CN117275158A - Intelligent surrounding biological identification tracking method and system - Google Patents
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- H—ELECTRICITY
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Abstract
The invention belongs to the technical field of data identification, and discloses an intelligent surrounding biological identification tracking method and system. Sensing an external intrusion boundary signal through a sensor, transmitting the signal to information processing equipment, screening and identifying the information processing equipment, and finding out intrusion behaviors to alarm; the linked spherical camera monitors; identifying and differentiating species of organisms by analyzing the features; transmitting the acquired information to a background storage control module through a network, and receiving a control signal of the background storage control module; solar energy power supply utilizes the photoelectric effect of semiconductor materials to convert solar energy into electric energy, stores the electric energy and supplies power to the sensing and spherical cameras. The invention can correspondingly adjust according to actual conditions, realize automatic monitoring alarm and biological identification storage record of airport boundary, reduce cost and improve the integral efficiency and safety guarantee of the airport.
Description
Technical Field
The invention belongs to the technical field of data identification, and particularly relates to an intelligent surrounding biological identification tracking method and system.
Background
The airport is used as a main place for civil aviation ground guarantee, and the safety and management in the area range are directly related to the safety of the airport and the normal operation of the ground guarantee. For airports, the periphery is a safety barrier which is directly and importantly isolated from the outside, and the protection of the periphery of the airport is particularly important. The advent of various organisms can pose a serious threat to the aerospace industry. Such as birds flying in the sky, small animals running on land, etc.
The domestic adoption of precautions such as ecological management, dummy, manual inspection and the like can play a certain role, but the problems that the data cannot be found in time and can not be stored, analysis and processing can not be performed and the like exist. How to improve the recognition efficiency and accuracy is a problem that must be studied and paid attention to.
Disclosure of Invention
In order to overcome the problems in the related art, the disclosed embodiments of the invention provide an intelligent surrounding biological identification tracking method and system.
The technical scheme is as follows: the intelligent surrounding biological recognition tracking method comprises the following steps:
s1, an enclosure detection module senses an external intrusion enclosure signal through a sensor and converts the external intrusion enclosure signal, the converted signal is transmitted to information processing equipment, the information processing equipment is utilized to screen and identify the signal, intrusion behaviors are found out, and an alarm is given;
s2, monitoring is carried out through a linked spherical camera, after the camera is positioned to a position, zooming is carried out by the camera, and track tracking is carried out in real time, so that automatic snapshot, tracking and rechecking are realized;
s3, the data analysis module identifies and distinguishes the type of the organism by analyzing the characteristic data, and based on the intelligent biological identification technology, the data of the collected organism is utilized to identify the type of the organism;
s4, the remote communication module transmits the acquired information to the background storage control module through a network and receives a control signal of the background storage control module;
s5, the solar charging module converts solar energy into electric energy by utilizing the photoelectric effect of the semiconductor material and stores the electric energy to supply power for the sensor and the spherical camera.
In step S1, the sensor adopts a physical quantity conversion device to convert the physical quantity of pressure, vibration, displacement, sound, temperature and light intensity generated during invasion into an electric signal and an electric parameter;
the information processing equipment is utilized to screen and identify the signals, find out the intrusion behavior and alarm, and the method comprises the following steps: comparing the continuously-changing analog signal output by the sensor with the value of the reference signal through a comparator, and if the analog signal is smaller than the reference signal, introducing interference instead of invading the signal; if the signal exceeds the reference signal, the signal is an intrusion behavior occurrence signal, so that the true intrusion behavior is found out to alarm.
In step S1, the enclosure detection module attaches a sensor based on a vibration detection method to the enclosure, the sensor senses the mechanical vibration of the enclosure caused by the intrusion behavior, converts the generated mechanical vibration signal into an electrical signal, and sends the electrical signal to the information processing device, and the information processing device finds out real intrusion alarm information and alarms through processing and screening the mechanical vibration signal;
the information processing equipment analyzes each mechanical vibration characteristic transmitted back by the vibration sensor through a big data model, and determines the amplitude and the intensity of vibration by detecting the value of a vibration signal in combination with the weather information at the time; and comparing the amplitude and the intensity of vibration through cloud computing, and comparing whether the collected mechanical vibration characteristics transmitted by adjacent or all vibration sensors are consistent or fluctuated within a set range, so as to judge whether the mechanical vibration is abnormal.
