41 results about "Perimeter Security" patented technology

The invention discloses a regional security management system based on multi-source data fusion, and relates to the technical field of security management. The system comprises a security intrusion detection model, a perimeter security linkage module and a security disposal effect evaluation module. According to the method, after key safety intrusion area marking is carried out on the designated area, when the perimeter safety condition of the designated area is monitored in real time, multi-source data is input into the designated safety intrusion detection model for analysis, the intrusion detection result containing the existence of the intrusion object and the perimeter safety is output, and if the intrusion object exists, the intrusion detection result is output. If yes, a perimeter security alarm mechanism is triggered immediately to take security linkage measures, and after security disposal is finished, security disposal effect evaluation is carried out to determine whether intrusion detection qualification verification is carried out or not, so that the security management efficiency of the perimeter of the specified area is improved, and the security of the specified area is ensured. The problem that in the prior art, when safety intrusion detection is carried out on the area perimeter, linkage synchronism of alarm and emergency response is poor is solved.

The invention discloses a lightweight optical fiber vibration intrusion event identification method and system for perimeter security and protection, and belongs to the technical field of optical fiber sensing technology and mode identification, and the method comprises the steps: collecting an original vibration signal of a perimeter monitoring region through a distributed optical fiber vibration sensing system; performing wavelet threshold de-noising preprocessing on the original vibration signal to obtain a de-noised signal; performing feature extraction on the denoised signal, and constructing a high-dimensional feature vector; performing dimension reduction processing on the high-dimensional feature vector by using a linear discriminant analysis method to obtain a low-dimensional classification feature vector; and inputting the low-dimensional classification feature vector into a pre-trained lightweight convolutional neural network model for classification and identification, and outputting a corresponding intrusion event category. According to the method, through cooperation of front-end LDA dimension reduction and a rear-end lightweight network, the model parameter quantity and calculation overhead are greatly reduced while high recognition precision is guaranteed, efficient real-time deployment on edge equipment is achieved, and the method is suitable for intrusion detection in perimeter security and protection.

The invention belongs to the technical field of distributed optical fiber sound wave sensing and artificial intelligence, and discloses a CNN-GRU-based DAS perimeter security real-time intrusion identification method, which comprises the following steps: extracting an original time sequence signal acquired by a DAS perimeter security system; performing S transformation on the original time sequence signal to obtain a two-dimensional time-frequency spectrum; 3, the two-dimensional time-frequency spectrum obtained through S transformation is input into a trained CNN-GRU network, the prediction probability is output through the CNN-GRU network, and the CNN-GRU network comprises a CNN network, an expansion layer, a first-layer GRU unit, a second-layer GRU unit, a full connection layer and a Softmax layer which are connected in sequence; and according to the prediction probability output by the CNN-GRU network, whether intrusion occurs and the intrusion type are judged. According to the method, efficient identification and classification of DAS intrusion signals can be realized, and the front-end processing complexity is remarkably reduced.

The embodiment of the invention provides a perimeter security system detection method and device, electronic equipment and a storage medium, and relates to the technical field of security. The method comprises the following steps: acquiring a first video obtained by shooting a perimeter detection area by a perimeter security system; superposing the target animation on the first video to obtain a second video, the target animation being an animation matted from a third video and moving the first sample object towards a preset direction, and the third video being shot by other devices except the perimeter security system; obtaining a judgment result whether the behavior of the first sample object in the second video can trigger the perimeter security system to give an alarm; inputting the second video into a perimeter security system for perimeter detection, and observing whether the perimeter detection triggers the perimeter security system to give an alarm or not to obtain an observation result; and if the judgment result is inconsistent with the observation result, determining that the perimeter security system is abnormal. According to the application, the reliability of the perimeter security and protection system is improved, and the operation and maintenance cost is reduced at the same time.

