CN108806155B - Security monitoring method based on Internet of things - Google Patents

Security monitoring method based on Internet of things Download PDF

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Publication number
CN108806155B
CN108806155B CN201810701562.7A CN201810701562A CN108806155B CN 108806155 B CN108806155 B CN 108806155B CN 201810701562 A CN201810701562 A CN 201810701562A CN 108806155 B CN108806155 B CN 108806155B
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personnel
unauthenticated
sound
person
playing
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CN108806155A (en
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余洪科
余忠保
刘秋
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Renhuai City Yun Xia Network Technology Co Ltd
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Renhuai City Yun Xia Network Technology Co Ltd
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    • GPHYSICS
    • G08SIGNALLING
    • G08BSIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
    • G08B15/00Identifying, scaring or incapacitating burglars, thieves or intruders, e.g. by explosives
    • G08B15/002Identifying, scaring or incapacitating burglars, thieves or intruders, e.g. by explosives with occupancy simulation
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06KRECOGNITION OF DATA; PRESENTATION OF DATA; RECORD CARRIERS; HANDLING RECORD CARRIERS
    • G06K9/00Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
    • G06K9/00221Acquiring or recognising human faces, facial parts, facial sketches, facial expressions
    • G06K9/00228Detection; Localisation; Normalisation
    • G06K9/00255Detection; Localisation; Normalisation using acquisition arrangements
    • GPHYSICS
    • G07CHECKING-DEVICES
    • G07CTIME 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
    • G07C9/00Individual registration on entry or exit
    • G07C9/30Individual registration on entry or exit not involving the use of a pass
    • G07C9/32Individual registration on entry or exit not involving the use of a pass in combination with an identity check
    • G07C9/37Individual 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

Abstract

The invention relates to the technical field of security monitoring methods, in particular to a security monitoring method based on the Internet of things, which comprises the following steps: a personnel detection step, namely detecting the position and the identity of indoor personnel, judging whether unauthenticated personnel with the identity not passing verification exists, if so, executing the simulation playing step, and if not, repeatedly executing the personnel detection step; a simulation playing step, playing preset scene simulation sound; a personnel analysis step, analyzing the behavior reaction of the unauthenticated personnel after hearing the scene simulation sound, judging whether the reaction of the unauthenticated personnel is abnormal or not, and if so, executing an alarm reminding step; and an alarm reminding step, namely sending alarm reminding to preset user equipment. The security monitoring method based on the Internet of things can automatically identify the identity of indoor personnel and solve the problem that the conventional security monitoring system is easy to generate false alarm when visitors visit.

Description

Security monitoring method based on Internet of things
Technical Field
The invention relates to the technical field of security monitoring methods, in particular to a security monitoring method based on the Internet of things.
Background
In recent years, with the increasing living standard of people, people pay more and more attention to the safety of family property. The traditional mechanical household defense system has many hidden dangers, and the traditional antitheft door and window has defects and hidden dangers in the aspects of overall attractiveness, emergency escape and the like, so that the pursuit of people for higher life quality is difficult to meet.
At present, monitoring systems are installed in many families, usually, a camera capable of accessing to a network is deployed indoors to achieve indoor video monitoring, however, the monitoring systems only perform indoor simple video monitoring, people are required to watch videos to perform real-time monitoring, indoor states cannot be automatically detected, and the monitoring systems are inconvenient to use.
Disclosure of Invention
The invention aims to provide a security monitoring method based on the Internet of things, which can automatically identify the identity of indoor personnel and solve the problem that the conventional security monitoring system is easy to generate false alarm when a visitor visits.
In order to solve the technical problem, the patent provides the following technical scheme:
the security monitoring method based on the Internet of things comprises the following steps:
a personnel detection step, namely detecting the position and the identity of indoor personnel, judging whether unauthenticated personnel with the identity not passing verification exists, if so, executing the simulation playing step, and if not, repeatedly executing the personnel detection step;
a simulation playing step, playing preset scene simulation sound;
a personnel analysis step, analyzing the behavior reaction of the unauthenticated personnel after hearing the scene simulation sound, judging whether the reaction of the unauthenticated personnel is abnormal or not, and if so, executing an alarm reminding step;
and an alarm reminding step, namely sending alarm reminding to preset user equipment.