Further, the big data model analyzes each mechanical vibration characteristic transmitted back by the vibration sensor, including: collecting data brought by a sensor and preprocessing the data; and suppressing interference signals of signals output by the sensor, and modifying and compensating the detected nonlinearity, gain error and zero error.
In step S2, track tracking is performed in real time, so as to realize automatic snapshot, tracking and rechecking, including:
the association relation between the sensor and the camera is pre-configured, when a signal fed back by a certain sensor is determined to be an intrusion signal, the spherical camera associated with the sensor is mobilized to monitor, so that the spherical camera rotates, after the spherical camera rotates to a specific position, the camera automatically zooms, zooms and amplifies a target image, changes the focal length of the lens, amplifies and presents a monitored target, and tracks in real time;
the trajectory tracking includes: when the monitored target moves, based on the monitoring principle of pixel change, the lens moves along with the target, the record moving track is transmitted to the system, the system receives and records the moving track, the camera automatically captures the photo of the invader, and the photo is transmitted to the background for storage, so that automatic capturing, tracking and rechecking are realized.
In step S3, biological species identification is performed using data of the collected living beings, including: comparing biometric data including appearance features, color features, sound features, motion features with feature data in a database to identify which creature belongs to; collecting biological data by using an acoustic sensor, a visual sensor, a motion sensor and a spherical camera based on an intelligent biotechnology identification technology, wherein signals collected by the sensors are used for detecting biological characteristics, and the characteristics are recorded as metadata; the AI learning technology is used for constructing a biological recognition model, and an acoustic sensor, a visual sensor, a motion sensor and a spherical camera are automatically adjusted.
In step S4, the remote communication module converts the information into an electrical signal by using a sensor, transmits the electrical signal to the background storage control module through a network, and transmits the collected sound, photo and video.
Further, the background storage control module receives and stores the transmitted data, detects and analyzes the transmitted data, stores analysis results, forms a large database, and uses the data in the large database for historical review and statistical analysis to formulate a control scheme.
Another object of the present invention is to provide an intelligent enclosure biometric tracking system, which implements the intelligent enclosure biometric tracking method, the system comprising:
the surrounding detection module senses an external invasion surrounding signal through a sensor and converts the external invasion surrounding signal, the converted signal is transmitted to the information processing equipment, the information processing equipment is utilized for screening and identifying the signal, and invasion behaviors are found and alarm is given;
after the spherical camera is linked and positioned to the position, the camera zooms, tracks in real time, and automatic snapshot, tracking and rechecking are realized;
the data analysis module is used for identifying and distinguishing the type of the organism by analyzing the characteristic data, and based on the intelligent biological identification technology, the data of the collected organism is utilized for biological type identification;
the remote communication module is used for transmitting the acquired information to the background storage control module through a network and receiving a control signal of the background storage control module;
the solar charging module is used for converting solar energy into electric energy by utilizing the photoelectric effect of the semiconductor material and storing the electric energy to supply power for the sensor and the spherical camera;
the background storage control module is used for receiving and storing the transmitted data, storing the detection data and the analysis process and the analysis result, and forming a large database for history review; meanwhile, all-weather biological data of the peripheral area of the airport is accumulated for statistical analysis, so that the activity rule of organisms is analyzed, and a biological prevention scheme is provided.
Furthermore, the surrounding detection module is matched with an electromagnetic induction coil on the ground, and the on-site linkage treatment equipment gives an audible and visual alarm and searches for a lamp.
By combining all the technical schemes, the invention has the following beneficial effects: the invention aims to find out the possibility in the prior art, provides an intelligent surrounding biological identification tracking method, aims to provide a basic basis for guaranteeing the safety of airport ground, improves the operation level and efficiency of related work units, stores and analyzes the operation level and efficiency, and provides support for follow-up data statistics.