The invention relates to the technical field of rail transit perimeter safety protection, and discloses a rail transit station perimeter intrusion logic early warning system, which comprises a detection point location network, a topology modeling module and a logic arbitration module, the topology modeling module constructs a grid topology model according to the physical coordinates of the point locations, and sets the detection point locations in the non-sensitive area as silent reference nodes; the logic arbitration module obtains real-time trigger data of a detection point location, calculates a cross-correlation characteristic value of a to-be-identified point location and a silent reference node, deducts a common-mode component in a characteristic signal flow when environment interference is identified, extracts a transient envelope fingerprint, matches a displacement continuity evolution rule, and outputs an alarm instruction. According to the method, coherent disturbance caused by train passing or electromagnetic discharge is stripped from an original signal by establishing an environment background interference reference, systematic false alarm is effectively inhibited, and accurate identification of an intrusion track in a complex random noise environment is realized.

The invention relates to the field of intelligent fences, and particularly discloses an intelligent fence system based on LORA networking, which constructs a low-cost and wide-area ad hoc network composed of a plurality of highly integrated intelligent fence devices. Each fence device serves as an independent terminal, and a control panel, a battery module, a Hall sensor and a fence telescopic belt are integrated in a cylindrical shell of each fence device. The key point is that an LORA communication module is integrated on the control panel instead of a traditional WiFi or 4G module. Therefore, numerous fence devices can automatically form a private long-distance wireless network, the fence devices can be accessed to the Internet only through one LORA gateway, and low-cost and high-efficiency perimeter security and protection are realized.

The application discloses a multi-dimensional perimeter security invasion event recognition method and recognition system, comprising: acquiring a phase-modulated interference signal by using a double Mach-Zehnder interferometer to construct a one-dimensional time sequence signal of an invasion event; converting the one-dimensional time sequence signal into a GPS signal and a two-dimensional time-frequency signal; a UAV shoots a video according to the GPS signal to form a three-dimensional video signal; an industrial computer performs synchronous recognition of the invasion event on the two-dimensional time-frequency signal and the three-dimensional video signal in a multi-dimensional feature extraction deep learning network which has been trained, multiplies the confidence of each type of event obtained and normalizes the confidence, and outputs an event with the maximum confidence as a final recognized event. The application not only extracts features of an invasion event by using an optical signal, but also extracts features by using a video signal shot by a UAV, multi-dimensionally describes the invasion event, widens the number of detectable invasion events, increases the pattern recognition accuracy, and increases the reliability of the system.

1. The name of the design product is: graphical user interface for perimeter security management of electronic equipment. 2. The use of the design product is: for display and human-computer interaction. 3. The design points of the design are: the graphical user interface content in the screen. 4. The picture or photo that best indicates the design points is: the front view. 5. The interface use is: the graphical user interface is used to show the interaction interface of air field security scene information, alarm statistical information, security equipment state information and other functions. The front view is the initial interface in the open state; click the "perimeter intrusion prevention" control of the front view to enter the interface change state diagram 1; in the interface change state diagram 1, move the mouse to the right side corresponding to the "alarm information" column content and stay, and the content of the interface change state diagram 2 will pop up.

1. The name of the design product: electronic fence pulse host. 2. The use of the design product: for perimeter security. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.

This invention provides a system and method integrating perimeter security and underground monitoring, relating to the fields of engineering safety monitoring and intelligent security technology. The system includes: a data acquisition module, a time synchronization module, a data processing module, and an alarm module. The data acquisition module includes multiple sensors deployed at different locations within the monitoring area, which collect vibration data at their respective locations. The time synchronization module synchronizes the vibration data transmitted by each sensor. The data processing module detects perimeter intrusion events and calculates relative changes in seismic velocity based on the vibration data. The data processing module also sends a corresponding alarm command to the alarm module when a perimeter intrusion event is detected or when the relative change in seismic velocity meets preset conditions. The alarm module executes corresponding alarm actions based on the alarm command. This invention can simultaneously and continuously monitor surface activity and underground mechanical conditions with reliable monitoring performance.

