CN114913638B - Fire control access control management method and system based on Internet - Google Patents
Fire control access control management method and system based on Internet Download PDFInfo
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- CN114913638B CN114913638B CN202210367438.8A CN202210367438A CN114913638B CN 114913638 B CN114913638 B CN 114913638B CN 202210367438 A CN202210367438 A CN 202210367438A CN 114913638 B CN114913638 B CN 114913638B
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- 238000007726 management method Methods 0.000 title abstract description 19
- 238000012544 monitoring process Methods 0.000 claims abstract description 33
- 238000004891 communication Methods 0.000 claims abstract description 16
- 239000000779 smoke Substances 0.000 claims abstract description 15
- 239000002245 particle Substances 0.000 claims abstract description 9
- 230000008030 elimination Effects 0.000 claims description 14
- 238000003379 elimination reaction Methods 0.000 claims description 14
- 238000001514 detection method Methods 0.000 claims description 12
- 238000000605 extraction Methods 0.000 claims description 12
- 238000001914 filtration Methods 0.000 claims description 12
- 238000007781 pre-processing Methods 0.000 claims description 12
- 239000013598 vector Substances 0.000 claims description 8
- 230000009466 transformation Effects 0.000 claims description 6
- 238000000034 method Methods 0.000 claims description 4
- 238000004364 calculation method Methods 0.000 claims description 3
- 238000005286 illumination Methods 0.000 claims description 3
- 230000001788 irregular Effects 0.000 claims description 3
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000012545 processing Methods 0.000 claims description 3
- 238000012360 testing method Methods 0.000 claims description 3
- 230000002457 bidirectional effect Effects 0.000 claims 1
- 239000000203 mixture Substances 0.000 claims 1
- 230000003111 delayed effect Effects 0.000 abstract description 3
- 238000005516 engineering process Methods 0.000 description 6
- 230000000694 effects Effects 0.000 description 4
- 238000003708 edge detection Methods 0.000 description 2
- 210000000720 eyelash Anatomy 0.000 description 2
- 210000000744 eyelid Anatomy 0.000 description 2
- 230000001603 reducing effect Effects 0.000 description 2
- 238000004904 shortening Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000007123 defense Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
- 230000003245 working effect Effects 0.000 description 1
Classifications
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- G—PHYSICS
- G07—CHECKING-DEVICES
- G07C—TIME OR ATTENDANCE REGISTERS; REGISTERING OR INDICATING THE WORKING OF MACHINES; GENERATING RANDOM NUMBERS; VOTING OR LOTTERY APPARATUS; ARRANGEMENTS, SYSTEMS OR APPARATUS FOR CHECKING NOT PROVIDED FOR ELSEWHERE
- G07C9/00—Individual registration on entry or exit
- G07C9/30—Individual registration on entry or exit not involving the use of a pass
- G07C9/32—Individual registration on entry or exit not involving the use of a pass in combination with an identity check
- G07C9/37—Individual registration on entry or exit not involving the use of a pass in combination with an identity check using biometric data, e.g. fingerprints, iris scans or voice recognition
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/22—Matching criteria, e.g. proximity measures
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- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B17/00—Fire alarms; Alarms responsive to explosion
- G08B17/10—Actuation by presence of smoke or gases, e.g. automatic alarm devices for analysing flowing fluid materials by the use of optical means
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B25/00—Alarm systems in which the location of the alarm condition is signalled to a central station, e.g. fire or police telegraphic systems
- G08B25/009—Signalling of the alarm condition to a substation whose identity is signalled to a central station, e.g. relaying alarm signals in order to extend communication range
-
- G—PHYSICS
- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
- G08B27/00—Alarm systems in which the alarm condition is signalled from a central station to a plurality of substations
- G08B27/001—Signalling to an emergency team, e.g. firemen
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J9/00—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting
- H02J9/04—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source
- H02J9/06—Circuit arrangements for emergency or stand-by power supply, e.g. for emergency lighting in which the distribution system is disconnected from the normal source and connected to a standby source with automatic change-over, e.g. UPS systems
- H02J9/068—Electronic means for switching from one power supply to another power supply, e.g. to avoid parallel connection
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Abstract
The invention discloses a fire control access control management method and a fire control access control management system based on the Internet, which belong to the technical field of access control management, wherein a monitoring unit is used for identifying a human body, detecting indoor gas concentration in real time, sensing indoor particle smoke concentration and sensing indoor temperature in real time, an alarm unit is used for positioning geographic position data of a fire condition, then automatically identifying and positioning the security and protection geographic position, and preferentially selecting the nearest security and protection point from the fire condition place, acquiring fire condition place information and security and protection place information acquired by a security and protection place acquisition module to integrate to form a single data packet, acquiring communication information of the security and protection point to carry out emergency call, and carrying out emergency treatment on the fire condition effectively in an automatic monitoring and alarming mode, so that delay rescue time is avoided, meanwhile, the situation that security and protection personnel are not easy to be delayed to enter rescue work due to damage of a main power supply line of the access control is avoided, the emergency evacuation time is shortened, and property loss is reduced.