The intelligent enclosure biological recognition tracking method comprises an enclosure detection module, a camera, a data analysis module, a remote communication module and a solar charging module, and can be correspondingly adjusted according to actual conditions, so that automatic monitoring alarm and biological recognition storage record of the airport enclosure are realized, the cost is reduced, workers are liberated from complex manual inspection work, the working center of gravity is changed to more reasonable analysis and future prevention planning, and the integral efficiency and safety guarantee of the airport are improved.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure;
FIG. 1 is a flowchart of an intelligent enclosure biometric tracking method provided by an embodiment of the invention;
FIG. 2 is a schematic diagram of an intelligent enclosure biometric tracking system provided by an embodiment of the present invention;
FIG. 3 is a schematic diagram of boundary detection according to an embodiment of the present invention;
FIG. 4 is a schematic view of a perimeter linked spherical camera in accordance with an embodiment of the present invention;
FIG. 5 is a schematic diagram of a data analysis method according to an embodiment of the present invention;
FIG. 6 is a schematic illustration of telecommunications of an embodiment of the present invention;
FIG. 7 is a schematic diagram of a solar charging module according to an embodiment of the invention;
FIG. 8 is a schematic diagram of a background storage control module according to an embodiment of the present invention;
in the figure: 1. a perimeter detection module; 2. a spherical camera; 3. a data analysis module; 4. a remote communication module; 5. a solar charging module; 6. and the background storage control module.
Detailed Description
In order that the above objects, features and advantages of the invention will be readily understood, a more particular description of the invention will be rendered by reference to the appended drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be embodied in many other forms than described herein and similarly modified by those skilled in the art without departing from the spirit or scope of the invention, which is therefore not limited to the specific embodiments disclosed below.
Embodiment 1 as shown in fig. 1, the intelligent surrounding biological identification tracking method provided by the embodiment of the invention includes:
s1, an enclosure detection module senses an external intrusion enclosure signal through a sensor and converts the external intrusion enclosure signal, the converted signal is transmitted to information processing equipment, the information processing equipment is utilized to screen and identify the signal, intrusion behaviors are found out, and an alarm is given;
it can be understood that the sensor is used as a physical quantity conversion device, and can convert physical quantities such as pressure, vibration, displacement, sound, temperature, light intensity and the like generated during invasion into electrical signals and electrical parameters which are easy to process;
the information processing equipment performs screening identification, and the finding out of the intrusion behavior to alarm comprises the following steps: comparing the signal detected by the sensor with a preset reference signal, namely comparing the continuously-changed analog signal output by the sensor with the value of the reference signal through a comparator, if the signal is smaller than the reference signal, the signal is considered to be an interference introduction but not an intrusion signal, and if the signal exceeds the reference value, the signal is considered to be an intrusion behavior occurrence signal, so that the real intrusion behavior is found out to alarm;
s2, monitoring is carried out through a linked spherical camera, after the camera is positioned to a position, zooming is carried out by the camera, and track tracking is carried out in real time, so that automatic snapshot, tracking and rechecking are realized;
the system is configured with an association relation between a sensor and the camera in advance, after determining that a signal fed back by a certain sensor is an intrusion signal, the system mobilizes the spherical camera associated with the sensor to monitor and enable the spherical camera to rotate, and after rotating and positioning the spherical camera to a specific position, the camera automatically zooms, zooms and amplifies a target image, enables the focal length of the lens to change, and enlarges and presents a monitored target, and tracks in real time, wherein the track tracking comprises: when a monitored target moves, based on a monitoring principle of pixel change, a lens moves along with the target, a record moving track is transmitted to an intelligent surrounding biological recognition tracking system, the system receives and records the moving track, and a camera automatically captures an invader photo and transmits the photo to a background for storage, so that automatic capturing, tracking and rechecking are realized.
S3, the data analysis module identifies and distinguishes the type of the organism by analyzing the characteristic data, and based on the intelligent biological identification technology, the data of the collected organism is utilized to identify the type of the organism;
illustratively, the type of organism is identified and distinguished by analyzing features, i.e., physiological features such as appearance, structure, coat, etc., behavioral features such as gait, sound, motion, etc. Based on intelligent biological recognition technology, the intelligent biological recognition system is closely combined with optical, acoustic, biological principles and the like through a computer, and is identified and authenticated according to the specific biological characteristics among each category, each characteristic of various organisms is maintained in a system database in advance as basic data, and when the surrounding intrusion occurs, the biological category recognition judgment is carried out by utilizing the biological data collected by the front end; the data collected by the sensors and the cameras are combined with the snap shots, biological characteristics of the snap shots are detected, including appearance characteristics, color characteristics, sound characteristics, action characteristics and the like, and the characteristics are compared with basic data characteristics in a database, so that which living beings belong to are identified.
