the safe concentration of sulfur dioxide, the safe concentration of hydrogen chloride and the safe concentration of hydrogen cyanide in main indoor smoke components stored in the cloud database, comparing the smoke component concentration of all classroom sub-areas in all classroom areas in the school with the corresponding safe concentration of smoke components, and obtaining the smoke component concentration contrast difference value set delta W of all classroom sub-areas in all classroom areas in the schooliR(Δwi1r,Δwi2r,...,Δwijr,...,Δwimr)，Δwijr is expressed as a comparison difference value between the concentration of the r-th smoke component of the jth classroom subregion in the ith teaching building region in the school and the corresponding safety concentration of the smoke component, and the comparison difference values of the concentrations of the smoke components of all the classroom subregions in all the teaching building regions in the school are sent to the cloud server in a set manner;
the cloud server is used for receiving a smoke component concentration contrast difference set of each classroom subregion in each classroom of the school, which is sent by the smoke component analysis module, extracting a contrast coefficient of each main smoke component stored in the cloud database, calculating a smoke concentration coefficient of each classroom subregion in each classroom region in the school, when the smoke concentration coefficient of a certain classroom subregion in a certain classroom region in the school is greater than a set smoke concentration coefficient threshold value, indicating that the smoke concentration of the classroom subregion exceeds the standard, counting classroom numbers of each subregion in each classroom region with the excessive smoke concentration, and sending each classroom subregion number in each classroom region with the excessive smoke concentration to the image acquisition module;
the image acquisition module is used for receiving numbers of all classroom sub-areas in all classroom building areas with the smoke concentration exceeding the standard, which are sent by the cloud server, acquiring images of all classroom sub-areas in all classroom building areas with the received smoke concentration exceeding the standard, and sending all the acquired images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard to the image processing module;
the image processing module is used for receiving the images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard, which are sent by the image acquisition module, normalizing the images of all the classroom sub-areas in all the classroom building areas with the smoke concentration exceeding the standard into images with consistent size and no deflection angle, performing image enhancement processing on the processed images to obtain enhanced images of all the classroom sub-areas in all the classroom areas with the smoke concentration exceeding the standard, and sending the enhanced images of all the classroom sub-areas in all the classroom areas with the smoke concentration exceeding the standard to the feature extraction module;
the characteristic extraction module is used for receiving the enhanced images of the classroom sub-areas in the teaching areas with the smoke concentration exceeding the standard, which are sent by the image processing module, extracting the characteristics of the enhanced images of the classroom sub-areas in the teaching areas with the smoke concentration exceeding the standard, extracting the characteristics of the enhanced images of the classroom sub-areas in the teaching building areas with the smoke concentration exceeding the standard, and sending the characteristics of the enhanced images of the classroom sub-areas in the teaching building areas with the smoke concentration exceeding the standard to the cloud server;
the cloud server is used for receiving the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard, extracting the standard image characteristics of the indoor fire, stored in the cloud database, comparing the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard image characteristics of the indoor fire, counting the similarity between the enhanced image characteristics of each classroom subregion in which the smoke concentration exceeds the standard image characteristics of the indoor fire, if the similarity of the contrast of each enhanced image characteristic of a certain classroom subregion is less than or equal to a set similarity threshold, indicating that the classroom subregion has no fire, and if the similarity of the contrast of a certain enhanced image characteristic of a certain classroom subregion is greater than the set similarity threshold, indicating that the classroom subregion has fire, counting numbers of all classroom subareas in each teaching building area with the fire, and sending the numbers of all classroom subareas in each teaching building area with the fire to an evacuation route setting module;
the evacuation route setting module is used for receiving numbers of all classroom sub-areas in all classroom building areas where the fire disaster occurs, which are sent by the cloud server, extracting three-dimensional models of all classroom building in the school, which are stored in the cloud database, obtaining model positions of all classroom sub-areas in all classroom building areas where the fire disaster occurs, simultaneously extracting all fire fighting channel positions in all three-dimensional models of all classroom building in the school, which are stored in the cloud database, screening the fire fighting channel closest to the model position of each classroom sub-area in all classroom building areas where the fire disaster occurs, setting evacuation routes of all classroom sub-areas in all classroom building areas where the fire disaster occurs, and sending the evacuation routes of all classroom sub-areas in all classroom building areas where the fire disaster occurs to the alarm display terminal;
the alarm display terminal is used for receiving the evacuation routes of all classroom sub-areas in the building area where the fire breaks out and sent by the evacuation route setting module, alarming and displaying, evacuating the personnel in and near the classroom sub-areas where the fire breaks out according to the displayed evacuation routes, and simultaneously giving an alarm to rescue timely fire fighters after receiving the alarm notification;
the cloud database is used for receiving the numbers of the classroom subregions in each teaching building region in the school sent by the region division module, simultaneously storing the safe concentration of carbon monoxide, the safe concentration of nitrogen dioxide, the safe concentration of sulfur dioxide, the safe concentration of hydrogen chloride and the safe concentration of hydrogen cyanide in the main components of indoor smoke, and storing the contrast coefficients of the main components of the smoke, which are respectively recorded as
And storing the standard image characteristics of the fire in the room, and storing the three-dimensional models of the teaching buildings in the school and the positions of the fire fighting channels in the three-dimensional models.