Description
Technical Field
The invention belongs to the technical field of access control management, and particularly relates to a fire control access control management method and system based on the Internet.
Background
The door control system is in the intelligent building field, is Access Control System, is abbreviated as ACS, refers to the forbidden authority of the door, and is used for preventing the door from being prepared, wherein the door in the broad sense comprises various passages capable of passing, including a door capable of passing by people, a door capable of passing by vehicles and the like, so that the door control comprises the vehicle door control. In the application of parking lot management, the entrance guard of vehicles is an important means for vehicle management, and is not aimed at collecting parking fees, but mainly for managing the access rights of vehicles, and the entrance guard safety management system is a novel modern safety management system, which integrates microcomputer automatic identification technology and modern safety management measures into a whole, and relates to a plurality of novel technologies such as electronics, machinery, optics, computer technology, communication technology, biotechnology and the like.
At present, in the fire control access control management application based on the internet, a plurality of identification modes are generally used for verifying the identity of an access person, and the conventional verification modes comprise face recognition, key identification and fingerprint identification modes, but in the application of various fields such as security protection, national defense, electronic commerce and the like, iris identification technology is usually used as an important point, but some factors influencing the iris identification effect are not overcome well, such as deformation of iris images, eyelid and interference of eyelash noise; when a fire occurs in a building, after the main power supply circuit of the access control is damaged and the condition of cutoff occurs, the access control cannot be opened in time, emergency evacuation of personnel is affected, security personnel are delayed to enter rescue work, larger property loss is generated, and certain potential safety hazard exists, so that the problem is solved by the fire control access control management method and system based on the Internet.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides a fire control access control management method and a fire control access control management system based on the Internet, which solve the problems that the iris recognition technology is usually used as the focus, but some factors affecting the iris recognition effect are not overcome well, such as deformation of iris images, eyelid and interference of eyelash noise; when a fire occurs in a building, after the main power supply circuit of the access control is damaged and the condition of cutoff occurs, the access control cannot be opened in time, emergency evacuation of people is affected, security personnel are delayed to enter rescue work, larger property loss is generated, and the problem of certain potential safety hazard is solved.
In order to achieve the above purpose, the present invention provides the following technical solutions: the utility model provides a fire control entrance guard management system based on internet, includes the monitor cell, monitor cell's output is connected with entrance guard's main control panel's input, entrance guard's main control panel's output is connected with alarm unit's input, entrance guard's main control panel's input is connected with power supply unit's output, power supply unit and power supply monitoring module both-way connection, power supply monitoring module's output is connected with entrance guard's main control panel and switch drive module's input, switch drive module's output is connected with entrance guard's main control panel's input.
The entrance guard main control panel comprises a face recognition module, a fingerprint recognition module, a secret key recognition module and an iris recognition module, wherein the iris recognition module comprises an iris image preprocessing module, the output end of the iris image preprocessing module is connected with the input end of the characteristic point extraction module, the output end of the characteristic point extraction module is connected with the input end of the noise elimination module, and the output end of the noise elimination module is connected with the input end of the characteristic matching module.
The power supply monitoring module is used for monitoring a parallel circuit between the standby power supply module and the main power supply module in real time, automatically identifying an electric brake instruction for starting the standby power supply module if the power is off between the main power supply module and the access control panel, and automatically identifying an electric brake instruction for stopping the standby power supply module if the power is on between the main power supply module and the access control panel.
