CN112991659A - Big data security monitoring management method with early warning processing function - Google Patents
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- G—PHYSICS
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- G08B17/06—Electric actuation of the alarm, e.g. using a thermally-operated switch
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Abstract
The invention provides a big data security monitoring management method with an early warning processing function, which comprises the following steps: collecting data, constructing a security model, installing monitoring hardware, a hardware combination model, fire early warning, robbery early warning and wireless interconnection; the floor vectorization model is constructed, a temperature alarm value of a temperature sensor is set, identification of a smoke detector is matched to serve as fire reference, fire sprinkler emergency treatment at a corresponding position can be started, an alarm is started to perform sound-light alarm, security personnel are reminded of processing, coordinates of the corresponding fire position are highlighted, position data are provided, noise packages for smashing noise simulation, breaking noise simulation and collision noise simulation are loaded through big data, a decibel threshold value is set, the sound sensor senses the type and decibel of noise at the corresponding position to serve as robbery reference, reminding is displayed in a terminal host, coordinates of the abnormal noise position are highlighted, and the security personnel are reminded of processing.
Description
Technical Field
The invention relates to the technical field of security monitoring management, in particular to a big data security monitoring management method with an early warning processing function.
Background
In the existing floor market, a security monitoring system is generally provided, wherein the security monitoring system is an independent and complete system formed by transmitting video signals in a closed loop from image pickup to image display and recording, can reflect a monitored object in real time, vividly and truly, can replace manpower to perform long-time monitoring in a severe environment, and is recorded by a video recorder;
however, the existing security monitoring system can only play a simple role in video monitoring, cannot identify fire, cannot identify robbery situations, and further cannot perform early warning processing on the security situations, so that the invention provides a big data security monitoring management method with an early warning processing function to solve the problems in the prior art.
Disclosure of Invention
Aiming at the problems, the invention provides a big data security monitoring management method with an early warning processing function, which is convenient for fire early warning, early warning of robbery and monitoring more comprehensively, provides corresponding position coordinates and is convenient for timely processing.
In order to realize the purpose of the invention, the invention is realized by the following technical scheme: a big data security protection monitoring management method with an early warning processing function comprises the following steps:
the method comprises the following steps: collecting data
Acquiring the structure distribution diagram data of the floor from the floor construction data, recording the detailed coordinate position, inputting the structure distribution diagram data of the floor into a metadata management system MDMS, describing a data set in the metadata management system MDMS, and taking out effective data;
step two: construction of Security model
Based on an EXIF principle of exchangeable image files, constructing a data model by taking digital images as carriers to fuse spatial positions and general form attributes, inputting effective data in the first step into the model, embedding associated coordinate information and distribution map attributes into a physical structure of the digital images, then cleaning similar repeated data in the effective data through sequencing improvement SNM algorithm to obtain accurate, clear and visual data fusion, comparing structural distribution map data of floors, analyzing whether the data fusion can meet the full coverage of the floor structure, if so, retaining the final data fusion, then importing the final data fusion into GML to realize the visualization of coordinate space data, and simultaneously carrying out space-time data vectorization by using SVG to form points, lines and planes and form specific data coordinates to construct a floor vectorization model;
step three: installation monitoring hardware
Observing the space image of floors in the model, arranging monitoring hardware at equal intervals in each floor, wherein the monitoring hardware comprises a camera, a temperature sensor, a smoke sensor and a sound sensor, recording the specific coordinates of the camera, the temperature sensor, the smoke sensor and the sound sensor, and then implementing the transformation in the floors according to the actual coordinates;
step four: hardware integration model
Inputting the floor vectorization model into a control host of a floor control room, displaying the floor vectorization model on a host screen, connecting a camera, a temperature sensor, a smoke sensor and a sound sensor with the control host of the floor control room, and corresponding the camera, the temperature sensor, the smoke sensor and the sound sensor at different coordinate positions to corresponding coordinates in the floor vectorization model;
step five: fire early warning
Setting coordinate highlight reminding in a floor vectorization model, associating coordinates with monitoring hardware in real time, inputting a temperature alarm value of a temperature sensor in a terminal control host, and taking the temperature alarm value and the identification of a smoke detector as fire references;
step six: early warning of theft and robbery
Connecting a control host computer with the Internet, loading sound data, wherein the data comprises smashing noise simulation, crushing noise simulation and collision noise simulation, constructing a noise packet, setting a threshold value of the noise simulation, connecting a sound sensor with the noise packet, and sensing the type and decibel of noise at a corresponding position by the sound sensor to serve as a robbery reference;
step seven: wireless interconnection
Set up 5G communication module in the control host computer, set up in security protection personnel's cell-phone and connect APP, connect 5G communication module, when the terminal host computer judges the condition of a fire, steals and robbes, utilize 5G communication module to send early warning data for security protection personnel's cell-phone APP in step to synchronous display corresponding coordinate position.