S4, the remote communication module transmits the acquired information to the background storage control module through a network and receives a control signal of the background storage control module;
s5, the solar charging module converts solar energy into electric energy by utilizing the photoelectric effect of the semiconductor material and stores the electric energy to supply power for the sensor and the spherical camera.
In step S1 of the embodiment of the present invention, the enclosure detection module attaches a sensor (front-end detection device) based on a vibration detection method (i.e., converting the detected vibration amount into a mechanical signal) to the enclosure, the sensor can sense the mechanical vibration of the enclosure caused by the intrusion behavior, converts the generated mechanical vibration signal into an electrical signal, and sends the electrical signal to the information processing device, and the information processing device finally finds out the real intrusion alarm information and alarms through processing and screening the mechanical vibration signals.
In the embodiment of the invention, the information processing equipment analyzes each mechanical vibration characteristic transmitted back by the vibration sensor through a big data model, and determines the amplitude and the intensity of vibration by detecting the value of the vibration signal in combination with the weather information at the time. And comparing the amplitude and the intensity of vibration through cloud computing, and comparing whether the collected mechanical vibration characteristics transmitted by adjacent or all vibration sensors are consistent or fluctuate within a reasonable range, so as to judge whether the mechanical vibration is abnormal.
In an embodiment of the present invention, the analysis of each mechanical vibration characteristic transmitted back by the vibration sensor by the big data model includes: collecting a large amount of data from a sensor and performing data preprocessing, the preprocessing comprising: the signals output by the sensor are suppressed in interference signals such as electrostatic shielding, low-frequency magnetic shielding, electromagnetic shielding and the like, and detected nonlinearity, gain errors and zero errors are modified and compensated, so that the linearity and measurement accuracy of the detection are improved.
In step S2 of the embodiment of the present invention, after the intrusion alarm is performed by the enclosure detection module, the system links the spherical camera to monitor, and when the spherical camera is positioned at a specific position, the zoom is performed, the track tracking is performed in real time, so as to realize automatic snapshot, tracking and rechecking, and perform automatic video recording storage, without searching manually, and reduce labor cost.
In step S3 of the embodiment of the present invention, the kind of organism is identified and discriminated by analyzing the characteristics. Its biological characteristics include appearance, behavior, sound, male-female difference, etc., and identify different biological species. And records these features as metadata. The aim of automatically identifying organisms by collecting various information is fulfilled.
In step S4 of the embodiment of the present invention, the remote communication module converts various information into electrical signals by using the sensor and transmits the electrical signals to the background storage control module through the network, so that the remote communication module has the function of sending sound, photos, videos, etc. collected through the front end. The method is responsible for transmitting the processed signals to the background storage control module through a network and receiving control signals of the background storage control module.
The background storage control module is mainly used for receiving and storing various data transmitted by the front end, including detection and analysis processes and analysis results, so as to form a large database, wherein the data can be used for historical review and statistical analysis, and a targeted prevention and treatment scheme is formulated.
In step S5 of the embodiment of the present invention, the solar charging module may supplement electric energy for the sensing device and the camera based on solar power supply. The solar power supply utilizes the photoelectric effect of the semiconductor material to convert solar energy into electric energy, stores the electric energy, supplies power to the front-end sensing device and the camera, and can save electric energy consumed by airports.
Through the embodiment, the technical scheme of the invention solves the technical problems that people always want to solve but still fail to obtain success: the sensor product has high economical efficiency, simple signal output and convenient use, can be very conveniently used by loading the sensor into the periphery, forms complementary linkage with the camera, tracks and shoots the camera in real time, actively warns when an intrusion target appears, tracks, snapshots, recognizes and records the target in real time, and achieves the effect of comprehensive distribution and control of the airport periphery.
Embodiment 2 as shown in fig. 2, the intelligent enclosure biometric tracking system provided in the embodiment of the present invention includes:
the enclosure detection module 1 attaches a sensor (i.e. front end detection equipment) based on a vibration detection method to the enclosure, the sensor can sense the mechanical vibration of the enclosure caused by intrusion behaviors, converts the generated mechanical vibration signals into electric signals, sends the electric signals to the information processing equipment, and finally finds out real intrusion alarm information and alarms through processing and screening the mechanical vibration signals. The information processing equipment analyzes each mechanical vibration characteristic transmitted back by the vibration sensor through the big data model, and compares the mechanical vibration characteristics transmitted by the adjacent or all vibration sensors through cloud computing by combining the weather information at the time so as to judge whether the mechanical vibration is abnormal. The reliability and the accuracy of information processing are improved, and the false alarm rate of the system is reduced.