The application utilizes piezoelectric energy storage sensors to perceive the stress distribution change of the surrounding environment of key places, integrates the electrical signals generated by piezoelectric effect, and starts the perimeter security system when the threshold is exceeded, and realizes perimeter security recognition through pattern recognition and other means. The passive sensor mechanism proposed in the application can effectively reduce the energy consumption required for the perimeter security system to maintain the on state when there is no intrusion event. The electrical signals generated by the piezoelectric energy storage sensor can be used as input signals to start the system, and also have signal acquisition function. With the energy storage system, it is expected to provide energy supplement for the perimeter security system. The application adopts a variety of passive stress sensors, and uses heterogeneous sensor data mutual verification to enrich the feature details of intrusion events, and greatly improves the intrusion event discrimination ability. At the same time, through the operation mode of "no abnormal standby, abnormal start" and the charging mode of "signal processing, energy storage", the running time of the passive perimeter security system is greatly improved, and a more feasible technical solution is provided for the super-long time continuous monitoring of the safety-related places.

The invention relates to an intelligent system for railway locomotive head perimeter panoramic safety monitoring, which comprises a plurality of fisheye camera modules arranged at the front end, the rear end and the side edge of a locomotive head and used for collecting real-time images of the bottom environment of the locomotive head; the image fusion module is used for fusing the real-time images obtained by the fisheye camera modules according to the positions of the fisheye camera modules to obtain a fused to-be-detected image; the intelligent detection module is used for receiving the fused to-be-detected image, performing target identification on a preset target in the to-be-detected image based on a pre-deployed artificial intelligence model, and performing position relation judgment on the detected target in a three-dimensional space of the locomotive head; and the early warning module is used for giving corresponding alarms according to different results of position relation judgment.

This invention relates to a vision-based method and system for identifying and classifying the boundary crossing behavior of intelligent agents in oilfield electronic fences. Belonging to the fields of oilfield perimeter security and computer vision technology, it addresses the problems of existing electronic fences, such as inability to identify target types, inability to quantify boundary crossing risks, single warning levels, and low system integration. The method involves target detection and continuous tracking of oilfield perimeter image data to obtain target type and movement trajectory. Boundary crossing verification is performed on the target's center position based on a polygonal electronic fence, and the boundary crossing distance from the target to the fence boundary is calculated. This distance is then fused with target type risk weights to obtain an adjusted boundary crossing distance. Classified warnings are implemented based on preset thresholds. Simultaneously, the warning information is visualized and logged, achieving accurate identification and differentiated warnings for boundary crossing behavior. This invention is applicable to perimeter security monitoring and intelligent risk warning in complex environments such as oilfield mining areas, well sites, and oil and gas storage areas.

The application discloses a method for reducing the false alarm rate of biological induction perimeter alarm, and particularly relates to the field of infrared induction technology; background temperature data of a monitoring area is acquired, a background thermal field benchmark model is constructed, and a background benchmark temperature value is calculated; current background temperature is acquired according to a preset time interval, and a dynamic background temperature difference drift rate is calculated; heat source change information is extracted from a thermal imaging image sequence, the variance of the heat source change in a time window is calculated, and the stability of the static heat source signal is obtained; the above two features are normalized, and a feature parameter set is constructed; the set is input into a fuzzy logic reasoning model, a PIR sensor signal credibility parameter is output according to a preset fuzzy rule; according to the credibility result, an alarm judgment path is dynamically selected, intelligent fusion and judgment of the PIR signal and the video recognition result are realized; the method can effectively identify the PIR false triggering risk in a complex thermal environment, reduce the false alarm rate, and improve the reliability and adaptability of the perimeter security system.

The application belongs to the technical field of airport perimeter security monitoring, and discloses an airport perimeter hierarchical early warning linkage method and system based on fuzzy logic reasoning. The method generates infrared and visible light panoramic images through panoramic scanning of the airport perimeter, detects and identifies the intrusion targets in the perimeter defense area in the infrared and visible light panoramic images through a multi-modal target detection algorithm based on deep learning, divides the intrusion target warning levels through a fuzzy logic algorithm, judges the priority of the intrusion target warning levels, uses an OPENCV algorithm library to mark the trajectories of multiple coordinate points closest to the intrusion target in the perimeter panoramic base map, displays the motion trajectory of the current intrusion target, and judges the intention of the intrusion target. The application can adapt to different airport environments through the self-optimization capability of the rule base, reduce the artificial patrol load while ensuring high reliability, and enhance the intelligent level and safety and control efficiency of the perimeter security system.