The further improvement lies in that: in the first step, after the valid data are taken out, the valid data are stored in the corresponding storage center according to the configured storage rule and the duplication is removed.
The further improvement lies in that: and in the second step, when the data fusion can not meet the full coverage of the floor structure, the effective data in the first step is used for supplementing repeatedly until the data fusion meets the full coverage of the floor structure.
The further improvement lies in that: in the third step, monitoring hardware is arranged on each floor at equal intervals, and the detection ranges between the adjacent monitoring hardware are ensured to have overlapped parts.
The further improvement lies in that: and in the fourth step, the camera, the temperature sensor, the smoke sensor and the sound sensor are connected with the control host machine of the floor control room through optical fibers, coaxial cables and microwave technology.
The further improvement lies in that: in the fifth step, when the temperature identified by the temperature sensor reaches a temperature alarm value, the terminal host identifies abnormal temperature, reminding is displayed in the terminal host, when the smoke sensor synchronously identifies smoke, the terminal host judges the fire, the terminal host is connected with the fire sprinkler in the floor, the fire sprinkler at the corresponding position is immediately started for emergency treatment after the fire is judged, the alarm is started for acousto-optic alarm, security personnel is reminded of processing, meanwhile, the coordinates of the corresponding fire position are highlighted in the vectorization floor model according to the identification of the monitoring hardware data of the corresponding position, position data are provided, and the security personnel directly observe the fire through the camera of the corresponding coordinate.
The further improvement lies in that: and in the sixth step, when the noise type belongs to the type in the noise packet and decibels reach a threshold value, the terminal host recognizes that the noise is abnormal and is suspected to be stolen or robbed, a prompt is displayed in the terminal host to prompt security personnel to process the noise, meanwhile, according to the recognition of monitoring hardware data of corresponding positions, coordinates of corresponding noise abnormal positions are highlighted in the floor vectorization model to provide position data, and the security personnel directly observe the fire through cameras of corresponding coordinates.
The further improvement lies in that: and in the seventh step, the connection APP in the mobile phone of the security personnel is connected with the 5G communication module by using the corresponding connection password.
The invention has the beneficial effects that: the invention constructs a floor vectorization model by acquiring the structural distribution map data of floors, performing space-time data vectorization by using SVG to form points, lines and planes and form specific data coordinates, starting a fire sprinkler at a corresponding position to perform emergency treatment by setting a temperature alarm value of a temperature sensor and matching with the identification of a smoke detector as a fire reference, simultaneously starting an alarm to perform sound-light alarm to remind security personnel to perform treatment, highlighting the coordinates of the corresponding fire position in the floor vectorization model, providing position data, loading noise packets for hitting noise simulation, breaking noise simulation and collision noise simulation by big data, setting decibel thresholds, using the sound sensor to sense the type and decibel of the noise at the corresponding position as robbery reference, displaying the reminding in a terminal host, highlighting the coordinates of the corresponding abnormal noise position, remind security protection personnel to handle to sum up, the condition of a fire early warning of being convenient for steals and robbes the early warning, and the control is more comprehensive to provide corresponding position coordinate, the in time processing of being convenient for, simultaneously, through the connection APP in 5G communication module connection security protection personnel cell-phone, security protection personnel of being convenient for know the security protection dangerous situation anytime and anywhere, it is more reliable.
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FIG. 1 is a flow chart of the present invention.
Detailed Description
In order to further understand the present invention, the following detailed description will be made with reference to the following examples, which are only used for explaining the present invention and are not to be construed as limiting the scope of the present invention.