According to the technical scheme, after the unauthenticated person exists indoors, the preset scene simulation sound is played, so that the scene simulation sound can play a certain frightening role on the unauthenticated person if the owner does not stay at home and pretends to be someone in the room, and meanwhile, if the unauthenticated person is a thief or a person with bad mind, the unauthenticated person can generate a certain fear psychology after hearing the scene simulation sound, and further abnormal behavior reactions can be generated; for example, after suddenly hearing the sound of opening the door with the key, the thief can immediately and quickly move to the escape direction of doors and windows and the like, and quickly escape to the direction far away from the doorway, or quickly escape to the hidden areas such as the inside of a cabinet and the bottom of a bed and the like to hide; and in the personnel analysis step, the behavior reaction of the unauthenticated personnel is analyzed, so that whether the unauthenticated personnel is a thief or not is judged, and an alarm prompt is sent to the user equipment in time. According to the technical scheme, the identity of the personnel is judged through the reaction of the personnel to the scene simulation sound, when a friend visits, the identity of the user does not need to be input in advance, the method is simple and convenient, the identification accuracy rate is high, the false alarm rate is low, indoor real-time monitoring can be achieved, illegal personnel are prevented from entering the room, and indoor financial safety is guaranteed.
Further, in the staff analyzing step, if it is detected that the response of the unauthenticated staff is not abnormal, the staff is marked as the authenticated staff, and an authentication prompt is sent to the preset user equipment.
The personnel who will react normally automatically add in the authentication personnel, avoid repeated detection, remind through the authentication, can make the user in time learn the indoor circumstances.
Further, the personnel analysis step comprises:
a movement analysis step of analyzing a movement direction, a movement speed and a stay area of the unauthenticated person according to the position change of the unauthenticated person;
and an anomaly analysis step, namely judging whether the behavior of the unauthenticated person is normal or not according to the playing position and the playing content of the scene simulation sound and the moving direction, the moving speed and the staying area of the unauthenticated person.
Firstly, the moving behavior of the unauthenticated person after hearing the scene simulation sound is analyzed, and then whether the behavior of the unauthenticated person is abnormal or not can be judged from three aspects of the moving direction, the moving speed and the staying area.
Further, the abnormality analyzing step includes:
a direction abnormity analysis step, namely judging whether an unauthenticated person moves towards a direction far away from the playing position of the scene simulation sound, a direction far away from the indoor space or a direction of a preset hiding area, if so, executing a speed abnormity analysis step, and if not, executing an area abnormity analysis step;
a speed abnormity analysis step, namely judging whether the moving speed of the unauthenticated person exceeds a preset value, if so, judging that the unauthenticated person has abnormal reaction, ending the abnormity analysis step, and if not, executing the regional abnormity analysis step;
and a region abnormity analysis step, namely judging whether the position of the unauthenticated person stays in a preset hiding region or not, and if so, judging that the unauthenticated person reacts abnormally.
The direction or speed alone is abnormal and is not enough to indicate that the behavior of the unauthenticated person is abnormal, for example, the person quickly runs to open the door after hearing the door opening sound, and the speed is abnormal at the moment, but the behavior is normal; or the person originally moves in the direction opposite to the sound source, and still moves in the direction away from the sound after hearing the scene simulation sound, so that the behavior is normal, and the person can be proved to have abnormal behavior only when the person hearing the scene simulation sound suddenly moves at a high speed and the moving direction is unreasonable, so that the direction abnormality analysis step and the speed abnormality analysis step can be used for more accurately judging whether the behavior of the person is abnormal or not. When the thieves and other personnel hear the sound, the thieves are likely to select a place to hide, in the scheme, the users can preset hiding areas in some houses in advance, and when unauthenticated personnel hear the sound, the thieves run to the hiding areas to stay, so that abnormal behaviors of the personnel can be shown, and problems exist.
Further, the person detecting step includes:
a personnel sensing step, wherein the position of each personnel is detected through an infrared sensor arranged indoors;
and a person identification step, namely sequentially collecting the face images of all persons and identifying the faces.