As a further aspect of the invention: the monitoring unit comprises an infrared detection module, a gas concentration detection module, a smoke sensing module and a temperature sensing module, and is specifically arranged inside each building.
The infrared detection module is an infrared detector for identifying a human body.
The gas concentration detection module is used for detecting the indoor gas concentration in real time.
The smoke sensing module is used for sensing the concentration of indoor particle smoke.
The temperature sensing module is used for sensing indoor temperature in real time.
As a further aspect of the invention: the alarm unit comprises a positioning module, a security place acquisition module and a security communication module.
The positioning module is used for: and the geographic position data is used for positioning the occurrence of fire.
The security place acquisition module is used for: the security geographic position is automatically identified and positioned, and the nearest security point from the place where the fire occurs is preferentially selected.
The security communication module is as follows: the system is used for integrating the fire place information acquired by the positioning module and the security place information acquired by the security place acquisition module to form a single data packet, and acquiring the communication information of the security points to make an emergency call.
As a further aspect of the invention: the power supply unit comprises a main power supply module and a standby power supply module.
The main power supply module comprises a main power generator and is used for directly supplying power to the access control main control panel.
The standby power supply module comprises a standby power supply generator, and the standby power supply module and the main power supply module are connected in parallel and store electric quantity through external commercial power.
As a further aspect of the invention: the switch driving module is used for acquiring a switch opening and closing instruction of the standby power supply module and automatically controlling the switch opening and closing of the standby power supply module.
As a further aspect of the invention: the specific implementation steps of the iris recognition module are as follows:
s1, firstly, preprocessing an obtained iris image through an iris image preprocessing module, extracting texture edges with obvious gray level changes in the horizontal and vertical directions in the iris image, ignoring partial weak textures which are easy to be influenced by illumination, and generating a direction energy characteristic template.
S101, firstly, positioning an image by adopting a Hough transformation algorithm, and normalizing the image by adopting a polar coordinate transformation algorithm of J.daugman, wherein the normalized image comprises ridges, spots and irregular blocks.
S102, filtering an image by designing a horizontal filtering operator and a vertical filtering operator, detecting texture edges of an iris image in two directions, and specifically comprising the following steps:
s103, filtering the iris image through a horizontal filter operator and a vertical filter operator, extracting texture edges with obvious gray level change, and obtaining differences between a horizontal-direction image convolution result and a vertical-direction convolution filter result, wherein an image formed by the differences is a direction energy feature map of the whole iris.
S2, after the directional energy feature map of the iris is obtained, extracting any multiple effective feature points in the feature map through a feature point extraction module, dividing the directional energy feature map of the iris into M multiplied by N blocks, wherein each block is 90/M multiplied by 360/N, each sub-block is marked as Imn (x, y), taking the point with the largest absolute value of each block as the effective feature point, and specifically extracting the effective feature points as follows:let Hkh (x, y) =argmax (Imn), k=90/M, h=360/N, and Hkh (x, y) constitute a new feature template of 30×60 size, as follows: />
S3, performing interference elimination processing on the preprocessed image through a noise elimination module, expanding the image, wherein the formula of image expansion is as follows:。
e is an image to be expanded, B is a structural element, B (Y) is obtained after the structural element B is translated by Y, if B (Y) is intersected with E and is not empty, the Y point is recorded, all the set Y formed by the Y points is called as the result that E is expanded by B, and the structural element B is designed into an identity matrix with the single size of 1.5 times that of a feature extraction operator, so that the denoising purpose can be achieved.
S4, extracting a characteristic template to be a binary characteristic, and performing matching operation by using a Hamming distance formula, wherein the Hamming distance is used as an index for distinguishing among iris tired internal classes, and the Hamming distance formula is as follows:amask and Bmask are noise templates of the test image and the registration image respectively, a noise area is set to 0 during calculation, and effective area sets 1, ai and Bi are feature vectors of the iris to be identified and feature vectors of the iris in the registration set respectively.