As shown in fig. 1, the embodiment provides a big data security monitoring management method with an early warning processing function, which includes the following steps:
the method comprises the following steps: collecting data
Acquiring the structure distribution diagram data of floors from the floor construction data, recording detailed coordinate directions, inputting the structure distribution diagram data of the floors into a metadata management system MDMS, describing a data set in the metadata management system MDMS, taking out effective data, and storing the effective data into a corresponding storage center according to configured storage rules and removing the weight after the effective data is taken out;
step two: construction of Security model
Based on the exchangeable image file EXIF principle, a data model is constructed by fusing spatial position and general form attributes with a digital image as a carrier, effective data in the step I are input into the model, associated coordinate information and distribution diagram attributes are embedded into a physical structure of the digital image, then similar repeated data in the effective data are cleaned through a sequencing improvement SNM algorithm to obtain accurate, clear and visual data fusion, structural distribution diagram data of floors are compared, whether the data fusion can meet the full coverage of the floor structure is analyzed, when the data fusion can not meet the full coverage of the floor structure, the effective data in the step I are used for repeated supplementation until the data fusion meets the full coverage of the floor structure, when the data fusion meets the requirement, final data fusion is reserved, and then the final data fusion is imported into GML to realize the visualization of coordinate space data, and simultaneously, carrying out space-time data vectorization by using SVG (scalable vector graphics), forming points, lines and planes, forming specific data coordinates, and constructing a floor vectorization model;
step three: installation monitoring hardware
Observing the space image of floors in the model, arranging monitoring hardware at equal intervals in each floor, wherein the monitoring hardware comprises a camera, a temperature sensor, a smoke sensor and a sound sensor, recording the specific coordinates of the camera, the temperature sensor, the smoke sensor and the sound sensor, ensuring that the detection ranges of adjacent monitoring hardware have overlapped parts, and then implementing the transformation in the floors according to the actual coordinates;
step four: hardware integration model
Inputting the floor vectorization model into a control host of a floor control room, displaying the floor vectorization model on a host screen, connecting a camera, a temperature sensor, a smoke sensor and a sound sensor with the control host of the floor control room through optical fibers, coaxial cables and microwave technology, and corresponding the camera, the temperature sensor, the smoke sensor and the sound sensor at different coordinate positions to corresponding coordinates in the floor vectorization model;
step five: fire early warning
Setting coordinate highlight reminding in a floor vectorization model, associating the coordinate with monitoring hardware in real time, inputting a temperature alarm value of a temperature sensor in a terminal control host, taking the temperature alarm value and the identification of a smoke detector as fire references, identifying the temperature of the temperature sensor as abnormal temperature when the temperature reaches the temperature alarm value, displaying reminding in the terminal host, judging the fire by the terminal host when the smoke sensor synchronously identifies smoke, connecting the terminal host with a fire sprinkler in the floor, starting the fire sprinkler at a corresponding position immediately after the fire is judged to be the fire, starting an alarm to perform sound and light alarm, reminding security personnel to process, identifying according to the monitoring hardware data at the corresponding position, and highlighting the coordinate at the corresponding fire position in the floor vectorization model, providing position data, and directly observing the fire condition by security personnel through a camera with corresponding coordinates;
step six: early warning of theft and robbery
Connecting a control host to the Internet, loading sound data, wherein the data comprises smashing noise simulation, crushing noise simulation and collision noise simulation, constructing a noise packet, setting a threshold value of the noise simulation, connecting a sound sensor with the noise packet, sensing the type and decibel of noise at a corresponding position by the sound sensor to serve as a robbery reference, identifying the terminal host as abnormal noise when the type of the noise belongs to the noise packet and the decibel reaches the threshold value, displaying a prompt in the terminal host to remind security personnel to process the abnormal noise, and meanwhile, according to the identification of monitoring hardware data at the corresponding position, highlighting the coordinate of the position with the abnormal noise in a floor vectorization model to provide position data, and directly observing the fire condition by the security personnel through a camera at the corresponding coordinate;
step seven: wireless interconnection
Set up 5G communication module in the control host computer, set up the connection APP in security protection personnel's cell-phone to correspond and go up the connection password, when the terminal host computer judges the condition of a fire, steals and robbes, utilize 5G communication module to send early warning data for security protection personnel's cell-phone APP in step, and the corresponding coordinate position of synchronous display.
The big data security monitoring management method with the early warning processing function constructs a floor vectorization model by acquiring the structural distribution map data of floors and carrying out space-time data vectorization by using SVG (scalable vector graphics), forming points, lines and surfaces and forming concrete data coordinates, can start the fire sprinkler at corresponding positions to carry out emergency processing by setting the temperature alarm value of a temperature sensor and matching with the identification of a smoke detector as fire reference, simultaneously starts an alarm to carry out sound-light alarm to remind security personnel to process, carries out highlight display on the coordinates of the corresponding fire positions in the floor vectorization model to provide position data, loads noise packets for hitting noise simulation, breaking noise simulation and collision noise simulation through big data, sets a decibel threshold value, uses the sound sensor to sense the type and decibel of the noise at the corresponding positions as robbery reference and displays reminding in a terminal host, and the coordinate highlight of corresponding noise abnormal position reminds security protection personnel to handle to sum up, and the early warning of being convenient for is robbed in the condition of a fire early warning of stealing, and the control is more comprehensive to provide corresponding position coordinate, be convenient for in time handle, simultaneously, through the connection APP in 5G communication module connection security protection personnel cell-phone, security protection personnel of being convenient for know the security protection dangerous situation anytime and anywhere, it is more reliable.
The foregoing illustrates and describes the principles, general features, and advantages of the present invention. It will be understood by those skilled in the art that the present invention is not limited to the embodiments described above, which are described in the specification and illustrated only to illustrate the principle of the present invention, but that various changes and modifications may be made therein without departing from the spirit and scope of the present invention, which fall within the scope of the invention as claimed. The scope of the invention is defined by the appended claims and equivalents thereof.