After the surrounding detection module 1 performs intrusion alarm, the system is linked with the spherical camera 2 to monitor, the spherical camera can clearly monitor scenes within a range of 200 meters, the camera can zoom, rotate inside to enable the visual field to become larger, and the spherical camera is arranged to automatically snapshot and record video. FIG. 3 is a schematic diagram of the enclosure detection according to an embodiment of the present invention; FIG. 4 is a schematic view of a perimeter linked spherical camera in accordance with an embodiment of the present invention;
a data analysis module 3 for identifying and discriminating the species of organism by analyzing the features. Its biological characteristics include appearance, behavior, sound, male-female difference, etc., and identify different biological species. The intelligent biotechnology-based identification technology can utilize various sensing sensors at the front end, such as acoustic sensors, visual sensors, motion sensors and cameras to collect biological data. The signals collected by these sensors can be used to detect biological characteristics, including appearance characteristics, color characteristics, sound characteristics, motion characteristics, etc., and compare these characteristics to those in a database to identify which organism belongs to. And record these features. The method can automatically identify organisms by collecting various information, and can provide more accurate and comprehensive species identification by performing big data processing. And the AI learning technology is utilized to continuously optimize and improve the system identification function. The AI learning technology can construct an accurate biological recognition model, and the data collection, pretreatment and processing are modeled, so that the system is automatically regulated by continuously collecting information on the basis of the modeling. Fig. 5 is a schematic diagram of a data analysis method according to an embodiment of the invention.
The remote communication module 4 connects the sensor with the background storage control module 6, which is formed by integrating a communication chip, a storage chip and the like on a circuit board, and the remote communication module converts various information into electric signals by using the sensor and transmits the electric signals to the background storage control module through a network, so that the remote communication module has the functions of sending sound, photos, videos and the like collected through the front end. The method is responsible for transmitting the processed signals to the background storage control module through a network, receiving the control signals of the background storage control module 6 and realizing the integrated flow of remote monitoring, control and management analysis. Wherein fig. 6 is a schematic diagram of remote communication according to an embodiment of the present invention.
The solar charging module 5 is used for supplementing electric energy for the sensing device based on solar power supply and the spherical camera 2 through a solar panel. The solar power supply utilizes the photoelectric effect of semiconductor materials to convert solar energy into electric energy, stores the electric energy and supplies the electric energy to the front-end sensing device and the camera, so that the problem that the traditional sensor adopts a field wired power-taking mode to supply power to electric devices in the sensor and is limited by working environment is solved, and the problems that the battery mode sensor is adopted but the built-in battery has small capacity and cannot supply power in time are solved; the problem of frame dropping at key moment of the camera is solved, and the camera is updated to be uninterrupted video for 24 hours. And can save the airport consumption electric energy. Fig. 7 is a schematic diagram of a solar charging module according to an embodiment of the invention.
The background storage control module 6 is configured to receive and store various data transmitted from the front end, including a process of detecting the data and analyzing the data, and store the analysis result to form a large database, where the data can be used for historical review, and support querying of species information intruded at a certain position at a certain moment in the query history. Meanwhile, all-weather biological data of the surrounding area of the airport is accumulated for statistical analysis, so that the method is used for analyzing the activity rule of organisms and guiding the airport to carry out scientific and reasonable biological prevention work. And executing punishment results for intruders, and formulating a targeted control scheme for species with top category ranks. FIG. 8 is a schematic diagram of a background storage control module according to an embodiment of the invention.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
The content of the information interaction and the execution process between the devices/units and the like is based on the same conception as the method embodiment of the present invention, and specific functions and technical effects brought by the content can be referred to in the method embodiment section, and will not be described herein.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, the specific names of the functional units and modules are only for distinguishing from each other, and are not used for limiting the protection scope of the present invention. For specific working processes of the units and modules in the system, reference may be made to corresponding processes in the foregoing method embodiments.