Through infrared sensor and face identification combination, the personnel's condition in the detection room that can be comprehensive.
Further, when the unauthenticated person is marked as the authenticated person, the face image of the person is shot, and the authentication prompt comprises the face image of the person. The user can conveniently distinguish whether the user is a friend or a relatives through the face image.
Further, the scene simulation sound comprises door opening sound, water flushing sound, cooking sound, conversation sound and calling sound, and the playing position of the scene simulation sound corresponds to the content of the scene simulation sound. The door opening sound, the water flushing sound, the cooking sound, the dialogue sound and the calling sound are all the sounds which are frequently generated in life, and the scene can be more real due to the fact that the playing position of the scene simulation sound corresponds to the content.
Further, in the simulation playing step, the scene simulation sound is played by adopting a sound directional propagation technology, so that unauthenticated persons can hear the scene simulation sound. The voice is prevented from influencing the personnel who pass the identity authentication.
Further, after the reaction of the unauthenticated person is abnormal, an indicator lamp adjusting step is also executed, and the indicator lamp adjusting step comprises the following steps:
the method comprises the following steps: tracking the position of the unauthenticated person, judging whether the unauthenticated person escapes from the room, if so, executing the next step, and if not, finishing the indicator lamp adjusting step;
step two: the brightness of the safety exit indicator lamp in the corridor is reduced, the preset navigation indicator lamp is turned on, and the navigation end point of the navigation indicator lamp is a preset security room.
Through the luminance that reduces the exit indicator in the corridor and open predetermined navigation indicator for the navigation indicator is more obvious, and then can attract the unauthenticated personnel's that flee attention, and then guides the unauthenticated personnel who probably have the problem to the security personnel indoor.
Drawings
Fig. 1 is a logic block diagram of a security monitoring system used in an embodiment of the security monitoring method based on the internet of things.
Detailed Description
The following is further detailed by way of specific embodiments:
the security monitoring method based on the internet of things uses the security monitoring system shown in fig. 1, and the system comprises a personnel detection module, a simulation playing module, a personnel analysis module, an authentication reminding module, an alarm reminding module and an indicator light adjusting module.
The personnel detection module is used for detecting the positions and identities of indoor personnel and judging whether unauthenticated personnel with the identities passing the verification pass exist or not.
In this embodiment, personnel detection module includes personnel response submodule piece and personnel identification submodule piece, and personnel response submodule piece is including evenly setting up the infrared sensor in indoor. The personnel identification submodule comprises an image acquisition unit and a face identification unit, and the image acquisition unit sequentially acquires face images of all personnel according to the detection data of the personnel sensing submodule and supplies the face identification unit to carry out face identification. Through infrared sensor and face identification combination, the personnel's condition in the detection room that can be comprehensive.
The simulation playing module is used for playing preset scene simulation sound after detecting that unauthenticated personnel exist indoors; in this embodiment, the scene simulation sound includes a door opening sound, a water flushing sound, a cooking sound, a dialogue sound, and a call sound, and a play position of the scene simulation sound corresponds to a content thereof. The door opening sound, the water flushing sound, the cooking sound, the dialogue sound and the calling sound are all the sounds which are frequently generated in life, and the scene can be more real due to the fact that the playing position of the scene simulation sound corresponds to the content. In this embodiment, the analog playing module adopts a sound directional propagation technology, and is configured to enable only unauthenticated persons to hear scene analog sound. The voice is prevented from influencing the personnel who pass the identity authentication.
The personnel analysis module is used for analyzing the behavior reaction of the unauthenticated personnel after hearing the scene simulation sound and judging whether the reaction of the unauthenticated personnel is abnormal or not; the personnel analysis module comprises a movement analysis submodule and an abnormity analysis submodule, wherein the movement analysis submodule is used for analyzing the movement direction, the movement speed and the stay area of the unauthenticated personnel according to the position change of the unauthenticated personnel.