A fire control access control management method based on the Internet comprises the following steps:
a. firstly, the monitoring unit is used for identifying a human body, detecting the indoor gas concentration in real time, sensing the concentration of indoor particle smoke and sensing the indoor temperature in real time.
b. And secondly, positioning the geographical position data of the fire through an alarm unit, automatically identifying and positioning the security and protection geographical position, preferentially selecting the nearest security and protection point from the fire place, integrating the fire place information with the security and protection place information acquired by the security and protection place acquisition module to form a single data packet, and acquiring the communication information of the security and protection point to make an emergency call.
c. The parallel circuit between the standby power supply module and the main power supply module is monitored in real time through the power supply monitoring module, if the power is off between the main power supply module and the access master control panel, the switch instruction for starting the standby power supply module is automatically identified, and if the power is on between the main power supply module and the access master control panel, the switch instruction for stopping the standby power supply module is automatically identified.
d. And secondly, the switch driving module acquires a switch opening and closing instruction of the standby power supply module and automatically controls the switch opening and closing of the standby power supply module.
e. When the identity is verified through the access control system, the identity is verified through face recognition, fingerprint recognition, key recognition or iris recognition.
Compared with the prior art, the invention has the beneficial effects that:
according to the invention, the monitoring unit is used for identifying a human body, detecting indoor gas concentration in real time, sensing indoor particle smoke concentration and sensing indoor temperature in real time, positioning geographical position data of a fire situation through the alarm unit, automatically identifying and positioning the geographical position of the fire situation, preferentially selecting the nearest security point away from the fire situation, acquiring fire situation information and security place information acquired by the security place acquisition module, integrating the fire situation information and the security place information to form a single data packet, acquiring communication information of the security point for emergency call, and the power supply monitoring module is used for monitoring a parallel circuit between the standby power supply module and the main power supply module in real time, automatically identifying a switch instruction for starting the standby power supply module if the main power supply module is powered off from the entrance guard main control panel, automatically identifying the switch instruction for closing the standby power supply module if the main power supply module is powered on from the entrance guard main control panel, and effectively carrying out emergency treatment on the fire situation in an alarm mode through automatic monitoring, avoiding delay rescue time, simultaneously avoiding that a main power supply circuit of an entrance guard is damaged and cannot be opened in time, shortening emergency rescue personnel from entering work, and reducing property loss;
according to the invention, the edge operator is used for edge detection of the iris image in the horizontal and vertical directions, the direction energy difference of the iris texture is extracted as the characteristic, the expansion noise template is used for interference elimination, the characteristic vector generated by the Hamming distance matching method is small, the matching speed is high, the anti-interference capability is strong, the noise interference of iris recognition is effectively overcome, and the iris recognition effect is further improved.
Drawings
Fig. 1 is a schematic block diagram of the system of the present invention.
Detailed Description
The technical scheme of the patent is further described in detail below with reference to the specific embodiments.
As shown in the figure, the invention provides a technical scheme that: the utility model provides a fire control entrance guard management system based on internet, includes the monitor cell, the output of monitor cell is connected with the input of access control master control panel, the output of access control master control panel is connected with alarm unit's input, access control master control panel's input is connected with power supply unit's output, power supply unit and power supply monitoring module both way junction, power supply monitoring module's output is connected with the input of access control master control panel and switch drive module, switch drive module's output is connected with the input of access control master control panel.
The entrance guard main control panel comprises a face recognition module, a fingerprint recognition module, a secret key recognition module and an iris recognition module, wherein the iris recognition module comprises an iris image preprocessing module, the output end of the iris image preprocessing module is connected with the input end of the characteristic point extraction module, the output end of the characteristic point extraction module is connected with the input end of the noise elimination module, and the output end of the noise elimination module is connected with the input end of the characteristic matching module.
The monitoring unit comprises an infrared detection module, a gas concentration detection module, a smoke sensing module and a temperature sensing module, and is specifically arranged inside each building.
The infrared detection module is an infrared detector for identifying a human body.
The gas concentration detection module is used for detecting the indoor gas concentration in real time.
The smoke sensing module is used for sensing the concentration of indoor particle smoke.
The temperature sensing module is used for sensing indoor temperature in real time.
The alarm unit comprises a positioning module, a security place acquisition module and a security communication module.
And a positioning module: and the geographic position data is used for positioning the occurrence of fire.
The security site acquisition module is used for: the security geographic position is automatically identified and positioned, and the nearest security point from the place where the fire occurs is preferentially selected.
And the security communication module is used for: the system is used for integrating the fire place information acquired by the positioning module and the security place information acquired by the security place acquisition module to form a single data packet, and acquiring the communication information of the security points to make an emergency call.