The invention relates to the technical field of radars, in particular to a radar and multi-camera combined perimeter security monitoring device and method, and the device comprises a radar module which is used for detecting a perimeter monitoring region and obtaining the target point cloud data of a target object; the visual camera module comprises a plurality of long-focus cameras which are connected in parallel, and the plurality of long-focus cameras are configured in a manner that field angles of the plurality of long-focus cameras are jointly spliced so as to cover a preset azimuth range of the perimeter monitoring area and output video data in the preset azimuth range; and the processing module is used for receiving the target point cloud data of the radar module and the video data of the visual camera module, and performing coordinate conversion and data fusion processing on the target point cloud data and the video data so as to realize real-time monitoring and identification of the target. According to the scheme, the time delay of the cameras can be reduced through splicing of multiple groups of long-focus cameras and combination of the radar, so that the monitoring efficiency of the perimeter area is improved.

The invention discloses a method for reducing the false alarm rate of biological induction perimeter alarm, and particularly relates to the technical field of infrared induction. Acquiring background temperature data of a monitoring area, constructing a background thermal field reference model and calculating a background reference temperature value; obtaining a current background temperature according to a preset time interval, and calculating a dynamic background temperature difference drift rate; heat source change information is extracted through the thermal imaging image sequence, the change variance of a heat source in a time window is calculated, and the static heat source signal stability is obtained; performing normalization processing on the two features, and constructing a feature parameter set; inputting the set into a fuzzy logic reasoning model, and outputting PIR sensor signal credibility parameters according to a preset fuzzy rule; according to a credibility result, an alarm determination path is dynamically selected, and intelligent fusion and determination of a PIR signal and a video identification result are realized; according to the method, the PIR false triggering risk in the complex thermal environment can be effectively identified, the false alarm rate is reduced, and the reliability and adaptability of a perimeter security system are improved.

The invention discloses a tower perimeter security and protection method and system based on multi-view fusion, relates to the field of high-voltage power transmission infrastructure security and protection, and aims to solve the problems of limited monitoring range, low recognition precision, rigid alarm and difficulty in deployment, operation and maintenance of an existing tower security and protection system. The method comprises the steps of video acquisition, preliminary screening of motion, target detection and tracking, dynamic defense area decision making and the like, is suitable for a remote scene without commercial power, and can realize accurate and intelligent security and protection of the periphery of a tower. The system comprises a multi-view perception layer, an edge calculation and communication layer, a cloud intelligent analysis platform and an intelligent power supply layer, wherein the multi-view perception layer realizes 360-degree dead-angle-free coverage through a high-definition intelligent camera; the edge calculation unit executes motion detection, improved YOLOv8 target detection and single-camera tracking; the cloud platform realizes cross-camera target association through a graph neural network, and dynamically adjusts the defense area level; the intelligent power supply layer ensures long-term field operation.

The invention relates to the technical field of perimeter security monitoring, and discloses a perimeter intrusion monitoring method based on an optical fiber sensing technology, and the method comprises the steps: deploying a main sensing optical cable according to a perimeter contour to form a first monitoring surface and a second monitoring surface which is not coplanar with the first monitoring surface, and enabling a vibration optical fiber host to emit a laser signal along the sensing optical cable, the sensing optical cable converts a vibration signal into scattered return light and transmits the scattered return light back to the vibration optical fiber host, the vibration optical fiber host sequentially performs photoelectric conversion processing and acquisition analysis on the returned scattered return light to finally obtain a suspected intrusion signal, and a suspected intrusion grading signal set in a specified time period is obtained in an equal period. Based on core data of a suspected intrusion grading signal set, an AI algorithm can be used for generating an intrusion fitting track after suspected intrusion point location grouping, the intrusion fitting track is judged, effective intrusion behaviors are judged and positioned, and an intrusion grading alarm result is obtained.