And the abnormity analysis submodule is used for judging whether the reaction of the unauthenticated person is normal or not according to the playing position and the playing content of the scene simulation sound and the moving direction, the moving speed and the staying area of the unauthenticated person. The anomaly analysis submodule comprises a direction anomaly analysis unit, a speed anomaly analysis unit and a region anomaly analysis unit: the direction abnormity analysis unit is used for judging whether the unauthenticated person has direction abnormity according to whether the unauthenticated person moves towards a direction far away from the playing position of the scene simulation sound, a direction far away from the indoor space or a direction towards a preset hiding area; the speed abnormity analysis unit is used for judging whether the speed of the unauthenticated person is abnormal or not according to whether the moving speed of the unauthenticated person exceeds a preset value or not when the direction of the unauthenticated person is abnormal or not, and judging that the unauthenticated person has abnormal reaction if the moving speed of the unauthenticated person exceeds the preset value; the area abnormity analysis unit is used for judging whether the unauthenticated person has an abnormal reaction according to the staying area of the unauthenticated person and the preset hiding area.
The alarm reminding module is used for sending an alarm reminding to preset user equipment after detecting that the response of the unauthenticated person is abnormal, and in the embodiment, the alarm reminding module sends an alarm short message to a preset mobile phone number of the user.
The personnel analysis module is also used for marking the personnel as the certificated personnel when the condition that the reaction of the uncertified personnel is not abnormal is detected, and the certification reminding module sends corresponding certification reminding to the preset user equipment.
The authentication reminding module is also used for shooting the face image of the person through the image acquisition unit when the unauthenticated person is marked as an authenticated person, and the authentication reminding comprises the face image of the person. The user can conveniently distinguish whether the user is a friend or a relatives through the face image. The personnel who will react normally automatically add in the authentication personnel, avoid repeated detection, remind through the authentication, can make the user in time learn the indoor circumstances.
The security monitoring method based on the Internet of things comprises the following steps:
a personnel detection step, namely detecting the position and the identity of indoor personnel, judging whether unauthenticated personnel with the identity not passing verification exists, if so, executing the simulation playing step, and if not, repeatedly executing the personnel detection step;
a simulation playing step, playing preset scene simulation sound; the scene simulation sound comprises door opening sound, water flushing sound, cooking sound, conversation sound and calling sound, and the playing position of the scene simulation sound corresponds to the content of the scene simulation sound. The door opening sound, the water flushing sound, the cooking sound, the dialogue sound and the calling sound are all the sounds which are frequently generated in life, and the scene can be more real due to the fact that the playing position of the scene simulation sound corresponds to the content. In the simulation playing step, the scene simulation sound is played by adopting a sound directional propagation technology, so that only unauthenticated persons can hear the scene simulation sound. The voice is prevented from influencing the personnel who pass the identity authentication.
A personnel analysis step, analyzing the behavior reaction of the unauthenticated personnel after hearing the scene simulation sound, judging whether the reaction of the unauthenticated personnel is abnormal or not, if so, executing an alarm reminding step, otherwise, marking the personnel as an authenticated personnel, and executing an authentication reminding step;
an authentication reminding step, namely sending authentication reminding to preset user equipment;
and an alarm reminding step, namely sending alarm reminding to preset user equipment.
Wherein, personnel analysis step includes:
a movement analysis step of analyzing a movement direction, a movement speed and a stay area of the unauthenticated person according to the position change of the unauthenticated person;
and an anomaly analysis step, namely judging whether the behavior of the unauthenticated person is normal or not according to the playing position and the playing content of the scene simulation sound and the moving direction, the moving speed and the staying area of the unauthenticated person.
The anomaly analyzing step comprises the following steps:
a direction abnormity analysis step, namely judging whether an unauthenticated person moves towards a direction far away from the playing position of the scene simulation sound, a direction far away from the indoor space or a direction of a preset hiding area, if so, executing a speed abnormity analysis step, and if not, executing an area abnormity analysis step;
a speed abnormity analysis step, namely judging whether the moving speed of the unauthenticated person exceeds a preset value, if so, judging that the unauthenticated person has abnormal reaction, ending the abnormity analysis step, and if not, executing the regional abnormity analysis step;
and a region abnormity analysis step, namely judging whether the position of the unauthenticated person stays in a preset hiding region or not, and if so, judging that the unauthenticated person reacts abnormally.