The power supply unit comprises a main power supply module and a standby power supply module.
The main power supply module comprises a main power generator and is used for directly supplying power to the access control main control panel.
The standby power supply module comprises a standby power supply generator, and the standby power supply module and the main power supply module are connected in parallel and store electric quantity through external commercial power.
The power supply monitoring module is used for monitoring a parallel circuit between the standby power supply module and the main power supply module in real time, automatically identifying an electric brake instruction for starting the standby power supply module if the power is off between the main power supply module and the access master control panel, and automatically identifying an electric brake instruction for stopping the standby power supply module if the power is on between the main power supply module and the access master control panel.
The electric brake driving module is used for acquiring an electric brake opening and closing instruction of the standby power supply module and automatically controlling the opening and closing of the electric brake of the standby power supply module.
The specific implementation steps of the iris recognition module are as follows:
s1, firstly, preprocessing an obtained iris image through an iris image preprocessing module, extracting texture edges with obvious gray level changes in the horizontal and vertical directions in the iris image, ignoring partial weak textures which are easy to be influenced by illumination, and generating a direction energy characteristic template.
S101, firstly, positioning an image by adopting a Hough transformation algorithm, and normalizing the image by adopting a polar coordinate transformation algorithm of J.daugman, wherein the normalized image comprises ridges, spots and irregular blocks.
S102, filtering an image by designing a horizontal filtering operator and a vertical filtering operator, detecting texture edges of an iris image in two directions, and specifically comprising the following steps:
s103, filtering the iris image through a horizontal filter operator and a vertical filter operator, extracting texture edges with obvious gray level change, and obtaining differences between a horizontal-direction image convolution result and a vertical-direction convolution filter result, wherein an image formed by the differences is a direction energy feature map of the whole iris.
S2, after the directional energy feature map of the iris is obtained, extracting any multiple effective feature points in the feature map through a feature point extraction module, dividing the directional energy feature map of the iris into M multiplied by N blocks, wherein each block is 90/M multiplied by 360/N, each sub-block is marked as Imn (x, y), taking the point with the largest absolute value of each block as the effective feature point, and specifically extracting the effective feature points as follows:let Hkh (x, y) =argmax (Imn), k=90/M, h=360/N, and Hkh (x, y) constitute a new feature template of 30×60 size, as follows: />
S3, performing interference elimination processing on the preprocessed image through a noise elimination module, expanding the image, wherein the formula of image expansion is as follows:
e is an image to be expanded, B is a structural element, B (Y) is obtained after the structural element B is translated by Y, if B (Y) is intersected with E and is not empty, the Y point is recorded, all the set Y formed by the Y points is called as the result that E is expanded by B, and the structural element B is designed into an identity matrix with the single size of 1.5 times that of a feature extraction operator, so that the denoising purpose can be achieved.
S4, extracting a characteristic template to be a binary characteristic, and performing matching operation by using a Hamming distance formula, wherein the Hamming distance is used as an index for distinguishing among iris tired internal classes, and the Hamming distance formula is as follows:
amask and Bmask are noise templates of the test image and the registration image respectively, a noise area is set to 0 during calculation, and effective area sets 1, ai and Bi are feature vectors of the iris to be identified and feature vectors of the iris in the registration set respectively.
A fire control access control management method based on the Internet comprises the following steps:
a. firstly, the monitoring unit is used for identifying a human body, detecting the indoor gas concentration in real time, sensing the concentration of indoor particle smoke and sensing the indoor temperature in real time.
b. And secondly, positioning the geographical position data of the fire through an alarm unit, automatically identifying and positioning the security and protection geographical position, preferentially selecting the nearest security and protection point from the fire place, integrating the fire place information with the security and protection place information acquired by the security and protection place acquisition module to form a single data packet, and acquiring the communication information of the security and protection point to make an emergency call.
c. The parallel circuit between the standby power supply module and the main power supply module is monitored in real time through the power supply monitoring module, if the power is off between the main power supply module and the access master control panel, the switch instruction for starting the standby power supply module is automatically identified, and if the power is on between the main power supply module and the access master control panel, the switch instruction for stopping the standby power supply module is automatically identified.
d. And secondly, the switch driving module acquires a switch opening and closing instruction of the standby power supply module and automatically controls the switch opening and closing of the standby power supply module.
e. When the identity is verified through the access control system, the identity is verified through face recognition, fingerprint recognition, key recognition or iris recognition.