Based on the technical solutions described in the embodiments of the present invention, the following application examples may be further proposed.
According to an embodiment of the present application, the present invention also provides a computer apparatus, including: at least one processor, a memory, and a computer program stored in the memory and executable on the at least one processor, which when executed by the processor performs the steps of any of the various method embodiments described above.
Embodiments of the present invention also provide a computer readable storage medium storing a computer program which, when executed by a processor, performs the steps of the respective method embodiments described above.
The embodiment of the invention also provides an information data processing terminal, which is used for providing a user input interface to implement the steps in the method embodiments when being implemented on an electronic device, and the information data processing terminal is not limited to a mobile phone, a computer and a switch.
The embodiment of the invention also provides a server, which is used for realizing the steps in the method embodiments when being executed on the electronic device and providing a user input interface.
Embodiments of the present invention also provide a computer program product which, when run on an electronic device, causes the electronic device to perform the steps of the method embodiments described above.
The integrated units, if implemented in the form of software functional units and sold or used as stand-alone products, may be stored in a computer readable storage medium. Based on such understanding, the present application implements all or part of the flow of the method of the above embodiments, and may be implemented by a computer program to instruct related hardware, where the computer program may be stored in a computer readable storage medium, where the computer program, when executed by a processor, may implement the steps of each of the method embodiments described above. Wherein the computer program comprises computer program code which may be in source code form, object code form, executable file or some intermediate form etc. The computer readable medium may include at least: any entity or device capable of carrying computer program code to a photographing device/terminal apparatus, recording medium, computer Memory, read-Only Memory (ROM), random access Memory (Random Access Memory, RAM), electrical carrier signals, telecommunications signals, and software distribution media. Such as a U-disk, removable hard disk, magnetic or optical disk, etc.
While the invention has been described with respect to what is presently considered to be the most practical and preferred embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but on the contrary, is intended to cover various modifications, equivalents, and alternatives falling within the spirit and scope of the invention.
Claims (10)
1. An intelligent surrounding biological identification tracking method is characterized by comprising the following steps:
s1, a surrounding detection module (1) senses external intrusion surrounding signals through a sensor and converts the external intrusion surrounding signals, the converted signals are transmitted to information processing equipment, the information processing equipment is used for screening and identifying the signals, intrusion behaviors are found out, and an alarm is given;
s2, monitoring is carried out through the linked spherical camera (2), after the camera is positioned to the position, zooming is carried out on the camera, and track tracking is carried out in real time, so that automatic snapshot, tracking and rechecking are realized;
s3, the data analysis module (3) identifies and distinguishes the type of the organism by analyzing the characteristic data, and based on the intelligent biological identification technology, the type of the organism is identified by utilizing the collected biological data;
s4, the remote communication module (4) transmits the acquired information to the background storage control module (6) through a network and receives a control signal of the background storage control module (6);
s5, the solar charging module (5) converts solar energy into electric energy by utilizing the photoelectric effect of the semiconductor material and stores the electric energy to supply power for the sensor and the spherical camera (2).
2. The intelligent enclosure biological recognition tracking method according to claim 1, wherein in step S1, the sensor adopts a physical quantity conversion device to convert the physical quantity of pressure, vibration, displacement, sound, temperature and light intensity generated during intrusion into an electric signal and an electric parameter;
the information processing equipment is utilized to screen and identify the signals, find out the intrusion behavior and alarm, and the method comprises the following steps: comparing the continuously-changing analog signal output by the sensor with the value of the reference signal through a comparator, and if the analog signal is smaller than the reference signal, introducing interference instead of invading the signal; if the signal exceeds the reference signal, the signal is an intrusion behavior occurrence signal, so that the true intrusion behavior is found out to alarm.
3. The intelligent enclosure biological recognition tracking method according to claim 1, wherein in step S1, an enclosure detection module (1) attaches a sensor based on a vibration detection method to an enclosure, the sensor senses enclosure mechanical vibration caused by intrusion behavior, converts a generated mechanical vibration signal into an electrical signal, and sends the electrical signal to an information processing device, and the information processing device finds out real intrusion alarm information and alarms through processing and screening the mechanical vibration signal;
the information processing equipment analyzes each mechanical vibration characteristic transmitted back by the vibration sensor through a big data model, and determines the amplitude and the intensity of vibration by detecting the value of a vibration signal in combination with the weather information at the time; and comparing the amplitude and the intensity of vibration through cloud computing, and comparing whether the collected mechanical vibration characteristics transmitted by adjacent or all vibration sensors are consistent or fluctuated within a set range, so as to judge whether the mechanical vibration is abnormal.