The personnel detection step comprises:
a personnel sensing step, wherein the position of each personnel is detected through an infrared sensor arranged indoors;
and a person identification step, namely sequentially collecting the face images of all persons and identifying the faces.
Through infrared sensor and face identification combination, the personnel's condition in the detection room that can be comprehensive.
In the authentication reminding step, when the unauthenticated person is marked as an authenticated person, the face image of the person is shot, and the authentication reminding comprises the face image of the person. The user can conveniently distinguish whether the user is a friend or a relatives through the face image.
And after the reaction of the unauthenticated person is abnormal, an indicator lamp adjusting step is also executed, wherein the indicator lamp adjusting step comprises the following steps:
the method comprises the following steps: tracking the position of the unauthenticated person, judging whether the unauthenticated person escapes from the room, if so, executing the next step, and if not, finishing the indicator lamp adjusting step;
step two: the brightness of the safety exit indicator lamp in the corridor is reduced, the preset navigation indicator lamp is turned on, and the navigation end point of the navigation indicator lamp is a preset security room.
In the technical scheme of the embodiment, the simulation playing module plays the preset scene simulation sound after detecting that unauthenticated persons exist indoors, so that the scene simulation sound can play a certain frightening role on the unauthenticated persons if the owner does not live at home to pretend to be someone indoors, and meanwhile, if the unauthenticated persons are thieves or people with bad mind, the unauthenticated persons can generate certain fear psychology after hearing the scene simulation sound, and further abnormal behavior reactions can be generated; for example, after suddenly hearing the sound of opening the door with the key, the thief can immediately and quickly move to the escape direction of doors and windows and the like, and quickly escape to the direction far away from the doorway, or quickly escape to the hidden areas such as the inside of a cabinet and the bottom of a bed and the like to hide; and the personnel analysis module analyzes the behavior reaction of the unauthenticated personnel so as to judge whether the unauthenticated personnel are thieves or not and timely send alarm prompt to the user equipment. According to the technical scheme, the identity of the personnel is judged through the reaction of the personnel to the scene simulation sound, when a friend visits, the identity of the user does not need to be input in advance, the method is simple and convenient, the identification accuracy rate is high, the false alarm rate is low, indoor real-time monitoring can be achieved, illegal personnel are prevented from entering the room, and indoor financial safety is guaranteed.
Firstly, the moving behavior of the unauthenticated person after hearing the scene simulation sound is analyzed, and then whether the behavior of the unauthenticated person is abnormal or not can be judged from three aspects of the moving direction, the moving speed and the staying area. The direction or speed alone is abnormal and is not enough to indicate that the behavior of the unauthenticated person is abnormal, for example, the person quickly runs to open the door after hearing the door opening sound, and the speed is abnormal at the moment, but the behavior is normal; or the person originally moves in the direction opposite to the sound source, and still moves in the direction away from the sound after hearing the scene simulation sound, so that the behavior is normal, and the person can be proved to have abnormal behavior only when the person hearing the scene simulation sound suddenly moves at a high speed and the moving direction is unreasonable, so that the direction abnormality analysis unit and the speed abnormality analysis unit can more accurately judge whether the behavior of the person is abnormal. When the thieves and other personnel hear the sound, the thieves are likely to select a place to hide, in the scheme, the users can preset hiding areas in some houses in advance, and when unauthenticated personnel hear the sound, the thieves run to the hiding areas to stay, so that the situation that the reaction behaviors of the personnel are abnormal and problems exist can be explained.
The pilot lamp adjusting module is connected with a pilot lamp control system of the whole building, and the pilot lamp adjusting module is used for reducing the brightness of the safety exit pilot lamp in the corridor after detecting that unauthenticated personnel escape from the room, and simultaneously starting a preset navigation pilot lamp, wherein the navigation end point of the navigation pilot lamp is a preset security room. Through the luminance that reduces the exit indicator in the corridor and open predetermined navigation indicator for the navigation indicator is more obvious, and then can attract the unauthenticated personnel's that flee attention, and then guides the unauthenticated personnel who probably have the problem to the security personnel indoor.