The invention relates to the technical field of perimeter security and protection, in particular to a tension type electronic fence perimeter intrusion prevention device and method.The device is characterized in that an electronic fence tension line is connected with an automatic tightening spring, an alarm host and a functional vertical rod, the alarm host is connected with an area management machine, and the area management machine is connected with a management computer; the functional vertical rod is connected with the alarm host. The alarm host detects the tension change and generates an alarm signal; the automatic tightening spring is used for unidirectionally tightening the electronic fence tension wire; the electronic fence tension line is used for completing tension calibration and carrying out intrusion and broken line detection; the functional vertical rod provides support; the area management machine is used for periodically waking up the alarm host, receiving the alarm signal and forwarding the alarm signal to the management computer; the management computer is used for system parameter configuration, operation state monitoring, alarm information processing and data storage management. Therefore, the problems that in the prior art, routing inspection and maintenance need to be conducted frequently, and the deterrent ability of a high-voltage pulse type perimeter system is lacked are solved.

The utility model relates to the technical field of security and protection in the planting industry, in particular to a perimeter security and protection system for protecting high-value commercial crops, which comprises a plurality of perimeter security and protection units, and a solar panel, a power management module and a lithium battery are mounted at the top of the overground part of each perimeter security and protection unit. An infrared sensor, an identity collector, an acoustic optical driver isolation module and an ultrasonic transmitter are installed on the side face in the overground part, and a core control chip, a 4G / NB communication module and a wireless Mesh networking module are further installed in the overground part. A micro-seismic sensor and a seismic wave simulation device are mounted in the underground part of the perimeter security unit; the system can detect overground targets and underground targets at the same time, achieves full-time and full-domain no snake and mouse damage in a planting area, is matched with a record identity card, effectively distinguishes persons allowed to enter, completely avoids false alarm and false driving, and achieves timely and effective protection of growing high-value commercial crops.

This invention relates to a BeiDou satellite positioning-assisted safety protection system and method for hydropower facilities, aiming to improve the structural safety and surrounding safety protection capabilities of hydropower facilities. The system includes a satellite monitoring subsystem, a perimeter monitoring subsystem, a ground differential station, and a safety protection server. The satellite monitoring subsystem receives real-time positioning signals from the BeiDou satellite and parameters such as displacement and settlement of the hydropower facility area. The ground differential station performs differential correction on the satellite signals to improve positioning accuracy. The perimeter monitoring subsystem monitors the safety data around the hydropower facility in real time. The safety protection server performs weighted processing on the data from the satellite and the perimeter monitoring subsystem, determines whether an anomaly has occurred by setting a threshold, and automatically adjusts the accuracy, frequency, range, or duration of the monitoring equipment when the threshold is exceeded. When the data from both subsystems exceed the threshold, the system triggers an emergency alarm. This invention can ensure the safe operation of hydropower facilities in unattended or remote application scenarios.

The application discloses a light-weighted optical fiber vibration intrusion event identification method and system for perimeter security, belongs to the field of optical fiber sensing technology and pattern recognition technology, and comprises the following steps: collecting original vibration signals of a perimeter monitoring area through a distributed optical fiber vibration sensing system; performing wavelet threshold denoising pretreatment on the original vibration signals to obtain denoised signals; performing feature extraction on the denoised signals to construct a high-dimensional feature vector; performing dimension reduction processing on the high-dimensional feature vector by using a linear discriminant analysis method to obtain a low-dimensional classification feature vector; inputting the low-dimensional classification feature vector into a pre-trained light-weighted convolutional neural network model for classification and recognition, and outputting corresponding intrusion event categories. The application cooperates the front-end LDA dimension reduction with the rear-end light-weighted network, greatly reduces the model parameter quantity and the calculation cost while ensuring high recognition accuracy, realizes efficient and real-time deployment on an edge device, and is suitable for intrusion detection in perimeter security.