The method comprises the following steps:
the monitoring unit is used for identifying a human body, detecting indoor gas concentration in real time, sensing indoor particle smoke concentration and sensing indoor temperature in real time, positioning geographical position data of a fire through the alarm unit, automatically identifying and positioning the geographical position of the fire, preferentially selecting the nearest security point away from the fire, acquiring fire point information and security point information acquired by the security point acquisition module to integrate to form a single data packet, acquiring communication information of the security point to carry out emergency call, the power supply monitoring module is used for carrying out real-time monitoring on a parallel circuit between the standby power supply module and the main power supply module, automatically identifying and starting an electric brake instruction of the standby power supply module if the main power supply module is powered off from an entrance guard main control panel, automatically identifying and closing the electric brake instruction of the standby power supply module if the main power supply module is powered on from the entrance guard main control panel, effectively carrying out emergency treatment on the fire in an automatic monitoring and alarming mode, avoiding delay rescue time, simultaneously avoiding that an entrance guard cannot be opened in time due to the occurrence of damage of a main power supply circuit, shortening emergency evacuation time, and reducing property loss.
The edge operator is used for edge detection of the iris image in the horizontal direction and the vertical direction, the direction energy difference of the iris texture is extracted as the characteristic, the expansion noise template is used for interference elimination, the characteristic vector generated by the Hamming distance matching method is small, the matching speed is high, the anti-interference capability is high, the noise interference of iris recognition is effectively overcome, and the iris recognition effect is further improved.
While the preferred embodiments of the present patent have been described in detail, the present patent is not limited to the above embodiments, and various changes may be made without departing from the spirit of the present patent within the knowledge of one of ordinary skill in the art.
Claims (6)
1. The utility model provides a fire control entrance guard management system based on internet, includes the monitoring unit, its characterized in that: the output end of the monitoring unit is connected with the input end of the entrance guard main control panel, the output end of the entrance guard main control panel is connected with the input end of the alarm unit, the input end of the entrance guard main control panel is connected with the output end of the power supply unit, the power supply unit is in bidirectional connection with the power supply monitoring module, the output end of the power supply monitoring module is connected with the input ends of the entrance guard main control panel and the electric brake driving module, and the output end of the electric brake driving module is connected with the input end of the entrance guard main control panel;
the entrance guard main control panel comprises a face recognition module, a fingerprint recognition module, a secret key recognition module and an iris recognition module, wherein the iris recognition module comprises an iris image preprocessing module, the output end of the iris image preprocessing module is connected with the input end of a characteristic point extraction module, the output end of the characteristic point extraction module is connected with the input end of a noise elimination module, and the output end of the noise elimination module is connected with the input end of a characteristic matching module;
the power supply unit comprises a main power supply module and a standby power supply module, the power supply monitoring module is used for monitoring a parallel circuit between the standby power supply module and the main power supply module in real time, automatically identifying an electric brake instruction for starting the standby power supply module if the power between the main power supply module and the access master control panel is off, and automatically identifying an electric brake instruction for stopping the standby power supply module if the power between the main power supply module and the access master control panel is on;
the specific implementation steps of the iris recognition module are as follows:
s1, preprocessing an obtained iris image through an iris image preprocessing module, extracting texture edges with obvious gray level changes in the horizontal and vertical directions in the iris image, ignoring partial weak textures which are easy to be influenced by illumination, and generating a direction energy characteristic template;
s101, firstly, positioning an image by adopting a Hough transformation algorithm, normalizing the image by adopting a polar coordinate transformation algorithm of J.daugman, wherein the normalized image comprises ridges, spots and irregular blocks;
s102, filtering an image by designing a horizontal filtering operator and a vertical filtering operator, detecting texture edges of an iris image in two directions, and specifically comprising the following steps:
s103, filtering the iris image through a horizontal filter operator and a vertical filter operator, extracting texture edges with obvious gray level change, and obtaining differences between a convolution result of the image in the horizontal direction and a convolution filter result in the vertical direction, wherein an image formed by the differences is a directional energy feature map of the whole iris;