2. The intelligent fire-fighting monitoring management cloud platform based on big data analysis of claim 1, characterized in that: the region division module divides each teaching building region, and comprises the following steps:
s1, numbering the teaching building areas in the school in sequence, wherein the numbering is 1,2, i, n;
s2, dividing each teaching building area into a plurality of classroom subareas from left to right and from bottom to top;
s3, sequentially numbering a plurality of classroom subareas, wherein the numbers of the classroom subareas are 1,2, a, j, a, m;
s4, forming a number set A of each classroom subregion in each classroom teaching building region in schooli(ai1,ai2,...,aij,...,aim)，aijAnd is shown as the number of the jth classroom subregion in the ith teaching building region in the school.
3. The intelligent fire-fighting monitoring management cloud platform based on big data analysis of claim 1, characterized in that: the smoke component detection module comprises a carbon monoxide concentration detection unit, a nitrogen dioxide concentration detection unit, a sulfur dioxide concentration detection unit, a hydrogen chloride concentration detection unit and a hydrogen cyanide concentration detection unit.
4. The intelligent fire-fighting monitoring management cloud platform based on big data analysis of claim 2, characterized in that: the carbon monoxide concentration detection unit is a carbon monoxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the carbon monoxide concentration of each classroom subregion in real time; the nitrogen dioxide concentration detection unit is a nitrogen dioxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the nitrogen dioxide concentration of each classroom subregion in real time; the sulfur dioxide concentration detection unit is a sulfur dioxide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the sulfur dioxide concentration of each classroom subregion in real time; the hydrogen chloride concentration detection unit is a hydrogen chloride concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the hydrogen chloride of each classroom subregion in real time; the hydrogen cyanide concentration detection unit is a hydrogen cyanide concentration sensor, is arranged at a monitoring point of each classroom subregion, and is used for detecting the hydrogen cyanide concentration of each classroom subregion in real time.
5. The intelligent fire-fighting monitoring management cloud platform based on big data analysis of claim 1, characterized in that: the smoke concentration coefficient calculation formula of each classroom subregion in each teaching building region in the school is
ξijExpressed as the smoke concentration coefficient of the jth classroom subregion in the ith classroom building region in school, e is expressed as a natural number, equal to 2.718,
respectively expressed as the contrast coefficients, Δ w, of carbon monoxide, nitrogen dioxide, sulfur dioxide, hydrogen chloride and hydrogen cyanide in the main constituents of the smokeijr is expressed asThe comparison difference between the concentration of the r-th smoke component of the jth classroom subregion in the ith school teaching building region and the corresponding safe concentration of the smoke component, wherein r is r1,r2,r3,r4,r5，w0r is expressed as the safe concentration of the r-th major smoke component in the room.
6. The intelligent fire-fighting monitoring management cloud platform based on big data analysis of claim 1, characterized in that: the image acquisition module comprises a plurality of high-definition cameras, wherein the high-definition cameras are respectively installed at monitoring points of all classroom sub-areas, the high-definition cameras correspond to the classroom sub-areas one to one, and images of all directions in all classroom sub-areas in the smog concentration exceeding the standard are acquired by adjusting the shooting directions of the high-definition cameras.
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| CN113225526A (en) * | 2021-04-01 | 2021-08-06 | 北京戴纳实验科技有限公司 | Laboratory smoke monitoring method and system |
| CN113225526B (en) * | 2021-04-01 | 2022-07-08 | 北京戴纳实验科技有限公司 | Laboratory smoke monitoring method and system |
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