Embodiments of the disclosure can provide systems and methods for providing a deployable perimeter security apparatus. The apparatus can include a frame with a box-shape, including a first opposing side and a second opposing side; an anchor device operable to extend from a third side of the frame; a first intermediate panel operable to telescope from the first opposing side of the frame; a second intermediate panel operable to telescope from the second opposing side of the frame; one or more telescoping panels, each operable to telescope from a leading side of at least one intermediate panel; one or more lead folding panels, each operable to mount to a leading side of at least one telescoping panel; and one or more extension folding panels, each operable to mount to either an extended side of at least one lead folding panel or an extended side of another extension folding panel.

The invention discloses an iron tower safety monitoring and guaranteeing system, and the system comprises a human body induction sensor which is used for detecting whether a person gets close to an iron tower or not; the tilt angle sensor is used for detecting the tilt state of the iron tower; the loudspeaker is used for playing voice; the control unit is used for controlling the playing of the loudspeaker according to the detection information of the human body induction sensor and the tilt angle sensor; and the communication equipment is used for transmitting the detection information of each sensor to a remote monitoring terminal through a communication network. A plurality of monitoring devices for human body induction, inclination angle, vibration, wind speed, image acquisition and the like are integrated on the tower body, real-time and comprehensive on-line monitoring of the structure state, the operation environment and the surrounding safety condition of the iron tower is achieved, monitoring data are transmitted remotely, the safety state of the iron tower can be detected in real time, and when potential safety hazards occur, the safety of the iron tower is guaranteed. Early warning information is sent out in time, and safety accidents of equipment and personnel are prevented.

A kind of gas station perimeter security defense linkage processing method and system belong to intelligent security and industrial safety production technical field, solve the problem of high false alarm rate of gas station security system, cannot effectively distinguish legal operating personnel and illegal intruder and emergency response lag.This method includes: by constructing the time-space operation filtering mechanism based on work order data: real-time extraction production operation system in the time-space characteristics of operation, with the logic operation of captured invasion target coordinates, filter out the alarm signal caused by legal operation.Combined with the threat level of regional dangerous attribute and visual behavior characteristics, when judged as high-risk threat, automatically link the process safety system through bottom hardware mapping to execute defense action.Security system and production control system are logically integrated for active defense of gas station.The present application is suitable for natural gas gate station, LNG storage and distribution station, pressure regulating station and oil depot, etc., which have very high requirements for fire and explosion prevention and personnel control.

The present disclosure relates to protective building elements and methods of manufacturing and providing such protective building elements. Protective building elements as disclosed herein may be utilized in various applications related, but not limited to, those requiring protection of perimeter security devices and associated power and / or data connections from ballistic, blast and physical attack.

The invention relates to a machine and continuous learning technology, in particular to a method for continuously learning new data features and categories. According to the method, three strategies of elastic weight consolidation, no-forgetting learning and experience playback are combined, rapid adaptation and learning of the model to new type or variant data in an actual deployment environment are realized, and meanwhile, the original category recognition capability is kept. The technology is applied to optical fiber sensing early warning scenes such as long-distance pipeline safety monitoring and perimeter security, new data features and categories can be continuously learned in the system operation process, and timely recognition and early warning of novel threats are achieved in a distributed optical fiber sensing system.

The invention relates to the technical field of microwave radars, in particular to a control system of a microwave radar and AI analysis high-voltage power transmission and distribution perimeter early warning device, which comprises a data acquisition module, a data processing module, a behavior recognition alarm module and a cloud storage module, according to the control system, the early warning data and the operation parameters are synchronously acquired through the data acquisition module, the comprehensive perception capability is provided for the system, the false alarm rate and the missing report rate of traditional perimeter security and protection are remarkably reduced, the environmental adaptability and the decision intelligent level of the system under long-term operation are improved, and the safety of the system is improved. The fundamental transformation from passive alarm to active, intelligent and reliable early warning is realized.