4. The intelligent perimeter biometric tracking method of claim 3, wherein the big data model analyzes each mechanical vibration signature transmitted back by the vibration sensor, comprising: collecting data brought by a sensor and preprocessing the data; and suppressing interference signals of signals output by the sensor, and modifying and compensating the detected nonlinearity, gain error and zero error.
5. The intelligent enclosure biological recognition tracking method according to claim 1, wherein in step S2, track tracking is performed in real time to realize automatic snapshot, tracking and rechecking, and the method comprises the following steps:
the method comprises the steps that an association relation between a sensor and a camera is pre-configured, after a signal fed back by a certain sensor is determined to be an intrusion signal, a spherical camera (2) associated with the sensor is mobilized to monitor, the spherical camera (2) rotates, when the rotation is positioned to a specific position, the camera automatically zooms, zooms and amplifies a target image, the focal length of a lens is changed, the monitored target is amplified and presented, and track tracking is performed in real time;
the trajectory tracking includes: when the monitored target moves, based on the monitoring principle of pixel change, the lens moves along with the target, the record moving track is transmitted to the system, the system receives and records the moving track, the camera automatically captures the photo of the invader, and the photo is transmitted to the background for storage, so that automatic capturing, tracking and rechecking are realized.
6. The intelligent perimeter biometric tracking method according to claim 1, wherein in step S3, the biometric category identification using the data of the collected living beings comprises: comparing biometric data including appearance features, color features, sound features, motion features with feature data in a database to identify which creature belongs to; collecting biological data by using an acoustic sensor, a visual sensor, a motion sensor and a spherical camera (2) based on an intelligent biotechnology identification technology, wherein signals collected by the sensors are used for detecting biological characteristics, and the characteristics are recorded as metadata; the AI learning technology is used for constructing a biological recognition model, and an acoustic sensor, a visual sensor, a motion sensor and a spherical camera (2) are automatically adjusted.
7. The intelligent enclosure biometric tracking method according to claim 1, wherein in step S4, the remote communication module (4) converts the information into electrical signals using sensors, transmits the electrical signals to the background storage control module (6) via a network, and transmits the collected sound, photo, video.
8. The intelligent perimeter biological identification tracking method according to claim 7, wherein the background storage control module (6) receives and stores the transmitted data, detects and analyzes the transmitted data, stores the analysis result, and forms a large database, and the data in the large database is used for historical review and statistical analysis to formulate a control scheme.
9. An intelligent perimeter biometric tracking system, wherein the system implements the intelligent perimeter biometric tracking method of any one of claims 1-8, the system comprising:
the surrounding detection module (1) senses an external invasion surrounding signal through a sensor and converts the external invasion surrounding signal, the converted signal is transmitted to the information processing equipment, the information processing equipment is utilized to screen and identify the signal, and invasion behaviors are found and alarm is given;
after the spherical camera (2) is positioned to the position, the camera zooms, tracks in real time, and automatic snapshot, tracking and rechecking are realized;
a data analysis module (3) for identifying and discriminating the type of the living being by analyzing the characteristic data, and performing the biological type recognition by using the data of the collected living being based on the intelligent biological recognition technology;
the remote communication module (4) transmits the acquired information to the background storage control module (6) through a network and receives a control signal of the background storage control module (6);
the solar charging module (5) is used for converting solar energy into electric energy by utilizing the photoelectric effect of the semiconductor material and storing the electric energy to supply power for the sensor and the spherical camera (2);
the background storage control module (6) is used for receiving and storing the transmitted data, storing the detection data and the analysis process and the analysis result, and forming a large database for history review; meanwhile, all-weather biological data of the peripheral area of the airport is accumulated for statistical analysis, so that the activity rule of organisms is analyzed, and a biological prevention scheme is provided.
10. The intelligent enclosure biometric tracking system of claim 9, wherein the enclosure detection module (1) is further configured to mate with an electromagnetic coil on the ground, and to provide audible and visual alarms and searchlight for the on-site linked treatment device.
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