Claims (8)
1. A big data security protection monitoring management method with an early warning processing function is characterized by comprising the following steps:
the method comprises the following steps: collecting data
Acquiring the structure distribution diagram data of the floor from the floor construction data, recording the detailed coordinate position, inputting the structure distribution diagram data of the floor into a metadata management system MDMS, describing a data set in the metadata management system MDMS, and taking out effective data;
step two: construction of Security model
Based on an EXIF principle of exchangeable image files, constructing a data model by taking digital images as carriers to fuse spatial positions and general form attributes, inputting effective data in the first step into the model, embedding associated coordinate information and distribution map attributes into a physical structure of the digital images, then cleaning similar repeated data in the effective data through sequencing improvement SNM algorithm to obtain accurate, clear and visual data fusion, comparing structural distribution map data of floors, analyzing whether the data fusion can meet the full coverage of the floor structure, if so, retaining the final data fusion, then importing the final data fusion into GML to realize the visualization of coordinate space data, and simultaneously carrying out space-time data vectorization by using SVG to form points, lines and planes and form specific data coordinates to construct a floor vectorization model;
step three: installation monitoring hardware
Observing the space image of floors in the model, arranging monitoring hardware at equal intervals in each floor, wherein the monitoring hardware comprises a camera, a temperature sensor, a smoke sensor and a sound sensor, recording the specific coordinates of the camera, the temperature sensor, the smoke sensor and the sound sensor, and then implementing the transformation in the floors according to the actual coordinates;
step four: hardware integration model
Inputting the floor vectorization model into a control host of a floor control room, displaying the floor vectorization model on a host screen, connecting a camera, a temperature sensor, a smoke sensor and a sound sensor with the control host of the floor control room, and corresponding the camera, the temperature sensor, the smoke sensor and the sound sensor at different coordinate positions to corresponding coordinates in the floor vectorization model;
step five: fire early warning
Setting coordinate highlight reminding in a floor vectorization model, associating coordinates with monitoring hardware in real time, inputting a temperature alarm value of a temperature sensor in a terminal control host, and taking the temperature alarm value and the identification of a smoke detector as fire references;
step six: early warning of theft and robbery
Connecting a control host computer with the Internet, loading sound data, wherein the data comprises smashing noise simulation, crushing noise simulation and collision noise simulation, constructing a noise packet, setting a threshold value of the noise simulation, connecting a sound sensor with the noise packet, and sensing the type and decibel of noise at a corresponding position by the sound sensor to serve as a robbery reference;
step seven: wireless interconnection
Set up 5G communication module in the control host computer, set up in security protection personnel's cell-phone and connect APP, connect 5G communication module, when the terminal host computer judges the condition of a fire, steals and robbes, utilize 5G communication module to send early warning data for security protection personnel's cell-phone APP in step to synchronous display corresponding coordinate position.
2. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: in the first step, after the valid data are taken out, the valid data are stored in the corresponding storage center according to the configured storage rule and the duplication is removed.
3. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: and in the second step, when the data fusion can not meet the full coverage of the floor structure, the effective data in the first step is used for supplementing repeatedly until the data fusion meets the full coverage of the floor structure.
4. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: in the third step, monitoring hardware is arranged on each floor at equal intervals, and the detection ranges between the adjacent monitoring hardware are ensured to have overlapped parts.
5. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: and in the fourth step, the camera, the temperature sensor, the smoke sensor and the sound sensor are connected with the control host machine of the floor control room through optical fibers, coaxial cables and microwave technology.
6. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: in the fifth step, when the temperature identified by the temperature sensor reaches a temperature alarm value, the terminal host identifies abnormal temperature, reminding is displayed in the terminal host, when the smoke sensor synchronously identifies smoke, the terminal host judges the fire, the terminal host is connected with the fire sprinkler in the floor, the fire sprinkler at the corresponding position is immediately started for emergency treatment after the fire is judged, the alarm is started for acousto-optic alarm, security personnel is reminded of processing, meanwhile, the coordinates of the corresponding fire position are highlighted in the vectorization floor model according to the identification of the monitoring hardware data of the corresponding position, position data are provided, and the security personnel directly observe the fire through the camera of the corresponding coordinate.
7. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: and in the sixth step, when the noise type belongs to the type in the noise packet and decibels reach a threshold value, the terminal host recognizes that the noise is abnormal and is suspected to be stolen or robbed, a prompt is displayed in the terminal host to prompt security personnel to process the noise, meanwhile, according to the recognition of monitoring hardware data of corresponding positions, coordinates of corresponding noise abnormal positions are highlighted in the floor vectorization model to provide position data, and the security personnel directly observe the fire through cameras of corresponding coordinates.
8. The big data security monitoring and management method with the early warning processing function according to claim 1, characterized in that: and in the seventh step, the connection APP in the mobile phone of the security personnel is connected with the 5G communication module by using the corresponding connection password.
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