s2, after the directional energy feature map of the iris is obtained, extracting any multiple effective feature points in the feature map through a feature point extraction module, dividing the directional energy feature map of the iris into M multiplied by N blocks, wherein each block is 90/M multiplied by 360/N, each sub-block is marked as Imn (x, y), taking the point with the largest absolute value of each block as the effective feature point, and specifically extracting the effective feature points as follows:
let Hkh (x, y) =argmax (Imn), k=90/M, h=360/N, and Hkh (x, y) constitute a new feature template of 30×60 size, as follows: />S3, performing interference elimination processing on the preprocessed image through a noise elimination module, expanding the image, wherein the formula of image expansion is as follows: />Wherein E is an image to be expanded, B is a structural element, B (Y) is obtained by translating the structural element B by Y, if B (Y) is intersected with E and is not empty, the Y point is recorded, and all the sets Y which meet the composition of the Y points are calledAs a result of E being expanded by B, the structural element B is designed into a single identity matrix with the size of 1.5 times that of the feature extraction operator, so that the denoising purpose can be achieved;
s4, extracting a characteristic template to be a binary characteristic, and performing matching operation by using a Hamming distance formula, wherein the Hamming distance is used as an index for distinguishing among iris tired internal classes, and the Hamming distance formula is as follows:amask and Bmask are noise templates of the test image and the registration image respectively, a noise area is set to 0 during calculation, and effective area sets 1, ai and Bi are feature vectors of the iris to be identified and feature vectors of the iris in the registration set respectively.
2. The internet-based fire access control management system of claim 1, wherein: the monitoring unit comprises an infrared detection module, a gas concentration detection module, a smoke sensing module and a temperature sensing module, and is specifically arranged in each building;
the infrared detection module is an infrared detector for identifying a human body;
the gas concentration detection module is used for detecting the indoor gas concentration in real time;
the smoke sensing module is used for sensing the concentration of indoor particle smoke;
the temperature sensing module is used for sensing indoor temperature in real time.
3. The internet-based fire access control management system of claim 1, wherein: the alarm unit comprises a positioning module, a security place acquisition module and a security communication module;
the positioning module is used for: geographic position data for locating a fire occurrence;
the security place acquisition module is used for: automatically identifying and positioning the security geographic position, and preferentially selecting the nearest security point from the place where the fire occurs;
the security communication module is as follows: the system is used for integrating the fire place information acquired by the positioning module and the security place information acquired by the security place acquisition module to form a single data packet, and acquiring the communication information of the security points to make an emergency call.
4. The internet-based fire access control management system of claim 1, wherein: the main power supply module comprises a main power generator and is used for directly supplying power to the access control main control panel;
the standby power supply module comprises a standby power supply generator, and the standby power supply module and the main power supply module are connected in parallel and store electric quantity through external commercial power.
5. The internet-based fire access control management system of claim 1, wherein: the switch driving module is used for acquiring a switch opening and closing instruction of the standby power supply module and automatically controlling the switch opening and closing of the standby power supply module.
6. An internet-based fire control access control method, according to any one of claims 1-5, characterized by comprising the following steps:
a. firstly, identifying a human body, detecting indoor gas concentration in real time, sensing indoor particle smoke concentration and sensing indoor temperature in real time through a monitoring unit;
b. secondly, positioning the geographical position data of the fire through an alarm unit, automatically identifying and positioning the security and protection geographical position, preferentially selecting the nearest security and protection point from the fire place, acquiring the fire place information and the security and protection place information acquired by a security and protection place acquisition module, integrating to form a single data packet, and acquiring the communication information of the security and protection point to make an emergency call;
c. the parallel circuit between the standby power supply module and the main power supply module is monitored in real time through the power supply monitoring module, if the power is off between the main power supply module and the access master control panel, the switch instruction for starting the standby power supply module is automatically identified, and if the power is on between the main power supply module and the access master control panel, the switch instruction for stopping the standby power supply module is automatically identified;
d. secondly, the switch driving module acquires a switch opening and closing instruction of the standby power supply module and automatically controls the switch opening and closing of the standby power supply module;
e. when the identity is verified through the access control system, the identity is verified through face recognition, fingerprint recognition, key recognition or iris recognition.
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