The foregoing are merely exemplary embodiments of the present invention, and no attempt is made to show structural details of the invention in more detail than is necessary for the fundamental understanding of the art, the description taken with the drawings making apparent to those skilled in the art how the several forms of the invention may be embodied in practice with the teachings of the invention. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.

Claims (9)

1. The security monitoring method based on the Internet of things is characterized by comprising the following steps: the method comprises the following steps:
a personnel detection step, namely detecting the position and the identity of indoor personnel, judging whether unauthenticated personnel with the identity not passing verification exists, if so, executing the simulation playing step, and if not, repeatedly executing the personnel detection step;
a simulation playing step, playing preset scene simulation sound;
a personnel analysis step, analyzing the behavior reaction of the unauthenticated personnel after hearing the scene simulation sound, judging whether the reaction of the unauthenticated personnel is abnormal or not, and if so, executing an alarm reminding step;
and an alarm reminding step, namely sending alarm reminding to preset user equipment.
2. The security monitoring method based on the internet of things as claimed in claim 1, wherein: and in the step of analyzing the personnel, if the condition that the reaction of the unauthenticated personnel is not abnormal is detected, marking the personnel as the authenticated personnel, and sending an authentication prompt to the preset user equipment.
3. The security monitoring method based on the internet of things as claimed in claim 1, wherein: the personnel analysis step comprises:
a movement analysis step of analyzing a movement direction, a movement speed and a stay area of the unauthenticated person according to the position change of the unauthenticated person;
and an anomaly analysis step, namely judging whether the behavior of the unauthenticated person is normal or not according to the playing position and the playing content of the scene simulation sound and the moving direction, the moving speed and the staying area of the unauthenticated person.
4. The security monitoring method based on the Internet of things as claimed in claim 3, wherein: the abnormality analyzing step includes:
a direction abnormity analysis step, namely judging whether an unauthenticated person moves towards a direction far away from the playing position of the scene simulation sound, a direction far away from the indoor space or a direction of a preset hiding area, if so, executing a speed abnormity analysis step, and if not, executing an area abnormity analysis step;
a speed abnormity analysis step, namely judging whether the moving speed of the unauthenticated person exceeds a preset value, if so, judging that the unauthenticated person has abnormal reaction, ending the abnormity analysis step, and if not, executing the regional abnormity analysis step;
and a region abnormity analysis step, namely judging whether the position of the unauthenticated person stays in a preset hiding region or not, and if so, judging that the unauthenticated person reacts abnormally.
5. The security monitoring method based on the internet of things as claimed in claim 1, wherein: the personnel detection step comprises:
a personnel sensing step, wherein the position of each personnel is detected through an infrared sensor arranged indoors;
and a person identification step, namely sequentially collecting the face images of all persons and identifying the faces.
6. The security monitoring method based on the internet of things as claimed in claim 2, wherein: when the unauthenticated person is marked as an authenticated person, the face image of the person is shot, and the authentication prompt comprises the face image of the person.
7. The security monitoring method based on the internet of things as claimed in claim 1, wherein: the scene simulation sound comprises door opening sound, water flushing sound, cooking sound, dialogue sound and call sound, and the playing position of the scene simulation sound corresponds to the content of the scene simulation sound.
8. The security monitoring method based on the internet of things as claimed in claim 1, wherein: in the simulation playing step, the scene simulation sound is played by adopting a sound directional propagation technology, so that unauthenticated persons can hear the scene simulation sound.
9. The security monitoring method based on the internet of things as claimed in claim 1, wherein: and after the reaction of the unauthenticated person is abnormal, an indicator lamp adjusting step is also executed, wherein the indicator lamp adjusting step comprises the following steps:
the method comprises the following steps: tracking the position of the unauthenticated person, judging whether the unauthenticated person escapes from the room, if so, executing the next step, and if not, finishing the indicator lamp adjusting step;
step two: the brightness of the safety exit indicator lamp in the corridor is reduced, the preset navigation indicator lamp is turned on, and the navigation end point of the navigation indicator lamp is a preset security room.
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